Why Lean Data will stop you worrying about Big Data

Every once in a while a new concept will come along. It is interesting that these new principles will trigger several behaviours in business leaders: panic, band wagon jumping, head in the sand or pragmatic consideration. I would like to encourage the latter of these with the concept of Big Data and offer the antipathy; “Lean Data” which is a lot less daunting and actually adds value.

The concepts of “Lean” derived from the automotive industry decades ago and since then has become a mind-set in many sectors. If you strip back the jargon, Lean is pretty simple; reduce waste in all its forms.

The principle of Lean is that you identify the customer (obvious for most businesses), you can also consider internal customers at the macro level. Then you find out precisely what the customer wants/needs from your business or department. Lean jargoneers will call this “Voice of the Customer”. Once you know this anything else that does not directly add to this value can be considered waste.

So what is Lean Data?

Again start with end points and identify what information is required. This will involve considering how and why it is used; often it is the basis of decision making (see the Business Management Cycle).

TIP: something we often do with clients is take one of their reports and discuss it with those who receive it. We ask them to highlight what they find useful. Once we have done this with all those on the circulation list it is incredible to see how much of the report is not adding value and is therefore waste. If you then consider the time and effort it takes to collect, create, present, print, manage and store that information and corresponding data, it is quite a cost.

Once you have understood what is and is not required you can clean out and redesign data processes. Here are a few design principles:

  • Data should be owned and stored in one place, everything else references it.
  • If a computer can do it, it should do it. Manual operations with data are time consuming, expensive and prone to error. Most desktop applications such as Excel and Access have the power to save hundreds of hours of time.
  • Presentation should have a professional design. Report and output that are hard to understand or read undermine their objectives.
  • Data entry should capture potential sources of error. “Garbage in, garbage out” is a very old expression but no less true today.

Once you have great quality data, stored appropriately with automated conversion processes providing timely, high quality outputs it could transform your business with the insights it produces.

Now where did we need “Big Data”? We didn’t. We started at the end and worked backwards. Big Data works the other way. Would you buy the entire contents of the supermarket before you bake a cake?

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