Byting Your Knowledge Workers: The Next Productivity Revolution
Beware, knowledge workers: Your halcyon days are numbered. You're in the process of being shaped into bits and bytes, numbers and equations, and your work lives will never be the same. Your organizations' productivity, however, may well spike up even as you're digitized.
At least, that's one of the arguments presented in The Numerati, a new book by Stephen Baker (2008).
For years now, researchers have been studying complex systems and trying to model them on computers. In some cases, they've even tried to model human beings. The Marines, for example, developed a simulation program called Project Albert, which simulates not only battlefield conditions but, through agent-based models, certain human attributes, from the skill levels of troops to their determination and trust.
Today, it's employees who are being modeled. Some mathematicians and computer scientists - whom Baker designates the "Numerati" - are striving to take digital data from the workplace and turn it into mathematical representations of employees themselves. Baker points to work being done at IBM, where a team of experts are trying to make sense out of reams of employee data, from resumes to cell phone records to e-mails and project records (virtually everything except personnel file information). "Why would companies intrude like this?" Baker asks. "Very simply, to boost our productivity" (p. 19).
While the execution of this ambitious idea is difficult, the idea behind it is relatively simple: If companies can digitally monitor and then model employees and their social networks, then they'll be much better at managing those workers in a way that maximizes productivity. Organizations should, for example, be better able to select team members who will work well (and under budget) with one another to successfully complete specific projects. They should also get better at determining which managers most successfully supervise which workers and knowing where their star employees are most effectively utilized. Some experts even believe that this trend will help organizations break knowledge workers' time or tasks into discrete parts. In theory, these parts can be efficiently strung together to boost the productivity of white-collar workers, much as the movements of assembly-line workers were measured and maximized for optimum productivity in the industrial revolution.
Baker's vision of the future workplace is, of course, both compelling and disturbing. It's compelling because it outlines some potentially rigorous ways of evaluating and enhancing knowledge workers' productivity. In many ways, it's a natural extrapolation of existing trends and technologies. Just as companies such as eHarmony claim to be able to bring together compatible people for the purpose of romantic relationships, employers may be able to match up colleagues for the purpose of strong work relationships. Or, just as websites such Expedia make it simpler for people to make cost-effective travel arrangements, mathematically based modeling systems might make it simpler for managers to make cost-effective staffing or relocation decisions.
But then there are those disturbing elements. The data that the Numerati use to measure and predict will probably be based on the close tracking of virtually everything people do while at work. Privacy becomes nil. All that web-surfing, solitaire-playing, pool-betting, YouTube-watching, friend-IMing behavior is both monitored and, ultimately, placed into some calculation. If you thought your job was stressful today, think about what the digital fishbowl of tomorrow could be like.
Another disturbing element is that, quite simply, people aren't equations. Yes, the keepers of Web surfing data can find out that a person who does one thing (let's say, reads a certain book) is more likely than average to do something else (let's say, buy a certain product), but it's all about profiles and correlations. And, as any researcher knows, correlation is not causation. Just because a person is statistically more likely than average to do something doesn't mean he or she will actually do it. If your employer is making judgments about your career based on statistical profiles, then you might be getting digitally pigeon-holed without even knowing it.
A third and related potential problem is that this is all new and things could go badly wrong. When Baker writes that planners want to "turn us into something that, like financial instruments, can be measured over time," it sends shivers up the spine (p. 24). After all, in light of our current financial crisis, turning people into financial-instrument-like abstractions seems like a dangerous notion - one that could have business leaders arguing that the "computer made me do it" when they wind up making lousy, costly management decisions.
i4cp Recommendation: Employers should keep an eye on these developments. Social network analysis has been around for some time and is already being turned into products and services. The further "digitalization" of workers is more of a work-in-progress, but it could potentially help businesses get closer to calculating the return on investment (ROI) on individual employees. This could help managers create more effective and fair compensation packages, for example, or could help them more accurately predict the ROI of development programs.
But employers should also beware of putting too much faith too quickly into such modeling. In the future, there will likely be many companies selling their worker-modeling wares to employers, promising high productivity returns. If the past is prologue, then some products will be better than others and none will be perfect. Organizations will need to become sophisticated buyers or builders of such products. And HR professionals will need to get used to the idea of becoming experts in "virtual human resources."
Documents used in the preparation of this TrendWatcher include the following:
At least, that's one of the arguments presented in The Numerati, a new book by Stephen Baker (2008).
For years now, researchers have been studying complex systems and trying to model them on computers. In some cases, they've even tried to model human beings. The Marines, for example, developed a simulation program called Project Albert, which simulates not only battlefield conditions but, through agent-based models, certain human attributes, from the skill levels of troops to their determination and trust.
Today, it's employees who are being modeled. Some mathematicians and computer scientists - whom Baker designates the "Numerati" - are striving to take digital data from the workplace and turn it into mathematical representations of employees themselves. Baker points to work being done at IBM, where a team of experts are trying to make sense out of reams of employee data, from resumes to cell phone records to e-mails and project records (virtually everything except personnel file information). "Why would companies intrude like this?" Baker asks. "Very simply, to boost our productivity" (p. 19).
While the execution of this ambitious idea is difficult, the idea behind it is relatively simple: If companies can digitally monitor and then model employees and their social networks, then they'll be much better at managing those workers in a way that maximizes productivity. Organizations should, for example, be better able to select team members who will work well (and under budget) with one another to successfully complete specific projects. They should also get better at determining which managers most successfully supervise which workers and knowing where their star employees are most effectively utilized. Some experts even believe that this trend will help organizations break knowledge workers' time or tasks into discrete parts. In theory, these parts can be efficiently strung together to boost the productivity of white-collar workers, much as the movements of assembly-line workers were measured and maximized for optimum productivity in the industrial revolution.
Baker's vision of the future workplace is, of course, both compelling and disturbing. It's compelling because it outlines some potentially rigorous ways of evaluating and enhancing knowledge workers' productivity. In many ways, it's a natural extrapolation of existing trends and technologies. Just as companies such as eHarmony claim to be able to bring together compatible people for the purpose of romantic relationships, employers may be able to match up colleagues for the purpose of strong work relationships. Or, just as websites such Expedia make it simpler for people to make cost-effective travel arrangements, mathematically based modeling systems might make it simpler for managers to make cost-effective staffing or relocation decisions.
But then there are those disturbing elements. The data that the Numerati use to measure and predict will probably be based on the close tracking of virtually everything people do while at work. Privacy becomes nil. All that web-surfing, solitaire-playing, pool-betting, YouTube-watching, friend-IMing behavior is both monitored and, ultimately, placed into some calculation. If you thought your job was stressful today, think about what the digital fishbowl of tomorrow could be like.
Another disturbing element is that, quite simply, people aren't equations. Yes, the keepers of Web surfing data can find out that a person who does one thing (let's say, reads a certain book) is more likely than average to do something else (let's say, buy a certain product), but it's all about profiles and correlations. And, as any researcher knows, correlation is not causation. Just because a person is statistically more likely than average to do something doesn't mean he or she will actually do it. If your employer is making judgments about your career based on statistical profiles, then you might be getting digitally pigeon-holed without even knowing it.
A third and related potential problem is that this is all new and things could go badly wrong. When Baker writes that planners want to "turn us into something that, like financial instruments, can be measured over time," it sends shivers up the spine (p. 24). After all, in light of our current financial crisis, turning people into financial-instrument-like abstractions seems like a dangerous notion - one that could have business leaders arguing that the "computer made me do it" when they wind up making lousy, costly management decisions.
i4cp Recommendation: Employers should keep an eye on these developments. Social network analysis has been around for some time and is already being turned into products and services. The further "digitalization" of workers is more of a work-in-progress, but it could potentially help businesses get closer to calculating the return on investment (ROI) on individual employees. This could help managers create more effective and fair compensation packages, for example, or could help them more accurately predict the ROI of development programs.
But employers should also beware of putting too much faith too quickly into such modeling. In the future, there will likely be many companies selling their worker-modeling wares to employers, promising high productivity returns. If the past is prologue, then some products will be better than others and none will be perfect. Organizations will need to become sophisticated buyers or builders of such products. And HR professionals will need to get used to the idea of becoming experts in "virtual human resources."
Documents used in the preparation of this TrendWatcher include the following:
- Baker, Stephen (2008). The Numerati. New York: Houghton Mifflin Company.