Tackling the ‘Excel Problem’ in small business (it’s more than just data quality)

One of the cool things about my job is that I get to talk to customers as they’re transitioning away from Excel. My favorite part is when customers tell me that we’ve given them back the hours they used to spend producing sales reports in Excel every week. That’s why recent posts around the blogosphere ([1], [2], [3]) that pointed out that Excel is a double-edged sword got my attention.

A bit of background— the data quality argument:

The general argument against Excel has been that Excel’s power is also its biggest downside: while it is incredibly easy to get started making spreadsheets, it’s also incredibly easy to make mistakes that cost companies millions or even billions of dollars.

The problem is not new—there were well-publicized spreadsheet errors made in the eighties— and it doesn’t seem to be getting better over time. In 2008, University of Hawai’i professor Raymond Panko published a summary of 13 field audits that checked spreadsheets used in ‘real-world’ environments. His analysis found that a whopping 88% of the spreadsheets had errors.

However, there’s more to the “Excel Problem” than data quality. Here’s why our customers are thrilled to leave Excel behind:

Beyond data quality: 3 problems that any solution to the “Excel Problem” should address

Here’s a quick story that touches on three distinct problems that we run into every day. See if you notice them as you read:

“A sales manager is opening a new branch in Connecticut. On his first day, he inherits a bunch of spreadsheets from the other offices that show that more than 50% of the deals the other offices close come from cold calls.
He hires a huge team of cold-callers, but for some reason the sales don’t start rolling in. He tries different scripts, better training, but nothing helps bring the new branch’s numbers up.

Months later, a mentor fills him in: the spreadsheets were fluff pieces. Since everybody knew that in the reports the owner used, “calls” == “hard work”, all the branch managers bumped up the call figures at the end of the month before sending the spreadsheet along to the central office.

As it turned out, cold calls were precisely the wrong thing to focus on if he actually wanted to grow the new branch.”

Did you catch all three?

1. Excel is far too complex

In evaluating possible solutions to the spreadsheet errors he described in his 2008 paper, Professor Panko wrote:

“… few spreadsheet developers have spreadsheeting in their job descriptions at all, and very few do spreadsheet development as their main task.”

The term ‘spreadsheet developer’ is great because putting together a sufficiently complex spreadsheet is akin to being a software developer. The Excel formulas are, quite simply, a programming language.

However, while a software developer is hired based on his or her software development skills, few people are evaluated based on their ability to put together a spreadsheet. What makes it worse is that since everybody has at least some knowledge of how to use Excel, many people misjudge their own expertise.

For the business owner in our story, Excel offered too much. The call-centric report was built once and then used for years without anybody really understanding how or why it works. Since building a new report from the ground up was too daunting, dozens of additions were made to the original report over the year, further obscuring the true drivers in the business. Rather than becoming a way to better understand business, Excel became a black box to hide what is really going on.

2. Excel makes it easy to build reports that paint a rosy picture

It’s human nature to present the best side of the story– whether we’re pitching a new startup idea, trying to impress the a date, or putting together an Excel sheet, we tend to over-state the positive in our stories because of a cognitive bias that psychologists call ‘illusory superiority’. It’s not all bad though, because in general we’re pretty good at detecting when somebody is deceiving us (or themselves).

While our ‘bullshit detectors’ work pretty well in face-to-face situations, we tend to fail when looking at Excel. Spreadsheets are hard to debug and we associate them strongly with analytical work. Instead of evaluating how the spreadsheet is built, we fall back on whether or not the result seems believable. Since Excel is hard to question, it covers up our human bias to paint a rosy picture.

3. Excel leads to stale reports

Before I joined InsightSquared, I worked at a large company that had invested heavily in reporting– expensive hardware and software, real-time reporting systems, and a fair-sized team to back it all up. Despite all this, every Monday morning I would see users copy and pasting data into spreadsheets manually. Employees would gather in the snack room, hoping that the hundreds of thousands of VLOOKUPs and dozens of tabs they had cranking wouldn’t crash their computers. Even the most advanced BI platform in the industry wasn’t enough to keep the company off of manually-updated reports.

The story is even worse at smaller firms. Most firms don’t even have Excel data connectors, or even a back end database for a connector to use. This means decisions within the organization grow stale as the reports used to make them slowly go out of date. Instead of a driver of action, Excel becomes an out-of-date roadmap.

What this means for anybody that tries to take on the ‘Excel Problem’:

The lesson I’ve learned at InsightSquared is that it’s not enough to fix the data quality problem.

These problems aren’t the same problems that cost JPMorgan billions of dollars– they are the problems of the small and medium sized businesses that depend on Excel but don’t have the resources of a large financial institution to build reporting technology, extensively train every user, and absorb huge losses. As more and more of the business world starts ‘running by the numbers’, it is critical to reduce complexity, protect from human bias, and prevent data from going stale for users who don’t have spreadsheet development in their job descriptions.

At InsightSquared, our goal is to solve the Excel problem for small and medium sizes businesses. We have the best Salesforce.com and ATS reporting in the industry, with reports that are easy to understand, accurate, and up-to-date. We deal with the Data Quality issue too!

If you or somebody you know is struggling with Excel, please drop us a line using the free trial button below.

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Adam von Reyn
Adam von Reyn
Adam is Director of Demand Generation at InsightSquared. Outside of InsightSquared, he's an avid skier, runner and live music fan. Adam has a BA in Economics from The University of Vermont and an MBA from The Tuck School of Business at Dartmouth. Follow him on Twitter @adamvonreyn
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Showing 3 comments
  • Daniel_C!
    Reply

    What is the best intuitive way to figure out problem with ‘bullshit detectors’ 😀 ???
    Well Thanks for sharing wisdom through this insightful article. One really need to have that ‘eye of am eagle’ to figure out such issues.

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