The Trellance Data Blog


Posted by Peter Keers, PMP on Jun 7, 2011 6:02:20 PM

I recently received a call from a former co-worker asking for advice on a sales analysis application her organization had been using for a couple of years. “It was started by a rookie sales manager who was an Excel guru in college”, she said. “At first, it was just a few spreadsheets about his product line. It impressed the other sales managers, me included. Eventually, all the product lines were involved and an analyst was hired to handle the creation and distribution of the reports”.

“Sounds like it’s working for you.”, I said. “So, what’s the problem?”

“It was working really well for a while”, she replied. “In fact, when the analyst started, she improved the formatting of the reports so they looked pretty official. Also, when there was a question that the standard reports didn’t cover, all I had to do was e-mail her and she would do a custom report in a couple of days.”

“So, the good times didn’t last?”, I ventured.

“No, it all started to fall apart when we added new reports that included inventory information.”, she said. “The analyst found that it was difficult to match up the sales and inventory data accurately. From that point forward, the entire reporting process slowed to a crawl. Special report requests took weeks and eventually even the standard reports were not delivered on time.”

“So where do things stand now?, I asked.

She sighed. “We hired a contractor to help the analyst get the reporting back on schedule and work through the special request backlog. That was three months ago. We just extended the contractor for another month because the report requests keep coming. The sales managers have gotten used to having more information available to make decisions. We are drowning in spreadsheets but seem to have less and less ability to use the information effectively. I just don’t see where it is going to end.”

My friend’s situation is not uncommon. A simple spreadsheet-based reporting system evolved into a chaotic jumble of pieced-together files that can simply be described as “Excel Hell”.

How did this happen? There are two major reasons:

  1. Excel is not an effective enterprise data handling tool. It is extremely flexible in formatting information but managing the data underlying the reports is not its strength.
  2. Most Excel Hell situations develop without involvement from the organization’s Information Technology (IT) area. In fact, functional departments often take matters into their own hands when they feel their needs are not being met by IT or they have limited budgets. These “home brew” efforts seem to start out well but rarely have the ability to scale up beyond their modest beginnings. As they grow the cost to maintain them is surprisingly expensive and time-consuming.

Is there any hope for those who seek to escape from Excel Hell?

Here are some steps that can start the process of exiting the chaos:

  1. Perform a SWOT (strengths/weaknesses/opportunities/threats) analysis of the current Excel-based system. Understand precisely what is good (business value) about the existing reports that should be retained. Then, document what is wrong with the current system and needs to be improved. This analysis should cover why the “do-it-yourself” effort came about in the first place (i.e. – why IT was not involved).
  2. Identify the most valuable reports that from the current system. Consider these as prototypes that will serve as the foundation for requirements specifications of a new system. Also document the special report requests over time to understand how information demand evolved.
  3. Meet with IT to discuss the analysis and have an open dialogue about what enterprise-level alternatives exist to meet reporting needs. The prototype reports will provide a starting point for defining requirements and special requests history will provide insight as to how information needs might change over time.
  4. Special attention needs to be devoted to understanding the source data behind the needed reports. What is the quality of the data? Is there a high degree of confidence in its accuracy and timeliness? How will reports access the data? If there are problems with the data, the future project to fix the reporting mess needs to place a high priority on dealing with data quality issues.
  5. Solid requirements for both reporting (front end) and underlying data (back end) will drive the selection of tools to replace Excel. Too often dazzling vendor demos are based on unrealistic test data. Vendors need to be provided with a realistic set of the organization’s data (warts and all) to properly demonstrate the pros and cons of their offerings.

After these steps, the future of the project will depend on the quality of the business case that can be made and the prevailing economic environment faced by the organization. The good news is, however, that technology advances are bringing down the costs and time to implement effective reporting and analytics solutions. Also, in difficult economic conditions, escaping Excel Hell leads to improved decision making that often pays for itself by assisting the organization in making better choices.

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Topics: Data Analytics