Minds, machines and business models 2

Published by Paul Brasington in Good work · Friday 10 Jan 2014 · 5:00
Tags: Neuroscience, business, structures

Since the industrial age, the machine has been the model for business (explicitly in the work of the late 19th century management theorist Frederick Winslow Taylor, whose thinking, though hardly fashionable or explicitly embraced, still dominates management ideas).

That’s probably because efficiency is directly correlated with profit, and making a business work like a machine seemed a good way of lowering costs and achieving consistent output.

The machines of the industrial age were large, mechanical, their processes sequential. Bryan Appleyard notes the significance of Babbage’s Difference Engine (a computational device) as the first machine with an abstract rather than tangible output, heralding a new and very different machine age, the one in which we’re now living. But coming from the first machine age we constructed organisations around the idea that managers should have as much control as possible, the scope for deviation written out of the program.

The very best, obvious way to achieve this was to replace human work with machines. This has duly happened, with ever more sophisticated robots in recent years eliminating the need for human labour even in tasks that once called for more advanced human skills. We’ve put machines into places that we’d reasonably expect to be about human interaction, whether in the ATMs that took over many common banking activities, or the automated call answering systems that pretend to be a first level of customer responsiveness.

Control and creativity

Machines bring their own management tasks: they have to be maintained, and upgraded in line with technology advances. But they do simplify, reducing the possible variables between management intention and output to the market (which itself is only okay if you see your relationship with the market as essentially one-way). This simplicity became all the more attractive in a world that was rapidly becoming more complex, as communications technology made globalisation possible. Businesses themselves had evolved into more complex structures, expanding their product ranges, their geographical reach, and the sophistication of their support functions, from human resources through logistics to marketing.

For a while this evolution seemed the most obvious means for managers to keep control of all the different elements that the business required, but as the functional complexity multiplied management theorists (and practitioners) began to talk of “core competencies”.

A different model quickly emerged, in which managers define their requirements, and then contract out to specialist suppliers to meet those requirements. On the face of it this model multiplies profit centres in the supply chain, and so would push costs up. In reality it rests on the assumption that specialist operators will be better at identifying and removing cost in their operations without compromising quality. Crucially it allows managers to shorten lines of accountability, restoring a sense of control in an ever more challenging world.

But this desire for control is only part of the story. In the last twenty years we have found ourselves moving into a different kind of machine age, driven by information technology (if the importance of the Difference Engine is that it’s the first machine with an abstract output, we’re only just beginning to experience how transformational this could be). This shift away from the mechanical demands a rethink of the machine model for those who remain in the workplace.

Machines are generally a poor source of competitive advantage. Early adopters of new technology may gain a useful early lead, but others will soon catch up (machines are relatively easy to replicate). This probably explains why in the last fifteen years or so management theory has put an increasing premium on creativity on business. What really defines a business is its culture (not what it makes). It seemed that at some level we no longer wanted the organisation to work like a machine, but to have a culture in which people could be spontaneous, where they routinely thought “out of the box”, a culture that was entrepreneurial and nurtured innovation and responsiveness.

The left brain world view doesn’t yield this ground easily. Managers have sometimes tried to make this kind of human creativity machine-like, following the idea that “knowledge management” could be an IT function. The American consultant and writer Don Tapscott sums up the folly of this (and suggests a necessary alternative).

“Knowledge management has failed. We had this view that knowledge is a finite asset, it’s inside the boundaries of companies, and you manage it by containerizing it.

“So, if we can get all of Jessica’s knowledge into this container, or computer system, then when she leaves the company we’ll still have Jessica, or we can get to Jessica in this container. And this was, of course, illusory, because knowledge is an infinite resource. The most important knowledge is not inside the boundaries of a company. You don’t achieve it through containerization, you achieve it through collaboration.”

(in an interview with McKinsey Quarterly January 2013)

It’s true that Tapscott is still thinking about technology (he is urging businesses to investigate and adopt social media), but that’s because he understands that technology can help us do human things more effectively, rather than working as a mechanised substitute for those activities (which are valuable exactly because they are unpredictable).

The crucial point here, and one which has attracted surprisingly little comment, is that there is a big contradiction between this ambition to foster creativity, and the prevailing, fundamental assumptions about the machine-like things managers should be doing to make a business run effectively. Something has to give.

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