Tuesday, September 27, 2005
enterprise automation and human productivity
Nearly everyone's job is increasingly defined by software, whether you work in a call center, as a currency trader, or a graphic designer in an ad agency managing a job workflow. If you use computers to work, sooner or later you will be drawn into a system to manage workflows, and these systems will be "rationalized" to improve productivity. Don't believe that because you use your brain for a living, or need to exercise creativity to do your work, that you are exempt for the march of enterprise automation.
Our inability to understand and measure the productivity of computer workflows is one of the most pressing issues facing modern society. Most of us use computers in some way to produce services of some sort. The logic of business to reduce costs means that corporations are always seeking ways to do more with less. Automation is the holy grail of cost reduction, and new applications to automate tasks involving computers are appearing all the time. What nearly all these applications promise is that work can be done faster, with fewer people. Often these applications do increase throughput, but it is not always the case that they improve productivity.
Enterprise automation -- using software to automate services across an enterprise -- very often repeats the same problems that accompanied industrial mass production automation. Before the development of lean production, manufacturers focused on almost exclusively on increasing throughput (output per work and/or per hour). They looked for ways to increase how many autos would be produced in an hour, and how to reduce the number of workers needed to produce those autos. The solution was to standardize production of common products based on interchangeable parts. This is exactly the approach currently used by enterprise applications.
In the case of auto production, the mass production system collapsed in the late 1970s. It proved unable to cope with the increasingly diverse demands of consumers (users). And the relentless automation caused workers to stretch beyond the limits of human capabilities. Harried workers did not notice quality problems when they were focused entirely on meeting production quotas. They saw the demands of the production system as dumbing down their work. They burned out.
As the case of auto production automation illustrates, productivity is about more than just getting faster, and using fewer people. Unless and until an enterprise can eliminate using people altogether -- more often a fantasy than a reality that will ever happen -- it needs to keep the cognitive and emotional needs of workers in central perspective when attempting to automate. People need to be engaged mentally in their work, and in control of the pacing and decisions. Without these, quality suffers, and productivity is elusive. The example of lean production in manufacturing, which uses workers to perform flexible tasks, and lets workers define tasks themselves, points to how the future of enterprise software needs to evolve.
Our inability to understand and measure the productivity of computer workflows is one of the most pressing issues facing modern society. Most of us use computers in some way to produce services of some sort. The logic of business to reduce costs means that corporations are always seeking ways to do more with less. Automation is the holy grail of cost reduction, and new applications to automate tasks involving computers are appearing all the time. What nearly all these applications promise is that work can be done faster, with fewer people. Often these applications do increase throughput, but it is not always the case that they improve productivity.
Enterprise automation -- using software to automate services across an enterprise -- very often repeats the same problems that accompanied industrial mass production automation. Before the development of lean production, manufacturers focused on almost exclusively on increasing throughput (output per work and/or per hour). They looked for ways to increase how many autos would be produced in an hour, and how to reduce the number of workers needed to produce those autos. The solution was to standardize production of common products based on interchangeable parts. This is exactly the approach currently used by enterprise applications.
In the case of auto production, the mass production system collapsed in the late 1970s. It proved unable to cope with the increasingly diverse demands of consumers (users). And the relentless automation caused workers to stretch beyond the limits of human capabilities. Harried workers did not notice quality problems when they were focused entirely on meeting production quotas. They saw the demands of the production system as dumbing down their work. They burned out.
As the case of auto production automation illustrates, productivity is about more than just getting faster, and using fewer people. Unless and until an enterprise can eliminate using people altogether -- more often a fantasy than a reality that will ever happen -- it needs to keep the cognitive and emotional needs of workers in central perspective when attempting to automate. People need to be engaged mentally in their work, and in control of the pacing and decisions. Without these, quality suffers, and productivity is elusive. The example of lean production in manufacturing, which uses workers to perform flexible tasks, and lets workers define tasks themselves, points to how the future of enterprise software needs to evolve.
Link to this article. posted by Michael Andrews @ 8:39 PM 
