Like many other industry observers I’ve heard overblown claims for information technology for decades. However, I’ve also observed that – eventually – reality catches up with vision. Finance and accounting departments are particularly resistant to change, yet because almost no corporations use adding machines or typewriters any more, it’s clear that transformative change can happen. Nonetheless, because users of business computing systems are inundated with “it’s better than ever” promotions by vendors, journalists and industry analysts, may have grown jaded and disbelieving. In the case of ERP systems that help run many organizations, that is too bad because we are finally at the point of a fundamental change in this business-critical software category.
Topics: Social Media, Mobile Technology, Operational Performance Management (OPM), Human Capital, Business Analytics, Business Collaboration, Cloud Computing, Business Intelligence (BI), Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Supply Chain Performance Management (SCPM), Accounting, Analytics, big data, Budgeting, CEO, C
Ventana Research coined the term “enterprise spreadsheet” in 2004 to describe a variety of software applications that add a desktop spreadsheet’s user interface (usually that of Microsoft Excel) to components that address the issues that arise when desktop spreadsheets are used in repetitive, collaborative enterprise processes. Enterprise spreadsheets are designed to provide the best of both worlds in that they offer the ease of use and flexibility of desktop spreadsheets while overcoming their defects – chiefly inability to maintain data integrity, lack of referential integrity and dimensionality, absence of workflow and process controls, limited security and access controls as well as poor auditability. All of these issues can cause serious problems for business use, which I’ll discuss below.
Topics: Operational Performance Management (OPM), Business Analytics, Uncategorized, Business Intelligence (BI), Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Information Management (IM), Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), Analytics, benchmark, enterprise spreadsheet, Fina
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, Social Media, forecasting, FP&A, Office of Finance, Operational Performance Management (OPM), Budgeting, Connotate, cryptic, equity research, Finance Analytics, Human Capital, Kofax, Statistics, Analytics, Business Analytics, Hadoop, Business Intelligence (BI), Customer Performance Management (CPM), Data, Datawatch, Financial Performance Management (FPM), Kapow, Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), import.io
Tagetik is a long-established vendor of financial performance management (FPM) software. Its full-featured suite includes planning, budgeting, consolidation, close management, disclosure management, analysis, dashboards and reporting. The software can be deployed on premises or in the cloud as multitenant software as a service or in a private cloud. Tagetik also offers pre-built integration with SAP and SAP HANA, Microsoft SharePoint and Qlik to best support a range of financial management needs.
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. 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). To date most dedicated applications have been far more difficult than spreadsheets for the average business user to use in the design and test phases. To convince people to switch to their dedicated application, a vendor must offer an alternative that lets users model, create reports, collect data and create dedicated data stores as easily as they can do it in a desktop spreadsheet. Spreadsheets are seductive for most business users because, even with a minimum amount of training and experience, it’s possible to create a useful model, do analysis and create reports. Individuals can immediately translate what they know about their business or how to present their ideas into a form and format that makes sense to them. They can update and modify it whenever they wish, and the change will occur instantly. For these business users ease of use and control trump putting up with the issues that routinely occur when spreadsheets are used in collaborative enterprise processes. Moreover, it’s hard to persuade “spreadsheet jockeys” who have strong command of spreadsheet features and functions that they should start over and learn how to use a new application. Those who have spent their careers working with spreadsheets often find it difficult to work with formal applications because those applications work in ways that aren’t intuitive. Personally these diehards may resist because not having control over analyses and data would diminish their standing in the organization. Nevertheless, there are compelling reasons for vendors to keep trying to devise dedicated software that an average business user would find as easy and intuitive as a desktop spreadsheet in the design, test and update phases. Such an application would eliminate the single most important obstacle that keeps organizations from switching. The disadvantages of using spreadsheets are clear and measurable. One of the most significant is that spreadsheets can waste large amounts of time when used inappropriately. After more than a few people become involved and a file is used and reused, issues begin to mount such as errors in data or formulas, broken links and inconsistencies. Changes to even moderately complex models are time-consuming. Soon, much of the time spent with the file is devoted to finding the sources of errors and discrepancies and fixing the mistakes. Our research confirms this. When it comes to important spreadsheets that people use over and over again to collaborate with colleagues, on average people spend about 12 hours per month consolidating, modifying and correcting the spreadsheets. That’s about a day and a half per month – or five to 10 percent of their time – just maintaining these spreadsheets. Business applications vendors started to address business users’ reluctance to use their software more than a decade ago when they began to use Microsoft Excel as the user interface (UI). This provides a familiar environment for those who mainly need to enter data or want to do some “sandbox” modeling and analysis. Since the software behind the UI is a program that uses some sort of database, companies avoid the issues that almost arise when spreadsheets are used in enterprise applications. There also are products that address some of the inherent issues with such as the difficulty of consolidating data from multiple individual spreadsheets as well as keeping data consistent. Visualization software, a relatively new category, greatly simplifies the process of collecting data from one or more enterprise data sources and creating reports and dashboards. As the enterprise software applications business evolves to meet the needs of a new generation of users, as I mentioned recently, it’s imperative that vendors find a way to provide users with software that is a real alternative to desktop spreadsheets. By this I mean enterprise software that provides business users with the same ability to model, create reports and work with data the way they do in a desktop spreadsheet as well as update and modify these by themselves without any IT resources. At the same time, this software has to eliminate all of the problems that are inevitable when spreadsheets are used. Only at that point will a dedicated application become a real alternative to using a spreadsheet for a key business process. Regards, Robert Kugel – SVP Research
Topics: Planning, ERP, Forecast, GRC, Operational Performance Management (OPM), Reporting, closing, dashboard, enterprise spreadsheet, Excel, plan, Analytics, Business Analytics, Business Collaboration, Accounting, Business Intelligence (BI), Business Performance Management (BPM), Customer Performance Management (CPM), Data, Financial Performance Management (FPM), Risk, Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), application, benchmark, Financial Performance Management, spreadsheet
One of the charitable causes to which I devote time puts on an annual vintage car show. The Concours d’Élegance dates back to 17th century France, when wealthy aristocrats gathered with judges on a field to determine who had the best carriages and the most beautiful horsepower. Our event serves as the centerpiece of a broader mission to raise money for several charitable organizations. One of my roles is to keep track of the cars entered in the show, and in that capacity I designed an online registration system. I’ve been struck by how my experiences with a simple IT system have been a microcosm of the issues that people encounter in designing, administering and using far more sophisticated ones. My most important take-away from this year’s event is the importance of self-service reporting. I suspect that most senior corporate executives – especially those in Finance – fail to appreciate the value of self-service reporting. It frees up the considerable resources organizations collectively waste on unproductive work, and it increases responsiveness and agility of the company as a whole.
Topics: Planning, Operational Performance Management (OPM), Reporting, Self-service, BizNet Software, Budgeting, dashboard, report, Analytics, Business Analytics, Business Intelligence, Business Intelligence (BI), Business Performance Management (BPM), Customer Performance Management (CPM), Data, Financial Performance Management (FPM), Information Applications (IA), Sales Performance Management (SPM), Supply Chain Performance Management (SCPM), Workforce Performance Management (WPM), BI, Financial Performance Management, Microsoft Excel, scorecard, Spreadsheets
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, forecasting, Governance, Operational Performance Management (OPM), Budgeting, close, Finance Analytics, Tax, tax data warehouse, Analytics, Business Analytics, CIO, Governance, Risk & Compliance (GRC), In-memory, Accounting, Business Intelligence (BI), Business Performance Management (BPM), CFO, Financial Performance Management (FPM), Information Applications (IA), Risk, risk management, Workforce Performance Management (WPM), CEO, Financial Performance Management, FPM
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, forecasting, Governance, Budgeting, close, Finance Analytics, Tax, tax data warehouse, Analytics, Business Analytics, CIO, Governance, Risk & Compliance (GRC), In-memory, Accounting, Business Intelligence (BI), Business Performance Management (BPM), CFO, Financial Performance Management (FPM), Information Management (IM), Risk, risk management, CEO, Financial Performance Management, FPM
Technology for the Office of Finance can have transformative power. Although progress has been slow at times, today’s finance organizations are fundamentally different from those of 50 years ago. For one thing, they require far fewer resources (chiefly people) to perform basic accounting, treasury and corporate finance tasks. In addition, public corporations report results sooner – sometimes weeks sooner – than they could in the mid-20th century. And finance departments are able to harness substantially more data and a wider array of analytics to promote insight and support more agile decision-making.
Topics: ERP, GRC, audit, finance transformation, legal, multinational, Tax, tax compliance, tax department, tax optimization, tax planning, Analytics, Business Analytics, Business Intelligence (BI), Business Performance Management (BPM), CFO, Financial Performance Management (FPM), Vertex, FPM, Innovation Awards, international tax
IBM hosted the Big Data and Analytics Analyst Insights conference in Toronto recently to emphasize the strategic importance of this topic to the company and to highlight recent and forthcoming advancements in its big data and analytics software. Our firm followed the presentations with interest. My colleagues Mark Smith and Tony Cosentino have commented on IBM’s execution of its big data strategy and its approach to analytics. As well, Ventana Research has conducted benchmark research on challenges in big data.
Topics: Big Data, Operational Performance Management (OPM), Bank, MRO, telematics, Analytics, Business Analytics, IBM, Operational Intelligence, Business Intelligence (BI), Business Performance Management (BPM), Customer Performance Management (CPM), Financial Performance Management (FPM), Sales Performance Management (SPM), FPM, Maximo, profitability management, TM1, Watson