July 2008 - Posts

  • Quick Reactions

    How often have we heard the phrase "We don't want to be reactive, we want to be proactive" with the implication that unless we're able to take action in anticipation of events which will impact our business, we're going to be in trouble?

    It may be true that taking pre-emptive action seems like a great thing to do when the information enables one to do so.  But as we seem to relearn every few years, past performance is no guarantee of future results, and models which use the past to predict the future are vunerable to changes which make those predictions invalid (just ask anyone at Bear Stearns).  Given that, I think it's worth asking what's wrong with developing really good reactions as an alternative (or compliment) to being proactive?

    In responding to events once they've happened, we have the advantage of potentially full information on them, and beyond that, we're not locked in by a system built on what we thought would happen, but are free to react to what actually has happened.  We're given the freedom to fully analyze and understand the situation.

    This needs to be balanced against the fact that if we wait too long to react, it's not much better than not reacting at all, but with the proper tools, I believe that reacting in real time can be even better than committing yourself to moving in one direction and hoping that reality accommodates you.

    What makes for tool set that allows for real-time reactions?  Though there may be others, in my mind there are two key features of such a tool set:

    1. A responsive, flexible analysis environment.  Given that one of the advantages of reactive analysis is that we're not limited by preconceived models, it's important that we not be limited by our tools.  The idea is to know what's happened as fast as possible, and if your tools limit the sorts of analysis you can perform, or can't perform them quickly, your reactions aren't as good as they could be.
    2. An infrastructure which supports real-time data capture and distribution.  Obviously to do any sort of analysis, appropriate input data is required.  If that data needs to go through a lengthy process of being captured, cleansed and transformed before it's available, reacting in real-time is essentially impossible.  The data needs to be available when it's fresh and it needs to be easy for analysts to get to.

     I'll go into more detail on the details of each of these items in subsequent posts.

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