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In Defense of the One Page Strategy

by Andrew White  |  April 14, 2017  |  Comments Off on In Defense of the One Page Strategy

What is strategy?

There are books galore on the topic.  I have presented many times on the topic too.  I have read widely (not enough, I admit) and continue to be amazed at both the use of the term, and the wide variations in the meaning associated with it.  The results of the lack clarity shows up in my every day work too.

I am currently reading an interesting collection of papers, packaged as “Strategy in the American War of Independence- A global approach” and one specific paper offers up an excellent view in the question.  The paper is “British Military Strategy” by Jeremy Black, MBE, professor of history at the university of Exeter.  He explains up front the usual interpretations of strategy and then offers a usable scope.

“…[T]here is the issue that strategy is usually discussed by military historians in terms of how wars are won.  That, however, is to misunderstand strategy or, rather, to operationalize it in terms of military activity when, in fact, the key to strategy is the political purposes that are pursued.  In short, strategy is a process of coping with problems and determining goals, and not one of meticulously examining and manipulating the details of the military plans and operations by which these goals are archived.”

This is brilliant since this sums up my life – and a number of other analysts in our team.  Once or twice a week I will be asked, like my peers, to review a clients’ strategy document.  It might be an IT strategy; it might be a data strategy; it might be a analytics or data and analytics strategy.  Invariably the document will be over 100 pages, typically nearer 200, and it will be a “meticulous examination and manipulation of the details of the plans and operations by which [these] goals are archived.”  In the majority of cases even the “goals” will be missing in that they will be stated in the form of IT activity (e.g. Implement a BI technology or solution; or migrate an ERP system) and not actually targeted at the “political outcome”, that is a measurable business outcome.

We have some good research on strategy.  Check out The Art of the One Page Strategy.  This is good advice. The challenge is not in the process, as outlined in this note, but in the definition and scope of “IT strategy”.

So we really have two issues here:

  • What is strategy?
  • Is data and analytics a strategy independently of IT (strategy)?

As Jeremy Black says, “strategy is a process of coping with problems and determining goals“.  The outcome should be guardrails that everyone can use to solve problems as they arise in the prosecution of the goals; and the goals need to express a business outcome.

So what of ‘data and analytics’ versus IT?  What of a data strategy versus an analytics strategy?  What of ‘data analytics’ – another term I hear of, thankfully infrequently.

The challenge here is that IT strategy tends to be different things for different organizations. For some firms it is a business driven process that includes information and technology.  For others it is a technology-focused thing, with very little mention of information (the “I” in IT).  Unfortunately the latter situation is all too common and so a need for a direct connection between business and outcome and the data and/or analytic needed has to be forged.  Maybe it would be better if we stopped saying “IT” and instead called out “I&T”.  See How to Create an Information and Technology Strategic Plan.

But we should be clear:

  • Data is used in several uses-cases; analytics and BI is one.  Compliance and operations or business apps is another.  Analytics and operations remain separate in most firms and will do so for many years.  As such a “data strategy” ought to be focused on any and all uses of data; and not be focused on “data managment” which tends to fall back on technology and infrastructure and lose sight of “why” data in the first palace.
  • Analytics is also misunderstood.  It is not meant to be achieved with a dashboard or a report or a piece of insight.  It was meant to focus on decision making.  But since data was missing, since feedback and business process were separate, analytics for most is today really about metrics and KPIs and insight via a cute dashboard.  So an analytics strategy really should not exist any longer; it should be a “data and analytics” strategy and the focus is not actually data or analytics: it should be about decision making and how decision making in context of a process and an outcome can improve same.
  • “Data analytics” is a meaningless term.  It might be short hand for “data for analytics” but it does not mean “data and analytics” since it does not make sense.

So we need to rethink our strategy.  We need to think of outcomes; we need to think what is in scope, and by definition what is out of scope, and we need a process (not just a deliverable) to prioritize goals.  This is not hard to do; it is not a hard scale.  That is, unless you avoid focusing on real business outcomes.

Jeremy Blacks’ paper nicely compares Britain’s goals in the War of Independence as being quite different to many other contemporary wars.  It’s strategy was, he says, about pacification.  It was not meant to be about a war of elimination.  But such goals were relatively new for such a scale and distance as this War was fought.  Of course, we all know how this War played out.  Let’s hope we can all write fascinating papers on the results of our effective, business relevant, data and analytics strategies.

If you are interested, we just updated our Strategic Roadmap for Enterprise Information Management.  In this note we define (a one page data and analytics, separate from technology) strategy in the context of a vision and the overall program that would lead, eventually, to the “meticulous examination and manipulation of the details of the [military] plans and operations by which these goals are archived”.  Effectively in this modern era we could rename EIM to “Data and Analytics Management” or maybe “Enterprise Data and Analytics program”.  The focus of EIM is clear – all uses of data including any analytics initiatives.  But what that means to your organization is what makes EIM unique.

Category: data-and-analytics  enterprise-information-management  strategy  

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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