IBM Planning Analytics with Watson is a comprehensive, cloud-based business planning application that supports what Ventana Research calls integrated business planning. We coined this term in 2007 to describe a high-participation approach to business planning that integrates strategy, operations and finance. Our Next Generation Business Planning Benchmark Research demonstrated the value of IBP: Organizations that link planning processes get better results. Sixty-six percent of organizations that have an integrated method say it works well or very well, compared to only 25% that have little or no connection between plans.
IBM Planning Analytics Enables Agility Based on Insight
Topics: Predictive Analytics, Office of Finance, embedded analytics, Business Intelligence, Business Planning, Financial Performance Management, Watson, Digital transformation, AI and Machine Learning, digital finance, profitability management
People Analytics: A New Generation of Workforce Insights
People analytics is a specific focus in Human Capital Management (HCM) that enables organizations to have data-driven insights that optimize the impact and value of the workforce. These analytics are essential for addressing a broad scope of HCM objectives, but while reducing compliance risks and highlighting demographic trends have dominated the people analytics landscape for decades, various technology-related advances have paved the way for these data insights to become more actionable, capable of addressing strategic issues such as improving organizational agility and employee productivity.
Topics: Predictive Analytics, Workforce Analytics, HR Analytics
Self-Describing Data Powers B2B Blockchain Distributed Ledgers
The use of blockchain distributed ledgers in business processes is now a common theme in many business software vendors’ presentations. The technology has a multitude of potential uses. However, presentations about the opportunities for digital transformation always leave me wondering: How is this magic going to happen? I wonder this because the details about how data flows from point A to point B via a blockchain are critically important to blockchain utility and therefore the pace of its adoption.
Topics: Planning, Predictive Analytics, Forecast, FP&A, Machine Learning, Reporting, budget, Budgeting, Continuous Planning, Analytics, Data Management, Cognitive Computing, Integrated Business Planning, AI, forecasting, consolidating
Predictive Finance Organizations Are More Valuable
Ventana Research uses the term “predictive finance” to describe a forward-looking, action-oriented finance organization that places emphasis on advising its company rather than fulfilling the traditional roles of a transactions processor and reporter. Technology is driving the shift away from the traditional bean-counting role. The cumulative evolution of software advances will substantially reduce finance and accounting workloads by automating most of the mechanical, rote functions in accounting, data preparation and reporting. (I recently summarized these in a “Robotic Finance”)
Topics: Planning, Predictive Analytics, Forecast, FP&A, Machine Learning, Reporting, budget, Budgeting, Continuous Planning, Analytics, Data Management, Cognitive Computing, Integrated Business Planning, AI
The treasury function in finance departments doesn’t get a lot of attention, but it’s a fundamentally important one: to ensure that all funds are accounted for and that there is sufficient cash on hand each day to meet operating requirements. Keeping track of and managing cash, especially in larger organizations, can be complicated because of multiple bank accounts, complex financing requirements and various methods of receiving and making payments; the complexity deepens when more than one currency is used across multiple jurisdictions, which also can pose regulatory issues.
Topics: Predictive Analytics, Office of Finance, credit, debt, Analytics, CFO, cash management, controller, Financial Performance Management
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, Predictive Analytics, Business Analytics, Business Intelligence, Cloud Computing, Information Management
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
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
SAP Faces Challenges with Customer Assurance and Digital Boardroom
There were two noteworthy themes in SAP CEO Bill McDermott’s keynote at this year’s Sapphire conference. One was customer assurance; that is, placing greater emphasis on making the implementation of even complex business software more predictable and less of an effort. This theme reflects the maturing of the enterprise applications business as it transitions from producing highly customized software to providing configurable, off-the-rack purchases. Implementing ERP will never be simple, as I have noted, but as companies increasingly adopt multitenant software as a service (SaaS), vendors will need to make their implementations as repeatable as possible and enable flexible configuration of parameters and processes that substantially reduce the billable hours required to complete a deployment. “Customer assurance” is an important stake in the ground, but it will be an empty concept unless there is complete overhaul of the entire value chain to take it beyond good intentions. Otherwise, customer assurance will be an ongoing rearguard action to overcome technology-driven challenges and disincentives for improvement. Business applications must be re-engineered to facilitate implementation, substantially reduce the likelihood of implementation errors and facilitate subsequent changes to adapt to changing business conditions. Moreover, software vendors’ partners will need to demonstrate that they can reliably cut a substantial number of billable hours per implementation engagement. This will require partners to restructure their business models. Neither of these changes will be easy to accomplish. To its credit SAP has set a course for increasing the simplicity of using its core ERP and financial management software. Getting there soon would greatly enhance its ability to retain if not gain customers in these mature markets.
Topics: Predictive Analytics, Sales Performance, SAP, Supply Chain Performance, Customer Performance, 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
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
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)
For several years I have been advocating that sales organizations adapt their processes and applications to optimize both sales performance and the customer experience. For details see my research agenda for last year. However, it appears that not many sales organizations have responded to this challenge; many can barely maintain their quarterly sales forecasts and monthly pipeline, track progress toward quotas and ensure that sales commissions are processed promptly and paid accurately. A great many are still using spreadsheets for these critical activities. Yet our benchmark research finds that more than half (61%) who use them for commissions said this makes the effort more difficult. Elsewhere, I have seen B2B sales organizations continue down the old path of annoying prospects with direct cold calling and email instead of nurturing real relationships. For B2C sales, the digital age of search engine optimization (SEO) and pay-per-click (PPC) has begun to haunt prospects by inserting ads in our personal social media channels. My research suggests that these practices are not due to bad intentions but to force of habit and lack of desire, time and resources to develop a modern strategy and plan. Most are just managing the basics of their sales processes and relying on sales force automation (SFA) systems, reporting and dashboards, which will only produce more of the same, less than optimal results.
Topics: Predictive Analytics, Sales Performance, Mobile Technology, Customer Performance, Operational Performance, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Financial Performance, Uncategorized, Financial Performance Management (FPM), Sales, SFA, SPM, Sales Performance Management, Sal
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: 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
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
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
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
Whatever Oracle’s cloud strategy had been the past, this year’s OpenWorld conference and trade show made it clear that the company is now all in. In his keynote address, co-CEO Mark Hurd presented predictions for the world of information technology in 2025, when the cloud will be central to companies’ IT environments. While his forecast that two (unnamed) companies will account for 80 percent of the cloud software market 10 years from now is highly improbable, it’s likely that there will be relentless consolidation, marginalization and extinction within the IT industry sector driven by cloud disruptions and the maturing of the software business. In practice, though, we expect the transition to the cloud to be slow and uneven.
Topics: Microsoft, Predictive Analytics, Sales Performance, SAP, Supply Chain Performance, ERP, Human Capital, Mobile Technology, NetSuite, Office of Finance, Reporting, close, closing, Controller, dashboard, Tax, Customer Performance, Operational Performance, Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Collaboration, IBM, Oracle, Business Performance Management (BPM), CFO, Data, finance, Financial Performance Management (FPM), Financial Performance Management, FPM, Intacct
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
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
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
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
Host Analytics Modeling Cloud Simplifies Planning and Reporting
Our benchmark research on next-generation business planning finds that a large majority of companies rely on spreadsheets to manage planning processes. For example, four out of five use them for supply chain planning, and about two-thirds for budgeting and sales forecasting. Spreadsheets are the default choice for modeling and planning because they are flexible. They adapt to the needs of different parts of any type of business. Unfortunately, they have inherent defects that make them problematic when used in collaborative, repetitive enterprise processes such as planning and budgeting. While it’s easy to create a model, it can quickly become a barrier to more integrated planning across the business units in an enterprise. As I’ve noted before, software vendors and IT departments have been trying – mainly in vain – to get users to switch from spreadsheets to a variety of dedicated applications. They’ve failed to make much of a dent because although these applications have substantial advantages over spreadsheets when used in repetitive, collaborative enterprise tasks, these advantages are mainly realized after the model, process or report is put to use in the “production” phase (to borrow an IT term).
Topics: Planning, Predictive Analytics, Marketing Planning, Reporting, Sales Forecasting, Budgeting, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Performance, Financial Performance, Business Planning, Demand Planning, Integrated Business Planning
Unit4 is a global business software vendor focused on business and professional services, the public sector and higher education. Recently company executives met with industry analysts to provide an update of its strategic roadmap and to recap its accomplishments since being acquired by a private equity firm in 2014. Unit4 is the result of successive mergers of ERP and business software companies, notably CODA and Agresso. The company is also a part-owner (with salesforce.com and others) of independently run FinancialForce, which sells a cloud-based ERP system built on the Force.com platform.
Topics: Predictive Analytics, Human Capital, Office of Finance, Operational Performance, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Financial Performance
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
Adaptive Insights Highlights Importance of Strategic Finance
Adaptive Insights held its annual user group meeting recently. A theme sounded in several keynote sessions was the importance of finance departments playing a more strategic role in their companies. Some participating customers described how they have evolved their planning process from being designed mainly to meet the needs of the finance department into a useful tool for managing the entire business. Their path took them from doing basic financial budgeting to planning focused on improving the company’s performance. This is one of the more important ways in which finance organizations can play a more strategic role in corporate management, an objective that more finance organizations are pursuing. Half of the companies participating in our Office of Finance benchmark research said that their finance organization has undertaken initiatives to enhance its strategic value to the company within the last 18 months.
Topics: Planning, Predictive Analytics, Human Capital, Marketing, Reporting, Sales Forecasting, Budgeting, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Performance, Financial Performance, Business Planning, Supply Chain, Demand Planning, Integrated Business Planning, Project Planning
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
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
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
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
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
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 data and information optimization sector in 2014 and will continue this research in 2015 and beyond. As it progresses the importance of making big data systems interoperate with existing enterprise and information architecture along with digital transformation strategies becomes critical. Done properly companies can take advantage of big data innovations to optimize their established business processes and execute new business strategies. But just deploying big data and applying analytics to understand it is just the beginning. Innovative organizations must go beyond the usual exploratory and root-cause analyses through applied analytic discovery and other techniques. This of course requires them to develop competencies in information management for big data.
Topics: Big Data, MapR, Predictive Analytics, Sales Performance, SAP, Supply Chain Performance, Human Capital, Marketing, Mulesoft, Paxata, SnapLogic, Splunk, Customer Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Cloudera, Financial Performance, Hortonworks, IBM, Informatica, Information Management, Operational Intelligence, Oracle, Datawatch, Dell Boomi, Information Optimization, Savi, Sumo Logic, Tamr, Trifacta, Strata+Hadoop
Making Business Planning More Accurate, Effective and Useful
Business planning includes all of the forward-looking activities in which companies routinely engage. Companies do a great deal of planning. They plan sales and determine what and how they will produce products or deliver services. They plan the head count they’ll need and how to organize distribution and their supply chain. They also produce a budget, which is a financial plan. The purpose of planning is to be successful. Planning is defined as the process of creating a detailed formulation of a program of action to achieve some overall objective. But it’s more than that. The process of planning involves discussions about objectives and the resources and tactics that people need to achieve them. When it’s done right, planning is the best way to get everyone onto the same page to ensure that the company is well organized in executing strategy. Setting and to a greater degree changing the company’s course require coordination. Being well coordinated in this case means being able to understanding the impact of the policies and actions in your part of the company on the rest of the company.
Topics: Big Data, Planning, Predictive Analytics, Sales Performance, Supply Chain Performance, Human Capital, Marketing, Office of Finance, Reporting, Sales Forecasting, Budgeting, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Performance, Customer & Contact Center, Financial Performance, Business Planning, Supply Chain, Demand Planning, Integrated Business Planning, Project Planning, S&OP
Last year Ventana Research released our Office of Finance benchmark research. One of the objectives of the project was to assess organizations’ progress in achieving “finance transformation.” This term denotes shifting the focus of CFOs and finance departments from transaction processing toward more strategic, higher-value functions. In the research nine out of 10 participants said that it’s important or very important for the department to take a more strategic role. This objective is both longstanding and elusive. It has been part of the conversation in financial management circles since the 1990s and has been a primary focus of my research practice since its inception 12 years ago. Yet our recent research shows that most finance organizations struggle with the basics and few companies are even close to achieving this desired transformation.
Topics: Big Data, Planning, Predictive Analytics, Governance, GRC, Office of Finance, Budgeting, close, end-to-end, Tax, Tax-Datawarehouse, Analytics, Business Performance, CIO, Financial Performance, In-memory, CFO, CPQ, Risk, CEO, Financial Performance Management, FPM
Office of Finance Research Demonstrates Importance of Using Effective Financial Software
Our recently published Office of Finance benchmark research assesses a broad set of functions and capabilities of finance organizations. We asked research participants to identify the most important issues for a finance department to address in a dozen functional areas: accounting, budgeting, cost accounting, customer profitability management, external financial reporting, financial analysis, financial governance and internal audit, management accounting, product profitability management, strategic and long-range planning, tax management and treasury and cash management. Among the key findings is this: Not using the most capable software is an underlying cause, often unrecognized, of process, analytics and data issues.
Topics: Mobile, Planning, Predictive Analytics, ERP, FP&A, Office of Finance, Reporting, Self-service, Budgeting, close, closing, computing, Controller, dashboard, Tax, Analytics, Business Intelligence, Business Performance, Cloud Computing, Collaboration, Financial Performance, CFO, Data, finance, Financial Performance Management, FPM, Microsoft Excel, Spreadsheets
In 2014, IBM announced Watson Analytics, which uses machine learning and natural language processing to unify and simplify the user experience in each step of the analytic processing: data acquisition, data preparation, analysis, dashboarding and storytelling. After a relatively short beta testing period involving more than 22,000 users, IBM released Watson Analytics for general availability in December. There are two editions: the “freemium” trial version allows 500MB of data storage and access to file sizes less than 100,000 rows of data and 50 columns; the personal edition is a monthly subscription that enables larger files and more storage.
Topics: Data Visualization, Predictive Analytics, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Information Applications, Information Management, Data Discovery, Watson
Technology Can Enhance Performance in Finance Departments
Finance transformation” refers to a longstanding objective: shifting the focus of CFOs and finance departments from transaction processing to more strategic, higher-value functions. Our upcoming Office of Finance benchmark research confirms that most of organizations want their finance department to take a more strategic role in management of the company: nine in 10 participants said that it’s important or very important. (We are using “finance” in its broadest sense, including, for example, accounting, corporate finance, financial planning and analysis, treasury and tax functions.) Finance departments have the ability and at least an implicit mandate to improve business performance and enable a corporation to execute strategy more effectively. Yet the research shows that becoming strategic is a work in progress. Most departments handle the basics well, but half fall short in areas that can contribute significantly to the performance of their company. More than three-fourths of participants said they perform accounting, external financial reporting, financial analysis, budgeting and management accounting well or very well. But only half said that about their ability to do product and customer profitability management, strategic and long-range planning and business development.
Topics: Big Data, Mobile, Performance Management, Predictive Analytics, Social Media, ERP, FP&A, Office of Finance, Reporting, Management, close, closing, computing, Controller, Tax, Analytics, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Collaboration, Financial Performance, CFO, finance, Tagetik, FPM
Finance Needs Better Analytics and Analytic Skills
Finance and accounting departments are staffed with numbers-oriented, naturally analytical people. Strong analytic skills are essential if a finance department is to deliver deep insights into performance and visibility into emerging opportunities and challenges. The conclusions of analyses enable fast, fully informed business decisions by executives and managers. Conversely, flawed analyses undermine the performance of a company. So it was good news that in our Office of Finance benchmark research 62 percent of participants rated the analytical skills of their finance organization as above average or excellent.
Topics: Big Data, Mobile, Planning, Predictive Analytics, ERP, FP&A, Office of Finance, Reporting, Self-service, Budgeting, close, closing, computing, Controller, dashboard, Tax, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Collaboration, Financial Performance, CFO, Data, finance, Tagetik, Financial Performance Management, FPM, Microsoft Excel, Spreadsheets
What’s Next?: The Interplay of Software and Hardware with Business and Consumers
“What’s next?” is the perennially insistent question in information technology. One common observation about the industry holds that cycles of innovation alternate between hardware and software. New types and forms of hardware enable innovations in software that utilize the power of that hardware. These innovations create new markets, alter consumer behavior and change how work is performed. This, in turn, sets the stage for new types and forms of hardware that complement these emerging product and service markets as well as the new ways of performing work, creating products and fashioning services that they engender. For example, the emerging collection of wearable computing devices seems likely to generate a new wave of software/hardware innovation, as my colleague Mark Smith has noted. This said, I think that the idea of alternating cycles no longer applies. It would be convenient if we could assign discrete time periods to hardware dominance and software dominance, but like echoes as they fade, the reverberations are no longer as neatly synchronized as they once were. Moreover, adoption and adaptation of technology by consumers reflected in the design of work, products and services always lags – and lags in different ways, further blurring the timing of cycles.
Topics: Mobile, Performance Management, Predictive Analytics, Sales Performance, Supply Chain Performance, ERP, Office of Finance, Reporting, Wearable Computing, Management, close, closing, computing, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Financial Performance, Workforce Performance, finance, FPM
Our benchmark research consistently shows that business analytics is the most significant technology trend in business today and acquiring effective predictive analytics is organizations’ top priority for analytics. It enables them to look forward rather than backward and, participate organizations reported, leads to competitive advantage and operational efficiencies.
Topics: Big Data, Predictive Analytics, Sales Performance, Statistics, IT Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Data Integration, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance
IBM Advances Business Experience in Using Advanced Analytics
The developed world has an embarrassment of riches when it comes to information technology. Individuals walk around with far more computing power and data storage in their pockets than was required to send men to the moon. People routinely hold on their laps what would have been considered a supercomputer a generation ago. There is a wealth of information available on the Web. And the costs of these information assets are a tiny fraction of what they were decades ago. Consumer products have been at the forefront in utilizing information technology capabilities. The list of innovations is staggering. The “smart” phone is positively brilliant. Games are now a far bigger business than motion pictures.
Topics: Big Data, Mobile, Predictive Analytics, Sales Performance, Social Media, Customer Experience, Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, IBM, finance, Sales Performance Management, Social, Financial Performance Management, SPSS
Our research consistently finds that data issues are a root cause of many problems encountered by modern corporations. One of the main causes of bad data is a lack of data stewardship – too often, nobody is responsible for taking care of data. Fixing inaccurate data is tedious, but creating IT environments that build quality into data is far from glamorous, so these sorts of projects are rarely demanded and funded. The magnitude of the problem grows with the company: Big companies have more data and bigger issues with it than midsize ones. But companies of all sizes ignore this at their peril: Data quality, which includes accuracy, timeliness, relevance and consistency, has a profound impact on the quality of work done, especially in analytics where the value of even brilliantly conceived models is degraded when the data that drives that model is inaccurate, inconsistent or not timely. That’s a key finding of our finance analytics benchmark research.
Topics: Big Data, Planning, Predictive Analytics, Governance, Office of Finance, Budgeting, close, Finance Analytics, Tax, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, CIO, Financial Performance, Governance, Risk & Compliance (GRC), In-memory, Information Applications, CFO, Risk, CEO, Financial Performance Management, FPM
Big Data Analytics Require Best Practices in Using Technology
Organizations should consider multiple aspects of deploying big data analytics. These include the type of analytics to be deployed, how the analytics will be deployed technologically and who must be involved both internally and externally to enable success. Our recent big data analytics benchmark research assesses each of these areas. How an organization views these deployment considerations may depend on the expected benefits of the big data analytics program and the particular business case to be made, which I discussed recently.
Topics: Big Data, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, IT Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Operational Intelligence, Workforce Performance, Strata+Hadoop
Finance Departments Still Lag in Using Advanced Analytics
Business computing has undergone a quiet revolution over the past two decades. As a result of having added, one-by-one, applications that automate all sorts of business processes, organizations now collect data from a wider and deeper array of sources than ever before. Advances in the tools for analyzing and reporting the data from such systems have made it possible to assess financial performance, process quality, operational status, risk and even governance and compliance in every aspect of a business. Against this background, however, our recently released benchmark research finds that finance organizations are slow to make use of the broader range of data and apply advanced analytics to it.
Topics: Big Data, Planning, Predictive Analytics, Governance, Office of Finance, Budgeting, close, Finance Analytics, Tax, Analytics, Business Analytics, Business Intelligence, Business Performance, CIO, Financial Performance, Governance, Risk & Compliance (GRC), In-memory, Information Management, CFO, Risk, CEO, Financial Performance Management, FPM
SAP Supercharges Business Intelligence with Analytics
SAP recently presented its analytics and business intelligence roadmap and new innovations to about 1,700 customers and partners using SAP BusinessObjects at its SAP Insider event (#BI2014). SAP has one of the largest presences in business intelligence due to its installed base of SAP BusinessObjects customers. The company intends to defend its current position in the established business intelligence (BI) market while expanding in the areas of databases, discovery analytics and advanced analytics. As I discussed a year ago, SAP faces an innovator’s dilemma in parts of its portfolio, but it is working aggressively to get ahead of competitors.
Topics: Predictive Analytics, SAP, Business Objects, IT Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, KXEN, Operational Intelligence, HANA, Lumira, SAP insider
Anaplan, a provider of cloud-based business planning software for sales, operations, and finance and administration departments, recently implemented its new Winter ’14 Release for customers. This release builds on my colleagues analysis on their innovation in business modeling and planning in 2013. Anaplan’s primary objective is to give companies a workable alternative to spreadsheets for business planning. It is a field in which opportunity exists. Our benchmark research on this topic finds that a majority of companies continue to use spreadsheets for their planning activities. Almost all (83%) operations departments use spreadsheets for their plans, as do 60 percent of sales and marketing units. Yet the same research shows that satisfaction with spreadsheets as a planning tool is considerably lower than satisfaction with dedicated planning applications. But despite general agreement in companies that the planning process is broken and spreadsheets are a problem, companies seem reluctant to break the bad habit of using spreadsheets. This conclusion suggests that either switching to dedicated software hasn’t been easy enough or that the results of doing it have not been compelling enough to motivate change. Anaplan intends to address both of these issues.
Topics: Big Data, Performance Management, Planning, Predictive Analytics, Sales Performance, Supply Chain Performance, Marketing, Office of Finance, Operations, Reporting, Budgeting, Controller, Operational Performance, Business Analytics, Business Performance, Cloud Computing, Financial Performance, In-memory, Workforce Performance, CFO, Sales Planning, Financial Performance Management, financial reporting, FPM, Integrated Business Planning
SAS Innovates the Potential of Business Analytics
SAS Institute, a long-established provider analytics software, showed off its latest technology innovations and product road maps at its recent analyst conference. In a very competitive market, SAS is not standing still, and executives showed progress on the goals introduced at last year’s conference, which I covered. SAS’s Visual Analytics software, integrated with an in-memory analytics engine called LASR, remains the company’s flagship product in its modernized portfolio. CEO Jim Goodnight demonstrated Visual Analytics’ sophisticated integration with statistical capabilities, which is something the company sees as a differentiator going forward. The product already provides automated charting capabilities, forecasting and scenario analysis, and SAS probably has been doing user-experience testing, since the visual interactivity is better than what I saw last year. SAS has put Visual Analytics on a six-month release cadence, which is a fast pace but necessary to keep up with the industry.
Topics: Predictive Analytics, IT Performance, LASR, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloudera, Customer & Contact Center, Hortonworks, IBM, Information Applications, SAS institute, Strata+Hadoop
Big Data Analytics Research Reveals Benefits of Investment
We recently released our benchmark research on big data analytics, and it sheds light on many of the most important discussions occurring in business technology today. The study’s structure was based on the big data analytics framework that I laid out last year as well as the framework that my colleague Mark Smith put forth on the four types of discovery technology available. These frameworks view big data and analytics as part of a major change that includes a movement from designed data to organic data, the bringing together of analytics and data in a single system, and a corresponding move away from the technology-oriented three Vs of big data to the business-oriented three Ws of data. Our big data analytics research confirms these trends but also reveals some important subtleties and new findings with respect to this important emerging market. I want to share three of the most interesting and even surprising results and their implications for the big data analytics market.
Topics: Big Data, Pentaho, Predictive Analytics, Sales Performance, Supply Chain Performance, IT Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance, Datawatch
Many businesses are close to being overwhelmed by the unceasing growth of data they must process and analyze to find insights that can improve their operations and results. To manage this big data they find a rapidly expanding portfolio of technology products. A significant vendor in this market is SAS Institute. I recently attended the company’s annual analyst summit, Inside Intelligence 2014 (Twitter Hashtag #SASSB). SAS reported more than $3 billion in software revenue for 2013 and is known globally for its analytics software. Recently it has become a more significant presence in data management as well. SAS provides applications for various lines of business and industries in areas as diverse as fraud prevention, security, customer service and marketing. To accomplish this it applies analytics to what is now called big data, but the company has many decades of experience in dealing with large volumes of data. Recently SAS set a goal to be the vendor of choice for the analytic, data and visualization software needs for Hadoop. To achieve this aggressive goal the company will have to make significant further investments in not only its products but also marketing and sales. Our benchmark research on big data analytics shows that three out of four (76%) organizations view big data analytics as analyzing data from all sources, not just one, which sets the bar high for vendors seeking to win their business.
Topics: Big Data, Predictive Analytics, SAS, Event Stream, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, CIO, Customer & Contact Center, Data Management, Information Applications, Information Management, Location Intelligence, Operational Intelligence, Discovery
Human Capital Analytics Delivers Benefits for Business
The market for human capital analytics is in flux, as companies begin to evaluate and adopt more capable tools and processes for this area of human capital management. A look at the tools organizations are using and plan to use for human capital analytics provides an example of this change. Our recently published benchmark research on human capital analytics shows that nearly nine in 10 (87%) organizations are still using spreadsheets for human capital analytics while fewer than two in five (37%) presently use a dedicated human capital analytics tool. However, it also shows the market’s greatest growth yet, as more than two in five (43%) organizations said they will implement dedicated tools in the future. And organizations are recognizing the imperative of making such an investment: Two-thirds of those in our research consider human capital analytics important or very important.
Topics: Big Data, Mobile, Predictive Analytics, Social Media, HCM, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Collaboration, Financial Performance, Information Management, Workforce Performance
A core objective of my research practice and agenda is to help the Office of Finance improve its performance by better utilizing information technology. As we kick off 2014, I see five initiatives that CFOs and controllers should adopt to improve their execution of core finance functions and free up time to concentrate on increasing their department’s strategic value. Finance organizations – especially those that need to improve performance – usually find it difficult to find the resources to invest in increasing their strategic value. However, any of the first three initiatives mentioned below will enable them to operate more efficiently as well as improve performance. These initiatives have been central to my focus for the past decade. The final two are relatively new and reflect the evolution of technology to enable finance departments to deliver better results. Every finance organization should adopt at least one of these five as a priority this year.
Topics: Big Data, Performance Management, Planning, Predictive Analytics, Sales Performance, Supply Chain Performance, Office of Finance, Budgeting, close, dashboard, PRO, Tax, Analytics, Business Analytics, Business Collaboration, Business Performance, CIO, Customer & Contact Center, Financial Performance, In-memory, CFO, Supply Chain, CEO, demand management, Financial Performance Management, FPM, S&OP
Senior finance executives and finance organizations that want to improve their performance must recognize that technology is a key tool for doing high-quality work. To test this premise, imagine how smoothly your company would operate if all of its finance and administrative software and hardware were 25 years old. In almost all cases the company wouldn’t be able to compete at all or would be at a substantial disadvantage. Having the latest technology isn’t always necessary, but even though software doesn’t wear out in a physical sense, it has a useful life span, at the end of which it needs replacement. As an example, late in 2013 a major U.K. bank experienced two system-wide failures in rapid succession caused by its decades-old mainframe systems; these breakdowns followed a similarly costly failure in 2012. For years the cost and risk of replacing these legacy systems kept management from taking the plunge. What they didn’t consider were the cost and risk associated with keeping the existing systems going. Our new research agenda for the Office of Finance attempts to find a balance between the leading edge and the mainstream that will help businesses find practical solutions.
Topics: Big Data, Planning, Predictive Analytics, Governance, GRC, Office of Finance, Budgeting, close, Tax, Analytics, Business Analytics, Business Collaboration, Business Performance, CIO, Cloud Computing, Financial Performance, Governance, Risk & Compliance (GRC), In-memory, CFO, Risk, CEO, Financial Performance Management, FPM
IBM Brings New Innovation in Analytics for Business Insights
Like every large technology corporation today, IBM faces an innovator’s dilemma in at least some of its business. That phrase comes from Clayton Christensen’s seminal work, The Innovator’s Dilemma, originally published in 1997, which documents the dynamics of disruptive markets and their impacts on organizations. Christensen makes the key point that an innovative company can succeed or fail depending on what it does with the cash generated by continuing operations. In the case of IBM, it puts around US$6 billion a year into research and development; in recent years much of this investment has gone into research on big data and analytics, two of the hottest areas in 21st century business technology. At the company’s recent Information On Demand (IOD) conference in Las Vegas, presenters showed off much of this innovative portfolio.
Topics: Predictive Analytics, IT Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, IBM, Information Applications, Data Discovery, Discovery, Information Discovery, SPSS
All the hubbub around big data and analytics has many senior finance executives wondering what the big deal is and what they should do about it. It can be especially confusing because much of what’s covered and discussed on this topic is geared toward technologists and others working outside of Finance, in areas such as sales, marketing and risk management. But finance executives need to position their organization to harness this technology to support the strategic goals of their company. To do so, they must have clarity as to what big data can do, what they want it to do, and what skills and tools they need to meet their objectives.
Topics: Big Data, Performance Management, Predictive Analytics, Customer Experience, Fraud, Governance, GRC, Office of Finance, audit, Controller, Analytics, Business Analytics, Business Performance, Cloud Computing, Financial Performance, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, CFO, compliance, finance, Risk, Financial Performance Management, financial risk management
Nuevora Takes Flexible Approach to Big Data Analytics
While covering providers of business analytics software, it is also interesting for me to look at some that focus on the people, process and implementation aspects in big data and analytics. One such company is Nuevora, which uses a flexible platform to provide customized analytic solutions. I recently met the company’s founder, Phani Nagarjuna, when we appeared on a panel at the Predictive Analytics World conference in San Diego.
Topics: Big Data, Predictive Analytics, IT Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Information Applications, Strata+Hadoop
Big Data and Analytics Helps Business Transform and Gain Competitive Advantage
In our benchmark research on business technology innovation, organizations ranked analytics the number-one priority (for 39%) among six technology trends. Big data, perhaps because it is a more technical concept, ranked fifth, with 11 percent of organizations calling it a top innovation priority. But in this time of global business, nonstop communications and fierce competition, more organizations are finding that big data and analytics together can help them cope with constant change. They can help organizations face imperatives such as increasing time-to-value and becoming more agile and adaptive.
Topics: Big Data, Predictive Analytics, Human Capital, IT Research, Analytics, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Information Applications, Talent Management
Tidemark Unifies New Generation of Business Planning Software
Tidemark announced the release of the Fall 2013 version of its eponymous cloud-based application that my colleague assessed earlier in 2013. This new release adds capabilities for labor planning and expense management as well profitability modeling and analysis. These two areas of planning and analysis are common to all businesses. The new release adds features that enhance the software’s ability to do sales forecasting, initiative planning and IT department planning. The company continues to refine its modeling capabilities to make it easier for people engaged in the planning process to translate their expectations and concerns into a quantified view of the future. For example, users now can build models using natural-language modeling. The objective is to eliminate the need for help from business analysts or experts trained in the use of a tool and immersed the details of the IT plumbing, such as the metadata used for specific general ledger accounts or operational data.
Topics: Big Data, Performance Management, Planning, Predictive Analytics, Sales Performance, Supply Chain Performance, Office of Finance, Reporting, Controller, Operational Performance, Analytics, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, In-memory, Workforce Performance, CFO, Tidemark, Financial Performance Management, financial reporting, FPM, Integrated Business Planning
CEOs and Executives Need Business Planning Software
Business planning is a new software category. These applications enable senior executives to integrate all the plans of business units into a single, integrated view, which helps them have more accurate plans, do more insightful what-if planning, achieve greater agility in reacting to changing business and economic conditions, and execute plans in a more coordinated fashion than was possible. Business planning software is intended for CEOs and COOs, who are not well served by current capabilities. Business planning software enables executives and managers to understand both the operational and the financial consequences of their actions, but it emphasizes the things that the various parts of the business focus on: units sold, sales calls made, the number and types of employees required, customers serviced and so on. Lines of business already do this but in a fragmented fashion using desktop spreadsheets circulated within silos via email. Business planning software provides a platform to support modeling in individual business units, individual planning processes and visualization of the impacts of changes in what-if scenarios. It offers a central data repository for all plans; our benchmark research shows the advantage of this approach: Companies that directly link individual business unit data to an integrated plan get more accurate results. To be specific, 22 percent of those with such links have very accurate budgets compared to just a handful with less direct links and none that employ summarized data.
Topics: Big Data, Performance Management, Planning, Predictive Analytics, Office of Finance, Reporting, Budgeting, Controller, Operational Performance, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Financial Performance, In-memory, Workforce Performance, CFO, Financial Performance Management, financial reporting, FPM, Integrated Business Planning
It’s Past Time for the Next Generation of Business Planning
Business planning as practiced today is a relic, a process hemmed in by obsolete conceptions of what it should be. I use the term “business planning” to encompass all of the forward-looking activities in which companies routinely engage, including, for example, sales, production and head-count planning as well as budgeting. Companies need to take a fresh view of all these, adopting a new approach to business planning that while preserving continuity makes a substantial departure from what most companies do now. Currently, in most organizations the budget is the only companywide business plan. However, while necessary for financial management and control, budgets are not especially useful for running an organization.
Topics: Big Data, Planning, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Office of Finance, Reporting, Budgeting, Controller, Operational Performance, Business Performance, Financial Performance, In-memory, Workforce Performance, CFO, Financial Performance Management, financial reporting, FPM, Integrated Business Planning
Find Out Which Is the Hottest Financial Performance Management Software
We recently issued our 2013 Value Index on Financial Performance Management. Ventana Research defines financial performance management (FPM) as the process of addressing the often overlapping people, process, information and technology issues that affect how well finance organizations operate and support the activities of the rest of their organization. FPM deals with the full cycle of finance department activities, which includes planning and budgeting, analysis, assessment and review, closing and consolidation, and internal and external financial reporting, as well as the underlying IT systems that support them. Our Value Index is informed by more than a decade of analysis of how well technology suppliers and their products satisfy specific business and IT needs. We perform a detailed evaluation of product functionality and suitability to task in five categories as well as of the effectiveness of vendor support for the buying process and customer assurance. Our resulting index gauges the value offered by each individual vendor and its products in supporting FPM, which is necessary for running an organization efficiently and effectively.
Topics: Mobile, Planning, Predictive Analytics, Office of Finance, Budgeting, closing, Consolidation, contingency planning, Analytics, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Financial Performance, CFO, Value Index, Financial Performance Management
R, the open source programming language for statistics and graphics, has now become established in academic computing and holds significant potential for businesses struggling to fill the analytics skills gap. The software industry has picked up on this potential, and the majority of business intelligence and analytics players have added an R-oriented strategy to their portfolio. In this context, it is relevant to look at some of the problems that R addresses and some of the challenges to its adoption.
Topics: Big Data, Predictive Analytics, Analytics, Business Analytics, Business Intelligence, Customer & Contact Center, Information Applications, Information Management
Many finance executives want to improve their department’s effectiveness in order to play a more strategic role in their company. However, frequently they find at least three serious challenges to achieving this sort of finance transformation. One is that too much time and resources are devoted to purely mechanical tasks. Another is that the information executives need is not always available immediately. A third is that they lack the data (which is unavailable or too difficult to access), the analytic tools or both to do rapid contingency planning. One area in the Office of Finance that needs particular attention is treasury, as I commented recently. Treasury management is a challenge because it’s highly detailed and demands complete accuracy. These requirements make it an area that can benefit from more automation.
Topics: Predictive Analytics, Office of Finance, Controller, credit, debt, Kyriba Financial Performance Management, Analytics, Business Performance, Financial Performance, CFO, cash management
Big Data Brewing Value in Human Capital Management
In recent months I have been asked a straightforward question by several clients: How do you define big data in the context of human capital management? More specifically, the question isn’t so much about the classic definition of big data – which includes the storage and use of high volume of data, high velocity of data and high variety of data, commonly known as the 3Vs – but really has two parts: What are the key differentiators between analytics applications and big data applications, and to what degree must an application include external data to be considered big data? Ventana Research has been covering big data for some time, and my colleague Tony Cosentino wrote about big data and workforce Analytics last September. But both human capital management and big data have evolved since then, so I think it’s worth writing about again.
Topics: Big Data, Predictive Analytics, Social Media, HCM, analytical discovery, Business Analytics, Business Intelligence, Workforce Performance
Along with other aspects of the finance organization, there’s increasing emphasis on having the treasury function play more of a strategic role in the organization. Typically, Treasury is charged with keeping track of and managing cash. Especially in larger organizations, this can be complicated because of multiple bank accounts, complex financing requirements and many methods of receiving and making payments; the complexity deepens when more than one currency is used across multiple jurisdictions, which also can pose regulatory issues. Treasury’s primary directive is to ensure that all funds are accounted for and that there is sufficient cash on hand each day to meet operating requirements. To accomplish this, finance professionals must perform key analytic tasks accurately to produce a clear picture of cash inflows and cash requirements. Analysis often is challenging because these numbers are constantly changing and because the process of collecting, analyzing and reporting all the data can be excessively time-consuming if done manually. This is a situation perfectly suited for dedicated applications that automatically manage the data needed to orchestrate treasury processes and provide analysis to inform decisions. Yet our benchmark research finds that more than half (56%) of companies with more than 1,000 employees either use spreadsheets exclusively or employ them heavily in conjunction with a treasury application.
Topics: Predictive Analytics, Office of Finance, Controller, credit, debt, Analytics, Business Performance, Financial Performance, CFO, cash management, Financial Performance Management
KXEN Provides Good Enough Modeling for Predicting Business Outcomes
Predictive analytics in an inherently difficult task and often takes specialized skills. While not easy, the business results of predictive analytics can be significant. 68% of companies say they use predictive analytics to create competitive advantage while 55% say that they increase revenue. KXEN is a software company that specializes in making predictive analytics easier to use by automating predictive analytic processes and some data preparation tasks. Like other predictive analytics companies, KXEN targets uses cases in risk and fraud prevention, operations and customer service, but given its end-user focus, it is natural that the company seems to be finding a niche on the customer-facing side of business in areas such as sales operations and marketing.
Topics: Predictive Analytics, Sales Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Information Applications, KXEN, Operational Intelligence, commodity models
IBM’s Big Data and Analytics Analyst Insights conference started me thinking about the longer-term potential impact of big data and related technologies on business management. I covered some of the near-term uses of big data and analytics in an earlier perspective. There are numerous uses of big data that can provide incremental improvements to existing processes and practices. Some of these will have a significant impact on changing business models, enabling new classes of products and services and improving performance. As well, the technology will have more profound, longer lasting effects. The ability to analyze large quantities of business-related data rapidly has the potential to set in motion fundamental changes in how executives and managers run their business. Properly deployed, it will enable a more forward-looking and agile management style even in very large enterprises. It will allow more flexible forms of business organization. None of these changes will be universal, and the old school will be with us for some time. Technology, however, will give executives and their boards of directors a powerful tool for strategic differentiation to achieve a sustainable competitive advantage.
Topics: Big Data, Planning, Predictive Analytics, Management, Budgeting, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, IBM, Information Management, decision, FPM, Watson
Five Principles for Optimizing Business Analytics
Organizations today must manage and understand a flood of information that continues to increase in volume and turn it into competitive advantage through better decision making. To do that organizations need new tools, but more importantly, the analytical process knowledge to use them well. Our benchmark research into big data and business analytics found that skills and training are substantial obstacles to using big data (for 79%) and analytics (77%) in organizations.
Topics: Data Science, Predictive Analytics, R, SAP, Analytics, Business Analytics, Business Intelligence, Business Performance, IBM, Information Applications, Operational Intelligence, Oracle
At this year’s annual SAP user conference, SAPPHIRE, the technology giant showed advances in its cloud and in-memory computing efforts. It has completed the migration of its conventional application suite and portfolio of tools to operate on SAP HANA, its in-memory computing platform, and made improvements in its cloud computing environment, SAP HANA Enterprise Cloud. The last time I analyzed SAP HANA was when it won our firm’s 2012 Overall IT Technology Innovation Award. Now HANA has been transitioned from just a database technology into a broad platform. SAP wisely consolidated its efforts previously known as SAP NetWeaver into SAP HANA. This resolves some confusion regarding HANA and NetWeaver in the cloud, which I assessed. The recently announced SAP HANA Platform now provides the enterprise class of HANA implementation in the cloud. It comes with a trial edition of the data and visual discovery technology now called SAP Lumira, whose price has been reduced to encourage adoption (and which I discuss more below). The use of in-memory databases for big data is accelerating: According to our technology innovation research, 22 percent of organizations are planning to use this technology over the next two years, and through 2015 it will have a higher growth rate than other approaches.
Topics: Big Data, Predictive Analytics, SAP, Social Media, Supply Chain Performance, Teradata, Mobile Technology, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, CIO, Cloud Computing, Customer & Contact Center, Financial Performance, Governance, Risk & Compliance (GRC), HP, Information Applications, Information Management, Workforce Performance, CFO, CMO, SAP EPM, SAP HANA, SAP Lumira, SAPPHIRE, Tagetik
Alteryx 8.5 Focuses on the User Experience of the “New Boss”
This year’s Inspire, Alteryx’s annual user conference, featured new developments around the company’s analytics platform. Alteryx CEO Dean Stoecker kicked off the event by talking about the promise of big data, the dissemination of analytics throughout the organization, and the data artisan as the “new boss.” Alteryx coined the term “data artisan” to represent the persona at the center of the company’s development and marketing efforts. My colleague Mark Smith wrote about the rise of the data artisan in his analysis of last year’s event.
Topics: Predictive Analytics, Sales Performance, Tableau, alteryx, Absolute Data, data artisan, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Data Integration, Information Applications, Operational Intelligence
Getting to the Next Generation of Finance Analytics
One of the most important IT trends over the past decade has been the proliferation of ever wider and deeper sets of information sources that businesses use to collect, track and analyze data. While structured numerical data remains the most common category, organizations are also learning to exploit semistructured data (text, for example) as well as more complex data types such as voice and image files. They use these analytics increasingly in every aspect of their business – to assess financial performance, process quality, operational status, risk and even governance and compliance. Properly applied, business analytics can deliver significant value by deepening insight, supporting better decision-making and providing alerts when situations require attention from managers or executives.
Topics: Planning, Predictive Analytics, Customer, Human Capital Management, Office of Finance, Budgeting, close, closing, Finance Analytics, PRO, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Financial Performance, CFO, Risk, costing, FPM, Profitability
I recently attended the annual SAS analyst summit to hear the latest company, product and customer growth news from the multi-billion-dollar analytics software provider. This global giant continues to grow its business and solutions to help with fraud prevention, marketing and risk. It lets users apply its analytic and statistical technology in practical applications for business. SAS can meet midsized businesses’ demand with packaging and pricing to ensure it is not seen as only affordable to Global 2000 companies. SAS’ growth in analytics should be no surprise, as our research finds analytics to be the first-ranked priority among technologies for innovating business.
Topics: Big Data, Predictive Analytics, Sales Performance, SAS, Fraud, GRC, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, CIO, Cloud Computing, Customer & Contact Center, Data Integration, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Operational Intelligence, Risk
I’ve frequently commented on the artificiality of the emerging software category of governance, risk and compliance (GRC). The term is used to a cover a combination of what were once viewed as stand-alone software categories, including IT governance, audit documentation and industry-specific compliance management, to name three examples. While it’s still common for specific types of software to be purchased piecemeal by different departments, these disparate areas have started a long convergence process. Since just about all controls and risk management efforts require a secure IT environment to be effective, there is a growing interdependence between effective IT governance and everything else connected with enterprise GRC.
Topics: Big Data, Performance Management, Predictive Analytics, Customer Experience, Governance, GRC, Management, Operational Performance, Analytics, Business Performance, Financial Performance, compliance, finance, Risk, financial risk management, IT Risk Management, Sarbanes Oxley, SOX
Big data analytics is being offered as the key to addressing a wide array of management and operational needs across business and IT. But the label “big data analytics” is used in a variety of ways, confusing people about its usefulness and value and about how best to implement to drive business value. The uncertainty this causes poses a challenge for organizations that want to take advantage of big data in order to gain competitive advantage, comply with regulations, manage risk and improve profitability. Should organizations invest further into visual or deep data discovery on big data, or delve more deeply into statistics and predictive analytics, or find new ways to integrate big data into current operational systems?
Topics: Predictive Analytics, Sales Performance, SAP, IT Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, IBM, Information Applications, Information Management, Data Discovery, big analytics
The Secrets to Big Data and Information Optimization Revealed in 2013 Research Agenda
Managing the access, storage and use of data effectively can provide businesses a competitive advantage. Last year I outlined what the big deal is in big data, as the initial focus on the volume, velocity and variety of data – what my colleague Tony Cosentino calls the three V’s – is only one small piece of how organizations should evaluate this technology. The more balanced approach is to include what he calls the three W’s – the what, so what and now what, which shifts the focus to an outcome-based view that can handle the time–to-value urgency found in business. Big data analytics can help assess the volume of data, while the velocity of data that is potentially in-motion is best handled by what we call operational intelligence. Beyond these, techniques and technology such as predictive analytics and visual discovery facilitate extracting more value from big data. Along with a wide variety of data, these tools help organizations focus on optimizing information assets. We will soon conduct benchmark research into information optimization to determine how organizations are dealing with their information today and what steps they are taking to improve. In-memory computing will surely be one of those steps, as it can significantly improve the time-to-insight equation.
Topics: Big Data, Master Data Management, Predictive Analytics, Sales Performance, MDM, Operational Performance, Business Analytics, Business Intelligence, Business Performance, CIO, Cloud Computing, Data Governance, Data Integration, Financial Performance, Information Applications, Information Management, Location Intelligence, Operational Intelligence, Product Information Management
For the past couple of years I’ve been pointing to the importance of in-memory computing to the future of business applications. It’s an integral part of Ventana Research’s business and finance research agenda for 2013, and it’s one of the core technologies that senior executives should have an appreciation for because it can transform all core business processes, especially those that are analytic in nature.
Topics: Mobile, Predictive Analytics, Real-time, Sales Performance, SAP, Supply Chain Performance, ERP, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, In-memory, Workforce Performance, CRM, finance, Social, Business Suite, Financial Performance Management, HANA
Businesses always see a lag between when technology makes some advance possible and when a majority of companies actually adopt it. There’s even a longer lag between the emergence of an advance in a business process or technique and the time it takes to become mainstream. When we write our research agendas at the top of each year, we have to strike a balance between focusing on the new and different, which is still many years away from general acceptance, and the mainstream, which has been anticipated for so long that it almost seems passé. Our research agenda for office of finance to support business for 2013, which I just finalized, is once again an attempt to balance the leading edge and the mainstream with an eye to practical solutions.
Topics: Big Data, Planning, Predictive Analytics, Sales Performance, Governance, GRC, Office of Finance, Budgeting, close, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Performance, CIO, Cloud Computing, Financial Performance, Governance, Risk & Compliance (GRC), In-memory, Workforce Performance, CFO, Risk, CEO, Financial Performance Management, FPM
What Every CEO Should Know About Software for Finance and Sales
This is the third in a series of blog posts on what CEOs (and for that matter, all senior corporate executives) need to know about IT and its impact on running a business. The first covered the high-level issues. As I noted, it’s not necessary for a CEO to be able to write Java code or master the intricacies of an ERP or sales compensation application. However, CEOs must grasp the basics of IT just as they must understand basic corporate finance, the production process and – at least at a high level – the technologies that support that process. My second post was about four supporting technologies that will drive change in business computing over the next five years. It relates examples of how applications can help every part of a business operate more effectively, not just efficiently. Now let’s turn our attention to finance and sales – and as I’ve noted in the previous posts, what follows is an “elevator pitch” treatment of what could be a much longer discussion.
Topics: Planning, Predictive Analytics, Sales, Sales Performance, Customer, Human Capital Management, Office of Finance, Budgeting, close, closing, PRO, Operational Performance, Analytics, Business Analytics, Business Performance, Customer & Contact Center, Financial Performance, Information Management, CFO, CEO, FPM, Profitability, SPM
Big data was big news in 2012 and probably in 2013 too. The Harvard Business Review talks about it as The Management Revolution. The Wall Street Journal says Meet the New Boss: Big Data, and Big Data is on the Rise, Bringing Big Questions. Given big data’s popularity in the press, you might think that the technology market is only about big data and how companies use the vast and growing amount of data now available to organizations. While this technology can provide a significant opportunity, the reality is that just having big data does not provide an organization with the intelligence to be more efficient or grow market share. It can provide the foundation on which organizations can assemble technologies and applications that can help realize these opportunities, but organizations need to focus on the big picture, which encompasses additional layers of technology that work together with big data. Our recent benchmark research on business technology innovation found that big data is not the top priority for business or IT; analytics, collaboration, mobile and cloud computing are all more important. Organizations do believe that big data is very important (25%), but if they were pushed to prioritize technologies, it would not top the list.
Topics: Big Data, Data Warehousing, Predictive Analytics, Social Media, Harvard Business Review, Wall Street Journal, IT Performance, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, CIO, Cloud Computing, Customer & Contact Center, Financial Performance, Information Management, Technology Innovation, Strata+Hadoop
IBM’s SPSS Shows Chops in Predictive Analytics
IBM acquired SPSS in late 2009 and has been investing steadily in the business as a key component of its overall business analytics portfolio. Today, SPSS provides an integrated approach to predictive analytics through four software packages: SPSS Data Collection, SPSS Statistics, SPSS Modeler and SPSS Decision Management. SPSS is also integrated with Cognos Insight, IBM’s entry into the visual discovery arena.
Topics: Predictive Analytics, Social Media, IT Performance, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Customer & Contact Center, IBM, Workforce Performance, SPSS
Salesforce Struggles to Deliver on the Dream of Analytics
I was at the Salesforce.com Dreamforce conference this week to hear about the latest advancements from the cloud computing software giant. Salesforce has helped revolutionize cloud computing for business, and its social media and collaborative technologies help advance business processes in sales, customer service and improve the interactions between employees, partners and customers. Salesforce has made great advancements in cloud, social and mobile technology, as I have assessed and my colleague did too.
Topics: Big Data, Predictive Analytics, QlikView, Sales Performance, Salesforce.com, Social Media, Gooddata, SnapLogic, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, InetSoft, Information Applications, Information Management, KXEN, Operational Intelligence, Cloud9 Analytics, Domo, Information Builder iway, Roambi
I had a refreshing call this morning with a vendor that did not revolve around integration of systems, types of data, and the intricacies of NoSQL approaches. Instead, the discussion was about how its business users analyze an important and complex problem and how the company’s software enables that analysis. The topic of big data never came up, and it was not needed, because the conversation was business-driven and issue-specific.
Topics: Big Data, Datameer, Predictive Analytics, Sales Performance, Supply Chain Performance, Planview, SuccessFactors, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, IBM, Information Management, Operational Intelligence, Workforce Performance, PivotLink
Good Data Stewardship Is Critical for Business Analytics
Our research consistently finds that defects in data are the root cause of a wide range of problems encountered by modern corporations. The magnitude of the problem correlates with the size of the company: Big companies have bigger headaches than midsize ones. Data issues diminish productivity in every part of a business as people struggle to correct errors or find workarounds. Issues with data are a man-made phenomenon, yet companies seem to treat bad data as some sort of force of nature like a tornado or earthquake – something that’s beyond their control to fix. At best they look for one-off workarounds and Band-Aids without tackling the root causes or recognizing the need to keep data issues in check. Data stewardship can and should be a part of a disciplined approach to management in the same way organizations implement quality control, cash management and legal compliance.
Topics: Big Data, Predictive Analytics, Sales Performance, Supply Chain Performance, GRC, IT Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, CIO, Customer & Contact Center, Financial Performance, Information Management, Operational Intelligence, Workforce Performance, CFO, finance, FPM
A study by the McKinsey Global Institute published earlier this year suggests a coming shortage of more than 140,000 workers with deep analytical skills and a shortage of more than 1.5 million data-literate managers. I’m not sure how the study defined these roles, but I’d guess that those with deep analytic skills are those folks building the complex models, and the data-literate managers are those executives, middle managers and analysts who interpret the results and use the models to help drive business decisions. In other words, businesses are facing two skills gaps – one related to those producing the analytics, the other related to those using them in some type of discovery or review purpose.
Topics: Big Data, Data Scientist, Predictive Analytics, Sales Performance, IT Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Operational Intelligence, Workforce Performance
Over the years Tibco has provided infrastructure for enterprise data integration and has built a substantial installed base. Now the company positions itself as supplying next-generation analytics for big data through service-oriented architecture (SOA). SOA has been around for a while; Ventana Research has been tracking it since 2006 and conducted benchmark research on SOA. But it remains a vaguely understood technology. Our research shows that SOA is not clearly defined in the market and that interpretations vary across the software industry. The basic function of an SOA is to provide common components and a common implementation that enable programmers to plug in and share applications through open application programming interfaces (APIs). In recent years, SOA has morphed into more of a general approach than a fixed set of standards. SOA architectures (though not always called SOA) are at the heart of modern platforms such as salesforce.com, Facebook and Amazon Web Services. In SOA Tibco competes with IBM and Oracle, among others.
Topics: Big Data, Predictive Analytics, Sales Performance, SOA, Spotfire, IT Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Complex Event Processing, Customer & Contact Center, Information Management, Operational Intelligence, Tibco, CEP, Service Cloud
Predictive Analytics Move Toward Center Stage
In this second in a blog series on business analytics I focus on the increasingly important area of predictive analytics. Our benchmark research into predictive analytics shows that while the vast majority of companies see this technology as important or very important for the future of their organizations, most are not taking full advantage of it. This finding suggests that there is an opportunity for companies to gain competitive advantage by implementing predictive analytics in the near term.
Topics: Big Data, Predictive Analytics, Sales Performance, Supply Chain Performance, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Operational Intelligence, Workforce Performance
Making Sense of the Swirling World of Business Analytics
Our benchmark research on business analytics suggests that it is counterproductive to take a general approach to the topic. A better approach is to focus on particular use cases and lines of business (LOB). For this reason, in a series of upcoming articles, I will look at our business analytics research in the context of different industries and different functional areas of an organization, and illustrate how analytics are being applied to solve real business problems.
Topics: Big Data, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, IT Performance, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance
Microstrategy Provides Hadoop and Predictive Analytics with Version 9.3
MicroStrategy, announced version 9.3. The announcement came out of Amsterdam this month just in front of MicroStrategy World, the company’s annual conference for the European market. Release 9.3 delivers significant updates in four main areas: big data, advanced analytics, automated administration and visual data discovery.
Topics: Big Data, MicroStrategy, Mobile, Predictive Analytics, Sales Performance, IT Performance, Operational Performance, Visual Insight, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Information Applications, Operational Intelligence, Workforce Performance, Digital Technology
My research into customer experience management shows that companies are increasingly aware that the customer experience has a profound impact on business success. In almost equal numbers, participants said it determines the loyalty of customers (21%), the propensity of customers to recommend the company to others (21%), the amount of additional purchases they make (19%) and their general level of satisfaction (19%). Furthermore, companies also realize that good experiences save money, because customers complain less (11%) and contact them less frequently (9%).
Topics: Predictive Analytics, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Analytics, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Vendor(s), Workforce Force Optimization
Is Your Vendor Hot in Financial Performance Management Software?
We recently issued our 2012 Value Index on Financial Performance Management (FPM). Ventana Research defines FPM as the process of addressing the often overlapping people, process, information and technology issues that affect how well finance organizations operate and support the activities of the rest of their organization. FPM deals with the full cycle of finance department activities, which includes planning and budgeting, analysis, assessment and review, closing and consolidation, internal financial reporting and external financial reporting, as well as the underlying information technology systems that support them. We construct the Index through a detailed evaluation of each product’s suitability to task in five categories, as well as the effectiveness of the vendor’s support for the buying process and customer assurance. The resulting index gauges the value offered by a vendor and its products.
Topics: Mobile, Planning, Predictive Analytics, Office of Finance, Budgeting, closing, Consolidation, contingency planning, Analytics, Business Analytics, Business Performance, Financial Performance, CFO, Value Index, Financial Performance Management
Agents Performance Management is Hot for Successful Customer Interactions
Our benchmark research into agent performance management shows that the majority of companies are not very mature in their use of people, processes, information and technology in handling customer interactions. Companies are most mature is their use of information, but even in this area they are hampered by their failure to use the latest technologies available to support their efforts.
Topics: Predictive Analytics, Sales Performance, Social Media, Customer Analytics, NICE Systems, Speech Analytics, Voice of the Customer, VPI, Call Copy, Enkata, Envision, Genesys, KnopahSoft, LiveOps, Operational Performance, Analytics, Business Analytics, Business Performance, Cloud Computing, Customer & Contact Center, Workforce Performance, Call Center, coaching, Compensation, Contact Center, Contact Center Analytics, Desktop Analytics, Text Analytics, OnviSource, Training, Verint, Workforce Force Optimization
One of the most important trends in business over the past 20 years has been the broadening use of information technology to manage and support activities. In the early decades of business computing, companies developed islands of automation for largely numeric functions such as billing, inventory management and accounting. Each ran on a proprietary system and engaged the time of a relative handful of employees. Today, just about everyone works with an IT system for at least some of their operational or administrative tasks. They rely on these systems to support many of their daily routines, from recording transactions to using analytics to provide alerts, insights and decision support.
Topics: Big Data, Performance Management, Predictive Analytics, Customer Experience, Governance, GRC, Management, IT Performance, Operational Performance, Analytics, Business Intelligence, Business Performance, Financial Performance, Governance, Risk & Compliance (GRC), compliance, finance, Risk, financial risk management, IT Risk Management
Risk has always been an integral part of business, but our recent Governance, Risk and Compliance (GRC) benchmark research shows that companies deal with risk with varying degrees of effectiveness – especially operational risk. A majority of companies lag in their overall GRC maturity, as I covered in a recent blog post. Operational risk management should be of greater interest to executives today because they can have greater control of it than before. The expansion of IT systems to automate and support most business processes has made it easier than ever to measure, monitor and report on what’s going on in a company. It’s now practical to expand the scope of operational risk management and improve companies’ effectiveness in handling risk events when they occur.
Topics: Big Data, Performance Management, Predictive Analytics, Sales Performance, Supply Chain Performance, Customer Experience, Governance, GRC, Management, IT Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance, compliance, finance, Risk, financial risk management
Our benchmark research on business analytics finds that just 13 percent of companies overall and 11 percent of finance departments use predictive analytics. I think advanced analytics – especially predictive analytics – should play a larger role in managing organizations. Making it easier to create and consume advanced analytics would help organizations broaden their integration in business planning and execution. This was one of the points that SPSS, an IBM subsidiary that provides analytics, addressed at IBM’s recent analyst summit.
Topics: Big Data, Performance Management, Planning, Predictive Analytics, Marketing, Modeling, Sales Forecasting, Analytics, IBM, Uncategorized, SPSS
Social Dynamx Enables Social Customer Service
I hear a lot of talk about the impact of social media on customer service and the contact center. My research into customer relationship maturity shows much of this is only talk. The research shows that while many companies have rushed to create a Twitter handle and a Facebook page and put video on YouTube, most are struggling to integrate social media into their customer service or more broadly their customer engagement strategy and processes.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Experience, Social CRM, Speech Analytics, Voice of the Customer, Analytics, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Social Dynamx
IBM Advances Predictive Analytics for Decision Management
At its Business Analytics Analyst Summit (Twitter: #IBMBAS12) this week, IBM unveiled its new release of analytics software for decision management. Over the last 25 years decision support systems have transformed into decision management, in which analytics, rules and optimization methods help organizations use information to guide optimal outcomes. IBM has experience and technology in these areas, most of it acquired, to apply to specific organizational needs in vertical industries. In addition, IBM has advanced its information management technologies to support big data and predictive analytics in operational environments. Its stream- and event-processing technology helps speed routing and analysis of information across business processes. Each of these are critical for supporting decision management technology needs for business processes.
Topics: Big Data, Predictive Analytics, Sales Performance, Supply Chain Performance, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, IBM, Workforce Performance, Business Process Management, Decision Management
SAS Expands Business Relevance in Using Analytics
After the SAS analyst event last year, I wrote that it is hard to keep track of everything SAS has to offer because it had so many products and developments in the pipeline. Back from this year’s event, I can report that 2011 was successful, its revenue and worldwide presence are up, and SAS continues to expand its channels to market. On top of everything I saw last year even more products and developments are in the pipeline, but the theme and focus remain the same: enabling business analytics.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Data Management, Customer Experience, Speech Analytics, Voice of the Customer, Management, Analytics, Business Analytics, Business Intelligence, Cloud Computing, Customer & Contact Center, Governance, Risk & Compliance (GRC), Contact Center Analytics, Desktop Analytics, Text Analytics, Vendor(s)
Vitria Aims To Boost Adoption of Operational Intelligence
Ventana Research was the first analyst firm to cover operational intelligence, and a while back I wrote how the products of Vitria support proactive customer service by using event data to anticipate likely impacts of operation issues on customer service. Our research into the use of analytics shows that while more mature companies have begun to adopt OI, they are mainly early adopters. In an effort to speed up adoption, Vitria has developed what it calls operational intelligence apps and it has opened up a trial program for companies to explore how they can help improve their operations using these new applications.
Topics: Predictive Analytics, Customer Analytics, Customer Experience, Social CRM, Speech Analytics, Vitria, Voice of the Customer, Operational Performance, Analytics, Cloud Computing, Customer & Contact Center, Customer Service, Information Applications, Operational Intelligence, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics
Jacada pioneered what I call a smart agent desktop when in 1990 it created the tools that allow companies to develop a desktop application that follows the process of handling a call, hides applications behind a simple-to-use interface and automates access and updating of systems. This smart agent desktop enables agents to answer calls more efficiently and effectively and to focus on the customer. The product includes tools that allow developers to map the process of handling different call types, build the user interface to match those processes, interface with applications and report on various aspects of how calls are handled.
Topics: Predictive Analytics, Customer Analytics, Customer Experience, Speech Analytics, Voice of the Customer, Jacada, Analytics, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics
Oversight Systems Focuses on Saving Money and Preventing Fraud
I recently spoke with Oversight Systems, an operational intelligence analytics company that uses predictive analytics and optimization to help companies save money, reduce the risk of loss and fraud, and reinforce corporate governance and compliance efforts. Ventana Research views operational intelligence as an emerging technology with the potential for a high return on investment. By continuously monitoring activities in a company’s IT systems, Oversight’s Web-based software continuously, consistently and objectively monitors all business processes to identifies opportunities to save money, cut fraud, minimize risk and provide real-time controls to support governance.
Topics: Big Data, Predictive Analytics, Sales Performance, Supply Chain Performance, Fraud, Governance, GRC, Office of Finance, audit, Operational Performance, Analytics, Business Analytics, Business Performance, Cloud Computing, Financial Performance, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, controls, Oversight Systems
Echopass Demonstrates Value of Contact Center in the Cloud
Our benchmark research into the contact center in the cloud shows that almost all companies now support multiple communication channels to engage with customers. Most of them also involve multiple business units in handling inbound and outbound interactions. More companies now support at-home agents, and contact centers are becoming more distributed. These scenarios are a good fit for cloud-based systems, and the research finds that the top three ways organizations said they can meet these challenges, and thus improve the way interactions are handled, are to improve training and coaching, adopt applications in the cloud and adopt communications in the cloud. It also shows that organizations have high expectations of cloud-based systems, expecting them to require less capital expenditure, facilitate innovation in interaction handling, lessen demand on in-house resources, including IT and better support home-based agents.
Topics: Predictive Analytics, Sales Performance, Customer Analytics, Customer Experience, Social CRM, Speech Analytics, Voice of the Customer, Echopass, Operational Performance, Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Information Applications, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications
Opera Solutions Orchestrates Intelligent Applications using Big Data and Predictive Analytics
Predictive analytics has the potential to help businesses increase the impacts of their actions by creating indicators that represent future outcomes based on existing behavior. This process becomes more complicated when they have to apply predictive analytics to what we call big data environments. As yet only 13 percent of organizations are using predictive analytics according to our business analytics benchmark research, although 37 percent indicated that predictive capabilities are very important to their business analytics efforts. Opera Solutions is one of the larger vendors of dedicated predictive analytics software, having more than 650 employees, more than 200 of them data scientists, who help organizations turn their data into actionable intelligence. There is opportunity for the company, as predictive analytics and visualization of data are two capabilities not available in four out of every five organizations according to our big-data benchmark research. Beyond creating indicators, Opera Solutions’ applications can generate signals that present results not only visually but also in English sentences that integrate the analytics and provide guidance for determining next steps. This sophisticated capability can help improve business processes and refine decision-making and truly interact with the application.
Topics: Big Data, Predictive Analytics, Opera Solutions, IT Performance, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Business Technology, CIO, Cloud Computing, Information Applications, Information Management, Information Technology, Operational Intelligence
Make It Simple for Customers To Engage with You
A recent research project involving 7,000 consumers carried out by the Harvard Business Review concluded that to retain customers and get them to buy more products, organizations must make it simple for people to engage with them, provide information they trust and allow them to weigh their options before they buy. The research found that consumers are bombarded with information and choices, and as a result they tend to go down the easiest route, which often leads them to take a blinkered view: I haven’t got the time and energy to consider options so I’ll take this one.
Topics: Predictive Analytics, Sales Performance, Social Media, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Analytics, Business Analytics, Business Collaboration, Cloud Computing, Customer & Contact Center, Customer Service, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Workforce Management
Interactive Intelligence Offers Customers Mobile Self-Service
Interactive Intelligence announced Interaction Mobilizer, the latest application in its growing portfolio of products. As I recently wrote, Interactive Intelligence has come a long way since it launched its first software-based PBX in 1994. It was a pioneer in offering contact center applications in the cloud, which now include communications in the cloud and products for workforce optimization. The latest announcement follows similar ones from other vendors also announcing applications to support mobile self-service. Each of those products supports slightly different sets of capabilities, but all of them follow the trend to provide organizations with another channel through which customers can interact with them, and support customers who want self-service capabilities from their smartphones or tablets.
Topics: Predictive Analytics, Sales Performance, Customer Analytics, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Information Applications, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Interactive Intelligence, Text Analytics, Unified Communications, Workforce Management
NICE Transforms Customer Experience through Mobile and Interaction Intelligence
I attended NICE Systems’ annual Interactions (Twitter #Interaction2012) conference in Nashville to get the latest from this growing global software business that focuses on customer-centric applications. If you have not heard of NICE you might not be primarily involved in managing and interacting with customers, the area in which NICE has been growing organically and by acquiring technology providers that complement its existing portfolio. As we discussed in recent analyses, and NICE acquired Merced Systems for its sales- and service-centric performance management applications and Fizzback for customer feedback management software. Both have helped it become a more strategically focused software business. NICE Systems targets enterprise contact centers as well as financial risk, compliance and security. NICE makes its applications available not just on-premises but also in software as a service and hosted environments.
Topics: Predictive Analytics, Sales Performance, Social Media, Customer Analytics, Customer Experience, Customer Feedback Management, NICE Systems, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Financial Performance, Governance, Risk & Compliance (GRC), Operational Intelligence, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Interactive Intelligence, Text Analytics, Unified Communications, Workforce Management
Customer Engagement Day Reveals New Issues and Opportunity
I recently attended the second in the series of customer engagement days organized by the Directors Club (GB & NI). The format of the event was the same as the first day that I wrote about and included three keynote presentations and three roundtable sessions where attendees discussed how organizations should engage with customers. As for the first event I chaired the roundtable on perfecting multichannel customer engagement in the contact center and gave a keynote on how social media is impacting the contact center.
Topics: Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Sustainability, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, NICE Systems, Social CRM, Speech Analytics, Voice of the Customer, Genesys, InContact, IT Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Financial Performance, Governance, Risk & Compliance (GRC), Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Interactive Intelligence, Text Analytics, Unified Communications, Workforce Management, Noble Systems, Verint
Verint Revamps Applications in Information-Driven Approach
Verint is one of the major players in the contact center market, with two suites of products that support contact centers and voice of the customer analysis. The company’s website shows that these suites have been put together from a combination of in-house developments and acquisitions (Blue Pumpkin, Witness Systems, Mercom, Iontas, GMT and Vovici are among them). Although this strategy has allowed Verint to create comprehensive suites of products in both areas, it also created issues with integration of the products and a lack of commonality in the user interface. These concerns were the main factors that kept Verint from being ranked as highly as it might have been in our last Value Index for Agent Performance Management (APM).
Topics: Predictive Analytics, Customer Analytics, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Workforce Management, Verint
Last December NICE Systems announced a definitive agreement to acquire Merced Systems. I have been covering both companies for several years, and initially it wasn’t obvious to me why the acquisition made sense. My colleague Mark Smith wrote about the deal and expressed concerns about how the acquisition would impact both sets of customers and both organizations. Now it turns out that the Merced acquisition will have a much bigger effect on NICE than expected.
Topics: Predictive Analytics, Sales Performance, Customer Analytics, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Workforce Management
SAS is one of the largest and best-known independent vendors of BI and analytics. The company’s website shows 16 product lines, and product variations to match almost every business analytics requirement in any industry. One of its core products lines is Customer Intelligence, which I wrote about last year. Customer Intelligence consists of four main components: strategy and planning, information and analytics, orchestration and interaction, and customer experience – among all these interesting areas, only the last really indicates what the products do.
Topics: Predictive Analytics, Sales Performance, SAS, Social Media, Customer Analytics, Customer Experience, Social CRM, Speech Analytics, Voice of the Customer, Customer Intelligence, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Cloud Computing, Customer & Contact Center, Customer Service, Information Applications, Information Management, Location Intelligence, Operational Intelligence, Contact Center Analytics, Desktop Analytics, Text Analytics
In the last several years many companies have shifted away from the mad pursuit of new customers toward focusing on retaining existing customers and winning more business from them. Against that background I expected to see a resurgence of customer relationship management processes and systems, but instead there is a growing focus on social media, customer experience management (CEM) and voice of the customer (VOC). I have already voiced my concerns on the level of focus on social business. My research into CEM shows that as yet few companies fully understand it or have the systems they need to support an enterprise-wide CEM initiative. The same seems to be true of VOC.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Workforce Management
ResponseTek Enhances Understanding of Customers
If they haven’t done so yet, businesses ought to become acquainted with two relatively new concepts: customer experience management (CEM) and voice of the customer (VOC). Ventana Research defines CEM as the practice of managing the customer experience at all touch points regardless of the communications channel being used. To manage that experience, three types of systems are directly helpful: smart desktop technology to help employees deliver great experiences to customers as they are occurring; smart self-service technologies that support easy-to-use, Web-based customer service; and customer feedback management to collect and analyze survey responses, free-form comments and social media posts. This focus is part of my research on trends and best practices in customer feedback management and is part of my latest research agenda. We define VOC as reports and analysis of all customer-related data (structured, unstructured and event-based), not just analysis of speech or feedback.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Callminer, ResponseTek, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics
Research Uncovers Keys to Using Predictive Analytics
As a technology, predictive analytics has existed for years, but adoption has not been widespread among businesses. In our recent benchmark research on business analytics among more than 2,600 organizations, predictive analytics ranked only 10th among technologies they use to generate analytics, and only one in eight of those companies use it. Predictive analytics has been costly to acquire, and while enterprises in a few vertical industries and specific lines of business have been willing to invest large sums in it, they constitute only a fraction of the organizations that could benefit from them. Ventana Research has just completed a benchmark research project to learn about how the organizations that have adopted predictive analytics are using it and to acquire real-world information about their levels of maturity, trends and best practices. In this post I want to share some of the key findings from our research.
Topics: Data Scientist, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, IT Performance, Business Analytics, Business Intelligence, Customer & Contact Center, Workforce Performance
I want to share my observations from the recent annual SAS analyst briefing. SAS is a huge software company with a unique culture and a history of success. Being privately held SAS is not required to make the same financial disclosures as publicly held organizations, it released enough information to suggest another successful year, with more than $2.7 billion in revenue and 10 percent growth in its core analytics and data management businesses. Smaller segments showed even higher growth rates. With only selective information disclosed, it’s hard to dissect the numbers to spot specific areas of weakness, but the top-line figures suggest SAS is in good health.
Topics: Big Data, Predictive Analytics, SAS, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Strata+Hadoop
Business Intelligence Revolution and Research Agenda for 2012
For most people involved with business intelligence (BI), these are exciting times. Using BI to improve business processes continues to motivate organizations to invest in BI. The focus on BI also empowers business analytics and can be rented in the cloud computing model of accessing software. New technologies are adding dimensions to BI and creating both excitement and confusion for enterprises implementing them. We offer a variety of accomplished research that can help organizations overcome the hype and understand how to use these technologies to improve business decision-making, and we’re planning new research in 2012 on these topics.
Topics: Mobile Business Intelligence, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Collaboration, Customer & Contact Center, Financial Performance, Information Management, Operational Intelligence, Workforce Performance
Expo Shows Maturity of Unified Communications
Like many other observers with a business perspective, I have been skeptical of unified communications, but a day I spent at the recent Unified Communications Expo 2012 went a long way to convincing me that unified communications has entered the mainstream. At this point I think organizations should consider it as a viable option to improve the efficiency of their communications systems, the ability to collaborate internally and with customers, and the effectiveness of their multimedia contact centers.
Topics: Microsoft, Predictive Analytics, Social Media, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Dell, NEC, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, IBM, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Workforce Management, Nokia, Vocalcom and Zeacom
Research Reveals Challenge of Building Customer Relationships
Businesses have long struggled to build ongoing, profitable relationships with their customers. Our new benchmark research into customer relationship maturity shows that this is not getting easier.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Workforce Management
Customer Engagement Day Highlights Issues for Companies
My namesake Jon Snow is chairman of the Directors Club (GB & NI), an association for professionals who focus on dealing with customers.Recently he organized the first of a series of customer engagement days designed to bring together senior representatives of U.K. companies to listen to a few presentations about hot issues in engaging with customers and more importantly to share experiences and concerns about key customer engagement issues in roundtable discussions, such as “the rise of the social enterprise,” “listening to the voice of the customer” and “mobile customers require a mobile strategy.” In addition to presenting a keynote on the state of social media in customer service, I chaired a discussion on “perfecting multichannel customer engagement in the contact center.”
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Workforce Management
Cicero provides what I call a smart desktop product. The software allows users to hide multiple applications behind an easy-to-use interface and build rules to complete tasks more efficiently and effectively, for example, specifying what field to complete next or the next question to ask a caller. It enhances customer experience management by enabling users to focus on the customers rather than on how to access the various systems, data and information needed to resolve interactions.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Experience, Voice of the Customer, Cicero, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics
Alteryx’s Business Analytics Empowers New Generation of Data Artisans
I attended the Alteryx user conference called Inspire 2012 (Twitter: #Inspire12) in Denver this week. This fairly new analytics software company has been gaining customers in a range of brand-name organizations such as Dick’s Sporting Goods, Supervalu, U.S. Cellular and VF Corp. The company focuses on meeting the needs of analysts across the business analytic spectrum including a geographic and location context for simplifying the analytic tasks and processes for the needs of business at the strategic and operational level.
Topics: Big Data, Mobile, Predictive Analytics, R, Sales Performance, Supply Chain Performance, alteryx, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Information Management, Data
The Customer and Contact Management Research Agenda for 2012
In all the years I have spent building contact centers and tracking this market, from both business and technology perspectives many things have not changed. Center managers are still under pressure to drive down costs, customers generally are not satisfied with the way their interactions are handled (perhaps less so), and organizations still aren’t making the most of customer interactions. However, as noted in my predictions for 2012, I am expecting more rapid change in the next couple of years than ever before with the advent of a collection of technologies that are already impacting business interactions with customer or by their actions.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Workforce Management
Zeacom Announces Full Support for Microsoft Lync
A few months ago, I evaluated Zeacom CommunicationsCenter (ZCC), which provides a multichannel contact center that is integrated closely with business process automation. This allows organizations to build a contact center tied to their interaction-handling processes and deliver any form of interaction to the person most qualified to handle it. At the time of my review, the product ran alongside products from the likes of Avaya, Cisco and NEC, and was resold and supported by the partner networks of these suppliers. There was also a beta test under way that supported integration with Microsoft Lync, which provides an alternative to using PBX products from these vendors.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Experience, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Zeacom
Enkata Expands Customer Analytics for a Better Customer Experience
The products of Enkata have generally been designed for what Ventana Research terms performance management for customer service and call centers, including applications connected to agent performance management (quality monitoring, coaching, training and related analytics) and operational performance analytics based on transactional, structured data. Recently Enkata has taken a new direction with its branding (“changing the customer experience”) and has been filling out its portfolio of products to include analytics for unstructured data, so it now includes speech (courtesy of a partnership with Callminer), desktop, cross-channel and text analytics; the last supports the analysis of customer surveys and social media posts.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Callminer, Enkata, Operational Performance, Analytics, Cloud Computing, Customer & Contact Center, Customer Service, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, Desktop Analytics, Text Analytics, Workforce Management, OpenSpan
Actuate Establishes Performance Analytics for Business Excellence
Business analytics and big data are common topics of conversation in the business and information technology markets, but these technologies are only building blocks to help businesses manage performance. Entering the conversation is Actuate, which for years has had a performance management division that provides software for managing progress toward objectives through a variety of analytic and action-focused techniques. The company has announced release of a promising new generation of its enterprise software, Actuate BIRT Performance Analytics.
Topics: Big Data, Mobile, Predictive Analytics, Sales Performance, Supply Chain Performance, Performance Analytics, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Information Management, Workforce Performance
Revolution Analytics Hosts Contest on Business Predicting the Future
Revolution Analytics recently announced the winners of its “Applications of R in Business” contest. Revolution Analytics has built a business around supporting R, an open source statistical software package, and extending it with features it licenses to customers. I served as a judge in the contest. Since I was in the midst of analyzing the data for our predictive analytics benchmark research, I was interested to see how the contestants applied predictive analytics techniques to specific business problems.
Topics: Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, Workforce Performance
When it comes to technology, debates about whether a particular name suits its category are rampant. Here is a link to one such argument about the term “big data” from Curt Monash, an analyst whom I respect a great deal. This debate rages in the Twittersphere also, as in this comment from Neil Raden, another analyst I respect, suggesting that “big data is a marketing term … imprecise by design.” Another term I’ve encountered resistance to recently is “predictive analytics.” See: (“Revolution Analytics Hosts Contest on Business Predicting the Future“).
Topics: Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Financial Performance, Workforce Performance
The Big, Cloudy, Mobile and Social World of MicroStrategy
MicroStrategy, one of the largest independent vendors of business intelligence (BI) software, recently held its annual user conference, which I attended with some of my colleagues and more than 2,000 other attendees. At this year’s event, the company emphasized four key themes: mobility, cloud computing, big data and social media. In this post, I’ll assess what MicroStrategy is doing in each of the first three areas. My colleague, Mark Smith, covered MicroStrategy’s social intelligence efforts in his blog. I’ll also share some opinions on what might be missing from the company’s vision.
Topics: Big Data, MicroStrategy, Mobile, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Operational Performance, Business Analytics, Business Intelligence, Cloud Computing, Customer & Contact Center, Workforce Performance, Strata+Hadoop
Confirmit Provides Customer Insights through Surveys
Ventana Research believes that to provide excellent customer experiences it is necessary to understand what customers want and their likely behaviors, and one direct way to achieve this is by collecting and analyzing customer feedback. The challenge for organizations in this regard is that most customers are reluctant to complete surveys unless they are provided at an appropriate time, in an easy-to-use format and through the channel of their choice. Confirmit’s Horizons products support collection and analysis of feedback from marketing campaigns, employees and customers. The core survey engine enables design and authoring of surveys, and add-on modules handle collecting data, panel management (of a panel of customers, employees or market segments to help focus business activities) and analysis and reporting. It was built on the Microsoft .Net platform, but the most recent release, version 16, extends support to other environments and browsers. This release also enhances security, scalability and availability so Confirmit can collect hundreds of millions of surveys for customers around the world. The product is available for deployment on-premises or as software as a service (SaaS).
Topics: Predictive Analytics, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Analytics, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Workforce Management, Confirmit
Feedback Management Can Improve the Customer Experience
There is a lot of talk today in customer service circles about the “voice of the customer” (VOC). For some people it means speech analytics (literally the voice of the customer), some others use it as an equivalent to the “360-degree view” of the customer, and for others it is about customer feedback. At Ventana Research we take a broader view and define VOC as reports and analysis that include as much customer information as possible. It should draw data from all available customer sources and use various forms of analytics to extract, report and analyze it as fully as possible. I am also an avid supporter of customer experience management (CEM) and urge companies to focus on the experiences customers receive at every touch point. This is where I see VOC and customer feedback come together.
Topics: Predictive Analytics, Customer Analytics, Customer Experience, Customer Feedback Management, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Workforce Management
Clarabridge Advances Customer Experience Management
Clarabridge is an established vendor of text analytics products, which it sells both directly to the market and indirectly through an extensive set of partnerships with companies such as MicroStrategy, IBM Cognos and Verint. Recently it has been marketing its applications under the category of customer experience management (CEM). To me, CEM is about personalizing and influencing the customer experience while an interaction is in progress. Organizations cannot do this without the right information about the customer, and text analytics is one of the primary tools that allows organizations to derive that information; in this way Clarabridge fits in CEM.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Clarabridge, Operational Performance, Analytics, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Workforce Management
My colleague Mark Smith and I recently chatted with executives of Tidemark, a company in the early stages of providing business analytics for decision-makers. It has a roster of experienced executive talent and solid financial backing. There’s a strategic link with Workday that reflects a common background at the operational and investor levels. As it gets rolling, Tidemark is targeting large and very companies as customers for its cloud-based system for analyzing data. It can automate alerts and enhance operating visibility, collaboratively assess the potential impacts of decisions and support the process of implementing those decisions.
Topics: Big Data, Data Warehousing, Master Data Management, Performance Management, Planning, Predictive Analytics, Sales Performance, GRC, Budgeting, Risk Analytics, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Cloud Computing, Customer & Contact Center, Data Governance, Data Integration, Financial Performance, In-Memory Computing, Information Management, Mobility, Workforce Performance, Risk, Workday, Financial Performance Management, Integrated Business Planning, Strata+Hadoop
Customer and Contact Center Management in 2012
After reviewing the benchmark research I carried out during 2011 into customer and contact center analytics, the use of technology in contact centers and the adoption of cloud-based contact centers and systems, I have come up with a list of critical investments that I predict will distinguish customer and contact center management in 2012.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Workforce Performance, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Workforce Management
What Enterprises Can Learn from Major Events and Surprises in 2011
Rather than make predictions for 2012, which are everywhere right now, I want to look back at some of the surprising events of 2011. I think it’s worth considering what happened that wasn’t expected and what these things might tell us about the information technology market. Here, in no particular order, are the most important ones I see.
Topics: Big Data, Mobile, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Operational Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Financial Performance, Workforce Performance
Cloud-Based Contact Center Research Finds Deployment Growth
Cloud-based systems have arrived as an option for how organizations source their IT systems, now and in the future. Proponents of the cloud – of which I am one – will tell you they have several major advantages over conventional on-premises systems. They require little upfront capital expenditure; the major costs come as a monthly “rental” charge for using the service rather than an annual license; they are less demanding on in-house resources; they are quicker, easier and less risky to implement; there is no annual maintenance fee as updates are built into the service charge; and organizations have disaster recovery taken care of by the vendor. With this background I recently carried out benchmark research to discover organizations’ current and likely adoption of cloud-based systems to support their contact center operations.
Topics: Predictive Analytics, Social Media, Customer Analytics, Customer Data Management, Customer Experience, Customer Feedback Management, Social CRM, Speech Analytics, Voice of the Customer, Operational Performance, Analytics, Business Mobility, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Desktop Analytics, Text Analytics, Unified Communications, Workforce Management
SAP Must Translate Technology Advances into Business Use
At its annual Influencer’s Summit in Boston, SAP offered multiple perspectives on where the company’s strategy and products are heading. Overall, I was struck by the essential similarities to its message on its strategic direction a decade ago. The overarching objective in its roadmap now, as then, is to have information technology increasingly adapt to the needs of individual users and how they choose to execute established/repetitive or ad-hoc processes, rather than forcing them to adapt to the limitations of the technologies they are using. Back then the idea was to create a comprehensive process framework – a closely coupled approach. Today, it’s essentially the opposite, as SAP products run on an architecture that enables flexibility – a loosely coupled approach – both in how the computing infrastructure is organized and how people execute their tasks. It seems to me that this reflects the impact of having choices between cloud-based software as a service (SaaS) and on-premises systems and the need to enable access through a variety of devices (from desktops to mobile handhelds and tablets). Mobility is