Spreadsheets Versus B.I. Applications: A New Détente

Thanks to easing tensions between fans of spreadsheets and B.I. apps, this morning meeting won't dissolve into a massive brawl.

Ever since the first business intelligence (B.I.) application came to market, a somewhat contentious relationship has existed between people who advocate the adoption of B.I. and those favoring the use of spreadsheets.

Early on, B.I. software vendors positioned their products as the superior alternative to spreadsheets. Why rely on old-school sheets of rows and columns, they argued, when you can use a dashboard that offers penetrating insight into business trends? And yet, for all the money poured into B.I. application development, the vast majority of workers continue to rely on spreadsheets.

The good news is, the tenor of conversation between B.I. advocates and the spreadsheet community has finally started to become more civil. Instead of positioning B.I. applications as a replacement for spreadsheets, the dialogue these days is focusing more on how the two can complement each other.

Howard Dresner, president of Dresner Advisory Services, suggests the reason for this newfound civility lies in one simple fact: there is no real substitute for a spreadsheet when it comes to intuitively and flexibly working with small amounts of data. “Arguably, spreadsheets such as Excel are really a class of BI applications,” he said.

When it comes to working with large amounts of data, B.I. applications are increasingly used not only for analytics, but also built-in data governance capabilities.

As tempting as it is to rely solely on spreadsheets, they can expose organizations to significant levels of risk. As a rule, spreadsheets require labor-intensive manual processes, and are highly error-prone, difficult to consolidate and integrate, and usually have no version-control capabilities. “You don’t really want to have a spreadsheet application be part of formal audit process,” noted Dresner.

All that being said, spreadsheet data is now routinely rolled up into B.I. applications. Thanks to the ubiquity of applications such as Excel, spreadsheets also remain an efficient way to distribute information.

Soumendra Mohanty, global lead for informatio​n management at Accenture, believes the combination of B.I. applications, spreadsheets, tablets and cloud computing is changing the way work gets done.

A good example of that paradigm shift is Host Analytics, which provides a set of corporate performance management tools based on applications created using Microsoft Excel. Delivered as a service in the cloud, Host Analytics recently added a BI module. “We want to provide a one stop shop for finance where spreadsheets meet B.I.,” explained Keri Brooke, vice president of marketing for Host Analytics.

But cultural issues may end up the biggest ones for organizations looking to achieve a rapprochement of sorts between B.I. applications and spreadsheet usage. IT and finance departments will need to work together toward a common goal: educating the rest of the organization about the inherent shortcomings associated with an informal, spreadsheet-only approach to management.

Once that’s accomplished, the organization then needs to standardize on trusted data, create a consistent method of delivering reports, track changes via journaling and Wikis, and establish an audit trail.

Fortunately, the cost of acquiring BI applications has dropped significantly. Whether it’s the use of open source or commercial software, delivered on-premise or via the cloud, BI application software has never been more affordable. In addition, the cost of integrating BI software with enterprise applications has dropped, along with the complexity associated with accomplishing that integration.

Of course, the debate over which type of BI application to use when continues on. But as adoption of standalone BI applications or the use of BI functionality within other applications continues to grow, the data that managers are using to make decisions becomes more reliable. That may not necessarily result in better decisions, but it will eliminate many of the bad data excuses that managers all too routinely use to justify poor decisions.

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