Is specialism killing your business?

Over the millennia, specialism has served us well. Human progress and economic wealth have been built on increasing division of labor and the development of professional competencies.

But specialism also has downsides. Those ‘professions’ become protective of themselves and operate as barriers to change. ‘Specialists’ like to think they are ‘special’ – they lose context, they become self-important. And these traits soon become sources of cost, delay and barriers to change.

Pro’s and Con’s

Specialism is attractive because it tends to link to higher wages and greater status and power. So people seek to position themselves as specialist and to form tribes with like-minded individuals. On one level, that of research and ‘good practice’, this is beneficial. When it evolves to constraining others, it is not.

Today, we have myriads of specialists. Professions like law, medicine and accounting have splintered into hundreds of sub-areas of expertise. Other job roles have followed suit. We have the theories of Adam Smith operating on steroids.

And the result? For many organizations, it is virtual inertia and incompetence. It becomes almost impossible to build consensus. Expertise rules, at the expense of balance and good judgment. Decisions increasingly flow to the top due to the incapability at lower levels to reach or enforce agreement. Business and government is becoming overwhelmed by the complexity of specialism.

A new approach

The answer, of course, is not to dismiss specialist knowledge, but to deploy it in new and different ways. Much current specialism must be automated. In the same way as machines took the jobs of weavers, blacksmiths, joiners and turners, they will now take those of many specialists. History shows that we move through cycles during which power groups emerge, gain control and then implode under the forces of progress.

Artificial intelligence systems are making specialist knowledge far more accessible and will make it also more reliable and fact-based. But having rapid and immediate access is not the same as interpreting and, more important, collating all that knowledge to reach an informed and balanced decision. And that’s why commercial judgment is becoming increasingly important – an ability to synthesize and reconcile data that may often be contradictory or in conflict and to develop a viable solution.

Mechanization was highly disruptive, yet ultimately drove improvement in social wealth and welfare. It also required a new breed of mechanics to manage it. Automation will be the same. And just as those who failed to mechanize or to hire mechanics went out of business, so will those who are too slow to adopt automation or to build the skills to manage its output.