Competition for customers is more intense today than ever before, and companies struggle to differentiate themselves from the competition. Our research repeatedly finds that customer experience is a key differentiator. Our research into next-generation customer engagement said the impetus for improving engagement is to improve the customer experience in almost three quarters (74%) of participants. One increasingly popular way to do this is to use customer journey maps, which show how companies plan to engage with customers: at what times, through which channels, at which touch points and with which business units or using which self-service technologies. Our benchmark research into customer relationship maturity shows that two-thirds (67%) of very customer-focused companies use customer journey maps. The top four uses are to develop more customer-focused employee training (by 78%), personalize customer experiences (76%), enhance customer experience processes (73%) and drill down on customer experience processes to the customer segment level (73%). Typically producing these maps has been a manual process, perhaps using process mapping tools; in these cases few companies were able to capture and visualize actual journeys. However, as more business units engage with customers and companies deploy multiple channels of engagement – including self-service – improving the customer experience and mapping the customer journey become more complex, and to keep up companies have to invest in processes and tools that help them automate the process of producing maps and capture data about and visualize actual customer journeys.
Topics: Big Data, Customer Analytics, Customer Experience Management, Customer Feedback Management, Speech Analytics, Customer Performance, Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, CRM, Text Analytics, ominchannel, voice of the customer (VoC), workforce optimization
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, Hadoop, pivotal, rstat
In our benchmark research at least half of participants that use spreadsheets to support a business process routinely say that these tools make it difficult for them to do their job. Yet spreadsheets continue to dominate in a range of business functions and processes. For example, our recent next-generation business planning research finds that this is the most common software used for performing 11 of the most common types of planning. At the heart of the problem is a disconnect between what spreadsheets were originally designed to do and how they are actually used today in corporations. Desktop spreadsheets were intended to be a personal productivity tool used, for example, for prototyping models, creating ad hoc reports and performing one-off analyses using simple models and storing small amounts of data. They were not built for collaborative, repetitive enterprise-wide tasks, and this is the root cause of most of the issues that organizations encounter when they use them in such business processes.
Topics: Planning, Sales Performance, ERP, Forecast, GRC, Reporting, closing, dashboard, enterprise spreadsheet, Excel, plan, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Financial Performance, Information Management, Accounting, Data, Risk, application, benchmark, Financial Performance Management, spreadsheet
Verint entered the enterprise market for customer feedback management when it acquired Vovici in August 2011. Since then the Vovici products have been integrated into Verint’s Customer Engagement Optimization suite, which includes products originally developed by Verint and Kana, which it also acquired. The current suite supports a range of capabilities that Verint groups into three categories: customer analytics (various types of analytics and Enterprise Feedback Management), customer engagement (which is largely the Kana products that support the agent desktop, email, chat and co-browsing, knowledge and case management, and Web-based self-service) and workforce optimization (quality monitoring, workforce management, desktop and process analytics, performance management and e-learning and coaching). Having this broad array of capabilities allows Verint to support a closed-loop approach to customer feedback and connect it to the processes with which to identify issues raised through feedback and take action to improve (through process change, training and coaching, for example).
Topics: Big Data, Customer Analytics, Customer Experience, Customer Feedback Management, Speech Analytics, Customer Performance, Analytics, Business Analytics, Cloud Computing, Customer Service, Call Center, Contact Center, Contact Center Analytics, Text Analytics, voice of the customer (VoC)
All lines of business are under pressure to meet targets and deliver expected results, but none is under more pressure than Sales. Like other organizations it must use information to derive insights about progress and problems and to decide what changes to make. Today businesses collect and analyze data from more data sources in more forms than ever before. To understand it they need effective analytics, and again none need it more than Sales.
Topics: Big Data, Sales, Sales Performance, sales analytics, Operational Performance, Business Analytics, Business Collaboration, Business Intelligence, Cloud Computing, Financial Performance, Information Applications, Sales Performance Management, SFA
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, forecasting, Marketing, Reporting, Budgeting, Controller, sales forecast, strategic, workforce, Customer Performance, Operational Performance, Business Analytics, Business Performance, Cloud Computing, Financial Performance, In-memory, Workforce Performance, CFO, Supply Chain, capital spending, demand, Financial Performance Management, financial reporting, FPM, Integrated Business Planning, S&OP, spreadsheet
Maximizing the performance and value of people in the workforce should be a primary focus for any business these days. It is a complex task, especially for larger organizations, and chances for success can be increased by investment in human capital management (HCM) applications. In this competitive software market SAP is making a strong push, aided by acquisitions in the last three years of SuccessFactors for talent management and more recently Fieldglass for contingent labor management. Recently I attended the SAP HCM analyst summit to hear about its direction and plans to grow its market share. The company has made progress since our last analyst perspective on it. Mike Ettling, SAP’s president for the HR line of business, discussed its newly refined strategy and organizational structure; the company has added executives from around the globe to emphasize its commitment to helping human resources organizations.
Topics: SAP, HCM, human resources, Learning, Performance, Recruiting, SuccessFactors, Operational Performance, Analytics, Business Analytics, Business Performance, Cloud Computing, Financial Performance, Compensation, HRMS, Vendor Management Systems, Workforce Analytics, Workforce Management, Workforce Planning
Data is an essential ingredient for every aspect of business, and those that use it well are likely to gain advantages over competitors that do not. Our benchmark research on information optimization reveals a variety of drivers for deploying information, most commonly analytics, information access, decision-making, process improvements and customer experience and satisfaction. To accomplish any of these purposes requires that data be prepared through a sequence of steps: accessing, searching, aggregating, enriching, transforming and cleaning data from different sources to create a single uniform data set. To prepare data properly, businesses need flexible tools that enable them to enrich the context of data drawn from multiple sources, collaborate on its preparation to serve business needs and govern the process of preparation to ensure security and consistency. Users of these tools range from analysts to operations professionals in the lines of business.
Topics: Big Data, Sales Performance, Supply Chain Performance, Customer Performance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Cloud Computing, Data Preparation, Financial Performance, Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance, Information Optimization
The idea of not focusing on innovation is heretical in today’s business culture and media. Yet a recent article in The New Yorker suggests that today’s society and organizations focus too much on innovation and technology. The same may be true for technology in business organizations. Our research provides evidence for my claim.
Recurring revenue is a term applied to business models that involve three types of selling and billing structures: a one-time transaction plus a periodic service charge; subscription-based services involving periodic charges; or a contractual relationship that charges periodically for goods and services. Telecommunications was the first major industry to use it, but recently the model has gained popularity in others. It is a major trend in information technology as an increasing number of companies offer software and hardware technology accessed as a service through cloud computing. Recurring revenue also has been transforming the entertainment business, as customers subscribe to rent movies, music and other creative digital products instead of owning them; this is part of the so-called “sharing economy” whose social impacts are wide-ranging.
Topics: SaaS, NetSuite, Recurring Revenue, Zuora, Billing, streaming, Customer Performance, Business Performance, Cloud Computing, Customer Service, Financial Performance, Accounting, Aria Systems, billing software, Intacct, invoicing
At its annual MicroStrategy World conference, this provider of analytics and business intelligence systems for business and IT introduced a new version of its flagship product, MicroStrategy 9s. Among many advances it adds enterprise grade security with MicroStrategy Usher as part of the maintenance update to its 9.4.1 release. Security is increasingly critical for analytics and BI. Technologies that work intensively with data, including reporting, business intelligence, analytics and data preparation, have access to a range of applications and databases and could leave gaps in access controls and security of essential business data. Already in 2015 the data breach at Anthem put more than 80 million medical records at risk. Our benchmark research in big data analytics finds that integration into security and user access frameworks is a very important capability to 37 percent of organizations.
Topics: Big Data, Mobile, Sales Performance, Governance, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Mobility, Business Performance, Cloud Computing, Customer & Contact Center, Information Applications, Information Management, Risk & Compliance (GRC), Security
Most people in business management admit that sales is more an art than a science. Organizations have long struggled to find the right mix to improve its effectiveness, and few get the most out of available technology. For many the default is still to use sales force automation (SFA) and spreadsheets to manage processes and try to increase the productivity of sales staff. In our view they should take a holistic approach to sales processes from contact to close and support everything from sales forecasting to pipeline management to compensation with applications designed for these purposes. Those in sales operations need to apply analytics to understand and fine-tune sales activities. Those in sales management need applications that can help recruit, engage and retain the best talent. Even more than elsewhere in business, in sales people matter, and the organizations that most empower their teams are likely to get the best results. Optimizing people and processes requires a balance of information and technology to support the various needs of the sales organization.
One of the issues in handling the tax function in business, especially where it involves direct (income) taxes, is the technical expertise required. At the more senior levels, practitioners must be knowledgeable about accounting and tax law. In multinational corporations, understanding differences between accounting and legal structures in various localities and their effects on tax liabilities requires more knowledge. Yet when I began to study the structures of corporate tax departments, I was struck by the scarcity of senior-level titles in them. This may reflect the low profile of the department in most companies and the tactical nature of the work it has performed. Advances in information technology have the potential to automate most of the manual tasks tax professionals perform. This increase in efficiency will enable tax departments to fill a more strategic, important role in the companies they serve.
Topics: Big Data, ERP, Governance, GRC, audit, finance transformation, legal, LongView, Tax, tax compliance, tax department, tax optimization, tax planning, Analytics, Business Analytics, Business Performance, Financial Performance, Information Management, Oracle, CFO, Risk & Compliance (GRC), Vertex, FPM, Innovation Awards, international tax, Thomson-Reuters multinational
Oracle is one of the world's largest business intelligence and analytics software companies. Its products range from middleware, back-end databases and ETL tools to business intelligence applications and cloud platforms, and it is well established in many corporate and government accounts. A key to Oracle's ongoing success is in transitioning its business intelligence and analytics portfolio to self-service, big data and cloud deployments. To that end, three areas in which the company has innovated are fast, scalable access for transaction data; exploratory data access for less structured data; and cloud-based business intelligence.
I recently attended a Cisco Collaboration analyst day in the U.K. and was impressed by what I heard and saw. Cisco of course is known as a supplier of network equipment and software, and it has long provided these through a global network of partners. But Cisco also has been in the contact center market for several years and has had success with its small and enterprise contact center systems, having more than 20,000 on-premises customers and revenue in excess of US $1.5 billion. Cisco markets the contact center systems as Customer Collaboration , but the portfolio is still based on its two longstanding contact center products: Unified Contact Center Enterprise and Unified Contact Center Express , designed for larger and smaller centers, respectively. Two other options are CiscoPackaged Contact Center Enterprise and Cisco Hosted Collaboration Solution for Contact Center (HCS-CC) . These both use the Enterprise products, but the first comes packaged and so has less options, and the second is based on cloud computing; both are easier to deploy and more affordable for a wider market than the other options.
Topics: Big Data, Customer Analytics, Customer Experience Management, Speech Analytics, Analytics, Business Collaboration, Cloud Computing, Customer & Contact Center, Customer Service, Call Center, Contact Center, Contact Center Analytics, Text Analytics, workforce optimization
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, Hadoop, Hortonworks, IBM, Informatica, Information Management, Operational Intelligence, Oracle, Datawatch, Dell Boomi, Information Optimization, Savi, Sumo Logic, Tamr, Trifacta
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, Reporting, Sales Forecasting, Budgeting, plan, strategic, 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
Managing investments in people and their performance is critical to every organization. It also is complicated. To support the various aspects of human capital management (HCM), organizations often use a variety of technology including systems for human resource management, talent management, workforce management and payroll management. Often these separate systems use their own information and are not well connected to each other. Today they are deployed both on-premises and in cloud computing environments, which further complicates integration. This situation disrupts processes and challenges HR departments and leaders to invest time and resources to correct it.
Topics: Supply Chain Performance, HCM, Human Capital, Human Capital Management, Operational Performance, Business Performance, Customer & Contact Center, Financial Performance, HRMS, Talent Management, Workforce Management
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, forecasting, Governance, GRC, Budgeting, close, end-to-end, quote-to-cash, Tax, Tax-Datawarehouse, Analytics, Business Performance, CIO, Financial Performance, In-memory, Accounting, Agent Performance Management, CFO, CPQ, Risk, risk management, CEO, Financial Performance Management, FPM
As organizations look to improve the competency and skills of their workers, learning management system (LMS) technology can help improve their efforts. Our latest benchmark research in next-generation learning management systems finds a range of progress in this regard. Our Performance Index analysis places organizations almost evenly between the two lowest (51%) and the two highest (49%) of four levels of performance. The results differ by size of company as measured by number of employees. For example, only 8 percent of small companies reach the highest Innovative level of performance, compared to 26 percent of very large companies, the largest percentage of any size. Analyzed by industry, the Finance, Insurance and Real Estate sector performs best: Two out of three (65%) are at the top two levels. We attribute this in part to the finance industry’s focus on processes and its need to comply with regulations and teach employees how to do so.
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, Reporting, Self-service, Budgeting, close, closing, computing, Controller, dashboard, planning and budgeting, report, Tax, Analytics, Business Intelligence, Business Performance, Cloud, Collaboration, Financial Performance, Accounting, CFO, Data, finance, BI, Financial Performance Management, FPM, Microsoft Excel, scorecard, Spreadsheets, treasury
This year presents much opportunity for organizations to use a new generation of technology to compete better, be more efficient in their business operations and engage their workforces to their full potential. We have identified and begun to track the following next-generation technologies: analytics, big data, collaboration, cloud computing, mobile technology and social media, and in 2014 we added wearable computing to the list. In 2015 we will intensify our focus on all of them specifically in our research agenda and as part of our line of business research agendas.
Topics: Big Data, Sales Performance, Social Media, Supply Chain Performance, Governance, Mobile Technology, Wearable Computing, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Collaboration, Customer & Contact Center, Financial Performance, Information Applications, Information Management, Location Intelligence, Operational Intelligence, Workforce Performance, Risk & Compliance (GRC), Technology Innovation