- Move from “Job” to “Project” to move skills easily and efficiently
- Code-ify learnings from “Projects” so an algorithm can be applied next time
“Companies everywhere struggle with the management of knowledge workers. They compete fiercely to find and retain the best talent, often accumulating thousands of managers in the process. For a while this is fine, but inevitably, usually when economic conditions turn less favorable, they realize that these expensive workers are not as productive as hoped, and in an effort to manage costs they lay off a large swath of them. Soon after, though, they’re out recruiting again.
Why do these companies struggle so much with what ought to be their most productive assets? The answer, I think, is rooted in a profound misunderstanding—despite decades of research and debate about the knowledge economy—of how knowledge work does and does not differ from the manual work we have come to understand so well. In particular, most companies make two big mistakes in managing knowledge workers. The first is to think that they should structure this workforce as they do a manual workforce—with each employee doing the same tasks day in and day out. The second (which derives in part from the first) is to assume that knowledge is necessarily bundled with the workers and, unlike manual labor, can’t readily be codified and transferred to others.
At desks and in meeting rooms, every day of their working lives, knowledge workers hammer away in decision factories. Their raw materials are data, either from their own information systems or from outside providers. They produce lots of memos and presentations full of analyses and recommendations. They engage in production processes—called meetings—that convert this work to finished goods in the form of decisions. Or they generate rework: another meeting to reach the decision that wasn’t made in the first meeting. And they participate in post-production services: following up on decisions.
Decision factories have arguably become corporate America’s largest cost, even at big manufacturers like P&G, because the salaries of these factory workers far exceed those of workers in physical factories. In pursuit of the twin goals of efficiency and growth, companies in the latter half of the 20th century spent ever-greater amounts on R&D, branding, information technology systems, and automation—all investments that necessitated hiring an army of knowledge workers.
One way to get a sense of the magnitude of knowledge workers’ rise in the modern workforce is to look at changes in cost of goods sold (COGS) and selling, general, and administrative expenses (SG&A) at large companies. COGS and SG&A spending—by far the largest cost items in any company—serve as a reasonably good proxy for blue-collar and white-collar workers respectively, because the costs of the former are embedded in COGS and those of the latter make up the majority of SG&A.
The Dow Jones 30 (DJ30) has always exemplified American big business: In 2012 its members had revenue of more than $3 trillion and approximately 8.5 million employees. In 1972, as this graph shows, the DJ30 aggregate spending on COGS was 72% of revenue and on SG&A was 13%. In the late 1970s SG&A began to grow as a proportion of revenue. In the following decade COGS began to fall. By 2012 their relative proportion had shifted dramatically, with COGS down to 51% and SG&A up to 24%.
The key to breaking the binge-and-purge cycle in knowledge work is to use the project rather than the job as the organizing principle. In this model, full-time employees are seen not as tethered to certain specified functions but as flowing to projects where their capabilities are needed. Companies can cut the numbers of knowledge workers they have on the payroll because they can move the ones they have around. The result is a lot less downtime and make-work.
This characterization of knowledge work is gaining traction among management thinkers. In “The Rise of the Supertemp” (HBR May 2012), Jody Greenstone Miller and Matt Miller describe an emerging class of managers who are focused on short-term, high-value-added, knowledge-based projects. Similarly, the Silicon Valley legend Reid Hoffman, with Ben Casnocha and Chris Yeh, suggests in “Tours of Duty: The New Employer-Employee Compact” (HBR June 2013) that organizing knowledge workers’ employment into time-bound “tours of duty” can help companies retain these workers and keep them happy. And although actually organizing knowledge work around projects may seem a radical idea in mainstream business, it is very familiar to professional services firms, some of which have become as large as manufacturing corporations. “