How to Reduce Spreadsheet Risks and Inefficiency with Modern Analytics

Microsoft Excel - Spreadsheet

The risks and inefficiencies of using spreadsheets to manage common business processes have become legion. This is a topic that will resonate with all involved in data, analytics, or financial management.

Most employees are being asked to do more with less every day, and when this is coupled with unprecedented external events, like the global COVID-19 pandemic, then how the work is done becomes as important as the output. If spreadsheets are being used extensively to do the work, then it’s just not scalable.

Over the last six months, Infor has asked over 150 organisations what stops them from becoming more data driven. If they were unable to scale rapidly to meet growing business demands; or if users are spending an enormous amount of time aggregating data to get to standard reports; or if the business is too dependent on IT or analysts to get the data needed because there is no self-service; if analytics isn’t being driven from the top down in the organisation because it’s not seen as an economic asset; or if Excel is used extensively, leading to inconsistent results all over the enterprise - inefficiencies abound

The results were clear. Infor found that 43% of the people surveyed lived in absolute spreadsheet misery, and 61% said they were wasting enormous amounts of time aggregating data in spreadsheets. Given that things are so bad and it’s such a prevalent problem in the enterprise, the question arises, why is that?

When insights need to be delivered very quickly, spreadsheets are a quick path to value. They’re highly available, easy to use, a bunch of data extracts can be extracted, and you’re off - and that’s fine, in some cases, to get that first insight. What happens when people start building processes around Excel and making ongoing decisions on this static data? That’s where the downside of these spread marts, for want of a better term, starts to appear.

Maybe someone overwrites a formula that invalidates all the data, and now people make decisions from inaccurate inputs. This is compounded when these files are sent to other parts of the organisation so people can enter their numbers. That creates a huge nightmare consolidating all those inputs. Now all the formulas must be reworked, and all the calculations checked to ensure that this new data aligns with the old data.

Thankfully, Infor’s modern data architecture could help businesses eliminate spreadsheet risks, and inefficiencies. With Infor Birst, d/EPM, and GRC, customers are removing slow, inefficient, and potentially risky spreadsheet-based processes from their organisations.

In the health sector, many spreadsheet reports are used to support various processes, including personal protective equipment (PPE) inventory. Maintaining the spreadsheet reports is manual and time-consuming. End-users must navigate the various set parameters and filters, which was a challenge for those who were not analysts. When a pandemic hits, and instant access to reliable data is essential, the drawbacks of this approach are eternally highlighted.


In these instances, Infor Birst could help. Users can deal with a certain amount of pain for so long, but when there is a crisis, it becomes clear that a better path is in dire need. When complex spreadsheets are replaced with several standard Birst dashboards fed from Infor Financials and Supply Management via the Infor Data Lake, easy access to information and reliable data is ensured.

Infor d/EPM also halves the time it takes to deliver monthly financial consolidations. Old school consolidation processes, based on spreadsheets, have high risks - including the challenges of doing currency conversions.

By replacing this manual and risky process with Infor d/EPM, clients find that they can load and process data several times a day and can view the first pass of the Profit & Loss (P&L) and balance sheet after just five or six days.


With trustworthy data, available in near real-time, businesses are empowered to increase efficiencies. Now they’re making important financial decisions with good data.