Software and Chicken Entrails

I had a collection of epiphanies today about Informational Software.

“Informational Software” is a term I use to describe software that helps you understand and make decisions about information. It is not a product and does not make your business money, but it can be used to help you understand your business and therefore, in theory, help you make money. For example, analytics software does not make you money, but you can use it to understand your traffic and hopefully to then minimize your costs and maximize your revenues. (Note that if you are selling an analytics package, this definition is still true, because in that case the software is a product, not an information tool*.)

Informational Software comes in two types: software that interprets trends and data and makes decisions for the user, and software that collects and reveals data so the user can make their own decisions. Expert systems are an example of the former, analytics packages are an example of the latter.

Let’s call this mess of data the chicken entrails. We want to read them and predict the future, right? Sure we do. That’s what chicken entrails are for.

Okay, enough definition. Here are the epiphanies:

First: If your users are untrained and the data is simple, your system can advise the user and/or make decisions for them. If they cannot read the entrails, or the entrails are too simple to bother the entrail readers, do not let/make them read the entrails.

Second: (Pay attention, this is the important bit) If your users are highly trained and the data is very complex, do not attempt to interpret the entrails for them. Just show them the entrails. Highly trained users who have asked you for information software do not want you to do their job, they want a tool to help them do their job better.

Third: My instinct is always write software that interprets entrails, regardless of the complexity and regardless of user knowledge. Learn to stop and figure out what it really needed.

Fourth: Interpreting complex data is really, really hard. On a small, knock-it-out project, it is almost certainly doomed to fail. Now reread the 2nd epiphany: On small, knock-em-out projects, it is completely unnecessary.

Right now I’m working on software that reveals entrails to some truly arcane masters of entrail reading. They have become masters because the information system currently available to them is literally designed to protect the data from their eyes. I have found two pieces of data, correlated them, and put them into a report, and they think I’m a super genius. Not because my software is smart, but because it is smart enough to be dumb.

I really like epiphanies where I suddenly realize that it is not necessary to be doomed to failure.

* And if you’re smart enough to reason “but what if you’re using your analytics tool to analyze the sales of your analytics tool”, I congratulate you on your cleverness. Can you also see the flaw in this reasoning?

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