Jan 07 2014

Data, data, everywhere, Our minds begin to shrink.

Data, data, everywhere, Yet no one thought to think.

We all use data everyday, no matter what you do, data is part of your life. In many professions it is obvious, in others, less so. Even as we dress in the morning the data available about the weather outside helps us to determine what to wear, whether to walk, ride or drive to our destinations, etc. In Dynamic Organisations data is used to help make problems obvious.

Many of us will have heard various quotes about data; some that aligned with my missive here are:

– “It is wrong to suppose that if you can’t measure it, you can’t manage it – a costly myth” W.E. Deming, The New Economics.

– “the most important figures that one needs for management are unknown or unknowable” W.E. Deming, Out of the Crisis.

– “Buffett found it ‘extraordinary’ that academics studied such things. They studied what was measurable, rather than what was meaningful. ‘As a friend [Charlie Munger] said, to a man with a hammer, everything looks like a nail.” Roger LowensteinBuffett: The Making of an American Capitalist.

– “If a measurement matters at all, it is because it must have some conceivable effect on decisions and behaviour. If we can’t identify a decision that could be affected by a proposed measurement and how it could change those decisions, then the measurement simply has no value” Douglas W. HubbardHow to Measure Anything: Finding the Value of “Intangibles” in Business.

On a recent project to improve a certain aspect of a client’s business there were a couple of elements of data that the client began collecting. This data was relatively easy to collect, albeit manually, the process was not huge. However, this brought about 2 questions for me; 1) Is this scalable? i.e. how many times do we add more & more data collection, filtering & distribution to someone’s workload by saying, it only takes a few minutes (they all add up). 2) What are we going to do with this data? Does the end justify the means?

Let’s take these separately for a moment. How many “little changes” do we make to our processes each day, week, month, year? How many are additional tasking? How many “it’s just a 2 minute job each week” are added to one person’s workload over a year? If every other week we give someone 2 minutes per week additional work, over a year we have added 45 hours work to their job, they’d effectively have to do an extra week’s worth of work each year.  (26 x 2 x 52 / 60 = 45)

Yes the intention is (usually) the additional data collected will lead to gains elsewhere or even within that person’s role, but how often do we check/act (PDCA)?

The other question posed is about the actual data being collected, what decisions will it drive, what actions will we take based on our findings. I always think of Covey’s 2nd Habit – Begin with the End in Mind. If we haven’t thought through the intended decisions & actions that may be made, then we may not be collecting the right data.

There may not be any definitive decisions at the outset, it may not be an “either this, or that”, depending on what we find, but we should have an idea of how we will use the data – and we must communicate that idea! Collecting data because “we can” does not mean it will be worth the effort. The second 2 quotes are both aligned on this thought.

Collecting data that is easy to collect doesn’t mean we will improve – we need to collect the right data that can drive the right decisions & actions. Remember, – just because we can, doesn’t mean we should!



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