The old adage, “people, process and technology” is as old as I am – probably you too.  In fact I suspect we will all likely call on this adage in at least one work-related meeting or dialog every week or so.  We are told, over and over, that everything comes down to, “people, process and technology.

It so happened that a colleague of mine shared around our MDM community today a link to an article titled, Thinking about ERP in an ever-changing world of data, by Anthony J Scriffignano, SVP, Chief Data Scientist, Dun and Bradstreet.  On my first pass of this article I moved to blog over a major blunder in the article.  But I re-read the article and found out two other items: one that can be discussed fairly, and then I determined that his conclusions in the article are reasonable – irrespective of his blunder.  So let me first talk of the blunder, then talk about the worthy part for discussion.

In the article, Mr. Scriffingnano suggest, “Enterprise Resource Planning (ERP) was born of a promise to provide a common, enterprise view of data and process across organizations.”  In fact this is the first sentence of the article and I suggest that it is wrong.  ERP was never about “single view of data”.  Let’s be clear, an enterprise data warehouse was meant to do that – and that was invented after ERP.

ERP was originally an attempt to unify what had become multiple silod systems that all were meant to connect to the enterprises’ general ledger.  Since it was hard to do, a “single view of financial transaction” was sought for the CFO/CEO and so ERP came along.  The “single process” idea was a secondary sales pitch that evolved over time.  Users assumed they might get single view of data – but that was never on any sales deck or pitch until, if ever, much later.

I have seen this first hand as a user of MRP systems, then being a vendor involved with ERP and SCM systems, than as an analyst talking to hundreds, if not thousands, of firms with the same experience.  ERP and “data” really don’t go well together – the majority of standard ERP blue prints and implementation plans ignore data integrity (worse case) and treat data as a second class citizen that can be entered into the ERP system via a flat screen without awareness of a) use of data before ERP, b) use of data after ERP, and c) data used across ERP (best case).  Clients with this issue are the largest single segment of client’s I speak with – year in, year out.

Now that I have gotten that off my chest, let me explore a useful point that Mr. Scriffingnano makes.  Later in the article he states, “A very powerful frame for considering change in an organization considers four factors at the outset: people, process, technology, and mindset.”  This new mindset is not quite explained, but the idea sounds good.  As far as I can tell, mindset implies how leaders (mentioned in the article) seek to influence culture (not mentioned in the article).  This is valid (if this is what he meant).  But I want to connect this to another data point.

A few weeks ago I was talking with a client and presenting a deck on how to build and sustain an effective data and analytics strategy.  During the presentation one question came from the floor: Can this idea/work help me sell to our company the idea that we all need to be data-driven?”  We explored “data driven” since that sounds techy.  And how many business people would use that phrase?  In fact, are we not taught to be “customer driven”?  Surely the “data driven” is some lower level underpinning that supports a more improved “customer driven” strategy.

So given this additional data point I want to consider updating the authors recommendation.  I don’t think you want a data driven enterprise; I think you want a customer driven enterprise that exploits data to the fullest.  As such, people, process and technology needs to be extended to people, process, data and technology.  If we call out data as a distinct asset (used by and within the other three), we might get sufficient focus on it.

(About the author: Andrew White is research vice president and distinguished analyst at Gartner Group. This post originally appeared on his Gartner blog, which can be viewed here).

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