Proactive decision making (and how to avoid running out of fuel)

This weekend, I ran out of fuel on my way home from golf. I’d played a good, quick round, won the comp and was on my way home around 10.30am feeling pretty good. Then, unexpectedly, my car ran out of petrol. This got me to thinking about the difference between reactive and proactive decision-making ...

Now typically, when fuel is getting low, I get a ‘warning’ light on the car dashboard. This is like your classic BI dashboard/scorecard – when something happens, the status may change from green to yellow or red. From this, I can then estimate that I need to refuel within some unknown but bounded number of kilometers, which I estimate based on past history to be somewhere  between 25-40km (I do tend to ‘cut it a bit fine’ sometimes!).  Similarly, in a business context, we watch for status indicators changing based on past history, then react based on experience, knowledge and ‘gut feel’, one of reasons why the traditional BI paradigm is sometimes referred to as being a “rear-view mirror”.  This is reactive decision-making.

However, this weekend, my fuel gauge was playing up, and didn’t indicate that I was low on fuel (it was still showing the tank as ¼ full). So, a few kilometers from leaving the golf course, I ground to a halt. If this was, by way of analogy, my ‘cash flow’ or similar financial indicator, I might be looking at a foreclosure or bankruptcy instead of the minor embarrassment of having to call the NRMA (Australian equivalent of AAA in the US or the AA in the UK) to be ‘rescued’.

At this stage, I still trusted my previously reliable indicator, the fuel gauge, so I had no idea of what could be causing the problem. Was it the alternator? Or worse? My NRMA patrolman (“management consultant”), in true Aussie larrikin fashion, bet me $20 that the problem was lack of fuel ie that my fuel gauge (financial ‘metric’) was misleading me. I took the bet. He won.

Ironically, my other vehicle has, instead of a fuel gauge, an onboard ‘algorithm’ which predicts, real-time, how many kilometers I can drive until the tank is empty. So if I’m burning rubber, it might drop to 8km to empty, if I’m driving on cruise control it might go up to 45km. This is proactive decision-making. I have a forward-looking view: if I do this, then this is the result. If it’s 40km to the nearest service station, I can adjust my driving accordingly in order to make it based on the fuel I have remaining. This is why moving beyond the traditional BI paradigm of reactive decision-making enables me to make better, more informed decisions. And avoid running out of fuel. Literally, or figuratively.

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    The Asia Pacific region provides a unique set of challenges (ความท้าทาย, cabaran) and opportunities (peluang, 机会). Our diverse culture, rapid technology adoption and positive market has our region poised for great things. One thing we have in common with the rest of the world is the need to be globally competitive while staying locally relevant. On this blog, our key regional thought leaders provide an Asia Pacific perspective on doing business, using analytics to be more effective, and life left of the date line.
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