Saturday, April 04, 2009

Excel as a planning tool

In the course of my consultancy I often come across examples of companies doing their planning in Excel. For small-scale scenarios this is fine, but we sometimes see amazingly big and complex systems built on Excel. I do not consider this to be best practice.

I have twittered about this a time or two and I every time I get responses from people asking me what I mean. I think this one of the great things about social media. As a (self-annointed) expert on BI I tend to think that this is an obvious point. In fact Twitter has reminded me that it is not.

What I am talking about is large sets of Excel spreadsheets sometime containing a good deal of complexity which are sent around a company by email to collectplanning data. Such systems often contain tens of thousands of Excel formulas and are sometimes augmented by BASIC code as well. In some cases the results are fed back into some transactional system, but not always.

So here are a few important points on this issue:
  • I am not at all critical of the idea of Excel addins. Addins are third party products that enhance Excel. In fact far from being critical of this class of product, I like them quite a bit, and MIS, the company I once worked for and which now belongs to Infor was one of the many vendors of useful products of this type. Recently all the big BI vendors have piled into this market. An in-depth discussion of this type of software is also the topic of one of the most popular documents at OLAPReport (login required).

  • I also do not criticize companies and people who create this kind of system. In many cases it is the only way they have to deal with the complexity they are presented with in the limited time the planning cycle allows. The ingenuity I have seen put into some of these systems these systems is amazing

Nevertheless, I think these systems are very problematic, and any company using them should invest time and energy reviewing them and attempting to find a good way to replace them. The reason is that the are expensive to maintain, limited in functionality -- particularly in the are of analysis and simulation -- and inevitably suffer from data quality issues.

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