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Software Infrastructure for Business Value

Neil Macehiter

On GPTs, organisational complements - management's role in effective IT adoption

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In a recent post Nicholas Carr calls out a recent Harvard Business Review article (currently freely accessible) by Andrew McAfee, whose work I highlighted in August. In the article, McAfee sets out to help managers grapple with the challenges of technology adoption in the face of an abundance of technologies, a chequered history of IT project success, a more general questioning (thanks to Carr) as to whether IT really matters and whether organisations should actually be doing IT themselves. I certainly found myself agreeing with a lot of the context setting from McAfee.

McAfee goes on to explain that:

technology projects are increasingly becoming managerial challenges rather than technical ones. What’s more, a well-run IT department isn’t enough; line managers have important responsibilities in implementing these projects

Again, difficult to refute. IT and business are so intimately intertwined these days and the focus of IT investment is shifting away from the automation of non-differentiating business processes in the back office and towards those processes which do differentiate: the ones which are often ad-hoc, dynamic and collaborative in nature. Unless the business is involved in identifying the right technology and then facilitating its adoption, the chances of success are limited. Whilst the business knows this, the problem is

they’re not clear where, when, and how they should get involved

Why? According to McAfee it's because managers lack a model for the role of IT, its organisational implications and what they should do to help it succeed. Our research here at MWD is certainly consistent with this. So, where does this model come from?

That's where GPTs - General Purpose Technologies - and organisational complements come into play. GPTs are

innovations so important that they cause jumps in an economy’s normal march of progress

with IT following on from earlier examples such as electric power, the transistor, and the laser. Organisational complements are changes in the ways that organisations do things which multiply the effects of GPTs. In the case of IT, these complements are better-skilled workers, improved teamwork, redesigned processes and new decision rights. McAfee believes that IT is different from other GPTs in terms of the relationships to these different complements. He believes there are three categories of IT which vary in terms of the importance of the different organisational complements:

- Function IT - assists with the execution of discrete tasks and doesn't bring complements with it e.g. spreadsheets, CAD
- Network IT - facilitates communication and collaboration between individuals and lets complements emerge e.g. email, blogs, wikis
- Enterprise IT - specifies and implements business processes and imposes complements e.g. ERP, CRM, SCM

One could certainly argue with the classification since different technologies may fall into different categories dependent on the business process but overall it makes a lot of sense to me - it's recognised, for example, that big enterprise applications often require changes to business processes and governance approaches.

This classification forms the basis of the missing model, since it provides managers with a way of thinking about the capabilities they need - task execution, communication etc - during technology selection; the complements they need to put in place to facilitate adoption; and the optimisation of complements they need to perform to maximise the return from technology. The article provides some useful case study-based examples of the model in use.

I think McAfee has done a great job of simplying things or, as Carr puts it:

in adding precision to the language we use to discuss complex subjects. It helps us get beyond big, ill-defined generalizations.

I, like Carr, think the classification of IT is too simplistic (but then it is a model!):

It can prevent us from seeing how categories blend together. By drawing bright lines between things, it can give the illusion that those things are more distinct than they really are. I sense that problem here (even while granting the usefulness of McAfee's categorization). Take the identification of CRM as an enterprise information technology. Isn't that assumption exactly what doomed so many big CRM projects? The projects lost sight of the fact that CRM is as much a functional tool, a tool that helps individual employees, like salespeople, do their work better, as an enterprise system. CRM, in other words, is as much FIT as EIT. And, in fact, there's a lot of NIT in it as well.

However, I disagree with Carr's conclusion:

McAfee's article may not be quite as clarifying as it is intended to be.

Had McAfee had stopped at the classification then I would have agreed. It's the marrying of the technology classification to the organisational implications where McAfee clarifies things, since it helps to facilitate a dialogue between business and IT in a language which both sides understand. Equally importantly, it moves beyond the technology selection phase to outline the role of the business during adoption and subsequent exploitation.

Neil Ward-Dutton, founder and Research Director of MWD Advisors offers his perspective on key software infrastructure issues, IT-business alignment and related things.

Neil Ward-Dutton

Neil Ward-Dutton is a co-founder of and Research Director at Macehiter Ward-Dutton, View more


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