Why Computers Didn’t Improve Productivity
“You can see computers everywhere but in the productivity statistics,” wrote Nobel-Prize-winning economist Robert Solow in 1987. His dictum spawned several decades of economic research aimed at solving the mystery that has become known as the ‘Solow Paradox’: massive investment in computers but no net gain in productivity.
In the 2010s, ‘digital transformation’ also turned into a meaningless buzzword, as almost every big company attempted one but most failed to get the expected gains. The benefits obtained from successful big data projects were also outweighed by mostly disappointments, generating renewed interest in the Solow Paradox.
A key to solving the Solow Paradox lies in recognizing that bureaucracy and computers are a marriage made in hell: computers generate a great deal more work, but not necessarily more useful work. In a bureaucracy, there is often no net gain. Until you tame bureaucracy, with more agile management, computers often make things worse.
The usual first response to encountering the Solow Paradox is disbelief: “If I have to write a few emails so that I don’t have to use a carrier pigeon, sign me up!”
But in a bureaucracy, the story of those few emails usually doesn’t end there. So, you send your few emails, and then you soon get email replies and comments. Now, you have to write more emails in reply to those emails, which are then sent up the hierarchy and to a chain of full-time reviewers, who each make a comment to show that they are useful.
So now you have to reconcile all these comments. And maybe you have to send more emails to explain to each reviewer how their particular comment has been dealt with, and you may get replies to those emails. And so on. What began as a few quick emails has turned into days of work by multiple people all over the organization. In a bureaucracy, computers help work spread like a virus.
Digital computing began differently, with a big success. The first digital computer, Colossus, was developed by British intelligence in the 1940s. It deciphered encrypted messages between Hitler and his generals: it helped win the Second World War, as David Price explains in his new book, Geniuses at War: Bletchley Park, Colossus, and the Dawn of the Digital Age(Knopf, June 2021.
Similar one-off triumphs were apparent with NASA’s moon landing in 1969, and with IBM’s computer, Watson, that defeated world-champion chess player Gary Kasparov and won the game show, Jeopardy. Yet widespread economic gains from computing have been harder to find.
When mainframe computer systems began appearing commercially in the 1950s, big firms were thrilled. Suddenly, in a single system, top managers could for the first time see the results of massive amounts of data. Computers were used by firms for critical applications like bulk data processing, enterprise resource planning, large-scale transaction processing, and industry and consumer statistics.
Mainframe computers were expensive and required significant expertise. The computers were physically huge and needed special cooling systems. Access to computing time was strictly rationed. The systems themselves were monolithic and could not interact with other systems. The systems were also difficult to adjust or re-program.
By the 1990s, huge sums of money were being lost in mainframe computing because the work of software development was always late, over budget, and plagued by quality problems. Some big projects were never finished at all. Software programmers were seen as culprits and were punished.
