I recently wrote about the need for organizations to take a holistic approach to the management and governance of data in motion alongside data at rest. As adoption of streaming data and event processing increases, it is no longer sufficient for streaming data projects to exist in isolation. Data needs to be managed and governed regardless of whether it is processed in batch or as a stream of events. This requirement has resulted in established data management vendors increasing their focus on streaming data and event processing through product development as well as acquisitions. It has also resulted in streaming and event specialists, such as Confluent, adding centralized management and governance capabilities to their existing offerings as they seek to establish or reinforce the strategic importance of streaming data as part of a modern approach to data management.
Confluent Addresses Data Governance for Data in Motion
Topics: Big Data, Cloud Computing, Data Governance, Streaming Analytics, Streaming Data & Events
Streaming Data Success Relies on Managing Data in Motion and At Rest
I recently noted that as demand for real-time interactive applications becomes more pervasive, the use of streaming data is becoming more mainstream. Streaming data and event processing has been part of the data landscape for many decades, but for much of that time, data streaming was a niche activity. Although adopted in industry segments with high-performance, real-time data processing and analytics requirements such as financial services and telecommunications, data streaming was far less common elsewhere. That has changed significantly in recent years, fueled by the proliferation of open-source and cloud-based streaming data and event technologies that have lowered the cost and technical barriers to developing new applications able to take advantage of data in-motion. This is a trend we expect to continue, to the extent that streaming data and event processing becomes an integral part of mainstream data-processing architectures.
Topics: Big Data, Data, Streaming Analytics, Analytics & Data, Streaming Data & Events
I have recently written about the importance of healthy data pipelines to ensure data is integrated and processed in the sequence required to generate business intelligence, and the need for data pipelines to be agile in the context of real-time data processing requirements. Data engineers, who are responsible for monitoring, managing and maintaining data pipelines, are under increasing pressure to deliver high-performance and flexible data integration and processing pipelines that are capable of handling the rising volume and frequency of data. Automation is a potential solution to this challenge, and several vendors, such as Ascend.io, have emerged in recent years to reduce the manual effort involved in data engineering.
Topics: Big Data, Cloud Computing, Data Management, Data, data operations
We’ve recently published our latest Benchmark Research on Data Governance and it’s fair to say, “you’ve come a long way, baby.” Many of you reading this weren’t around when that phrase was introduced in 1968 to promote Virginia Slims cigarettes, but you may have heard the phrase because it went on to become a part of popular culture. We’ve learned a lot about cigarettes since then, and we’ve learned a lot about data governance, too.
Topics: Big Data, Data Governance, Data Management, Analytics & Data
Looker Simplifies Business Intelligence in the Cloud
Organizations face various challenges with analytics and business intelligence processes, including data curation and modeling across disparate sources and data warehouses, maintaining data quality and ensuring security and governance. Traditional processes are slow when transforming large and diverse datasets into something which is easily consumable in BI. And, it can take days or weeks to create reports and dashboards — maybe longer if processes change and new data sources are introduced. Our Analytics and Data Benchmark Research shows that the most time-consuming processes are preparing data, reviewing it for quality issues and preparing reports for presentation and distribution.
Topics: Big Data, Analytics, Business Intelligence, Cloud
Natural Language Processing Enables Self-service Analytics & BI
Natural language processing (NLP) is a field that combines artificial intelligence (AI), data science and linguistics that enables computers to understand, interpret and manipulate text or spoken words. NLP includes generating narratives based on a set of data values, using text or speech as inputs to access information, and analysing text or speech, for instance, to determine its sentiment. There are various techniques for interpreting human language, ranging from statistical and machine learning (ML) methods to rules-based and algorithmic approaches. In this perspective, we will focus on two aspects of NLP: natural language query (NLQ), which offers the ability to use natural language expressions to discover and understand data, and natural language generation (NLG), which uses AI to produce written or spoken narratives from a dataset. NLQ and NLG enable business personnel to communicate information needs with business intelligence (BI) systems more easily.
Topics: Big Data, Analytics, natural language processing, NLP
2021 Analytics and Data Value Index: Market Observations and Perspective
Having just completed the 2021 Ventana Research Value Index for Analytics and Data, I want to share some of my observations about how the market has advanced since our assessment two years ago. The analytics software market is quite mature and products from any of the vendors we assess can be used to effectively deliver information to help your organization improve its operations. However, it’s also interesting to see how much the market continues to advance and how much investment vendors continue to make.
Topics: Big Data, Key Performance Indictors, embedded analytics, exadata, Analytics, Business Collaboration, Business Intelligence, Collaboration, Data Preparation, Digital Technology, natural language processing, Conversational Computing, AI and Machine Learning, collaborative computing, mobile computing
The Value Index for Analytics and Data Classifies and Rates Vendors
I am happy to share insights gleaned from our latest Value Index research, an assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Data 2021 is the distillation of a year of market and product research by Ventana Research. Drawing on our Benchmark Research, we apply a structured methodology built on evaluation categories that reflect the real-world criteria incorporated in a request for proposal to analytics and data vendors supporting the spectrum of business intelligence. Using this methodology, we evaluated vendor submissions in seven categories: five relevant to the product experience ﹘ adaptability, capability, manageability, reliability and usability ﹘ and two related to the customer experience ﹘ TCO/ROI and vendor validation.
The Digital Technology Market Agenda for 2021: Predictability in Unpredictable Times
I’m proud to share Ventana Research’s 2021 market agenda for digital technology. Our focus in this agenda is to deliver expertise to help organizations prioritize technology investments that increase workforce effectiveness and organizational agility, ensuring ongoing operation during any type of disruption.
Topics: Big Data, Analytics, Cloud Computing, Internet of Things, Digital Technology, Robotic Process Automation, blockchain, Conversational Computing, AI and Machine Learning, mobile computing, extended reality
In this analyst perspective, Dave Menninger takes a look at data lakes. He explains the term “data lake,” describes common use cases and shares his views on some of the latest market trends. He explores the relationship between data warehouses and data lakes and share some of Ventana Research’s findings on the subject. He also provides an assessment of the risks organizations face in working with data lakes and offers recommendations for maximizing the potential of data.
Topics: Big Data, Data Warehousing, Analytics, Business Analytics, Business Intelligence, Data Governance, Data Management, Data Preparation, data lakes
Effectively managing data privacy and security is a high-stakes matter. When an organization doesn’t get it right, it often becomes front-page news and occasionally becomes a subject of litigation. Yet organizations face an equally challenging imperative to ensure that business users have easy access to the data they need. Depending on how they are implemented, data governance policies can inhibit access to data, making it harder to find and utilize the data assets of an organization.
Topics: Big Data, Analytics, Business Intelligence, Collaboration, Data Governance, Data Preparation, Information Management, Internet of Things
Conversational Computing and More News from Oracle Analytics Summit 2019
The Oracle Analytics Summit 2019 was the inaugural user event for Oracle Analytics customers, and they also broadcast the video for thousands of others. You can watch the keynote at https://www.youtube.com/watch?v=eY0IPNqzsy4. Executives talked about some big organizational changes, including Bruno Aziza joining last year to lead the analytics organization. This event marked a transition and "a new beginning" for the Oracle Analytics portfolio, as the company announced three new analytics products.
Topics: Big Data, Data Science, Oracle Cloud, Oracle
Big Data, Machine Learning and Alteryx Inspires 2019
Alteryx Inspire 2019, this year's user conference for Alteryx, drew around 4500 customers, partners, and prospects to Nashville’s Gaylord Opryland Resort & Convention Center in Tennessee last month. The strong attendance was a reflection of the strong growth Alteryx has experienced over the last year; roughly 50% growth year-over-year. This year's conference focused on Alteryx's evolution from data preparation to AI and machine learning, and both were front and center.
Topics: Big Data, Data Science, alteryx, Machine Learning, Data Integration, Data Management, Alteryx Inspire
Embedded Data and Information Builders Summit 2019
Summit 2019, Information Builders' annual user conference, drew about 1000 attendees this year, including customers, partners and prospects all working with Information Builders' technologies. Under new leadership, Summit 2019 showcased the direction Information Builders is moving in the next couple of years.
Topics: Big Data, embedded analytics, Analytics, Data Integration, Data Management, Information Builders, IOT, Streaming Data, Information Builders Summit 2019
Data Management on Display at Informatica World 2019
This year, I attended Informatica World 2019, Informatica's annual user conference. The main focus this year was on the cloud with a heavy does of AI. Under that focus, Informatica's conference emphasized capabilities across six areas (all strong areas for Informatica): data integration, data management, data quality & governance, Master Data Management (MDM), data cataloging, and data security.
Topics: Big Data, Data Quality, Master Data Management, Data Governance, Data Management, Informatica, data lakes, Informatica World, Data Storage
Qonnections 2019 is Qlik's annual user conference. Key news from this year's conference centered on acquisitions of Podium Data and Attunity, along with an expansion of certifications on Google Cloud Platform, AWS, and Azure, with the ability to support Red Hat OpenShift. Many of these announcements were centered on a key theme of a cloud and SaaS-first approach.
Topics: Big Data, Analytics, Cloud Computing, Data Integration, Data Management, Information Management, Qlik, Qlik Qonnections
Consolidation around Cognos 11.1 and other news from IBM Analytics University
IBM's Analytics University (held in both Miami and Stockholm) brought about some large changes. Big announcements this year included a consolidation of IBM's Watson Analytics into Cognos 11.1, helping provide some clarity to their analytics offerings, along with new visualizations and better data preparation. This also includes a new conversational assistant to help generate narrative explanations of displays and interactive queries. For the full breakdown of IBM's Analytics University 2018, and my analysis of all the largest announcements, watch my latest hot take.
Topics: Big Data, Analytics, Business Intelligence, Data Preparation, AI, natural language processing
Once again I attended Tableau's Users Conference, along with 17,000 other attendees, affectionately self-referred to as "data nerds". Pushing the envelope in data capabilities and access, Tableau introduced the "Ask Data" feature, allowing users to prose natural language queries and receive a response, along with new data preparation capabilities and other enhancements to help data analysts. Further, Tableau announced new developer enhancements including a new developer program to better align tools built for Tableau with Tableau's interface. For the full breakdown of Tableau User Conference 2018, and my analysis of all the largest announcements, watch my hot take video.
Topics: Big Data, Data Governance, Data Integration, Data Preparation, Tableau Software, data lakes
This year, Teradata rebranded the Teradata users conference from "Partners" to "Analytics Universe", and there is a reason for it. For decades, Teradata has represented the high end of the analytic database, but new innovations and technologies are adding flexibility to Teradata's licensing as they compete. For the full breakdown of Teradata's Analytics Universe 2018, and my analysis of all the largest announcements, watch my hot take video.
Topics: Big Data, Data Warehousing, Teradata, Analytics, Data Governance, Data Management, Data Preparation, Information Management, Data, Digital Technology
In 2017 Strata + Hadoop World was changed to the Strata Data Conference. As I pointed out in my coverage of last year’s event, the focus was largely on machine learning and artificial intelligence (AI). That theme continued this year, but my impression of the event was of a community looking to get value out of data regardless of the technology being used to manage that data. The change was subtle: The location was the same; the exhibitors were largely the same; attendance was similar this year and last. But there was no particular vendor or technology dominating the event.
Topics: Big Data, Data Science, Machine Learning, Analytics, Business Intelligence, Data Governance, Data Integration, Data Preparation, Information Optimization, Digital Technology, Machine Learning and Cognitive Computing
PROS Holdings is a software vendor with two distinct but related sets of products. The company began in 1985 offering revenue management software to airlines, hospitality and rental car companies. More recently it added price and revenue management software focusing on B2B services, chemicals and energy, consumer goods manufacturers, food and beverage, healthcare, insurance and technology. This note focuses on the B2B portion of the business.
Topics: Big Data, Sales, Customer Experience, Marketing, Office of Finance, Analytics, Data Preparation, Sales Performance Management, Financial Performance Management, Price and Revenue Management, Digital Marketing, Digital Commerce, Pricing and Promotion Management, Sales Enablement and Execution
Was accounting ever cool? Well, yes, in a nerdy sort of way. Double-entry bookkeeping, codified in the 15th century by Fra Luca Pacioli, a Franciscan friar and pal of Leonardo Da Vinci, was essential for the expansion of trade and the creation of the modern corporation. Bookkeeping and accounting were as important to economic development as two other financial inventions – insurance and fractional reserve banking. Double-entry bookkeeping is an elegant system, simple yet powerful. It supports the accurate recording of transactions and the economic condition of a business as well as analyses of its performance. That’s cool.
Topics: Big Data, Office of Finance, Continuous Planning, business intelligence, Analytics, Financial Performance Management, Enterprise Resource Planning, ERP and Continuous Accounting
A Superior Employee Experience – A New Business Imperative
Employee engagement has been a dominant theme in both human capital management (HCM) and the systems to manage it in recent years; lately (though not necessarily appropriately) it is a topic often equated with the notion of the employee experience. On a related point, Gallup’s annual employee engagement survey has consistently found the majority of today’s workforce to be disengaged, defined as “not enthusiastic or passionate about their work.” Interest in the degree to which HCM technology can improve employee engagement (or mitigate disengagement) now rivals the attention given to such perennial chief human resources officer (CHRO) concerns as attracting and retaining top talent and retooling the workforce.
Topics: Big Data, Data Science, Human Capital Management, Machine Learning, Learning Management, Analytics, Business Intelligence, Cloud Computing, Collaboration, HRMS, Workforce Management, Digital Technology, Workforce Optimization
We now are well beyond the year depicted in 2001: A Space Odyssey, a cinematic perspective on the future of artificial intelligence in which HAL 9000, a computer, is able to simulate human behavior and control machines. Anyone reviewing the past two years of marketing around AI in the business technology industry can be forgiven for believing that we have arrived at the futuristic state Stanley Kubrick imagined. We have not.
Topics: Big Data, Data Science, Mobile, Customer Analytics, Customer Engagement, Customer Experience, Machine Learning, Mobile Technology, Analytics, Business Intelligence, Cloud Computing, Collaboration, Customer Service, Data Governance, Data Integration, Data Preparation, Internet of Things, Contact Center, Information Optimization, Digital Technology, Machine Learning and Cognitive Computing, Cybersecurity, Billing and Recurring Revenue, Workforce Optimization, collaboration for business
Blockchains are attractive because their built-in security and trust factors make them useful for almost all business interactions involving organizations and individuals. Blockchains have two basic functions. One is as a method for handling transactions involving property such as land deeds, trademarks or other assets. The second involves exchanges of data such as identities of individuals or businesses, the location of an object at a point in time or weather conditions. All interactions involving property or assets include the transfer of data as well, of course, but some blockchain use cases are informational only.
Topics: Big Data, Data Science, Mobile, Marketing Performance Management, Office of Finance, business intelligence, Analytics, Cloud Computing, Data Governance, Data Integration, Data Preparation, Internet of Things, Digital Technology, Digital Marketing, Digital Commerce, Operations & Supply Chain
Workday recently presented a technology summit for industry analysts. The presentations focused on Workday’s ongoing product advancements as well as its approach to employing emerging technologies. These technologies include artificial intelligence (AI) and machine learning (ML), robotic process automation (RPA) and bots utilizing natural language processing. Ventana Research uses the term “robotic finance” to refer to these technologies when used in the office of finance. In our view, they will have a profound impact on the nature of white-collar work over the coming decade. Financial management and ERP software vendors are focusing on these technologies because they will disproportionately affect finance and accounting departments: I estimate that their adoption has the potential to eliminate one-third of the accounting department’s workload within a decade.
Topics: Big Data, Data Science, Mobile, Machine Learning, Office of Finance, Continuous Planning, Cloud Computing, Collaboration, Financial Performance Management, ERP and Continuous Accounting
We are have arrived at the May 25, 2018 date when the European Union’s General Data Privacy Regulations (GDPR) become enforceable, following what has been a two-year transition period. Companies were given this time to put in place reasonable measures and the systems necessary to support the legislation’s wide-ranging personal data privacy requirements, which apply to any organization with more than 250 employees that serves EU citizens. While this regulation will apply in the EU, it has implications for any organization in the world that provides services involving the personal data of any EU citizen.
Topics: Big Data, Data Science, Mobile, Sales, Customer Analytics, Customer Engagement, Customer Experience, Marketing, Analytics, Business Intelligence, Cloud Computing, Collaboration, Data Governance, Data Integration, Data Preparation, Internet of Things, Contact Center, Digital Technology, Digital Marketing, Digital Commerce, Cybersecurity, Billing and Recurring Revenue, collaboration for business, mobile marketing
Beyond Digital Transformation: Effective Technology Innovation in 2018
Advancing the potential of any business requires continuous improvement in the processes and technology that support it. Many companies have embraced attempts at a digital transformation, and it’s become a goal to which organizational resources and budgets have been dedicated around the globe.
Topics: Big Data, Data Science, Mobile, Sales, Customer Analytics, Customer Engagement, Customer Experience, Human Capital Management, Machine Learning, Marketing, Marketing Performance Management, Mobile Technology, Office of Finance, Wearable Computing, Analytics, Business Intelligence, Cloud Computing, Collaboration, Customer Service, Data Governance, Data Integration, Data Preparation, Internet of Things, Contact Center, Information Optimization, Product Information Management, Digital Technology, Digital Marketing, Digital Commerce, Operations & Supply Chain, Machine Learning and Cognitive Computing, Pricing and Promotion Management, Cybersecurity, Billing and Recurring Revenue, Workforce Optimization, collaboration for business, mobile marketing
Ventana Research recently published the findings of our benchmark research on Data Preparation, which examines the practices organizations use to accomplish data preparation. We view data preparation as a sequence of steps: identifying, locating and then accessing the data; aggregating data from different sources; and enriching, transforming and cleaning it to create a single uniform data set. Using data to accomplish organizational goals requires that it be prepared for use; to do this job properly, businesses need flexible tools that enable them to enrich the context of data drawn from multiple sources and collaborate on its preparation as well as ensure security and consistency. Users of data preparation tools range from analysts to operations professionals in the lines of business to IT professionals.
Topics: Big Data, Analytics, Data Preparation
SAP Data Hub Orchestrates Data for Business and IT
I recently attended SAP TechEd in Las Vegas to hear the latest from the company regarding its analytics and business intelligence offerings as well as its data management platform. The company used the event to launch SAP Data Hub and made several other data and analytics announcements that I’ll cover below.
Topics: Big Data, SAP, Machine Learning, Analytics, Data Preparation, SAP TechEd
Joining the Ventana Research Team and Community
I’m thrilled to announce to my HCM vendor and practitioner network as well as the ever-expanding Ventana Research community that I’m now directing Ventana’s HCM practice. I will be working closely with our CEO and Chief Research Officer Mark Smith, who is a fellow HCM enthusiast and thought leader.
Topics: Big Data, Data Science, Mobile, Human Capital Management, Machine Learning, Learning Management, Analytics, Cloud Computing, Collaboration, Internet of Things, HRMS, Workforce Management, Payroll Optimization, Customer Digital Technology
At Strata Data NY, Focus is on Machine Learning and AI
The Strata Data Conference is changing and it’s changing in a good way. At the recent Strata Data Conference in New York, Mike Olson, chief strategy officer at Cloudera, which co-sponsored the event, commented that at prior events we used to talk about the “Hadoop zoo animals,” meaning the various components of the Hadoop ecosystem of which I have written previously. Following last fall’s Strata event, I observed that the conference was evolving to focus on the use of data. Advancing that evolution, this year’s event focused on a particular type of usage: artificial intelligence (AI) and machine learning. The evolution from a focus on zoo animals to a focus on business value using advanced analytics shows further maturation of the big data market.
Topics: Big Data, Machine Learning, Analytics, Hadoop, Artificial intelligence
There’s been some speculation in the market that Hadoop may be disappearing. Some of this speculation has been driven by vendors that have recently downplayed Hadoop in their marketing efforts. For example, the Strata+Hadoop World conference is now known as the Strata Data Conference. The Hadoop Summit is now known as the Dataworks Summit. In Cloudera’s S-1 filing with the SEC for its initial public offering, the term “Hadoop” appears only 14 times, while the term “machine learning” appears 83 times. So, if some of the vendors that created the market appear to be pivoting away from Hadoop, does your organization need to do something similar, or is there a role for Hadoop in your IT architecture?
Artificial Intelligence and Machine Learning in Business Applications
The application of artificial intelligence (AI) and machine learning (ML) to business computing will have a profound impact on white collar professions. This is especially true in heavily rules-based functions such as accounting. Companies recognize the transformational potential of AI and ML, but the progression and pace of the adoption of these technologies is unclear. Some applications of AI and ML are already in use but others are a decade or more away from replacing human tasks.
Topics: Big Data, Machine Learning, Office of Finance, Analytics, CFO, finance, CEO, AI, accountants, NLP, Accounting
Hortonworks Helps IBM Big Data Potential with Hadoop
Recently Hortonworks announced some significant additions to its products at the DataWorks Summit. These additions reflect the fact that the big data market continues to evolve, as I have previously written.
Topics: Big Data, Machine Learning, Analytics
This is my second analyst perspective based on our IoT Benchmark Research. In the first, I discussed the business focus of IoT applications and some of the challenges organizations are facing. Now I’ll share some of the findings about technologies used in IoT applications and the impact those technologies appear to have on the success of users’ projects.
Topics: Big Data, Analytics, Business Intelligence, IOT, NoSQL
Broken Analytics and BI? Natural Language and Notifications Can Help
If we look at the focus of technology vendors for analytics and business intelligence or business applications providers deploying these capabilities in the last five years, we see that they have elevated the importance on the value of visualization and dashboards. These promotions might be understandable, but will they make business and the people using them more intelligent?
Topics: Big Data, Data Science, Mobile, Machine Learning, Analytics, Business Intelligence, Cloud Computing, Collaboration, Information Optimization, Digital Technology, Machine Learning and Cognitive Computing
More than a year ago I wrote from personal experience about the challenges our firm encountered with Salesforce’s cloud computing systems and customer service and if we can trust them for business in the cloud. That perspective covered a range of issues that the behemoth cloud computing applications and platform company is facing regarding its service and technology. While Salesforce has shifted its customers like us and others to a different cloud computing environment, as it did in moving us off its #NA14 cloud computing instance, core challenges of its customer experience and billing processes persist. After the last customer experience incident, I contacted its executives about the need for operational improvement; it was clear in the dialogue that they saw some but not all of our experience as issues important to improving its customer processes. It was good to get some immediate attention, but my hope was to speak for all SMB companies in pointing out the importance of effective communications and escalating notifications and interactions when those customer moments go sour, so the customer isn’t forced to turn to social media to be heard. This was an area where Salesforce had significant room for improvement in customer engagement, reflecting a pattern we see in our benchmark research, which finds the most common challenges in almost half of organizations are integration of channels of engagement and managing activities as silos.
Topics: Big Data, Sales, Office of Finance, Analytics, Cloud Computing, Collaboration, Product Information Management, Sales Performance Management, Digital Commerce, Sales and Operations Planning, Machine Learning and Cognitive Computing, Sales Enablement and Execution, Machine Learning Digital Technology, Sales Planning and Analytics
This year various types of organizations are embracing machine learning like it is going out of style – or maybe it would be better to say coming into style. And now with a little investigation on LinkedIn finds over half million professionals with machine learning in their job title. Machine learning is the application of specific data science algorithms that become more accurate as the system records more outcomes and processes more data. This improvement is referred to as “learning,” hence the name. There are good reasons machine learning is growing so rapidly, but there are pitfalls to avoid as well.
Topics: Big Data, Data Science, Analytics, Business Intelligence, Cloud Computing, Machine Learning and Cognitive Computing, Machine Learning Digital Technology
Informatica Asserts Its Commitment to the Cloud and Machine Learning
Informatica reintroduced itself to the world at its recent customer conference, Informatica World, in San Francisco. The company took advantage of the event to showcase its new branding in an effort to change the way customers think about the company. Informatica has been providing information services in the cloud for more than a decade. Even though cloud revenue comprises a minority of Informatica’s business, in absolute terms, the revenue is significant, and company executives want the public to recognize Informatica as a leader in cloud-based data management services for enterprises. Presenters also made notable product announcements, discussed below, including the application of machine learning to the data management process.
Topics: Big Data, Data Science, Analytics, Business Intelligence, Cloud Computing, Data Governance, Data Integration, Data Preparation, Information Optimization, Machine Learning and Cognitive Computing, Machine Learning Digital Technology
MicroStrategy Deepens Potential of Analytics and BI Platform
I recently attended the MicroStrategy World conference, which was held in Washington, D.C. and it celebrate its 20th anniversary, which is why MicroStrategy hosted the event near its headquarters. Over the past 20 years, the market and technology for business intelligence and analytics have significantly changed, and in several changes, MicroStrategy has been at the forefront. Now is a good time to examine the company’s position in the market and its latest offerings in context of the analytics market direction that I recently presented.
Topics: Big Data, Mobile Technology, Analytics, Business Intelligence, Digital Technology
Supercharge Sales Analytics with Digital Technologies
Our firm regularly explores the impacts of new technologies on business. Analytics is foremost among recently emerging technologies, which our benchmark research consistently confirms. In our research on next-generation sales analytics, fourth-fifths (82%) of participating organizations cited analytics as the most important technology trend for sales; however, several other technologies also are adding power and flexibility to the use of sales analytics.
Topics: Big Data, Sales, Mobile Technology, Office of Finance, Analytics, Cloud Computing, Collaboration, Product Information Management, Sales Performance Management, Digital Commerce, Machine Learning and Cognitive Computing, Sales Enablement and Execution, Machine Learning Digital Technology, Sales Planning and Analytics
Vendavo Brings Intelligence to Pricing and Profitability
Vendavo recently held its annual Profit Summit, a combination of a user group conference and a forum for covering evolving trends and techniques in business-to-business (B2B) pricing. Especially in emerging categories like pricing and revenue management, this sort of event provides an opportunity to assess the state of the market and the maturity of the applications. As I’ve noted, adoption of price and revenue management software has been slow in the B2B segment of commerce due to multiple obstacles. The challenges include change management, as well as data and process issues.
Topics: Big Data, Sales, Office of Finance, Analytics, Cloud Computing, Sales Performance Management, Price and Revenue Management, Digital Commerce, Pricing and Promotion Management, Sales Enablement and Execution, Sales Planning and Analytics
The importance of analytics for sales organizations is clear and, as I pointed out in my recent analyst perspective on the next generation of sales analytics, these capabilities optimize revenue potential. However, utilizing sales analytics requires a set of data skills that most organizations still find challenging and are thus not fully prepared to support. The efficient access and preparation of data underlies any analytics processes, which must meet demanding needs that are not always automated. Our research into next generation sales analytics has found many impediments that must be addressed and is a critical part of our expertise agenda for sales organizations.
Topics: Big Data, Sales, Machine Learning, Office of Finance, Analytics, Cloud Computing, Collaboration, Product Information Management, Sales Performance Management, Digital Technology, Digital Commerce, Sales and Operations Planning, Machine Learning and Cognitive Computing, Sales Enablement and Execution, Sales Planning and Analytics
New Generation of Sales Analytics Can Optimize Revenue Potential
I have been following advances in sales analytics since the 1990s. Over the last five years, however, I have seen evolution, not innovation. In most cases the information that analytics provides is too complicated and not contextualized enough for sales people who are not analytics experts to understand, let alone take action on. As I pointed out in my 2017 research agenda on sales, analytics is essential for planning that improves the impacts of sales efforts and meets the goals of the organization.
Topics: Big Data, Sales, Mobile Technology, Office of Finance, Analytics, Cloud Computing, Collaboration, Product Information Management, Sales Performance Management, Digital Commerce, Sales and Operations Planning, Machine Learning and Cognitive Computing, Sales Enablement and Execution, Machine Learning Digital Technology, Sales Planning and Analytics
CFO and Finance Should Take Leadership Role in Pricing
Pricing is an issue that affects almost every for-profit company that doesn’t sell purely commodity products. A corporation’s approach to pricing can range from highly disciplined to ad hoc and from fully centralized to decentralized. The issue of centralized or decentralized depends a great deal on the markets the company serves, its organizational structure and its culture. However, a disciplined approach to price setting and negotiation is always superior to an ad hoc approach. This is especially true for non-commodity B2B businesses, which I believe have lagged other types of business in managing their pricing strategically. (Some would argue that there is no such thing as a pure commodity business, but that’s another issue.) Increasing pricing discipline in the company is one way for the CFO to engage more strategically in managing the business.
Topics: Big Data, Office of Finance, Continuous Planning, Analytics, Sales Performance Management, Financial Performance Management, Price and Revenue Management, Pricing and Promotion Management, Sales Enablement and Execution, ERP and Continuous Accounting, Sales Planning and Analytics
Oracle recently held its second ERP Cloud Summit with industry analysts. The all-day event wasn’t just about ERP. The company covered a range of its business applications, including financial performance management as well as its Adaptive Intelligent Applications. And it wasn’t just about the cloud. After more than a decade of steady developments, ERP systems have begun to change fundamentally, facilitated by the growing availability of new technologies including cloud computing, advanced database architecture, collaboration, user interface design, mobility, analytics and planning. Here are my key takeaways from the event:
Topics: Big Data, Data Science, Mobile, Customer Experience, Human Capital Management, Machine Learning, Office of Finance, Analytics, Data Integration, Internet of Things, Cognitive Computing, HRMS, Financial Performance Management, Mobile Marketing Digital Commerce, Digital Marketing, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, ERP and Continuous Accounting
Ventana Research recently announced the results of its latest Benchmark Research, Next-Generation ERP. The enterprise resource planning (ERP) system is at the core of nearly every company’s record-keeping and management of business processes. Its smooth and uninterrupted functioning is essential to an organization’s accounting and finance functions. In manufacturing and distribution, ERP manages inventory and logistics. Some companies use it to handle human resources functions like tracking employees, payroll and related costs.
Topics: Big Data, Mobile, Human Capital Management, Office of Finance, Cloud Computing, Collaboration, Inventory Optimization, Work and Resource Management, Enterprise Resource Planning, ERP and Continuous Accounting
I recently attended SAS Institute’s analyst relations conference. There the company provided updates on its financial performance and its Viya platform and a glimpse into some of its future plans.
Topics: Big Data, Data Science, Mobile Technology, business intelligence, Analytics, Cloud Computing, Collaboration, Data Governance, Data Integration, Data Preparation, Internet of Things, Information Optimization, Machine Learning and Cognitive Computing, Machine Learning Digital Technology
Cloudera provides database and enabling technology for the big data market and overall for data and information management. As my colleague David Menninger has written, the big data and information management technology markets are changing rapidly and require vendors to adapt to them. Cloudera has grown significantly over the last decade and now has approximately 1,000 customers and provides support and services in countries around the world. Its product and technology strategy is to provide a unified data management platform, Cloudera Enterprise, that can meet the data engineering and science needs for a range of analytic and operational database applications. Its primary focus is its Enterprise Data Hub, which as a data lake can handle organizations’ big data and analytical needs. As David Menninger asserts, the data lake is a safe way to invest in big data. It also helps shift the focus away from the V’s (volume, velocity and variety) of big data to the A’s, which are analytics, awareness, anticipation and action.
Topics: Big Data, Data Science, Machine Learning, business intelligence, Analytics, Cloud Computing, Data Governance, Data Integration, Data Preparation, Internet of Things, Cognitive Computing, Information Optimization, Digital Technology
Digital Process Reengineering Drives Business Change
Business process reengineering was a consulting fashion in the early 1990s that spurred many companies to purchase their first ERP systems. BPR proposes a fundamental redesign of core business processes to achieve substantial improvements in market and customer responsiveness, productivity, cycle times and quality. ERP systems support business process reengineering by guiding the step-by-step execution of the redesigned process to ensure that it is performed consistently. They also automate the handoffs between individuals and departments to accelerate completion of that process.
Topics: Big Data, Data Science, Mobile, Customer Analytics, Customer Experience, Machine Learning, Office of Finance, Wearable Computing, Continuous Planning, Analytics, Business Intelligence, Cloud Computing, Data Integration, Internet of Things, Financial Performance Management, Digital Technology, Digital Marketing, Digital Commerce, Operations & Supply Chain, Enterprise Resource Planning, Machine Learning and Cognitive Computing, ERP and Continuous Accounting, Sales Planning and Analytics
In tracking NICE for a decade I have seen the company grow, through a series of acquisitions and product developments, from a vendor largely of workforce management systems to one that offers a full suite of workforce optimization products. It is now advancing what I call a customer experience platform that builds on top of my last coverage of it advancing its efforts. This includes systems to manage assisted channels of engagement (primarily the telephone), digital channels of engagement, workforce optimization, advanced analytics and tight integration with business applications such as CRM. NICE is on the road to building such a platform using existing and newly developed products and those that it recently acquired from Nexidia and inContact. It will take time before a fully integrated platform is available, but the company has already taken steps toward this goal.
Topics: Big Data, Customer Analytics, Customer Engagement, Customer Experience, Mobile Technology, Analytics, Cloud Computing, Collaboration, Customer Service, Contact Center, CRM, Digital Technology
I am happy to provide my personal perspective on the potential of sales organizations, processes and technology to supercharge business activity in 2017. The sales processes of organizations – whether they involve digital commerce or direct or indirect physical selling – should be part of continuous optimization efforts to reach maximum results. To do this, the people leading and running sales processes must be able to use technology that supports their responsibilities and analyzes the crucial information coming into the business. For almost 15 years, we have advocated for sales applications and tools that are necessary to optimize sales effectiveness and improve the outcomes of their sales efforts. The available portfolio is much larger than sales force automation (SFA) and involves more than the continued use of CRM, which has clear limits in its ability to manage customer relationships. The applications on offer include many facets of sales: coaching, compensation management, contract management, configure price quote (CPQ), forecasting, quota and territory management, planning and optimization, pricing and revenue optimization, and target or market intelligence. New applications designed for sales also enable digital effectiveness that can transform organizations. Let me provide my perspective on six topics that are shaping the way sales can and should operate in 2017, and which are part of our sales research agenda for the year.
Topics: Big Data, Sales, Machine Learning, Mobile Technology, Office of Finance, Analytics, Cloud Computing, Collaboration, Product Information Management, Sales Performance Management, Digital Technology, Digital Commerce, Operations & Supply Chain, Sales and Operations Planning, Machine Learning and Cognitive Computing, Sales Enablement and Execution, Sales Planning and Analytics
More businesses are using software to implement and support a strategic pricing strategy designed to optimize revenue and margins in business-to-business (B2B) transactions because it can help improve results at the bottom line. “Optimize” in this instance means managing the trade-off that usually exists between revenue and profitability objectives in order to support a company’s strategy and capabilities in a given market. Business-to-business pricing management is Ventana Research’s term for such processes and applications. Software built for this purpose centralizes control and enforces consistency in pricing while assisting sales agents in negotiating prices that achieve desired business objectives. It enables agents to use techniques that can increase the revenue from a transaction, the margin on the sale or the probability of closing the sale.
Topics: Big Data, Data Science, Sales, Office of Finance, Analytics, Cloud Computing, Sales Performance Management, Financial Performance Management, Price and Revenue Management, Pricing and Promotion Management, Sales Enablement and Execution, ERP and Continuous Accounting
ShoreTel Offers Communications and Contact Centers
Until recently most organizations deployed systems on their own premises to build communications and contact center infrastructures, which often required them to integrate products from several vendors. In the past few years many vendors have moved their systems to the cloud, and others have begun as cloud-based suppliers. This trend has opened up the opportunity for more organizations to take advantage of modern communication systems and contact centers. Using the cloud for either, or both can save money and resources, reduce risk, and make available more integrated, multi-channel systems. While the adoption of such systems has undoubtedly increased and is likely to continue to do so, our benchmark research into next-generation contact centers in the cloud finds that many organizations still prefer to remain on premises, and adoption of cloud-based systems occurs on a case-by-case basis. In addition, many organizations look for vendors that support multiple models so they have the option of starting out using one model but transitioning later to another, including to a hybrid model in which some systems are on-premises and others are cloud-based..
Topics: Big Data, Mobile, Customer Analytics, Customer Engagement, Customer Experience, Machine Learning, Wearable Computing, Analytics, Business Intelligence, Cloud Computing, Collaboration, Internet of Things, Contact Center, Digital Commerce, Subscription Billing
IoT Challenges Organization and Technological Readiness
The Internet of Things (IoT) is a technology that extends digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This advance enables virtually any device to transmit its data, to which analytics can then be applied to facilitate monitoring and a range of operational functions. IoT can deliver value in several ways. It can provide organizations with more complete data about their operations, which helps them improve efficiencies and so reduce costs. It also can deliver a competitive advantage by enabling them to reduce the elapsed time between an event occurring and operational responses, actions taken or decisions made in response to it.
Topics: Big Data, Wearable Computing, Analytics, Internet of Things, Digital Technology
Senior finance executives and finance organizations that want to improve their performance must recognize the value of technology as a key tool for doing high-quality work. Consider how poorly your organization would perform if it had to operate using 25-year-old software and hardware. Having the latest technology isn’t always necessary, but it’s important for executives to understand that technology shapes a finance organization’s ability to improve its overall effectiveness.
Topics: Big Data, Data Science, Mobile, Human Capital Management, Mobile Technology, Office of Finance, Continuous Planning, Analytics, Business Intelligence, Cloud Computing, Collaboration, Financial Performance Management, Price and Revenue Management, Inventory Optimization, Operations & Supply Chain, Enterprise Resource Planning, Sales and Operations Planning, Machine Learning and Cognitive Computing, ERP and Continuous Accounting
Research Agenda Will Track Big Data and Information Management in 2017
Big data has become an integral part of information management. Nearly all organizations have some need to access big data sources and produce actionable information for decision-makers. Recognizing this connection, we merged these two topics when we put together our recently published research agendas for 2017. As we plan our research, we focus on current technologies and how they can be used to improve an organization’s performance. We then share those results with our readers.
Topics: Big Data, Data Science, Analytics, Data Governance, Data Integration, Data Preparation, Information Management, Internet of Things, Machine Learning and Cognitive Computing, Machine Learning Digital Technology
Research Agenda Will Guide Business Analytics in 2017
Ventana Research analysts recently published our research agendas for 2017. As we put together these plans we think about the forces that are shaping the markets that we cover and then craft agendas that study these issues to provide insights for our community. I’ve been working in the business intelligence (BI) and analytics market for nearly 25 years, and throughout that time the industry has been trying to make analytics useful to increasingly wider audiences. That focus continues to today. Better search and presentation methods, including visual discovery and natural-language processing, are promising ways to engage more users. We also see organizations supporting their users in specific functional roles with relevant and accessible analytics. My colleagues examine these issues as part of their agendas in the Office of Finance, Sales, Marketing, Customer Experience, Operations and Supply Chain, and Human Capital Management. While their agendas include analytics within specific domains, my own research focuses on a range of analytics issues across domains including cloud computing, mobility, collaboration, data science and the Internet of Things.
Topics: Big Data, Data Science, Mobile Technology, Analytics, Business Intelligence, Cloud Computing, Collaboration, Internet of Things, Machine Learning and Cognitive Computing, Machine Learning Digital Technology
Vertex Enterprise Addresses Today’s Tax Challenges
I’ve long advocated the use of effective technology in the tax function, especially for organizations that operate in multiple jurisdictions or have complex legal structures manage direct tax provision and analysis using outdated or inappropriate tools. Our Office of Finance benchmark research reveals that most organizations use spreadsheets to manage their tax provision and analysis: Half (52%) rely solely on spreadsheets, and another 38 percent mainly use them. I recommend to corporations that operate in multiple countries and that have even a moderately complex legal entity structure that they consider establishing what I call a tax data warehouse of record.
Topics: Big Data, Office of Finance, Continuous Planning, Analytics, Financial Performance Management, ERP and Continuous Accounting
Pentaho 7.0 Brings Visualization and Data Preparation
The business intelligence market is bounded on one side by big data and on the other side by data preparation. That is, to maximize their performance in using information, organizations have to collect and analyze ever increasing volumes of data while the tools available are constantly evolving in the big data ecosystem that I have written about. In our benchmark research on big data analytics, half (51%) of organizations said they want to access big data using their existing BI tools. At the same time, as I have noted, end users are demanding self-service access to data preparation capabilities to facilitate their analyses.
Topics: Big Data, Analytics, Business Intelligence, Collaboration, Data Integration, Data Preparation, Information Management, Internet of Things
B2B Price and Revenue Optimization Goes Mainstream
Price and revenue optimization (PRO) is a business discipline used to produce demand-based pricing; it applies market segmentation techniques to achieve strategic objectives such as increased profitability or greater market share. In essence, PRO enables companies to surf the demand curve using dynamic rather than fixed pricing to achieve the most desirable trade-offs between revenue volume and profit margins. The trade-off is defined by strategic factors such as the company’s market position, product and service portfolio, and marketing strategy.
Topics: Big Data, Data Science, Sales, Office of Finance, Analytics, Cloud Computing, Sales Performance Management, Financial Performance Management, Price and Revenue Management
The big data market continues to evolve, as I have written previously. Vendors are attempting to differentiate their offerings as they seek to encourage customers to pay for technology that they could potentially download for free.
Topics: Big Data, Analytics, Business Intelligence, Internet of Things, Information Optimization
IBM recently held its inaugural World of Watson event. Formerly known as IBM Insight, and prior to that IBM Information on Demand, the annual event, attended by 17,000 people this year, showcases IBM’s data and analytics and the broader IBM efforts in cognitive computing. The theme for the event, as you might guess, was the Watson family of cognitive computing products. I, for one, was glad to spend more time getting to know the Watson product line, and I’d like to share some of my observations from the event.
Topics: Big Data, Data Science, Machine Learning, Analytics, Cloud Computing, Data Governance, Data Integration, Internet of Things, Information Optimization, Machine Learning and Cognitive Computing
Ventana Research recently awarded Workday a 2016 Technology Innovation Award for its newly released application, Workday Planning, because it simplifies and streamlines the budgeting and planning processes while facilitating collaboration, deepening visibility into spending and enabling tight fiscal control. These capabilities can help a variety of user organizations in several ways.
Topics: Big Data, Marketing, Office of Finance, Budgeting, Controller, In-memory, CFO, Workday, demand management, Financial Performance Management, financial reporting, FPM, Integrated Business Planning
SYSPRO is a 35-year-old software vendor that focuses on selling enterprise resource planning (ERP) systems to midsize companies, particularly those in manufacturing and distribution. In manufacturing, SYSPRO supports make, configure and assemble, engineer to order, make to stock and job shop environments. The company attempts to differentiate itself through vertical specialization and its years of ongoing development, which can reduce the need for customization and cut the cost of initial and ongoing configurations to suit the needs of companies in these industries, thereby reducing the total cost of ownership. Worldwide its targeted verticals include electronics, food, machinery and equipment and medical devices; in the United States, SYSPRO adds automotive parts (original equipment and after-market) and energy. The company’s development efforts follow a design philosophy that balances its target customers’ need for software capabilities that are on par with larger enterprises with their resource constraints (chiefly limited financial resources and technical staffs). Its software can be deployed on-premises or in the cloud.
Topics: Big Data, SaaS, ERP, Governance, Human Capital Management, Office of Finance, close, Continuous Accounting, Analytics, CIO, Cloud Computing, Collaboration, CFO, CRM, CEO
I recently spent time at Strata+Hadoop World 2016 in New York. I attended this event and its predecessor, Hadoop World, off and on for the past six years. This one in New York had a different feel from previous events including the most recent event in San Jose at the end of March. Perhaps because of its location in one of the financial and commercial hubs of the world, the event had much more of a business orientation. But it’s not just location. Past events have been held in New York also, and I see the business focus as a sign of the Hadoop market maturing.
Topics: Big Data, Predictive Analytics, Strata+Hadoop
I recently attended Oracle OpenWorld for the first time in several years. The message at this year’s event was clear: Oracle is all in on the cloud. I had heard the message, but I didn’t get the full impact until I arrived at the Moscone Center in San Francisco. All signage at the event contained the word “cloud,” and Oracle issued 18 press releases in conjunction with OpenWorld related to cloud computing. I also found out that Oracle has its own definition of “cloud.”
Topics: Big Data, Office of Finance, Analytics, Business Intelligence, Cloud Computing
Oracle Adapts Business Applications Intelligently in the Cloud
The annual Oracle OpenWorld user group meeting provides an opportunity to step back and take a longer view of business, industry and technology trends affecting the company. Last year, after listening to Larry Ellison’s and Mark Hurd’s vision for the future of IT, I wrote that Oracle had to continue shifting its focus to business applications because the accelerating shift to cloud computing would lead corporations to outsource their IT infrastructures, services and security to third parties. Eventually, this would substantially shrink the market for corporate IT departments, which has been Oracle’s strength. At this year’s conference the company demonstrated how it is applying its technology strengths to create a competitive advantage that it can apply to its broad business applications portfolio.
Topics: Big Data, Performance Management, SaaS, ERP, Office of Finance, Analytics, Cloud Computing, PaaS, Digital Technology
I recently attended Oracle OpenWorld for the first time in several years. The message at this year’s event was clear: Oracle is all in on the cloud. I had heard the message, but I didn’t get the full impact until I arrived at the Moscone Center in San Francisco. All signage at the event contained the word “cloud,” and Oracle issued 18 press releases in conjunction with OpenWorld related to cloud computing. I also found out that Oracle has its own definition of “cloud.”
Topics: Big Data, Predictive Analytics, Business Analytics, Business Intelligence, Cloud Computing, Information Management
Industry Changes Shake Up Customer Experience Management
I have been involved in the call center and customer engagement market for more than 25 years, first as a consultant and systems integrator and for the past 11 years as an industry analyst. There have been lots of changes in that time but never as many as in the last 12 to 18 months. A simple illustration of the change is how I group vendors.
Topics: Big Data, Social Media, Mobile Technology, Customer Performance, Business Analytics, Cloud Computing, Call Center
Teradata Takes On Cloud and Developers with Big Data & Analytics
Teradata recently held its annual Partners conference, at which gather several thousand customers and partners from around the world. This was the first Partners event since Vic Lund was appointed president and CEO in May. Year on year, Teradata’s revenues are down about 5 percent, which likely prompted some changes at the company. Over the past few years Teradata made several technology acquisitions and perhaps spread its resources too thin. At the event, Lund committed the company to a focus on customers, which was a significant part of Teradata’s success in the past. This commitment was well received by customers I spoke with at the event.
Topics: Big Data, Predictive Analytics, Business Analytics, Business Intelligence, Cloud Computing, Information Management
Value Index Analysis Finds Workforce Optimization Market Mature
Ventana Research has published its Workforce Optimization 2016 Value Index. The Value Index provides a comprehensive evaluation of contact center workforce optimization vendors based on responses to our RFP-like questionnaire, which was constructed using insights gained from our recent benchmark research into workforce optimization and our knowledge of the market. In our definition workforce optimization systems include interaction recording, agent quality management, workforce management, agent compensation management, training and coaching, and interaction-handling analytics. The research shows that organizations have deployed many of these applications and by doing so have achieved efficiencies in handling interactions, improved outcomes of those interactions and improved both customer and employee satisfaction.
Topics: Big Data, Customer Experience, Mobile Technology, Customer Performance, Cloud Computing, Call Center
Vendavo Builds Price and Revenue Optimization into Business Processes
Vendavo is a vendor of business-to-business (B2B) price and revenue optimization software, which I have written about. A major focus of the conference sessions this year at the company’s annual user group meeting was on practical approaches to successful price optimization initiatives. While this category of software has been achieving increasing acceptance, penetration is still limited in the B2B segment, which includes, for example, industrial goods and services.
Topics: Big Data, Sales Performance, Customer Performance, Operational Performance, Business Analytics, Business Performance, Financial Performance, Vendavo, price, pricing, optimization, revenue, cu
A Recipe for Cooking with the Hadoop Ecosystem
It’s part of my job to cover the ecosystem of Hadoop, the open source big data technology, but sometimes it makes my head spin. If this is not your primary job, how can you possibly keep up? I hope that a discussion of what I’ve found to be most important will help those who don’t have the time and energy to devote to this wide-ranging topic.
Topics: Big Data, Business Analytics, Business Intelligence, Information Management, Operational Intelligence
It often seems to business-to-business (B2B) marketers as if the only people who understand them are other B2B marketers. They feel that salespeople don’t get what they do day-to-day, that friends and family don’t understand what they do for a living, and most of all that the executives to whom they report have no interest in what they do – that is, until the last day of the quarter. Then they require that B2B marketers deliver positive, lead-generating and revenue-producing results in reports that detail how their efforts supported sales in the previous 90 days. And they expect those results to be reported in a format understandable to all.
Topics: Big Data, Sales Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Operational Intelligence, Hive9 Marketing Performance Management
Denodo Makes Data Virtualization Relevant to Big Data and Analytics
Data virtualization is not new, but it has changed over the years. The term describes a process of combining data on the fly from multiple sources rather than copying that data into a common repository such as a data warehouse or a data lake, which I have written about. There are many reasons for an organization concerned with managing its data to consider data virtualization, most stemming from the fact that the data does not have to be copied to a new location. It could, for instance, eliminate the cost of building and maintaining a copy of one of the organization’s big data sources. Recognizing these benefits, many database and data integration companies offer data virtualization products. Denodo, one of the few independent, best-of-breed vendors in this market today, brings these capabilities to big data sources and data lakes.
Topics: Big Data, Business Analytics, Business Intelligence, Information Management, Information Optimization, Data virtualization, data integration, data lake,
RapidMiner Brings Self-Service to Predictive Analytics
Predictive analytics is a rewarding yet challenging subject. In our benchmark research on next-generation predictive analytics at least half the participants reported that predictive analytics allows them to achieve competitive advantage (57%) and create new revenue opportunities (50%). Yet even more participants said that users of predictive analytics don’t have enough skills training to produce their own analyses (79%) and don’t understand the mathematics involved (66%). (In the term “predictive analytics” I include all types of data science, not just one particular type of analysis.)
Topics: Big Data, Data Science, Predictive Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing
Modeling Revenue Recognition for Contracts to Meet New Regulations
I recently wrote about the challenge some companies will face in planning and budgeting when new revenue recognition rules go into effect in most countries in 2018. It’s important for companies that will be affected to be sure they have the appropriate systems, processes and training to handle the more difficult demands imposed by the new rules. With the change in accounting, the time lag between when a contract is signed and when a company recognizes revenue from it may be more variable and less predictable than in the past. In extreme cases, performance measured by financial accounting will diverge materially from the “real” economic performance of the organization. Consequently, executives – especially those leading publicly listed companies – will need the ability to look at their plans from both perspectives and be able to distinguish between the two in assessing their company’s performance. In companies where the timing of revenue recognition can diverge substantially from current methods, financial planning and analysis (FP&A) groups will need to be able plan using models that incorporate financial and managerial accounting methods in parallel. They will need to be able to identify actual-to-plan variances caused by differences in contract values booked in a period and differences between the expected and actual timing of revenue recognized from contracts signed in a period.
Topics: Big Data, Sales Performance, Business Performance, Financial Performance, Uncategorized
Qlik helped pioneer the visual discovery market with its QlikView product. In some respects, Qlik and its competitors also spawned the self-service trend rippling through the analytics market today. Their aim was to enable business users to perform analytics for themselves rather than building a product with the perfect set of features for IT. After establishing success with end users the company began to address more of the concerns of IT, eventually creating a robust enterprise-grade analytics platform. This approach has worked for Qlik, driving growth that led to an initial
public offering in 2010. The company now generates more than half a billion dollars in revenue annually, making it one of the largest independent analytics vendors. Of which based on their company and products was rated a Hot Vendor in our 2015 Value Index on Analytics and Business Intelligence and one of the highest ranked in usability.
Topics: Big Data, Mobile Technology, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Information Management, Uncategorized, Qlik, Analytics, Qlik Sense, Qlik, Business intell
NICE Systems Doubles Down on Customer Experience
NICE Systems was one of the first vendors I started to cover when I joined Ventana Research more than 11 years ago. Back then it was a pure-play vendor of workforce optimization (WFO) systems and was creating a portfolio of products by developing its own systems and acquiring niche vendors of call recording, quality management, workforce management, performance management and analytics. Over the years its portfolio has grown with new features, improved integration between the component parts, centralized administration and management capabilities, and a standard, modern user interface. The latest version of its core Workforce Optimization product was rated a Hot vendor in our 2015 WFO Value Index. It is still
undergoing development, and a new version is being marketed as Adaptive WFO as it uses analytics to become more information-driven.
Topics: Big Data, Customer Performance, Business Analytics, Cloud Computing, Uncategorized, Call Center
Contact Centers Need Radical Change to Meet Consumers’ Expectations
I have been involved in the contact center industry for more than 25 years and often see organizations that are slow in keeping up with consumers’ expectations; many of them seem reluctant to change, regardless of the need to do so. For example, agents of my cell phone operator ask the same four questions at the start of a call as they did 30 years ago; my bank supports several channels of communication, but it doesn’t provide the same information on all channels; and a well-known airline couldn’t tell me where my bag was for 36 hours (it was at the airport where I departed!). My list goes on, and I am sure you have your own.
Topics: Big Data, Social Media, Customer Performance, Business Analytics, Cloud Computing, Uncategorized, Call Center
Big Data Drives Price and Revenue Optimization
Information technology enables a data-driven management style that was not feasible until powerful, affordable computers became generally available. There’s no bright line marking when this became possible; the process is ongoing. People were using financial analytics long before ENIAC, the first general-purpose computer, appeared, but the metrics available were not especially timely, broadly applicable to day-to-day situations or comprehensive enough to inform most management decision-making. Even today, there are many areas of business management where companies continue to operate much as they have in the past. One of those is pricing.
Topics: Big Data, Sales Performance, Office of Finance, Customer Performance, Operational Performance, Business Analytics, Business Performance, Financial Performance, Uncategorized
Industry Veteran Brings Leadership on Sales and Marketing
If you’re a sales or marketing executive or manager, your window of business opportunity is closing rapidly. In fact it started closing the day you began your job. Time is not on your side – and your career may well hang in the balance. I want to help you shift that balance to your advantage.
Topics: Big Data, Predictive Analytics, Sales Performance, Social Media, Mobile Technology, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Uncategorized, Sales, Marketing, Sales Performance Management, Ma
Planning Is Necessary for Revenue Recognition Under ASC 606 and IFRS 15
New rules governing revenue recognition for contracts will go into effect for most companies in 2018. The Financial Accounting Standards Board (FASB), which administers Generally Accepted Accounting Principles in the U.S. (US-GAAP) has issued ASC 606, and the International Accounting Standards Board (IASB), which administers International Financial Reporting Standards (IFRS) used in most other countries, has issued IFRS 15. The two are very similar and will enforce fundamental changes in this area of accounting. The new rules will affect companies that use even moderately complex contracts in their dealings with customers. They include, for example, contracts that are structured using tiered pricing or volume discounts or ones that routinely involve modifications, such as adding or dropping users, or that allow seasonal changes to services. The changes necessitate an extensive review of an organization’s contracting and accounting policies and processes and are likely require changes to procedures and systems. Companies affected by the new rules also will need to examine their planning and budgeting processes. Those that currently use desktop spreadsheets for planning and budgeting should consider adopting dedicated planning and budgeting software in order to cope effectively with the increased complexity of planning in this new environment.
Topics: Big Data, Business Performance, Financial Performance, Uncategorized
Next Generation of Product Information Management Empowers Digital Business
Organizations in all industries face various difficulties in managing product information. The most serious is providing complete, engaging information to consumers and customers on the internet. Newly developed products, mergers and acquisitions, changes to pricing and promotions in online commerce spur business growth, but these factors also increase the amount and complexity of product-related data and content. In addition the digital economy offers a new generation of services that are sold by subscription and packaged in various options and price points. As well, global diversification of suppliers, customers and business partners forces organizations to manage data quality and consistency in multiple locations, currencies and languages.
Topics: Big Data, Sales Performance, Supply Chain Performance, PIM, Product Information Management, Sales, Market, Customer Performance, Operational Performance, Business Analytics, Business Performance, Cloud Computing, Financial Performance, Information Management, Uncategorized, Information Optimization
Can We Trust Salesforce for Business in the Cloud?
I have been meaning to write about Salesforce since its Dreamforce 2015 conference. Salesforce provides a platform, tools and applications for business and IT who claims to be the ‘no software’ company which as you will read is exactly what happened on May 10th. Heck, Salesforce is making a lot of advances on its platform, its applications and even with Analytics and the Internet of Things. These changes are at the center of what at our analyst firm calls digital business innovation. Much of what it’s doing is very good, but now I am questioning whether the company’s foundation of business processes and technology platform has reached a point at which it can’t grow any further without impacting its own customers’ operations and success. That may be a harsh statement, but I think my reasoning will become clear as you read this perspective.
Topics: Big Data, Sales Performance, NA14, Customer Performance, Operational Performance, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Financial Performance, Uncategorized
It has been more than five years since James Dixon of Pentaho coined the term “data lake.” His original post suggests, “If you think of a data mart as a store of bottled water – cleansed and packaged and structured for easy consumption – the data lake is a large body of water in a more natural state.” The analogy is a simple one, but in my experience talking with many end users there is still mystery surrounding the concept. In this post I’d like to clarify what a data lake is, review the reasons an organization might consider using one and the challenges they present, and outline some developments in software tools that support data lakes.
Topics: Big Data, Predictive Analytics, Social Media, Business Analytics, Business Intelligence, Governance, Risk & Compliance (GRC), Information Management, Uncategorized, Information Optimization
Digital Business Innovation and Enterprise Messaging Work Well Together
Organizations are facing a digital transformation, as I have written, that is rapidly changing the applications and services that businesses use to operate and deliver information. This new digital generation addresses the expectations of consumers and business partners for information and service in real time. One example of it is enterprise messaging. Recently I wrote about the shift to this technology and the challenges it poses for organizations that lack sufficient skills. However, new messaging appliances and virtualized messaging can carry some of this burden. By interconnecting them, organizations can be more confident in their ability to support the range of information and applications that operate in real time, not only for people but on devices and machines.
Topics: Big Data, Sales Performance, Social Media, Supply Chain Performance, Enterprise messaging, Internet of Things, IoT, mid, Customer Performance, Operational Performance, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Governance, Risk & Compliance (GRC), Information Management, Uncategorized
New Generation of Enterprise Messaging Supports Digital Transformation
Enterprise messaging is the technology backbone of communications for applications and systems within and between organizations. Both its importance and its complexity are growing as organizations increasingly have to provide real-time responses to business customers and consumers as well as their own business professionals who support them and their internal supply chains. The variety of use cases for enterprise messaging also is growing rapidly, expanding to the Internet of Things (IoT) market of sensors and devices including wearable technology; to new generations of applications and services for consumers and customers; to cloud computing and the shift to platform or infrastructure as a service (PaaS or IaaS); and to real-time big data and analytics. All of these innovations will enable these types of transformation to digital business that is impacting organizations around the world.
Topics: Big Data, Social Media, Supply Chain Performance, Enterprise messaging, Internet of Things, IoT, mid, Mobile Technology, Customer Performance, Operational Performance, Business Performance, Cloud Computing, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Uncategorized, Information Optimization
Internet of Things Requires Operational Intelligence
The emerging Internet of Things (IoT) is an extension of digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation means that virtually any device can generate and transmit data about its operations – data to which analytics can be applied to facilitate monitoring and a range of automatic functions. To do these tasks IoT requires what Ventana Research calls operational intelligence (OI), a discipline that has evolved from the capture and analysis of instrumentation, networking and machine-to-machine interactions of many types. We define operational intelligence as a set of event-centered information and analytic processes operating across an organization that enable people to use that event information to take effective actions and make optimal decisions. Ventana Research first began covering operational intelligence over a decade ago.
Topics: Big Data, Predictive Analytics, Supply Chain Performance, IOT, OperationalIntelligence, Real-time, Operational Intelligence, Uncategorized
Mastering Marketing Mayhem in a Meaningful, Meticulous Manner
I hope this title captures your attention; I’m trying to make a point about the chaos going on in managing and operating marketing. What marketing needs in 2016 is to manage and optimize its efforts in a more unified manner. This perspective kicks off a new series on the challenges for marketing to automate or execute tasks and manage toward maximum performance. We all know that the craft of marketing is in need of significant transformation, from the CMO throughout the entire marketing organization and all the way out to the experience of consumers and customers. But this may be a fanciful mission, as applications and technology does not really automate marketing let alone manage it. Most marketing automation products are specialized applications that are not used by marketing management, let alone front-line marketing managers; they are for specialized needs in demand generation or digital marketing that personalizes inbound and outbound interactions with contacts for the purpose of advancing dialogue and creating relationships. Marketing automation, like its cousin sales force automation, has been a placeholder category that describes only a narrow slice of marketing, and the term has been co-opted by the industry for its own purposes. Though some observers predict that CMOs will outspend CIOs and other leaders of the business in technology investments, I have debunked this ludicrous idea; even if it were true, that would not make marketing departments much more efficient in their management and operations. To counterbalance the silliness of the marketing automation dialogue, I plan to bring you a series on key areas for investment to start the conversation. Evaluating them should help Marketing demonstrate its commitment to promoting effectively its organization and its products and services. Here is an overview of the many issues in the landscape.
Topics: Big Data, Predictive Analytics, Social Media, Customer Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Financial Performance, Information Applications, Operational Intelligence, Uncategorized, CMO, Information Optimization, Sales Performance Management (SPM)
Qlik Makes Sense of its Analytics and Business Value
At the 2015 technology analyst summit in Austin, Texas, analytics and business intelligence software vendor Qlik discussed recent market and product developments and explained its roadmap and strategy for 2016. Discussion topics included its Qlik Analytics Platform and QlikView 12.0, Qlik Sense and Qlik DataMarket, applications built on the platform but also how it is expanding its analytics experience for business.
Topics: Big Data, Mobile Technology, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Uncategorized, Information Optimization
Exploiting Cryptic Data for Securities Analysis
I coined the term “cryptic data” to mean information that isn’t easy to find or access by people who could make use of it. In one instance, cryptic data offers professional investors – portfolio managers and securities analysts – a source of proprietary information that can improve their ability to pick stocks and achieve superior performance relative to their benchmarks. Automation through technology now makes collecting cryptic data substantially more efficient than manual methods and thus makes accessing it practical. In particular, Web scraping tools (what I call “data drones”) can be programmed to retrieve specific information once or on an ongoing basis. Although this data is accessible to anyone, it requires insight and experience to understand how to use it for superior investment performance.
Topics: Big Data, Analytics, Business Analytics, Business Performance, Financial Performance, Uncategorized
Informatica Advances Big Data Management for Data Preparation and Hadoop
On Monday, March 21, Informatica, a vendor of information management software, announced Big Data Management version 10.1. My colleague Mark Smith covered the introduction of v. 10.0 late last year, along with Informatica’s expansion from data integration to broader data management. Informatica’s Big Data Management 10.1 release offers new capabilities, including for the hot topic of self-service data preparation for Hadoop, which Informatica is calling Intelligent Data Lake. The term “data lake” describes large collections of detailed data from across an organization, often stored in Hadoop. With this release Informatica seeks to add more enterprise capabilities to data lake implementations.
Topics: Big Data, Business Intelligence, Information Applications, Information Management, Uncategorized
Businesses and their human resource organizations feel pressure to maximize the value of their human capital in today’s intensely competitive world. Many have made or considered investments in new applications that better exploit information to efficiently recruit, engage and retain the best talent. Advanced applications not only advance these processes but also help management assess the performance of the workforce and compensate individuals fairly so that they advance their careers and find the level of employee satisfaction in the organization. A year ago I outlined the priorities in human capital management (HCM). During the past year our research found a significant number of companies lacking a unified HCM strategy that includes processes and the applications to support it. As others advance, HR organizations that are not equipped with such skills, resources and tools risk falling behind in human capital management as it contributes to business success.
Topics: Big Data, Predictive Analytics, Governance, HCM, HR, HRMS, Workforce Management, Learning Mana, Human Capital, Mobile Technology, Wearable Computing, Customer Performance, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Financial Performance, Governance, Risk & Compliance (GRC), Information Management, Uncategorized, Financial Performance Management (FPM)
I recently attended the SAS Analyst Summit in Steamboat Springs, Colo. (Twitter Hashtag #SASSB) The event offers an occasion for the company to discuss its direction and to assess its strengths and potential weaknesses. SAS is privately held, so customers and prospects cannot subject its performance to the same level of scrutiny as public companies, and thus events like this one provide a valuable source of additional information.
Topics: Big Data, Predictive Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Information Applications, Information Management, Uncategorized
Digital Technology Agenda for Business in 2016
Technology innovation is accelerating faster than companies can keep up with. Many feel pressure to adopt new strategies that technology makes possible and find the resources required for necessary investments. In 2015 our research and analysis revealed many organizations upgrading key business applications to operate in the cloud and some enabling access to information for employees through mobile devices. Despite these steps, we find significant levels of digital disruption impacting every line of business. In our series of research agendas for 2016 we outline the areas of technology that organizations need to understand if they hope to optimize their business processes and empower their employees to handle tasks and make decisions effectively. Every industry, line of business and IT department will need to be aware of how new technology can provide opportunities to get ahead of, or at least keep up with, their competitors and focus on achieving the most effective outcomes.
Topics: Big Data, Predictive Analytics, Sales Performance, Supply Chain Performance, Governance, Mobile Technology, Operational Performance Management (OPM), Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Location Intelligence, Operational Intelligence, Uncategorized, Workforce Performance, Business Performance Management (BPM), Financial Performance Management (FPM), Information Optimization, Sales Performance Management (SPM)
Spark Summit Shows Momentum in Adoption of Apache Spark
Last week I attended Spark Summit East 2016 at the New York Hilton Midtown. It revealed several ways in which Spark technology might impact the big data market.
Topics: Big Data, Predictive Analytics, Business Analytics, Business Intelligence, Information Applications, Information Management, Operational Intelligence, Uncategorized
Cryptic Data: Challenges and Rewards in Finding and Using It
Using information technology to make data useful is as old as the Information Age. The difference today is that the volume and variety of available data has grown enormously. Big data gets almost all of the attention, but there’s also cryptic data. Both are difficult to harness using basic tools and require new technology to help organizations glean actionable information from the large and chaotic mass of data. “Big data” refers to extremely large data sets that may be analyzed computationally to reveal patterns, trends and associations, especially those related to human behavior and interaction. The challenges in dealing with big data include having the computational power that can scale to the processing requirements for the volumes involved; analytical tools to work with the large data sets; and governance necessary to manage the large data sets to ensure that the results of the analysis are accurate and meaningful. But that’s not all organizations have to deal with now. I’ve coined the term “cryptic data” to focus on a different, less well known sort of data challenge that many companies and individuals face.
Topics: Big Data, Data Science, Planning, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, FP&A, Human Capital, Marketing, Office of Finance, Operational Performance Management (OPM), Budgeting, Connotate, cryptic, equity research, Finance Analytics, Kofax, Statistics, Operational Performance, Analytics, Business Analytics, Business Performance, Financial Performance, Business Performance Management (BPM), Datawatch, Financial Performance Management (FPM), Kapow, Sales Performance Management (SPM)
The imperative to transform the finance department to function in a more strategic, forward-looking and action-oriented fashion has been a consistent theme of practitioners, consultants and business journalists for two decades. In all that time, however, most finance and accounting departments have not changed much. In our benchmark research on the Office of Finance, nine out of 10 participants said that it’s important or very important for finance departments to take a strategic role in running their company. The research also shows a significant gap between this objective and how well most departments perform. A large majority (83%) said they perform the core finance functions of accounting, fiscal control, transaction management, financial reporting and internal auditing, but only 41 percent said they play an active role in their company’s management. Even fewer (25%) have implemented a high degree of automation in their core finance functions and actively promote process and analytical excellence.
Topics: Big Data, Planning, Predictive Analytics, Social Media, Governance, GRC, Human Capital, Mobile Technology, Office of Finance, Budgeting, close, Continuous Accounting, Continuous Planning, end-to-end, Tax, Tax-Datawarehouse, Analytics, Business Analytics, Business Collaboration, Business Performance, CIO, Cloud Computing, Financial Performance, In-memory, Uncategorized, CFO, CPQ, Risk, CEO, Financial Performance Management, FPM
Research Agenda: Big Data and Information Optimization in 2016
The big data market continues to expand and enable new types of analyses, new business models and new revenues streams for organizations that implement these capabilities. Following our previous research into big data and information optimization, we’ll investigate the technology trends affecting both of these domains as part of our 2016 research agenda.
Topics: Big Data, Analytics, Business Analytics, Business Intelligence, Data Preparation, In-memory, Information Management, Operational Intelligence, Uncategorized, Information Optimization
Research Agenda: Using Business Analytics to Make the Most of Data in 2016
Throughout the course of our research in 2016, we’ll be exploring ways in which organizations can maximize the value of their data. Ventana Research believes that analytics is the engine and data is the fuel to power better business decisions. Several themes emerged from our benchmark research on incorporating data and analytics into organizational processes, and we will follow them in our 2016 Business Analytics Research Agenda:
Topics: Big Data, Predictive Analytics, Mobile Technology, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Information Management, Operational Intelligence, Information Optimization
Pardon the Interruption: Industry Veteran Returns to Ventana Research
Some followers of Ventana Research may recall my work here several years ago. Here and elsewhere I have spent most of my career in the data and analytics markets matching user requirements with technologies to meet those needs. I’m happy to be returning to Ventana Research to resume investigating ways in which organizations can make the most of their data to improve their business processes; for a first look, please see our 2016 research agenda on Big Data and Information Optimization. I relish the opportunity to conduct primary market research in the form of Ventana’s well-known benchmark research and to help end users and vendors apply the information collected in those studies.
Topics: Big Data, Predictive Analytics, Analytics, Business Analytics, Business Intelligence, Information Management, Internet of Things, IOT, Operational Intelligence, Unicorns, Information Optimization
Research Agenda: Transforming Customer Engagement in 2016
I have been involved in the contact center, CRM and customer engagement business for more than 25 years. Yet only in the past few years have I seen much change. Until recently nearly all organizations focused on handling customer interactions as efficiently and inexpensively as possible; few made much effort to manage customer relationships over the complete customer life cycle. However, over the last 18 months, the scene has begun to change very rapidly, and I expect that to continue and even accelerate during 2016.
Topics: Big Data, Customer Analytics, Customer Engagement, Customer Experience, Speech Analytics, Voice of the Customer, Analytics, Cloud Computing, Customer & Contact Center, Customer Service, Uncategorized, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
Anodot Provides Anomaly Detection and Operational Intelligence
A new company has emerged in the market for real-time analytics software. Anodot came out of stealth mode in late 2015 with $3 million in funding. It is led by three founders: CEO David Drai, whose company Cotendo was acquired by networking company Akamai Technologies in 2012; Ira Cohen, chief data scientist, who previously held that position at Hewlett-Packard; and Shay Lang, who serves as VP of R&D. Unlike most vendors in the space, the company is delivering anomaly detection and operational intelligence through software as a service (SaaS).
Topics: Big Data, Predictive Analytics, Operational Performance Management (OPM), Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Internet of Things, Operational Intelligence, Uncategorized
Customer Experience in 2016 Infuses New Digital Technologies
There were significant technology developments in customer experience management during 2015. Multichannel contact centers in the cloud took hold of the contact center infrastructure market; I counted 21 vendors offering such services. A variety of vendors entered the market for customer analytics, combining analysis of structured data, speech recordings, text, desktop data, Web contacts, and events and processes to provide a comprehensive “360-degree” view of the customer and customer journey maps to track individual interactions over time. In addition a range of self-service or digital customer service applications became available, including mobile apps, voice-activated virtual agents, interactive video and Q&A websites and chat driven by natural-language processing. Digitally connected devices (the Internet of Things [IoT]) and wearable devices began to emerge. In 2016 I will track and try to anticipate the impact these technologies have on the customer experience.
Topics: Big Data, Customer Analytics, Customer Engagement, Customer Experience, Speech Analytics, Voice of the Customer, Customer Performance, Analytics, Cloud Computing, Customer Service, Uncategorized, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
IBM Redesigns Cognos to Improve User Experience and Self-Service
IBM redesigned its business intelligence platform, now called IBM Cognos Analytics. Expected to be released by the end of 2015, the new version includes features to help end users model their own data without IT assistance while maintaining the centralized governance and security that the platform already has. Our benchmark research into information optimization shows that simplifying access to information is important to virtually all (97%) participating organizations, but it also finds that only one in four (25%) are satisfied with their current software for doing that. Simplification is a major theme of the IBM Cognos redesign.
Topics: Big Data, Mobile Technology, Wearable Computing, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Uncategorized, Visualization, Cognos, Information Optimization, Risk & Compliance (GRC), Watson, cognos analytics
Diabolocom Provides Customer Interaction in the Cloud Solution
In our benchmark research into contact centers in the cloud, nearly two-thirds (63%) of companies said that adopting applications in the cloud would enable them to improve how they handle customer interactions, and slightly fewer than half (44%) said that adopting communication systems in the cloud would deliver similar benefits. Several vendors now provide such systems. Diabolocom is the latest one to brief me on its products. Founded in 2005 and having around 30 employees, it has headquarters in France (and its website is in French), but it has a global presence, primarily for supporting French companies that have offices around the world. Its contact center products are available only in the cloud and extend beyond basic multichannel communications to other applications connected with handling customer interactions.
Topics: Big Data, Customer Analytics, Customer Engagement, Customer Experience, Speech Analytics, Voice of the Customer, Customer Performance, Analytics, Cloud Computing, Customer Service, Uncategorized, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
Oracle Advances Applications and Technology for Customer Experience
Oracle has built one of the world’s largest software portfolios through a combination of developing products in-house and acquisitions. In the last few years it has put great effort into transitioning from providing its applications as on-premises products to making them available in the cloud. It also has worked to add customer experience capabilities to its range of business applications. Improving the customer experience is a top priority as our next generation customer engagement research found in almost three quarters (74%) of organization. In doing so it has developed a common user interface across the applications to address modern user expectations and has built a platform to support common capabilities in all its products. Recently I had the opportunity to study the strides Oracle has made in these areas as well as to identify some issues that still need to be resolved.
Topics: Big Data, Customer Engagement, Customer Experience, Customer Performance, Analytics, Cloud Computing, Customer Service, Uncategorized, Call Center, Contact Center, CRM
Tableau Continues Evolution of Analytics Platform
Tableau Software’s annual conference, which company spokespeople reported had more than 10,000 attendees, filled the MGM Grand in Las Vegas. Various product announcements supported the company’s strategy to deliver value to analysts and users of visualization tools. Advances include new data preparation and integration features, advanced analytics and mapping. The company also announced the release of a stand-alone mobile application called Vizable . One key message management aimed to promote is that Tableau is more than just a visualization company.
Topics: Big Data, Tableau, Mobile Technology, data viz, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Visualization, Information Optimization, Risk & Compliance (GRC)
Informatica Navigates Carefully to Broader Data Management
This has been a dramatic year for Informatica, a major provider of data integration software. In August it was acquired and taken private by Permira funds and Canada Pension Plan Investment Board for about US$5.3 billion. This change was accompanied by shifts in its management. CEO Sohaib Abbasi became chairman and now has left, and many executives were replaced while Anil Chakravathy became CEO from being the Chief Product Officer. The new owners appear to have shifted the company’s strategic priorities to emphasize profitability with reduced headcount and return on the purchase investment. Despite these changes, during the past six months Informatica has made key product announcements that will impact its future and the future of data management.
Topics: Big Data, Data Quality, Master Data Management, MDM, Operational Performance Management (OPM), Cloud Computing, Data Integration, Data Management, Data Preparation, Governance, Risk & Compliance (GRC), Informatica, Information Management, Business Performance Management (BPM), Information Optimization, Risk & Compliance (GRC)
Datawatch Bolsters Data Preparation for all Information Assets
The need for businesses to process and analyze data has grown in intensity along with the volumes of data they are amassing. Our benchmark research consistently shows that preparing data is the most widespread impediment to analytic and operational efficiency. In our recent research on data and analytics in the cloud, more than half (55%) of organizations said that preparing data for analysis is a major impediment, followed by other preparatory tasks: reviewing data for quality and consistency (48%) and waiting for data and information (28%). Organizations that want to apply analytics to make more effective decisions and take prompt actions need to find ways to shorten the work that comes before it. Conventional analytics and business intelligence tools are not designed for data preparation, but new software tools can enable business users independently or in concert with IT to perform the tasks needed.
Topics: Big Data, Sales Performance, Supply Chain Performance, Human Capital, Marketing, Monarch, Operational Performance Management (OPM), Customer Performance, Business Analytics, Business Intelligence, Business Performance, Data Preparation, Financial Performance, Governance, Risk & Compliance (GRC), Information Management, Uncategorized, Business Performance Management (BPM), Datawatch, Information Optimization, Risk & Compliance (GRC)
Transera is an established vendor of contact center in the cloud systems and analytics, and as I discovered at the Salesforce Dreamforce ’15 conference and during a recent briefing, it has added support for managing voice interactions for users of salesforce.com Service Cloud. Its core product, Global Omni-Channel Contact Center, now supports voice, email, chat and Twitter, which are managed centrally through a routing engine that treats all interactions in the same way. This ensures that companies have a central view of how interactions are being handled, and they can manage the rules to guide customers to the channel most appropriate for what they are trying to achieve and route the interaction to the most qualified person. An enhanced scripting engine allows users to script the ways in which different types of interactions are handled, and a recording engine captures all calls and makes them available for analysis. Transera also has added capabilities to produce real-time analysis of contact center performance through dashboards and analytics that show a single view across all sites and data sources. Operational and business metrics can be calculated using multiple data sources, and a variety of visualization capabilities enable the analysis can be displayed in the format most appropriate for a specific user and occasion. All the systems are available in the cloud and are scalable enough to support companies of all sizes, including those with centers in multiple sites.
Topics: Big Data, Customer Engagement, Customer Experience, Speech Analytics, Customer Performance, Analytics, Business Analytics, Cloud Computing, Customer Service, Uncategorized, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
Pentaho Poised for Exploiting Internet of Things
PentahoWorld 2015, Pentaho’s second annual user conference, held in mid-October, centered on the general availability of release 6.0 of its data integration and analytics platform and its acquisition by Hitachi Data Systems (HDS) earlier this year. Company spokespeople detailed the development of the product in relation to the roadmap laid out in 2014 and outlined plans for its integration with those of HDS and its parent Hitachi. They also discussed Pentaho’s and HDS’s shared intentions regarding the Internet of Things (IoT), particularly in telecommunications, healthcare, public infrastructure and IT analytics.
Topics: Big Data, Pentaho, Mobile Technology, Wearable Computing, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, IOT, Operational Intelligence, Uncategorized, Information Optimization, Risk & Compliance (GRC)
The enterprise resource planning (ERP) system is a pillar of nearly every company’s record-keeping and management of business processes. It is essential to the smooth functioning of the accounting and finance functions. In manufacturing and distribution, ERP also can help plan and manage inventory and logistics. Some companies use it to handle human resources functions such as tracking employees, payroll and related costs. Yet despite their ubiquity, ERP systems have evolved little since their introduction a quarter of a century ago. The technologies shaping their design, functions and features had been largely unchanged. As a measure of this stability, our Office of Finance benchmark research found that in 2014 companies on average were keeping their ERP systems one year longer than they had in 2005.
Topics: Big Data, Microsoft, SAP, Social Media, Supply Chain Performance, ERP, FP&A, Human Capital, Mobile Technology, NetSuite, Office of Finance, Reporting, close, closing, Controller, dashboard, Reconciliation, Operational Performance, Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Collaboration, Financial Performance, IBM, Oracle, Uncategorized, CFO, Data, finance, Financial Performance Management, FPM, Intacct
The emerging Internet of Things (IoT) extends digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This innovation enables devices designed for it to generate and transmit data about their operations; analytics using this data can facilitate monitoring and a range of automatic functions.
Topics: Big Data, Predictive Analytics, Mobile Technology, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, IOT, Operational Intelligence, Uncategorized
Three Tools to Boost Omnichannel Customer Experience
Much is written about omnichannel customer experience, and various software vendors now claim to focus on the customer experience. With various degrees of credibility they range from providers of communication channel management to workforce optimization, voice of the customer, self-service, analytics and even CRM. This bandwagon raisesthe question of what omnichannel customer experience really is and how companies can achieve it. Our benchmark research into next-generation customer engagement shows that consumers now engage with companies through as many as 17 channels of engagement though companies on average support six. The research also shows that every business group, with the exception of IT, engages with prospects and customers at different times during the customer life cycle. Customers today, we know, are more demanding than ever. They want to choose the channel and time of engagement. They want the process to be easy, and they want to be recognized so responses can be personal to them. They expect consistent responses regardless of channel and not to have to repeat actions if they change channels. They want agents empowered to resolve an issue at the first try. Finally, at the end of the interaction they want to feel good about how it went and the outcome.
Topics: Big Data, Sales Performance, Customer Analytics, Customer Experience, Speech Analytics, Analytics, Business Collaboration, Cloud Computing, Customer & Contact Center, Customer Service, Operational Intelligence, Uncategorized, Call Center, Contact Center, Contact Center Analytics, Text Analytics
The State of Product Information Management Software for Business and IT
The importance of product information management (PIM) has become clear in recent years and especially as it relates to master data management. As I recently wrote handling this business process effectively and using capable software should be priorities for any organization in marketing and selling its products and services but also interconnecting the distributed supply chain. Our research on product information management can help organizations save time and resources in efforts to ensure that product information is an asset to facilitate efficiency in many business processes. Through years of benchmarking, we have developed a blueprint for managing and improving product information. Using this approach enables companies to more effectively align and link their activities and processes. Of course achieving effectiveness also requires using applications that create consistent, reliable product information. We regularly update our Value Index for PIM to enable companies to evaluate vendors and their applications’ suitability for use in all business processes requiring product information.
Topics: Big Data, Master Data Management, Sales Performance, Supply Chain Performance, Enterworks, Marketing, Operational Performance Management (OPM), Stibo Systems, Webon, Business Performance, CIO, Financial Performance, IBM, Informatica, Information Management, Oracle, Information Optimization, Product Information Management, Riversand
Product Information Management Trumps Master Data Management
Ventana Research defines product information management (PIM) as the practice of using information, applications and other technology to effectively support product-related processes across the customer, commerce and supply chain. As organizations increase the number and diversity of products and services they offer to customers and partners, they increasingly need to address limitations in the ways they manage and distribute product information, including related attributes and content that describes the products. At the same time, competitive pressures require them to be able to incorporate large amounts of new content – video and images, for example – quickly while ensuring that the information presented to customers is accurate, operational processes run uninterrupted and timely data is available for business analysis. In an environment in which consumers, suppliers and partners use multiple channels to get to product information – including websites, kiosks, smartphones and tablets – it is essential that the organization always be able to present complete and up-to-date product information to inspire interest and facilitate purchases.
Topics: Big Data, Master Data Management, Supply Chain Performance, Governance, Marketing, Operational Performance Management (OPM), CIO, Information Management, Business Performance Management (BPM), Financial Performance Management (FPM), Information Optimization, Product Information Management, Sales Performance Management (SPM)
Subscriber Experience Impacts Recurring Revenue
The digital economy has changed the way many companies provide products. Some no longer deliver packaged products but provide them as services over a network, typically the Internet. Telecommunications providers in particular are familiar with this business model and have developed processes and systems that use innovations such as product bundles that include elements of fixed charges (such as cost of installation) and variable charges based on usage (such as the number of calls made) and means of registering customers on the network, collecting usage data, invoicing and collections. This model has been adopted increasingly by the software industry, replacing a single license fee and maintenance charges for on-premises products with software as a service in which users access products over the Internet and pay per user and/or for usage. Adoption of this model by other types of business has led them to think of customers as subscribers.
Topics: Big Data, Sales Performance, Customer Analytics, Customer Engagement, Customer Experience, Marketing, Customer Performance, Operational Performance, Analytics, Cloud Computing, Customer Service, Financial Performance, CRM
Splunk Takes on Internet of Things and Bolsters Enterprise Security
Splunk’s annual gathering, this year called .conf 2015, in late September hosted almost 4,000 Splunk customers, partners and employees. It is one of the fastest-growing user conferences in the technology industry. The area dedicated to Splunk partners has grown from a handful of booths a few years ago to a vast showroom floor many times larger. While the conference’s main announcement was the release of Splunk Enterprise 6.3, its flagship platform, the progress the company is making in the related areas of machine learning and the Internet of Things (IoT) most caught my attention.
Topics: Big Data, Predictive Analytics, Machine Learning, IT Analytics & Performance, Operational Performance, Plunk, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Management, Internet of Things, Operational Intelligence, Data, Information Optimization
The concept and implementation of what is called big data are no longer new, and many organizations, especially larger ones, view it as a way to manage and understand the flood of data they receive. Our benchmark research on big data analytics shows that business intelligence (BI) is the most common type of system to which organizations deliver big data. However, BI systems aren’t a good fit for analyzing big data. They were built to provide interactive analysis of structured data sources using Structured Query Language (SQL). Big data includes large volumes of data that does not fit into rows and columns, such as sensor data, text data and Web log data. Such data must be transformed and modeled before it can fit into paradigms such as SQL.
Topics: Big Data, Predictive Analytics, Software as a Service, IT Analytics & Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Management, Operational Intelligence, Data, Information Optimization
Operationalize Predictive Analytics for Significant Business Impact
One of the key findings in our latest benchmark research into predictive analytics is that companies are incorporating predictive analytics into their operational systems more often than was the case three years ago. The research found that companies are less inclined to purchase stand-alone predictive analytics tools (29% vs 44% three years ago) and more inclined to purchase predictive analytics built into business intelligence systems (23% vs 20%), applications (12% vs 8%), databases (9% vs 7%) and middleware (9% vs 2%). This trend is not surprising since operationalizing predictive analytics – that is, building predictive analytics directly into business process workflows – improves companies’ ability to gain competitive advantage: those that deploy predictive analytics within business processes are more likely to say they gain competitive advantage and improve revenue through predictive analytics than those that don’t.
Topics: Big Data, Microsoft, Predictive Analytics, SAS, Social Media, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Operational Intelligence, Oracle, Information Optimization, SPSS, Rapidminer
Insights from Dreamforce ‘15 Exceeds Expectations
I recently attended my first U.S. Dreamforce, the annual salesforce.com event designed to showcase its products and services as well as those of its partners, and I was impressed. I was told that Dreamforce ‘15 would be big, and it was – just about every hotel, restaurant, meeting room in San Francisco seemed to have been taken over for the week, and still the company had to bring in a cruise ship to accommodate people and events. I was told it would be manic, and it was – more than 100,000 attendees, and buses and cabs blocking surrounding streets. I was told it would be busy, and it was – more than 600 conference sessions. I was told it would educational, and it was – I gained many insights into new product developments, both from salesforce and several of its partners. Here are some of the key takeaways for my research practice.
Topics: Big Data, Sales Performance, Social Media, Customer Analytics, Customer Experience, Marketing, Mobile Technology, Speech Analytics, Wearable Computing, Customer Performance, Analytics, Business Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
Business Case for Predictive Analytics is Simpler Than You Think
Our benchmark research into predictive analytics shows that lack of resources, including budget and skills, is the number-one business barrier to the effective deployment and use of predictive analytics; awareness – that is, an understanding of how to apply predictive analytics to business problems – is second. In order to secure resources and address awareness problems a business case needs to be created and communicated clearly wherever appropriate across the organization. A business case presents the reasoning for initiating a project or task. A compelling business case communicates the nature of the proposed project and the arguments, both quantified and unquantifiable, for its deployment.
Topics: Big Data, Microsoft, Predictive Analytics, SAS, Social Media, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Operational Intelligence, Oracle, Information Optimization, SPSS, Rapidminer
Cloud-Based Analytics Requires Hybrid Data Access and Integration
As I discussed in the state of data and analytics in the cloud recently, usability is a top evaluation criterion for organizations in selecting cloud-based analytics software. Data access of cloud and on-premises systems are essential antecedents of usability. They can help business people perform analytic tasks themselves without having to rely on IT. Some tools allow data integration by business users on an ad hoc basis, but to provide an enterprise integration process and a governed information platform, IT involvement is often necessary. Once that is done, though, using cloud-based data for analytics can help, empowering business users and improving communication and process .
Topics: Big Data, Sales Performance, Software as a Service, Mobile Technology, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Information Management, Operational Intelligence, Data
Calabrio Supercharges Workforce Optimization with Analytics for Customer Engagement
Calabrio is a vendor of workforce optimization software whose core product is Calabrio ONE. It includes the common workforce optimization applications: call recording, quality management, workforce management and analytics. The company is rated Hot in our 2015 Workforce Optimization Value Index, and its product suite is the highest rated in the Usability category. Since our assessment, each of the modules has undergone upgrades, Calabrio has introduced more cloud-based services, and its analytics has undergone extensive changes to support customer experience management. The aim of these enhancements is to provide a single view of the customer that includes customer interactions across all channels, help companies streamline processes through workflow and automation, support more users and provide more deployment options. The Calabrio ONE Cloud Edition supports the full suite in a multitenant environment and is scalable to support companies of all sizes. It also enables users to store data, such as call recordings, in cloud-based services such as Amazon Web Services. I have reviewed these enhancements and note the most significant changes.
Topics: Big Data, Customer Feedback Management, Customer Performance, Business Analytics, Cloud Computing, Call Center
NICE Delivers Customer Journey Maps for Customer Engagement
Through a continuing program of acquisitions and internal development, NICE Systems has transitioned from being a vendor of workforce optimization systems to one focused on aspects of the customer experience, notably voice of the customer (VOC), customer engagement analytics and customer journey mapping. It is also moving to cloud-based services from products installed on customers’ premises and is taking a business-solution approach (providing previously integrated and configured products that address specific business issues) rather than general-purpose products. All of these changes are evident in its latest services, which link VOC, real-time journey mapping and predictive analytics to address common customer service and engagement issues. The foundation for these packages are products I have previously covered – Fizzback for multichannel customer surveying and feedback analysis and Causata for a big data analytics platform that includes predictive analytics capabilities – along with its own customer engagement analytics platform, which can link customer data from disparate sources. The result, for example, is that journey maps can show all interactions on all channels a customer uses to try to resolve issues, including the customer sentiment at each touch point and the outcome of the journey.
Topics: Big Data, Customer Feedback Management, Customer Performance, Business Analytics, Business Collaboration, Cloud Computing, Call Center
Pitney Bowes Doubles Down on Customer Engagement
From its history of managing postal mail, Pitney Bowes has expanded into products for data management, analytics and location intelligence, as my colleague Mark Smith noted. Continuing this expansion through internal development and acquisitions of vendors such as Portrait Software and RTC, it has added to its portfolio products that include customer information management and customer engagement.
Topics: Big Data, Customer Performance, Business Analytics, Business Collaboration, Cloud Computing, Call Center
Data and Analytics in the Cloud is a Reality Today
Our recently completed benchmark research on data and analytics in the cloud shows that analytics deployed in cloud-based systems is gaining widespread adoption. Almost half (48%) of participating organizations are using cloud-based analytics, another 19 percent said they plan to begin using it within 12 months, and 31 percent said they will begin to use cloud-based analytics but do not know when. Participants in various areas of the organization said they use cloud-based analytics, but front-office functions such as marketing and sales rated it important more often than did finance, accounting and human resources. This front-office focus is underscored by the finding that the categories of information for which cloud-based analytics is most often deemed important are forecasting (mentioned by 51%) and customer-related (47%) and sales-related (33%) information.
Topics: Big Data, Software as a Service, Operational Performance Management (OPM), Analytics, Business Analytics, Business Collaboration, Business Intelligence, Customer & Contact Center, Operational Intelligence, Business Performance Management (BPM), Data, Information Optimization
Tagetik’s Solid Financial Performance Management Suite
Tagetik is a long-established vendor of financial performance management (FPM) software. Its full-featured suite includes planning, budgeting, consolidation, close management, disclosure management, analysis, dashboards and reporting. The software can be deployed on premises or in the cloud as multitenant software as a service or in a private cloud. Tagetik also offers pre-built integration with SAP and SAP HANA, Microsoft SharePoint and Qlik to best support a range of financial management needs.
Topics: Big Data, Governance, Human Capital, Office of Finance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Dashboards, Financial Performance
Optimization Analytics Comes to the Mass Market
Optimization is the application of algorithms to sets of data to guide executives and managers in making the best decisions. It’s a trending topic because using optimization technologies and techniques to better manage a variety of day-to-day business issues is becoming easier. I expect optimization, once the preserve of data scientists and operations research specialists will become mainstream in general purpose business analytics over the next five years.
Topics: Big Data, Performance Management, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Performance, Financial Performance, Information Management, Price Optimization
Data Preparation is Essential for Predictive Analytics
Our research into next-generation predictive analytics shows that along with not having enough skilled resources, which I discussed in my previous analysis, the inability to readily access and integrate data is a primary reason for dissatisfaction with predictive analytics (in 62% of participating organizations). Furthermore, this area consumes the most time in the predictive analytics process: The research finds that preparing data for analysis (40%) and accessing data (22%) are the parts of the predictive analysis process that create the most challenges for organizations. To allow more time for actual analysis, organizations must work to improve their data-related processes.
Topics: Big Data, Microsoft, Predictive Analytics, alteryx, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Operational Intelligence, Oracle, Information Optimization
The Strategic Tax Department is a Priority for Longview
Longview’s recent Dialog user group meeting highlighted the company’s continued commitment to providing much needed automation tools for improving tax department performance – tools that enable the tax function to play a more strategic role in the management of a company. The sessions also covered the capabilities contained in the company’s latest release, Longview 7.2 Update 2 and gave customers a detailed product evolution roadmap following their merger with arcplan.
Topics: Big Data, LongView, Analytics, Business Performance, Financial Performance
Is NPS the Best Measure of Customer Experience?
Recently my colleague Tony Cosentino wrote an analyst perspective asserting that big data analytics will displace net promoter score (NPS) for more effectively measuring the entire customer experience. This prompted a response from Maxie Schmidt-Subramanian, asserting that big data and NPS aren’t the only ways to measure customer experience success. The main point of Tony’s piece, as I interpret it, is that NPS is just a number, but big data analytics can reveal much more about customer behavior and intentions, and it can link these to business outcomes. On the other hand Maxie argues that whether or not companies use NPS, when it comes to measuring the customer experience, they rely too much on surveys and no one metric does the entire job. While to a large extent I agree with both arguments, from a business perspective I don’t think either addresses three very important questions. The first is what actually is the customer experience? Second, how should it be measured? And third, what is the best use of big data in relation to customer experience?
Topics: Big Data, Customer Performance, Operational Performance, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Call Center
Skills Gap Challenges Potential of Predictive Analytics
The Performance Index analysis we performed as part of our next-generation predictive analytics benchmark research shows that only one in four organizations, those functioning at the highest Innovative level of performance, can use predictive analytics to compete effectively against others that use this technology less well. We analyze performance in detail in four dimensions (People, Process, Information and Technology), and for predictive analytics we find that organizations perform best in the Technology dimension, with 38 percent reaching the top Innovative level. This is often the case in our analyses, as organizations initially perform better in the details of selecting and managing new tools than in the other dimensions. Predictive analytics is not a new technology per se, but the difference is that it is becoming more common in business units, as I have written.
Topics: Big Data, Microsoft, Predictive Analytics, alteryx, Operational Performance Management (OPM), Customer Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Location Intelligence, Oracle, Information Optimization
Predictive Analytics: Investing and Selecting Software Properly
To impact business success, Ventana Research recommends viewing predictive analytics as a business investment rather than an IT investment. Our recent benchmark research into next-generation predictive analytics reveals that since our previous research on the topic in 2012, funding has shifted from general business budgets (previously 44%) to line of business IT budgets (previously 19%). Now more than half of organizations fund such projects from business budgets: 29 percent from general business budgets and 27 percent from a line of business IT budget. This shift in buying reflects the mainstreaming of predictive analytics in organizations, which I recently wrote about .
Topics: Big Data, Microsoft, Predictive Analytics, alteryx, Customer Performance, Analytics, Business Analytics, Business Intelligence, Operational Intelligence, Oracle, Business Performance Management (BPM), Rapidminer
Predictive Analytics Enters the Business Mainstream
Our recently released benchmark research into next-generation predictive analytics shows that in this increasingly important area many organizations are moving forward in the dimensions of information and technology, but most are challenged to find people with the right skills and to align organizational processes to derive business value from predictive analytics.
Topics: Big Data, Predictive Analytics, alteryx, Customer Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Operational Intelligence
Companies Need Disruptive Customer Experience Technologies
Our benchmark research into next-generation customer engagement finds that the top priorities in customer service for companies are to improve the customer experience (said 74%) and their customer service performance (70%). To do this, the technological steps most companies expect to improve customer engagement are to deploy collaboration systems, redesign the customer portal, deploy internal mobile applications, deploy mobile customer service apps and use social media for customer service. All of these we regard as potentially innovative and required digital technologies. Deeper analysis of the results finds key primary drivers for these priorities. Employees across the organization are handling customer interactions, but customers expect consistent responses no matter who they engage with. Customers are using more electronic channels of engagement, but here, too, they expect consistent responses. People on both sides are engaging more while they are on the move, so mobile support for employees and customers has become essential. Let’s consider how each of these five technologies can help companies meet these challenges and improve customer engagement.
Topics: Big Data, Customer Performance, Business Analytics, Business Collaboration, Cloud Computing, Call Center
Big Data Analytics Will Displace Net Promoter Score (NPS) for Measuring Customer Experience
Our benchmark research into big data analytics shows that marketing in the form of cross-selling and upselling (38%) and customer understanding (32%) are the top use cases for big data analytics. Related to these uses, organizations today spend billions of dollars on programs seeking customer loyalty and satisfaction. A powerful metric that impacts this spending is net promoter score (NPS), which attempts to connect brand promotion with revenue. NPS has proven to be a popular metric among major brands and Fortune 500 companies. Today, however, the advent of big data systems brings the value and the accuracy of NPS into question. It and similar loyalty metrics face displacement by big data analytics capabilities that can replace stated behavior and survey-based attitudinal data with actual behavioral data (sometimes called revealed behavior) combined with unstructured data sources such as social media. Revealed behavior shows what people have actually done and thus is a better predictor of what they will do in the future than what they say they have done or intend to do in the future. With interaction through various customer touch points (the omnichannel approach) it is possible to measure both attitudes and revealed behavior in a digital format and to analyze such data in an integrated fashion. Using innovative technology such as big data analytics can overcome three inherent drawbacks of NPS and similar customer loyalty and satisfaction metrics.
Topics: Big Data, Customer Performance, Business Analytics, Business Performance, Operational Intelligence, Information Optimization
Envision Offers Comprehensive Suite for Workforce Optimization
Envision is a vendor of workforce optimization software that I have been following for many years. It is rated a Hot vendor in our 2015 Workforce Optimization Value Index. It offers a full suite of products, including interaction capture, quality monitoring, workforce management, coaching and training, agent compensation management and workforce analytics. In an analysis last year I wrote about how, in an effort to make workforce optimization more accessible and affordable, it created an architecture optimized to run in the cloud. During a recent update, CEO and founder Rodney Kuhn said that the company continues to focus on the cloud while adding new capabilities, especially in interaction capture, agent evaluation and coaching, and analytics.
Topics: Big Data, Customer Performance, Cloud Computing, Call Center
OnviSource Opens Up Workforce Optimization for Contact Center Excellence
OnviSource is a 10-year-old vendor of workforce optimization software whose core product, OnviCenter 7, includes interaction capture, quality monitoring, workforce management, coaching and training, and workforce analytics. The company is rated a Hot vendor in our 2015 Workforce Optimization Value Index. It scored highly in the Manageability, Usability and Reliability categories but was held back by lack of compensation management (for which it provides input to third-party products) and some analytics capabilities. The 2015 Workforce Optimization Value Index shows how competitive the workforce optimization market is: The top seven vendors are separated by fewer than three percentage points, OnviSource ranking fourth.
Topics: Big Data, Customer Experience, Customer Performance, Cloud Computing, Call Center
IBM’s Vision user conference brings together customers who use its software for financial and sales performance management (FPM and SPM, respectively) as well as governance, risk management and compliance (GRC). Analytics is a technology that can enhance each of these activities. The recent conference and many of its sessions highlighted IBM’s growing emphasis on making more sophisticated analytics easier to use by – and therefore more useful to – general business users and their organizations. The shift is important because the IT industry has spent a quarter of a century trying to make enterprise reporting (that is, descriptive analytics) suitable for an average individual to use with limited training. Today the market for reporting, dashboards and performance management software is saturated and largely a commodity, so the software industry – and IBM in particular – is turning its attention to the next frontier: predictive and prescriptive analytics. Prescriptive analytics holds particular promise for IBM’s analytics portfolio.
Topics: Big Data, Planning, Predictive Analytics, Governance, Human Capital, Budgeting, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Performance, Cloud Computing, Financial Performance, Visualization
Corvisa Brings New Generation of Contact Center Communications in the Cloud
Contact centers in the cloud are increasingly popular alternatives to managing them on a company’s own premises. Running many business applications on hardware owned and managed by a third party is relatively straightforward and requires less support internally. Also the payment model changes from a license to a recurring fee, and typically the vendor provides updates as part of the fee. The challenge with placing a contact center in the cloud is that it is not a single system or even a collection of similar systems. The center includes infrastructure systems to manage communication channels, a network to support telephone extensions and access points to business applications, specialist systems such as routing and IVR, business applications (such as ERP, CRM and workforce management) and performance management and analytics systems; increasingly the contact center has to support mobile and social media as well. Moving all these to the cloud in an integrated manner is a complex task.
Topics: Big Data, Customer Feedback Management, Customer Performance, Business Collaboration, Cloud Computing, Call Center
Salesforce Helps Companies Innovate in Customer Management
In recent years I have tracked Salesforce, its product development and its announcements. Despite having grown into a giant corporation, it continues to introduce innovations. At a recent analyst day in the U.K., I followed up on the company’s overall direction, some key product developments and a new service to help drive adoption of innovative customer-related processes. Salesforce’s primary aim is to help organizations market and sell to, service, engage with and know their customers through innovative processes and cloud-based systems. To support these efforts, it has made significant updates to its marketing, service community and analytics clouds. For example, it has added Marketing Cloud Predictive Decisions to its Marketing Cloud. The new module enables marketers to apply analytics to a range of customer-related data to gain a more complete picture of their customers and from it build more personalized marketing messages and campaigns. Business users can set up their own analytics, determine next best actions and deliver marketing messages and dialogues through multiple communication channels. Predictive Decisions helps transform marketing’s approach from general one-off marketing campaigns to one-to-one, personalized dialogues through channels that individuals prefer. On another front, the company has enhanced its Service Cloud with Service Cloud Intelligence Engine. This product also runs across multiple channels. It dynamically pushes work to the right employee, based on the skill set required to handle the task and the history of the request, and at the same time it distributes and manages the workload across employees who handle customer interactions. Analytics here provides an enhanced view of customers so that dialogues concerning a case can be viewed and preserved across all channels. In other developments Community Cloud has been enhanced to expand the range of expert groups to engage, deliver customer self-service as part of a community, and do this on smart mobile devices. Analytics Cloud now can ingest larger volumes and types of customer-related data, including interaction data. It enables both business users and analysts to use a wider range of data sources to find answers to specific questions, also on mobile devices. It also includes capabilities for developers to build specific analytic apps for targeted business uses. My colleague has assessed the product in Salesforce Analytics Cloud Delivers Wave of Elegant Dashboards. All of these developments and existing capabilities have been brought together on what Salesforce calls the Customer Success Platform. It is built on the company’s cloud infrastructure, and as well as its own cloud-based apps, it includes all the partner apps available on the Salesforce app store. A “scalable metadata platform” glues everything together. It includes data and objects, a mobile user interface, collaboration tools, analytics, workflow and identity management. Enhancements enable developers to build mobile apps for both customers and employees more easily. In the pipeline are capabilities to use wearable technology to collect and display data. Salesforce’s efforts to help companies “do business in a new way” reflect challenges that many companies encounter in trying to serve customers more effectively. Our research into next-generation customer engagement shows that the three most common challenges are integrating systems (49%), managing communication challenges in a unified way and not as silos (47%) and inconsistent responses and information in customer interactions (33%). My research and customer case studies lead me to conclude that changing processes is the biggest challenge. To meet this challenge Salesforce has introduced a consulting program called Ignite. This collaborative consulting service aims to help organizations design their customer management vision and execution roadmap. It is comprised of four steps: discovery, inspiration and design, prototyping and iteration and doing it. Discovery uses joint workshops and interviews with key stakeholders to introduce the program and its objectives, gain buy-in and discover the current state. Inspiration and design is another series of joint workshops to develop ideas and envision the desired state. Prototyping and iteration uses the new ideas to develop prototypes of how the new vision can be delivered. The “do” step presents and demonstrates the prototypes to stakeholders and develops a value statement and an implementation plan so the business can decide the way forward. Overall this seems to be a fairly typical consulting service that focuses on customer engagement and associated processes, systems and metrics, but it is deliberately collaborative and tailored around Salesforce applications and tools. The main innovation I see is that it is designed to uncover new ways of working that organizations may not have considered. Business, especially around customer engagement, is changing more rapidly than ever, and it is hard for organizations to keep up with technology developments and learn how to gain maximum benefit from them. Ignite should help Salesforce customers identify how they can improve customer management and introduce new approaches to keep ahead of the competition. The Salesforce Customer Success Platform is a comprehensive package of systems that focus on customer management processes, underpinned by improved integration, analytics and collaborative capabilities. Our research consistently finds that most companies are still relatively immature in the use of people, processes, information and systems for customer management. I therefore recommend companies seeking to survive and prosper in today’s highly competitive markets assess how the Salesforce products and service can help. Regards, Richard J. Snow VP & Research Director
Topics: Big Data, Customer Feedback Management, Customer Performance, Business Analytics, Business Collaboration, Cloud Computing, Call Center
Vertex Enterprise Supports Tax Department’s Effectiveness
Companies trust their tax departments with a highly sensitive and essential task. Direct (income) taxes usually are the second largest corporate expense, after salaries and wages. Failure to understand and manage this liability is expensive, whether because taxes are overpaid or because of fines and interest levied for underpayment. Moreover, taxes are a political issue, and corporations – especially larger ones – must be mindful of the reputational implications of their tax liabilities.
Topics: Big Data, Analytics, Business Performance, Financial Performance
Genesys Advances Omnichannel Experience for Customer Engagement
I recently wrote about six technologies that can help companies deliver experiences that live up to their customers’ expectations: an integrated multichannel infrastructure, analytics, a smart agent desktop, business applications such as workforce management and knowledge management, collaboration and mobile apps. They should be closely integrated to simplify system administration, to support processes that have been disconnected because they required multiple systems and to be easy to use. In my experience few vendors provide systems that meet all these goals so I was keen to learn about the latest version of the Genesys Customer Experience Platform which was the recipient of 2014 Ventana Research T Technology Innovation award for contact center in its works with IBM Watson Engagement Advisor.
Topics: Big Data, Customer Feedback Management, Customer Performance, Business Analytics, Cloud Computing, Call Center
Verint Introduces Gamification Software to Motivate and Engage the Workforce
Some new words can give the wrong impression. Take “gamification,” for example. It may sound as if employers are inviting their employees to play games just for fun, when actually this is a technique increasingly being used to recognize achievement and thus help improve performance. Several workforce management software vendors have introduced gamification systems that support setting targets, measuring achievement against those targets, rewarding players who meet their target and displaying winners who do best at meeting or exceeding their targets. This concept is not entirely new in contact centers, which long have used notice boards that recognize achievements such as “agent of the month,” which is also an award to the employee best meeting his or her targets. A new product called Verint Gamification supports similar capabilities but visualizes them in more engaging ways that link meeting personal goals with enterprise objectives.
Topics: Big Data, Customer Feedback Management, Customer Performance, Cloud Computing, Call Center
NICE Systems Engages Analytics to Optimize Customer Experience
NICE Systems is an established vendor of workforce optimization products that has long included analytics in its portfolio. Its latest release in this area, NICE Customer Experience Analytics, focuses on mapping, understanding and managing customer journeys and metrics. The product is built on NICE’s common technology platform, which consists of three functions: collect, understand and optimize. The Collect segment has tools to help manage customer-related data and ingest data from multiple data sources; Understand uses analytics tools to analysis the data and produce reports, dashboards and other forms of output; and Optimize uses the outputs to help users improve business tasks such as improve customer satisfaction and net performer scores, suggest next best actions and reduce customer effort.
Topics: Big Data, Customer Performance, Business Analytics, Cloud Computing, Call Center
Who’s Hot in Analytics and Business Intelligence
Ventana Research recently completed the most comprehensive evaluation of analytics and business intelligence products and vendors available anywhere. As I discussed recently, such research is necessary and timely as analytics and business intelligence is now a fast-changing market. Our Value Index for Analytics and Business Intelligence in 2015 scrutinizes 15 top vendors and their product offerings in seven key categories: Usability, Manageability, Reliability, Capability, Adaptability, Vendor Validation and TCO/ROI. The analysis shows that the top supplier is Information Builders, which qualifies as a Hot vendor and is followed by 10 other Hot vendors: SAP, IBM, MicroStrategy, Oracle, SAS, Qlik, Actuate (now part of OpenText) and Pentaho.
Topics: Big Data, Data Quality, Predictive Analytics, Gartner, Governance, Customer Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Applications, Information Management, Operational Intelligence, Value Index, Strata+Hadoop
In the Digital Economy, the Customer Experience Is Critical
Advertising and marketers tell us we now live in a “digital economy.” That implies the economy is based on and depends on digital technologies. It certainly is true that many consumers, especially younger ones, have changed the ways they interact with each other and businesses; they are now more likely to use digital channels of communication, particularly email, websites, text messaging, instant messaging and social media. In this digital world, where customers can search globally for products and services and change suppliers instantly, it is critical for companies to focus on the customer experience.
Topics: Big Data, Customer Feedback Management, Customer Performance, Cloud Computing, Call Center
New Research to Examine Best Practices in Customer Interactions and Experience with Cloud Computing
In 2013, Ventana Research carried out groundbreaking benchmark research into contact centers in the cloud. It revealed that customer pressures have forced companies to support an increasing variety of channels of interaction. This research investigated the systems companies were using then or were planning to use, particularly cloud computing, to manage these channels. The research uncovered three major challenges: integration of systems, channels of communication supported as silos and customers receiving inconsistent information across channels. We found that to overcome these challenges, companies most often were planning to improve agent training and coaching (73%), to deploy contact center applications such as CRM and workforce optimization in the cloud (63%) and to adopt communications management systems in the cloud (44%). Further benchmark research shows continuing changes. The number of channels customers use continues to grow, and in particular more customers prefer to use digital self-service channels such as chat, visual IVR, voice-activated virtual agents and social forums. On the business side more employees across the organization have become involved in handling interactions, including finance and HR departments, mobile customer service and home agents. As channels proliferate more companies have realized that they need a single, comprehensive view of their customers that includes a history of their interactions, the channels they used for those interactions and likely actions they might take as a result of the outcomes of those interactions.
Topics: Big Data, Customer Feedback Management, Customer Performance, Cloud Computing, Call Center
In covering Verint for several years I have watched it go from selling call recording systems to adding workforce optimization software, analytics, and support for multiple channels of interaction with customers. Its latest product, Customer Engagement Optimization, increases support for customer engagement and managing the customer experience. Verint has achieved this expansion through a combination of acquisitions and in-house development. Its acquisition of Kana enabled it to go from supporting workforce optimization with some analytics to supporting multiple channels of customer engagement, workforce optimization and advanced analytics. I have written several times that this approach has its advantages – acquisitions shorten the time it takes to add new capabilities and extend the scope of the products – and disadvantages – it creates challenges in producing fully integrated products and developing a common user interface so the products are easier to use. During a recent briefing I saw that the company continues its efforts to advance in all these areas.
Topics: Big Data, Customer Feedback Management, Customer Performance, Business Analytics, Cloud Computing, Call Center
Analytics and Business Intelligence: Multifaceted and Evolving Technology
Just a few years ago, the prevailing view in the software industry was that the category of business intelligence (BI) was mature and without room for innovation. Vendors competed in terms of feature parity and incremental advancements of their platforms. But since then business intelligence has grown to include analytics, data discovery tools and big data capabilities to process huge volumes and new types of data much faster. As is often the case with change, though, this one has created uncertainty. For example, only one in 11 participants in our benchmark research on big data analytics said that their organization fully agrees on the meaning of the term “big data analytics.”
Topics: Big Data, Data Quality, Predictive Analytics, Gartner, Customer Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Information Applications, Information Management, Value Index, Strata+Hadoop
Does Pricing and Revenue Optimization Make My Bottom Line Look Fatter?
Managing prices has always been an activity of keen interest to businesses, but it has become even more critical to do it well. Over the past decade many companies have found their ability to raise prices has been constrained by intense competition resulting from Internet commerce, global competition and other factors. One tool for dealing with this pressure is price and revenue optimization (PRO), an analytic methodology that calculates how demand varies at different price levels and then uses that algorithm to recommend prices that should optimally balance revenue and profit objectives. Computer-supported PRO began in earnest in the 1980s as the airline and hospitality industries adopted revenue management practices in efforts to maximize returns from less flexible travelers (such as people on business trips) while minimizing the unsold inventory by selling incremental seats on flights or nights in hotel rooms at discounted prices to more discretionary buyers (typically vacationers). Price and revenue optimization algorithms are designed to enable a company to achieve fatter profit margins than are possible with a monolithic pricing strategy. Using PRO, airlines and hotels catering mainly to less price-sensitive business travelers found they could match discounters’ fares and rates to fill available seats and rooms without having to forgo profits from their high-margin customers.
Topics: Big Data, Performance Management, Sales, Office of Finance, Operational Performance Management (OPM), Analytics, Business Analytics, Business Performance Management (BPM), Financial Performance Management (FPM), Sales Performance Management (SPM), analytical application, Price Optimization
Nexidia Brings Compliance and Process Management to Interaction Analytics
Nexidia is a leading vendor of speech analytics vendor. I recently wrote about how it has enhanced its architecture to include text analytics and improve overall system performance. Version 11 of its Neural Phonetic Speech Analytics continues these enhancements to make the product faster and more accurate in its results.
Topics: Big Data, Customer Performance, Business Analytics, Cloud Computing, Call Center
The Importance of Well-Managed Processes for Planning
It’s stating the obvious to say that how well executives manage planning processes has a big impact on how well a business unit or company plans. However, one significant source of the value of our benchmark research is that it establishes hard evidence – the numbers – that transforms mere assertions into proof points. This is particularly important when people within an organization want to improve a process. Change management is facilitated by providing senior executives with facts to back up assertions related to solving a business issue. Our recently completed next-generation business planning research provides insight into the importance of managing the planning process well and identifies some components of good management.
Topics: Big Data, Predictive Analytics, Sales, Sales Performance, Supply Chain Performance, Marketing, Customer Performance, Operational Performance, Business Analytics, Business Performance, Cloud Computing, Financial Performance, Supply Chain, S&OP
VPI Applies Business Intelligence to Customer Experience
VPI is a well-established vendor of workforce optimization systems and rated a Hot Vendor in our 2015 Workforce Optimization Value Index. It offers a full suite of products for this market. Notable among them is Performance Reporting, which produces reports and dashboards showing a range of analysis and metrics about telephony, agent performance, coaching and customer success, along with alerts to inform employees of required actions. It combines data from a range of sources, both structured and unstructured, using speech analytics, and works in real or near real time. Performance Reporting is the basis for a new product, Customer Experience BI, which uses many of the same capabilities but focuses more on the customer experience while retaining the contact center capabilities. Our benchmark research into next-generation customer analytics shows this to be an important development as just under two-thirds (63%) of participants said they are considering investing in customer analytics to improve the customer experience.
Topics: Big Data, Customer Performance, Business Analytics, Cloud Computing, Call Center
Enghouse Interactive Expands Portfolio of Contact Center Systems
Enghouse Interactive is one of three divisions of Enghouse Systems, a publicly traded Canadian company founded in 1984. The other two divisions provide network technology to telecommunications providers and applications for public and private transportation companies; Enghouse Interactive owns the company’s three contact center systems. The corporate group has a history of growth – it now has a market capitalization of more than US$1 billion - achieved both organically and through an aggressive acquisition policy. The same applies to Enghouse Interactive. Its three core products are built on three acquisitions – Syntellect in 2002, CosmoCom in 2011 and Zeacom in 2012. Each of these has been enhanced by a combination of in-house development and integration with other acquired products. The three products are maintained and developed independently, something Enghouse Interactive says will continue for the foreseeable future. However it is working to integrate its latest acquisitions with all three products, so each will gain new capabilities.
Topics: Big Data, Customer Analytics, Customer Experience, Customer Feedback Management, Speech Analytics, Customer Performance, Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
Tracking the Customer Journey Is Critical for Engagement
Competition for customers is more intense today than ever before, and companies struggle to differentiate themselves from the competition. Our research repeatedly finds that customer experience is a key differentiator. Our research into next-generation customer engagement said the impetus for improving engagement is to improve the customer experience in almost three quarters (74%) of participants. One increasingly popular way to do this is to use customer journey maps, which show how companies plan to engage with customers: at what times, through which channels, at which touch points and with which business units or using which self-service technologies. Our benchmark research into customer relationship maturity shows that two-thirds (67%) of very customer-focused companies use customer journey maps. The top four uses are to develop more customer-focused employee training (by 78%), personalize customer experiences (76%), enhance customer experience processes (73%) and drill down on customer experience processes to the customer segment level (73%). Typically producing these maps has been a manual process, perhaps using process mapping tools; in these cases few companies were able to capture and visualize actual journeys. However, as more business units engage with customers and companies deploy multiple channels of engagement – including self-service – improving the customer experience and mapping the customer journey become more complex, and to keep up companies have to invest in processes and tools that help them automate the process of producing maps and capture data about and visualize actual customer journeys.
Topics: Big Data, Customer Analytics, Customer Experience, Customer Feedback Management, Speech Analytics, Customer Performance, Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics
Alpine Chorus Brings Collaboration and Predictive Analytics to Big Data
In many organizations, advanced analytics groups and IT are separate, and there often is a chasm of understanding between them, as I have noted. A key finding in our benchmark research on big data analytics is that communication and knowledge sharing is a top benefit of big data analytics initiatives, but often it is a latent benefit. That is, prior to deployment, communication and knowledge sharing is deemed a marginal benefit, but once the program is deployed it is deemed a top benefit. From a tactical viewpoint, organizations may not spend enough time defining a common vocabulary for big data analytics prior to starting the program; our research shows that fewer than half of organizations have agreement on the definition of big data analytics. It makes sense therefore that, along with a technical infrastructure and management processes, explicit communication processes at the beginning of a big data analytics program can increase the chance of success. We found these qualities in the Chorus platform of Alpine Data Labs, which received the Ventana Research Technology Innovation Award for Predictive Analytics in September 2014.
Topics: Big Data, Predictive Analytics, Sales Performance, Supply Chain Performance, alpine data labs, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Financial Performance, Strata+Hadoop
Verint Advances Feedback Management to Improve Customer Experience
Verint entered the enterprise market for customer feedback management when it acquired Vovici in August 2011. Since then the Vovici products have been integrated into Verint’s Customer Engagement Optimization suite, which includes products originally developed by Verint and Kana, which it also acquired. The current suite supports a range of capabilities that Verint groups into three categories: customer analytics (various types of analytics and Enterprise Feedback Management), customer engagement (which is largely the Kana products that support the agent desktop, email, chat and co-browsing, knowledge and case management, and Web-based self-service) and workforce optimization (quality monitoring, workforce management, desktop and process analytics, performance management and e-learning and coaching). Having this broad array of capabilities allows Verint to support a closed-loop approach to customer feedback and connect it to the processes with which to identify issues raised through feedback and take action to improve (through process change, training and coaching, for example).
Topics: Big Data, Customer Analytics, Customer Experience, Customer Feedback Management, Speech Analytics, Customer Performance, Analytics, Business Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, Text Analytics
A New Generation of Analytics Offers Help for Sales
All lines of business are under pressure to meet targets and deliver expected results, but none is under more pressure than Sales. Like other organizations it must use information to derive insights about progress and problems and to decide what changes to make. Today businesses collect and analyze data from more data sources in more forms than ever before. To understand it they need effective analytics, and again none need it more than Sales.
Topics: Big Data, Sales, Sales Performance, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Financial Performance, Information Applications, Sales Performance Management, SFA
Integrated Business Planning Is More Effective
Ventana Research recently released the results of our Next-Generation Business Planning benchmark research. Business planning encompasses all of the forward-looking activities in which companies routinely engage. The research examined 11 of the most common types of enterprise planning: capital, demand, marketing, project, sales and operations, strategic, supply chain and workforce planning, as well as sales forecasting and corporate and IT budgeting. We also aggregated the results to draw general conclusions.
Topics: Big Data, Planning, Predictive Analytics, Sales, Sales Performance, Social Media, Supply Chain Performance, Human Capital Management, Marketing, Office of Finance, Reporting, Budgeting, Controller, Customer Performance, Operational Performance, Business Analytics, Business Performance, Cloud Computing, Financial Performance, In-memory, Workforce Performance, CFO, Supply Chain, capital spending, demand management, Financial Performance Management, financial reporting, FPM, Integrated Business Planning, S&OP
Data is an essential ingredient for every aspect of business, and those that use it well are likely to gain advantages over competitors that do not. Our benchmark research on information optimization reveals a variety of drivers for deploying information, most commonly analytics, information access, decision-making, process improvements and customer experience and satisfaction. To accomplish any of these purposes requires that data be prepared through a sequence of steps: accessing, searching, aggregating, enriching, transforming and cleaning data from different sources to create a single uniform data set. To prepare data properly, businesses need flexible tools that enable them to enrich the context of data drawn from multiple sources, collaborate on its preparation to serve business needs and govern the process of preparation to ensure security and consistency. Users of these tools range from analysts to operations professionals in the lines of business.
Topics: Big Data, Sales Performance, Supply Chain Performance, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Cloud Computing, Data Preparation, Financial Performance, Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance, Information Optimization
Process Trumps Innovation in Business Analytics
The idea of not focusing on innovation is heretical in today’s business culture and media. Yet a recent article in The New Yorker suggests that today’s society and organizations focus too much on innovation and technology. The same may be true for technology in business organizations. Our research provides evidence for my claim.
Topics: Big Data, Sales, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Financial Performance, Information Management
MicroStrategy Powers Up Security for Analytics and BI
At its annual MicroStrategy World conference, this provider of analytics and business intelligence systems for business and IT introduced a new version of its flagship product, MicroStrategy 9s. Among many advances it adds enterprise grade security with MicroStrategy Usher as part of the maintenance update to its 9.4.1 release. Security is increasingly critical for analytics and BI. Technologies that work intensively with data, including reporting, business intelligence, analytics and data preparation, have access to a range of applications and databases and could leave gaps in access controls and security of essential business data. Already in 2015 the data breach at Anthem put more than 80 million medical records at risk. Our benchmark research in big data analytics finds that integration into security and user access frameworks is a very important capability to 37 percent of organizations.
Topics: Big Data, Mobile, Sales Performance, Governance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Cloud Computing, Customer & Contact Center, Information Applications, Information Management, Risk & Compliance (GRC), Security
One of the issues in handling the tax function in business, especially where it involves direct (income) taxes, is the technical expertise required. At the more senior levels, practitioners must be knowledgeable about accounting and tax law. In multinational corporations, understanding differences between accounting and legal structures in various localities and their effects on tax liabilities requires more knowledge. Yet when I began to study the structures of corporate tax departments, I was struck by the scarcity of senior-level titles in them. This may reflect the low profile of the department in most companies and the tactical nature of the work it has performed. Advances in information technology have the potential to automate most of the manual tasks tax professionals perform. This increase in efficiency will enable tax departments to fill a more strategic, important role in the companies they serve.
Topics: Big Data, ERP, Governance, GRC, Office of Finance, audit, finance transformation, LongView, Tax, Analytics, Business Analytics, Business Performance, Financial Performance, Information Management, Oracle, CFO, Risk & Compliance (GRC), Vertex, FPM, Innovation Awards, Thomson-Reuters multinational
Oracle Advances Analytics and Business Intelligence for Big Data and Cloud Computing
Oracle is one of the world's largest business intelligence and analytics software companies. Its products range from middleware, back-end databases and ETL tools to business intelligence applications and cloud platforms, and it is well established in many corporate and government accounts. A key to Oracle's ongoing success is in transitioning its business intelligence and analytics portfolio to self-service, big data and cloud deployments. To that end, three areas in which the company has innovated are fast, scalable access for transaction data; exploratory data access for less structured data; and cloud-based business intelligence.
Topics: Big Data, Customer Performance, endeca, OBIEE, OBIFS, Analytics, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Oracle
Cisco Provides a Portfolio of Contact Center Products
I recently attended a Cisco Collaboration analyst day in the U.K. and was impressed by what I heard and saw. Cisco of course is known as a supplier of network equipment and software, and it has long provided these through a global network of partners. But Cisco also has been in the contact center market for several years and has had success with its small and enterprise contact center systems, having more than 20,000 on-premises customers and revenue in excess of US $1.5 billion. Cisco markets the contact center systems as Customer Collaboration , but the portfolio is still based on its two longstanding contact center products: Unified Contact Center Enterprise and Unified Contact Center Express , designed for larger and smaller centers, respectively. Two other options are CiscoPackaged Contact Center Enterprise and Cisco Hosted Collaboration Solution for Contact Center (HCS-CC) . These both use the Enterprise products, but the first comes packaged and so has less options, and the second is based on cloud computing; both are easier to deploy and more affordable for a wider market than the other options.
Topics: Big Data, Customer Analytics, Customer Experience, Speech Analytics, Analytics, Business Collaboration, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, Text Analytics
Big Data Research Agenda and Trends are Bolder in 2015
Big data has become a big deal as the technology industry has invested tens of billions of dollars to create the next generation of databases and data processing. After the accompanying flood of new categories and marketing terminology from vendors, most in the IT community are now beginning to understand the potential of big data. Ventana Research thoroughly covered the evolving state of the big d