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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.

vr_NG_Finance_Analytics_04_accurate_data_is_key_for_finance_analyticsA main requirement for the data used in analytics is that it be accurate because accuracy affects how well finance analytic processes work. One piece of seemingly good news from the research is that a majority of companies have accurate data with which to work in their finance analytics processes. However, only 11 percent said theirs is very accurate, and there’s a big difference between accurate enough and very accurate. The degree of accuracy is important because it correlates with, among other things, the quality of finance analytics processes and the agility with which organizations can respond to and plan for change.

Although almost all (92%) of the companies that have very accurate data also have a process that works well or very well, that assessment drops to 43 percent of companies that said their data is just accurate. Even in small doses, bad data has an outsized impact on finance analytic processes. Inaccuracies, inconsistencies and not comparable data can seriously gum up the works as analysts search for the source of the issue and then try to resolve it. As issues grow, dissatisfaction with the process increases. Just 22 percent of those with somewhat accurate data and none of the companies with data that is not accurate said their company has a process that works well or very well.

To be truly useful for business, analytics provided to executives, managers and other decision-makers must be fresh. The faster a company can deliver the assessments and insight as to what just happened, the sooner company can respond to those changes. Almost all (85%) companies with very accurate data said they are able to respond immediately or soon enough to changes in business or market conditions, but only 35 percent of those with accurate data and just 24 percent of those with somewhat accurate data are able to do so.

Moreover, having data that is timely enables companies to react in a coordinated fashion as well as quickly. Companies that are able to operate in a coordinated fashion are usually more successful in business than those that are somewhat coordinated in the same way that a juggler who is somewhat coordinated drops a lot of balls. Almost all (86%) companies whose data is all up-to-date said they are able to react to change in a coordinated or very well coordinated fashion, compared to just 38 percent of those whose data is mostly up-to-date and 19 percent that have a significant percentage of stale data. Three-fourths (77%) of companies that have very accurate data are able to respond to changes in a coordinated or very well coordinated fashion, but just one-third (35%) of those with accurate data and 14 percent with somewhat accurate data are able to accomplish this.

Speed is essential in delivering metrics and performance indicators if they are to be useful for strategic decision-making, competitive positioning and assessing performance. Companies that can respond sooner to opportunities and threats are more able to adjust to changing business conditions. The research finds that fewer than half (43%) of companies are able to deliver important metrics and performance indicators within a week of a period’s end – that is, soon enough to respond to an emerging opportunity or threat.

One way to speed up the delivery of analytics is to have analysts vr_NG_Finance_Analytics_09_too_much_time_to_prepare_datafocus their time on the analytics. But the research shows that not many do: A majority of analysts spend the biggest chunk of their time dealing with data-related issues rather than on the analysis itself. Two-thirds (68%) of participants reported that they spend the most time dealing with the data used in their analytics – waiting for it, reviewing it for quality and consistency or preparing it for analysis. Only one-fourth (28%) said their efforts focus most on analysis and trying to determine root causes, which are the main reasons for doing the analysis in the first place. In other words, in a majority of companies, analysts don’t spend enough time doing what they are valued and paid for.

The results also show that there are negative knock-on effects of spending time on data-related tasks rather than on analysis. More than half (56%) of the companies that spend the biggest part of their time working on analytics can deliver metrics and indicators within a business week, compared to just one-third (36%) of those that spend the biggest part of the time grappling with data issues. Having high-quality, timely and accessible data therefore is essential to reaping the benefits of finance analytics.

dataData 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 a force of nature like a tornado or an earthquake that’s beyond their control to fix. Our benchmark research on information management suggests that inertia in tackling data issues is more organizational than technical. Companies simply do not devote sufficient resources (staff and budget) to address this ongoing issue. One reason may be because the people who must confront the data issues in their day-to-day work fail to understand the connection between these and getting the results from analytics that they should.

Excellent data quality is the result of building quality controls into data management processes. Our research finds a strong correlation between the degree of data quality efforts in finance analytics and the quality of the finance department’s analytic processes and output, and ultimately its timeliness and its value to the company. Corporations generally – and finance organizations in particular – must pay closer attention to the reliability of the data they use in their analytics. The investment in having better data will pay off in better analytics.

Regards,

Robert Kugel – SVP Research

Our benchmark research on enterprise spreadsheets explores the pitfalls that await companies that use desktop spreadsheets such as Microsoft Excel in repetitive, collaborative enterprise-wide processes. Because people are so familiar with Excel and therefore are able to quickly transform their finance or business expertise into a workable spreadsheet for modeling, analysis and reporting, desktop spreadsheets became the default choice. Individuals and organizations resist giving up their spreadsheets, so software vendors have come up with adaptations that embrace and extend their use. I’ve long advocated finding user-friendly spreadsheet alternatives.

One of the first adaptations was for application vendors to use a vr_ss21_spreadsheets_arent_easily_replacedspreadsheet (either a grid format or Excel itself) as a user interface. In these products users seem to be working in a familiar spreadsheet environment, but the interface is tied to an application that has controlled business logic, formulas and workflows, and the data is held in a relational or multidimensional database. This approach can give organizations the best of both worlds: the familiarity of a spreadsheet but in a structure that addresses most of the technological flaws inherent in desktop spreadsheets. Yet this approach isn’t always enough. It is fine for business processes in which a third-party application is the appropriate choice, but in many other situations where people collaborate using the same model, analytical methods and data, a spreadsheet – not an application – is the better choice. Moreover, our research finds multiple reasons why companies continue to rely on spreadsheets. More than half (56%) of participants pointed to user resistance to change, and many others cited a business case that wasn’t strong enough (that is, the benefits of switching did not merit the costs) and a related issue: that alternatives are too expensive.

In collaborative processes where a spreadsheet is the most practical tool, another alternative is a technology developed by Boardwalktech. The company’s Collaboration Platform (BCP) products support a secure, two-way exchange of data between multiple users.

Instead of having to collect multiple spreadsheets through the email system and then combine them, BCP users can automatically share information at the individual cell level when they want. For instance, working offline in a spreadsheet model individuals can enter actual results and evaluate changes to a forecast or plan, playing with whatever what-if scenarios they see fit. When finished, they can connect to the Boardwalktech server and click to share the updated information with others in the organization. Those people will have immediate access to the changed data.

This approach offers advantages to the way most organizations collaborate with spreadsheets. For example, the exchange of data between spreadsheet users is immediate and takes place at the cell level rather than replacing the entire spreadsheet. Thus, unlike when spreadsheets are exchanged through email, updates can be automatic and far more secure. When spreadsheets are connected through a server, contention (that is, two people trying to change the same data at roughly the same time) is an issue. Most server-based spreadsheets (such as applications built on an Excel server) deal with contention by controlling changes at the file or record-object level, employing a check-in and check-out methodology or record locking to control concurrency. This means that an entire spreadsheet or large portions of it cannot be altered until one person has finished making changes. This process can cause substantial delays. In contrast, BCP enables concurrent, multiuser collaboration at the cell level. Especially in larger spreadsheets shared among multiple users, that can cut down on delays in updates and changes because multiple people can be making updates to different parts of the spreadsheet at the same time.

Another attractive feature of Boardwalktech’s approach – especially when compared with collaborating on spreadsheets over email – is that individuals can share only a portion of their spreadsheet (even just the contents of a single cell) with other individuals. Adam, for example, may want to share only a few lines of summarized information from his forecast with Betsy, who needs it to drive some – but not all – of her projections in her part of the business. Adam and Betsy have different spreadsheets with different row and column structures, yet the shared data remains synchronized regardless of the changes they make to their individual spreadsheets. Colleen, a business analyst, may have a complex formula that every other analyst must use, and this formula will evolve over time because of changing business conditions. David and Ed will always be using the same, correct and up-to-date formula in their own, individual spreadsheets that used by others in the organization without having to check for updates.

Boardwalktech offers several prebuilt templates that support inter- and intra-business collaborative processes. For the latter, one area in which a third-party application often is not a viable solution is where analytical models of data and reports must be shared between companies. Cost, implementation times, existing software environments and licensing issues often make that impractical. Browser-based solutions may be more difficult for people to navigate through compared with a spreadsheet, especially if substantial amounts of data must be updated and people need to enter data across multiple dimensions. As well, people in different organizations may use incompatible approaches to modeling that reflect the different needs of their organizations. The ability to share only essential elements of spreadsheets without having to homogenize models and data structures eliminates serious barriers to collaboration. In addition, even within companies these issues can come into play, especially for cross-functional processes or among different business units.

Boardwalktech’s products include configurations for processes where spreadsheets are heavily used today. These include sales and operations planning (S&OP), trading partner collaboration, supply and demand planning and sales and revenue forecasting. For finance organizations the company offers treasury and cash management and tax planning as well as budgeting and planning. There is also a project and portfolio management offering, which can be used by IT organizations, facilities management, R&D and others to plan, assess and forecast projects and project-like efforts. These can be deployed singly or in combination. One of the advantages of implementing, say, a sales and revenue forecasting application along with budgeting and planning is that the sales forecasting can easily tie in with the budgeting, meaning that these top-line numbers, which are managed by the sales organization, can be updated instantly in the budget and at whatever level of granularity is necessary. As well, Boardwalktech’s IT Process Platform allows companies to take any spreadsheet-driven collaborative process and eliminate many of the inherent defects.

In 2013 Boardwalktech had couple of key steps forward with new integration framework using its ‘SuperMerge’ technology and advancements to configuring templates that are used for access and input. Both of which help further embrace and extend use of spreadsheets. For most organizations, spreadsheets are an indispensable tool but they are not always the appropriate technology, especially when used in repetitive, collaborative enterprise-wide processes. It’s important to understand their limitations and not abuse them. In some cases, third-party or internally developed dedicated applications are the right choice. In others, embracing and extending existing spreadsheet-driven processes is the most practical approach. If your organization is currently using desktop spreadsheets for some collaborative business process, it probably is putting up with a host of issues that are the inevitable result of the spreadsheet’s inherent shortcomings. If so, I recommend evaluating Boardwalktech’s collaboration platform.

Regards,

Robert Kugel – SVP Research

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