Thursday 28 May 2009

Data-centric decision-making: an update

I have been attempting to live data-centrically – a challenge in all sorts of ways:
  1. Changing my habits is difficult. They are stubbornly ingrained; perhaps the definition of a habit. I am on auto-pilot for much of the day – simply so that I can get through my work. The point of the study was to switch off auto-pilot, but it’s wasn’t so easy.
  2. Data doesn’t exist for lots of things – in some trivial and some less trivial areas.
  3. Too much data exists in some areas – much of it not joined-up or misleading. But then it was ever thus: lies, damned lies, and statistics. Getting data to be informative involves work – lots of it.
  4. I was on holiday for a week. The Highlands of Scotland so completely calmed my soul that I forgot there was any other sort of data apart from how many lambs can run down a grassy slope. Doing that funny kicking thing that lambs do.

Habits which already included data, business financials, for example, were easy. Our internal systems that provide information on projects, financials and data I need on a day to day basis were taken for granted and used by the auto-pilot.

The evidence for and against a tidy desk is no more settled, but my workspace is now clear. Whether a tidy desk improves my work is a controversial idea, but the sense of calm and control is worth the effort. Is this living data-centrically? No – there is just no data on this, just opinions, preferences and tips from those brave enough to offer anything this subject.

Useful data is difficult – no doubt - it needs work and is therefore slow to gather. Successful data is then quickly assimilated and taken for granted. The systems I work on are invariably involved in presenting data in a useful and orderly way to enable better decision making. Maybe its when they are taken for granted that we know we have done a good job.

When I tried to gather data in an unstructured way I found much data to be illusory. It somehow fooled me into feeling that it contributes when in reality it didn’t change my thinking or my actions. There is plenty of data loaded with agendas and bias – and plenty of opinions; neither was much use for this exercise. Cherry-picking here and there is neither scientific nor useful, and is perhaps why so much is ignored. Putting a toe into the turbulent waters of the energy sector seemed to turn out so much contradictory data that it made my head spin.

When weekends and holidays (bank or otherwise) are taken out of the equation, I am only 10 days into the study. I’m unconvinced that any of the above is particularly illuminating, but I promised an update. Take it as work in progress.


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