Alan Turing, Computers and Strategic Management

Alan Turing

Alan Turing developed many of the basic concepts for digital computers in the 1930s. In 1943, he came to the United States to exchange ideas and experiences with scientists and engineers at Bell Labs. He spent a great deal of time talking with Claude Shannon, the father of modern information theory, about their mutual interest in digital computers.

One day while having lunch in an AT&T executive dining room, Turing was describing his ideas about what a “thinking machine” could do.

"His high-pitched voice already stood out above the general murmur of the well-behaved junior executives grooming themselves for promotion within the Bell corporation. Then he was suddenly heard to say: 'No, I’m not interested in developing a powerful brain. All I’m after is just a mediocre brain, something like the President of the American Telephone and Telegraph Company.'"

(Andrew Hodges, Alan Turing: An Enigma, p. 251.)


Given the abysmal record of AT&T top management since the divestiture in 1984, even a mediocre brain, human or computer, would have been an improvement.

I don’t believe that large corporations in a global, rapidly-changing competitive environment can be managed in any meaningful way by humans. Failure rates are high, mediocre financial performance common. Integrated planning systems like those from SAP and Oracle are an intermediate step towards computer-based strategic management.

Strategic management might be based on computer simulations of different sets of short-run and long-run strategies. In an uncertain, often discontinuous external environment and with strategies interrelated in complicated ways, operational and financial outcomes are often highly uncertain. Computer simulations that could capture some of this complexity would be an improvement over current planning methods.

At a minimum, companies will be able to react faster to unexpected change and have a better idea of the financial consequences of changing different sets of strategies. This would be a source of competitive advantage.

Computer simulations compared to human top management strategists have the advantage of continuity. Managers come and go, often with large gaps in specific knowledge and implementing disruptive changes in strategy based on personal past experience. In contrast, computer simulations of an organization embody continuous knowledge and experience. As assumptions and forecasts are replaced by actual data, strategies can be revised in intervals closer to real time.

Simulations can also learn over long periods of time, even suggesting new strategies and probably chances of success.  A few companies are already using algorithms based on concepts from chaos and complexity theory to forecast and plan. Neural net models hold out the possibility that computer programs will be able to choose among competing strategies.

The drawback will be that simulations will, to some extent, be “black boxes” to human managers, producing unexpected results in unknowable ways. This will change the training and mentality of managers.

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