Best of Breed or One Vendor?

Analytics folks need a good set of tools to do their work. I won't get into a SAS vs. SPSS discussion (different tools for different situations. Ok, I got into it) but I did want to talk really briefly about choosing an analytic "stack." By stack, I mean the set of entire tools that enable high quality analytic work; The tools that you need for data extractions, transformation, and loading, data QA, analysis, reporting and data mining, etc. In my organization the stack includes Netezza and Sybase as our database platform, SAS for our data ETL, QA and access, SAS for our ad hoc analysis/data mining, and Business Objects for standard reporting.

if you look not too closely, you can see a common theme. SAS is the dominant vendor. Do we use a lot of SAS because they make the best products for each part of our stack? No, but their products are good and they are well integrated. By concentrating our purchases on one vendor we reduce the integration costs; we are assured that the products are going to work well together. Or at least that we can hold someone accountable if the disparate products don't play nicely. In fact, SAS wrote a Netezza database connector for us when we needed it.

The other option is to take a best of breed approach and buy your products from multiple vendors. The advantage in going best of breed is that you can really tailor your stack to your needs. For example, you may need a lot of control over the charts created by your analysis tools and only one vendor allows you to have that control (I once worked for a company whose tick marks on charts had to point away from the chart. You can actually select this option in Excel, but most vendors don't allow such fine control. Having such a fine level of control over the look of the output was considered a "requirement" for our business intelligence platform.)

So which approach should you take? My advice is to fight the logic of best of breed. I know it is difficult to pick products that are not the best fit for your situation. Fight it. In my experience, most of these products are more similar then different. Think about word processors. Most of us use Word, but would not shy away from trying Open Office (actually, I am writing this post using Google Documents). Word processors all have the same basic functionality. Word may be very full featured, but most of us just use it as a text editor with a touch of formatting. Similarly, the stats packages are more similar than different. Those little features or very specialized functions that seemed so important when you were making your purchase decisions won't make a lick of difference in the quality of your team's analytics. What does make a difference to your team's effectiveness is their ability to deploy and exchange data between applications. There are times when you need to select a "best of breed" application; when you to use proprietary analytic techniques that are offered by a single vendor. But in general, you are better off giving up the perfect analytical app for one that is well integrated into an analytic suite. My advice is to stick with one vendor for your analytic stack or at least minimize the number of times you change vendors as data moves up your stack.