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Productivity Improvements – What We Have Been Looking For?

by Andrew White  |  April 18, 2017  |  Submit a Comment

An article in this week’s Economist has me all agog.  In “Algorithmic Retailing- How Otto, a German e-commerce firm uses Artificial Intelligence“, there is talk and examples of how AI helps improve the performance of current business processes and yet did not reduce the number of people involved in those processes.  The examples turn on the use of deep learning to predict better what people will buy ahead of time.

The result is less wasted inventory purchases, and increased margins, service level and retail performance.  Additional headcount has even  been increased to meet the improved demand.  Overall productivity has improved.  And more importantly this is not a winner-take-all firm like Amazon or Google- this is a case study of a smaller firm and so good news for us all for different reasons.

This is just the kind of example we in the IT industry need to find and make example off.  We should not of course go off half-cocked and all roll over and say AI ‘is it’ but the example is an excellent start.  The fact that this is not a winner-takes-all firm getting even bigger is a key need we should be looking for.  Too much of our global economy is dominated by very large firms getting even larger and this bodes badly for us all.  Another article explores this challenge – see Shumpeter: Crony Capitalism – Bright Minds in Chicago Worry about the State of the Competition in America.

AI is also a complex innovation.  AI has been around for a while and evolves every now and the.  The new batch is focused what is called deep learning, in the industry.  This is a form of multi-layered neural network.  Such engines ‘learn’ be reading lots of data and discovering patterns in that data.  Literally the more data you have the better, as bias will over time decline due to the law of big numbers (really big data).

AI needs to be applied.  So it is not an innovation that you simply license, deploy, and then crank up the margin.  You have to apply it to a problem.  The consumer forecasting and service problem that Otto hit on is not unique.  In fact many e-commerce and retail firms are in the middle of an arms race with AI warheads.  Other industries need to uncover their own problems and opportunities to optimize, or innovate with.

So AI is a promising innovation due to the nature of its value necessarily shown in this one article.  But AI looks more like a platform innovation too, that may spin-off any number of other innovations – that may appear short or long term term in being realized.  This is also good news for productivity geeks since we need to see new innovations take a long-time developing many new, hard-to-forecast places for subsequent innovation.  AI may prove to be one of these.  So all in all, an exciting article at just the right time.

 

 

 

 

Category: artificial-intelligence  deep-learning  e-commerce  productivity  retail-industry  

Andrew White
Research VP
8 years at Gartner
22 years IT industry

Andrew White is a research vice president and agenda manager for MDM and Analytics at Gartner. His main research focus is master data management (MDM) and the drill-down topic of creating the "single view of the product" using MDM of product data. He was co-chair… Read Full Bio




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