How do you measure the productivity of someone like a librarian? Is it based on the number of reference sessions they service per hour? How about a researcher? Do you measure their productivity by the number of requests they process? Information work productivity is not measured in terms of output, as easily as say, the output of chocolates on a factory assembly line. People in the IT world, however, are interested in doing just that with information work -- finding ways to measure it in terms of productivity.

The Information Work Productivity Council held the Information Work Productivity Forum (presentations available) to announce the work they're doing in developing metrics and industry benchmarks for information work productivity (IWP). As Steve Lohr points out in a NY Times article, "Technology and Worker Efficiency" (also available on IHT.com), this council is looking for ways to account for improvements in productivity and present methodologies and cases that demonstrate best practices for productivity. While the council is described as an independent group of companies and academics gathered to research this issue, there is no denying that IT manufacturers and service companies/consultancies involved are behind this effort to benefit directly from the product of the group's research. Being able to provide metrics for IWP will give them the justification for selling IT systems and the consulting services that will provide gains in information work productivity.

The problem of quantifying productivity in information work is an old one. Relatively new, however, is that information technology has been used to support information work. Technology manufacturers and consultants attempt to attribute significant gains in some IWP to IT, but cannot clearly identify where these relationships exist. Richard Waters writes in the Business Day article, "Technocrats keep mulling over how to measure productivity", that "in an economic downturn, buyers of technology were demanding more proof that their purchases would have a direct influence on productivity. The body of knowledge needed to make this case simply did not exist." The need to measure the output of information work was made most prevalent by Peter Drucker, who argued that it needed to be measured as much as any process in the industrialized world. But history tells us that measuring knowledge work output hasn't been as easy as measuring manufacturing productivity. A common thread in the presentations given at the Forum was that focus needs to be placed on information processes rather than on technologies when looking for measurable aspects of information work that could be identified as contributing to IWP. Their focus, therefore, has been on merely identifying measurable aspects of information work. Much of the R&D presentations attest to this focus. The obvious outcome will be to enable companies such as Microsoft, which spearheaded this effort, to use these metrics for providing ROI numbers and justification for selling IT services.

Perhaps secondary, but equally important, is to use this research to uncover the real value of information work and the various aspects that determine IWP and sucesss -- including social, cultural, political, procedural and organizational aspects of information and knowledge work -- and to relate to businesses how IWP is clearly related to organizational and economic health. While these aspects seem soft and immeasurable, they are clearly the targets for investigation. John Seely Brown, Xerox PARC Chief Scientist and author of "The Social Life of Information", pointed out in his presentation, that observing users using methodologies coming from anthropology might be the right approach. Letting the world give us the solutions is wiser than letting IT determine the way and forcing people into that. Brown thinks IT should fit into the social fabric. The impact of this type of thinking might be to leverage the diversity in the information ecology and to allow the formation of loosely coupled systems. Clearly, if the direction IT takes is to be driven by these organic elements, then we need to understand them.

Richard Waters echoes this sentiment in Business Day saying that, "[i]t takes more than simply buying the latest personal computer applications from Microsoft or a faster router from Cisco Systems to raise the output of office workers. Redesigning business processes to make the best use of the technology, and teaching people how to use it effectively, may be more time-consuming and costly."

Craig Samuel, Chief Knowledge Officer for HP Services, shows one way they are trying to understand knowledge workers' information sharing by using visualization to map where corporate knowledge and connections between knowledge workers reside. He adds, however, that "...most knowledge workers are wary of sharing what they know: they believe that knowledge is power." Hoarding knowledge may be sensible with proprietary or secure data. It's probably closer to the truth that in this economy, companies that have a knowledge culture, characterized by openness in sharing and which provide incentives for doing so, are likely to succeed in being innovation leaders. His point seems to be that encouraging cultural aspects that support knowledge sharing affects productivity. So how do we understand that in order to measure it?

Gary Bridge, Vice President of Cisco's Internet Business Solutions Group (IBSG), also echoes the theme of this council in saying that positive evironments in the world encourage productivity gains without necessitating tradeoffs/pain. On a macro level, he believes that a positive environment can be described as one that: fosters an environment of innovation, provides good public institutions (supported by IP protection, good courts and legal systems), maintains a superior educational system (with focus on math and science), and provides of widespread broadband access to all citizens. Driving the business with positive environments means also aligning the business strategy with the tech vision, getting cross functional leaders' support of this strategy, providing a clear definition of your core and context and then measuring sets of metrics (e.g. employee productivity and customer satisfaction) rather than individual metrics.

While some of the presentations -- all given by sponsors of the IWPC -- were laden with company and product advertisement in the guise of analysis of IWP issues, I found others quite valuable at raising issues that are relevant to the problem of understanding what was at issue when trying to measure IWP. While the corporate presenters alluded to the issues at a high level, the R&D presentation gave, perhaps, the most insight. Researchers indicated that they are not yet close to providing real and final metrics, but are only beginning to identify the common and relevant areas that might be measurable. Their research appears to be driven mainly by interviews and surveys. John Seely Brown's thoughts about where and how to look are relevant here, because they suggest a type of observation that is not based on elliciting data by asking questions about individual aspects of information work, it is concerned with taking a holistic approach to observing user processes. This approach, applied to various business processes means conducting a host of observational methodologies to find where productivity is affected. In the end, these observations can perhaps find ways of being supported by IT. Understanding how productivity is affected in information work clearly remains a difficult nut to crack, but by placing focus in the right places, this group seems most fit to do it.