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What to do? A little ERP? A little IOT? A little big data? Who Know...Who Cares?

05 Sep 2016

I recently questioned if IT (as a body) really knows how to identify what investments really drive productivity.  I explored this question in a number of blogs, culminating in this: Never Say Never  -How to Become More Productive.  The bottom line goes something like this:

  • Some kinds of IT do help individual firms improve productivity
  • Since all firms are different (they have different maturity capability, different systems, different data, different methods and more), it is logical to assume that not all firms will get the same improvement or performance from the exact same investment approach
  • At a macro level we cannot prove that IT as a whole is driving productivity which is a bit of a bummer on the marketing front

If we also add onto the top of this another generalisation the picture gets even murkier.  Over the last 40-odd years, something like 40-60% of IT-based (that would be data, or technology – since they can be different!) initiatives are subject to a methodical ROI analysis; the rest of the IT investments tend to be faith-based or shall we say, “part of a broader strategy”. This data emerges from numerous publications and research in the US and Europe (mostly UK) but also more recently from our own analysis of global firms and their strategies.

So we should conclude possibly some depressing news and some good news. The depressing news is that we are not that sure over what to do next. The good news is that it might not matter that much. I think that’s mostly good news….

I noted in a recent Information Management article, “CEOs Want to Innovate – They’re Just Not Always Sure How“, some review of 2016 KPMG CEO survey. The bottom line of the article is that spend on data and analytics is going to continue (to increase) but CEOs are not altogether sure how that investment will help drive innovation. Let’s be clear – innovation and productivity are not the same – but they are related. Innovation can drive many things and many of those things, if successful, will improve productivity.  In fact we might be hard pressed to find a “successful innovation” that worsened productivity.

This is a most interesting situation to be in.  We have slow global growth, opportunities still abound, increasing competition, increasingly a more regulated environment, troubling low commodity prices keeping inflation at bay, and cheap money to fund investment, yet depressingly low capital investment.  And on top of all this, IT (as a source for innovation and productivity improvement) remains challenged to show its worth.  I think its time we started to take a more pragmatic and in some cases new look at what we do with IT.  We might need to apply some proven techniques from outside of classic IT and apply them to what we do.  Take, for example, the finance industry.

Gartner has been talking about ‘data as an asset’ for some time.  Truly many folks have – no one has a monopoly on this idea.  But what does this mean?  How does the acceptance of this idea change behaviour of the CEO, or the CIO, or IT at large?  Last year we asked senior business leaders if they valued their data assets.  We got back a really odd finding: over 50% of senior business leaders thought their firms DID value information assets. This is hogwash.  They might think that someone in their firm does but they do not.  At least, if they do, those users live in a box and don’t speak to anyone else alive to share the news.

IT and specifically data and analytic-based investments (and I include IOT, business applications and so on) rarely take into account the value of the data before or after the effort (an asset-based or balance sheet view) and as I said before, something like 50% try to do some kind of ROI or return/yield based analysis.  But even those ROI/yield analyses are silod – one project at a time. There is no model to help determine the dependent and synergistic return of any given sequence of investments:

  1. ERP, followed by classic BI, followed by MDM, followed by advanced analytics, or
  2. MDM, followed by advanced analytics, followed by ERP, followed by classic BI

No one can tell you which sequence is best.  So we really need to start developing new tools centered around Infonomics and Information Yield models. We need to take a leaf out of the accounting and finance world to understand better the value and likelihood that our chosen investments will drive productivity and innovation.  If we do not, maybe we can let go our procurement officers since it might not matter what we spend our firm’s money on. It will be 50/50 odd that we will win in the market place.  I’d like to improve those odds. Don’t you?

Article by Andrew White, Gartner Blog Network

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