Big Data - The Antithesis of Lean Thinking

   

It’s too bad lean thinking is free. I suppose that’s not entirely true; a lean transformation actually costs a few bucks for the learning – consultants, books and training. But it is nothing like the cost of an ERP system, and it pales in comparison to ERP thinking on steroids – ‘Big Data’. Because the ERP and Big Data providers play in such a high dollar arena they can and do spend a lot on very focused marketing efforts. IBM, a company that stands to gain quite a bit from Big Data becoming the focus of business management, is providing “software, curriculum, case studies—including guest speakers” to Rensselaer Polytechnic Institute, Fordham, Yale and about 300 other schools. Too bad those schools aren’t cranking out kids steeped in lean thinking, but there is no one who stands to make a enough money from peddling lean in a position to buy college curriculums on such a scale.

There may well be a place for Big Data in science, but in business Big Data is the polar opposite of going to the gemba - lean thinking - and a singularly bad idea. Effective decisions are made by empowered employees who share the company vision, and they are made one at a time at the point of attack, where the work is actually being done. Big Data, like ERP systems, are built on the premise that mountains of data collected at the gemba must be gathered, sorted, analyzed and acted upon by smart people in far away headquarters buildings, in the offices of planners and buyers, by business analysts … just about anyone other than the people at the scene of the action the data describes.

A May 2011 report by McKinsey Global Institute and McKinsey’s Business Technology Office found that by 2018, the United States could face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as an additional shortfall of 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.” The fact that, when they are found, those “140,000 to 190,000 people with deep analytical skills” will all be 100% non-value adding wasted corporate bloat – just so much more overhead – is apparently not part of the equation. Not to mention that fact that the 1.5 million managers and analysts without sufficient analytical know how who are already squarely in the waste column.

To understand just how convoluted the thinking is, read this from the HBR Blog, called “The Value of Big Data Isn’t The Data”.

Here's an example. Imagine, for a moment, that you run an organization with multiple restaurant outlets and you have amassed point-of-sale data for each of your franchisees, but none of them are using that data because they just don't get what they need from it. They need insight as to how their stores are doing and what they should do next. You need to give each of them a report that actually explains how they are doing in comparison to themselves over time, how they might compare to other restaurants, and where there might be shortfalls.”

So what sort of information Big Data actually do? “Foot Long Hot Dogs were this week's weakest menu item with average daily sales of fewer than 140 units. Bringing the store's daily sales of Hot Dogs up to the same level as the co-op's would add about $566 more profit each month. Over a year, that's an extra $6,828. The store only needs to sell six more units per day to accomplish this.”

At how many levels is this scenario absurd?

For one, do the highly skilled analysts really think the guy running the hot dog stand doesn’t know that he would make more money of he sold more hot dogs? Are they really so full of themselves (and so disdainful of people actually running things)?

Wouldn’t it be just as accurate – and a whole lot cheaper – to keep track of the number of hot dogs sold with hash marks on a white board in the restaurant kitchen? The problem with that is that the people actually making and selling hot dogs would have the data they need, but the big brains at headquarters wouldn’t … not a problem for a lean thinker, but a wholly unacceptable situation for a corporate bureaucrat.

Of course, All Business is Local. Selling hot dogs at the restaurant is all about the local alternatives hot dog eating customers have, and absolutely nothing to do with how well another restaurant in another city is doing. Using Big Data for benchmarking is of next to no value in the real world.

And of course, the biggie – “Bringing the store's daily sales of Hot Dogs up to the same level as the co-op's would add about $566 more profit each month. Over a year, that's an extra $6,828. The store only needs to sell six more units per day to accomplish this.”

Typical headquarters analytical output – An overwhelming blast of the obvious, and absolutely nothing useful for the people who already know that, but are wrestling every day with how to sell more hot dogs.

That last point is pretty much the story of corporate information – for just about all big companies (the big ERP users and the ones chomping at the bit for Big Data) and too many not so big ones. Data from the places where people are actually doing things – creating value for customers – is gathered and used by headquarters staffers (usually with little or no real front line experience) and manipulated to create ‘gotcha metrics’ that are intended to find any and every mistake the value creators make. And make no mistake, the example in the article is just another example of this.

There is little in Big Data for people on the front lines, but their corporate critics will think they died and went to heaven with it.

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