In 1998, when we wrote about what knowledge managers do, the focus of the CKO was knowledge generation and sharing, making information available over the Internet, and creating enterprise organization schemes. Today, the focus is shifting away from content, access, and sharing toward performance and getting results — e.g. reducing the cost of health care, making government services more effective, designing breakthrough products. This requires increasing the productivity of knowledge workers, the 25 to 50% of employees in advanced economies that find, create, package, distribute and apply knowledge. In this article we look at how the new focus is changing the complexion of information services and describe a support system for attaining it — for ourselves, our colleagues, and our organizations.

Productivity, performance, and results
We are beginning to get a handle on the downstream side of knowledge management — identifying content and experts, creating and organizing repositories for them, assembling information resources into a one-stop-shop called a portal. Now we are turning more attention to the upstream side — increasing the productivity of individual knowledge workers, applying knowledge to solve new challenges, leveraging intellectual assets across the information supply chain.

This time it's about people and process, not about technology. Some observers suggest that we already have too much technology for organizations to digest. It's not about building business cases, conducting usability studies, creating taxonomies, or finding a more efficient search engine. It's about finding key business problems and figuring out how to deploy all information assets — data, published material, technology, people, standards, and processes. The goal is to achieve measurable results, such as reducing the number of deaths from a certain disease, reducing the number of accidents in a manufacturing plant, or increasing the number of profitable new products.

You don't have to build a business case, because in defining the problem you have articulated the need and the appropriate metric. You don't have to conduct usability studies because the key players, not the IT function, drive the process, help design the solution, and test the prototype. You don't create taxonomies from content alone or select new a new search engine simply by conducting a vendor "bake-off." Instead, you select and customize navigation tools to fit the specific situation. Here are some examples of what we mean:

1. Due in part to Michael Milkin's philanthropy, the prostate cancer death rate has declined more than four times that of overall cancer rates during the past decade. He did it by drastically cutting the wait time for grant money, flooding the field with fast cash, funding therapy-driven ideas rather than basic science, holding researchers he funds accountable for results, and demanding collaboration across disciplines and among institutions, private industry, and academia).

For info pros, this means finding or attracting the best researchers, compiling and analyzing test results, promoting and facilitating collaboration.

2. Partners Health System, an organization of Harvard teaching hospitals in the Boston area, reduced "adverse drug events" (mistakes made by doctors in prescribing drugs) by 55%. It has also resulted in fewer medical errors, fewer malpractice suits, and much faster response in introducing new knowledge to doctors. The key to achieving these results is an automated system for ordering drugs and tests that integrates data from separate data stores — patient records, doctor referrals, online repositories of journal articles and drug databases, and formularies of approved drugs.

For info pros, this means integrating data and information from multiple different systems, normalizing metadata, designing and implementing business rules, and making information available in the right context.

3. In the early 1980s, a defense industry contractor was competing to produce tactical missiles. Each competitor tested six working prototypes; none were satisfactory. A scientist, who was not an official member of the project team, called the primary participants to a meeting. He proposed detailed changes that he had worked out by himself during just one week of concentrated effort. Without notes, for several hours, he walked his colleague through the redesign, explaining all the software, wiring and hardware changes that would be required to win the competition. His changes were supported and the company won the contract.

For info pros, this means identifying people with critical business knowledge and creating a mentoring system to make it possible to transfer their know-how through practice, observation, problem solving, and experimentation.

10 new realities
Since we wrote "Upstream knowledge management," we and our members have had to adapt to 10 new realities:

1. Open source software. The success of the open source movement not only means new software and a new way to acquire it, it also underscores an alternative development paradigm — global collaboration fueled by the pride of individuals instead of corporate or venture capital funding. Will this paradigm work in a corporate environment? If so, how do you promote and facilitate it? If not, how do you form alliances with external practitioners?

2. XML-aware databases and applications. XML is doing for data exchange among computer programs what the Internet did for data exchange via e-mail. XML is forcing people to develop "schemas" (models of how data is organized) and work together to develop standard schemas for different uses. That means helping business units model their data and processes, identify and create metadata, and select an appropriate architecture for data integration.

3. Personal publishing tools, such as wikis and blogs. Wikis, software for collaborative authoring and editing, show that the open source development model would work not only for software but also for content. Blogs, personal publishing software, not only make it easy for individuals to create their own daily newspapers but also to publicize and syndicate their publications. But how do you aggregate relevant material, assure consistent quality, and make content findable?

4. Mandatory regulations for financial and legal disclosure. The Sarbanes-Oxley Act has forced companies to adopt data management strategies that are both more comprehensive and cost effective. Consistent metadata across all systems — databases, documents, and e-mail — is key to this effort.

5. Voluntary reporting for corporate responsibility. A growing number of global corporations are adopting voluntary standards for reporting the impact of their operations on the environment, society, and the economic system. This forces companies to gather and analyze data in new ways and to tailor reporting to new stakeholder groups.

6. A global market for knowledge work. When highly educated people in India and China can compile business intelligence, design new products, and tutor U. S. school kids in English, it casts a spotlight on the productivity of our own knowledge workers. What tasks can our people do better than their peers in Asia? What should we be doing to help companies improve the information productivity of their knowledge workers? What should we be doing to protect our own livelihoods?

7. The network as computing platform. Instead of buying a new program to do a specific computing task, why not use a service available on the Internet? The success of services like Google's Gmail and Salesforce.com have proven to be viable alternatives to proprietary software packages. What are the pros and cons of delivering information services on a network platform as opposed to Windows, Linux, or the Apple operating system?

8. Availability of information "widgets." Innovative vendors are using a new collection of standards called Web Services to provide snippets of code that allow non-programmers to create new services. For example, you can take rental notices from one Web site and match them with Google maps to show prospective renters where a property is located. Should we be pressing software vendors for more of these widgets? Is it feasible to create a kind of Home Depot stocked with information widgets along with the expertise to help business units select and use them?

9. Privacy and security concerns. There are technical issues, of course, like how search engines handle user permissions and document access codes, but there are social and managerial issues as well. When does mass customization, with its voracious appetite for personal information, yield diminishing returns? How can we make it possible for individuals to assemble and control all their personal information in a single electronic briefcase?

10. Escalating costs of health care, education, defense, and disaster relief. In these knowledge-intensive industries, it's crucial to lower costs and increase effectiveness. To do otherwise is politically, morally, and practically untenable.

The common denominators here are collaboration outside organization boundaries, decentralized models for knowledge creation and distribution, a higher level of institutional responsibility for security, privacy, and transparency, and an urgent need for greater effectiveness in a broad spectrum of knowledge-intensive industries.

Gearing up for the new realities
What would you do if an executive or department manager asked for your help in meeting performance targets in a knowledge-intensive process? Who would you need on your team? What skills would you need? What information would you need to know or gather from those participating in or affected by the process? What software tools would you and your team need?

On a more fundamental level, what kind of support system would prepare you to answer these questions? Here's what our wish list looks like:

• Trend-spotting service. Ideally, we'd like to know about trends before they become a priority for top management. We'd like a service that not only alerts us to new developments but helps us put them in the context of information performance and productivity.

• Access to experts. Having identified a trend, we'd like to find people who have experience with it, not just as a reporter or researcher, but as a practitioner. We'd like the chance to meet these people face to face in a small group setting where we could ask questions and listen to questions posed by our peers.

• Connections knowledge base. We'd like a knowledge base that would track connections between selected people, products, events, and trends. When a significant change happens, like a popular new service gets acquired or a prominent venture capital firm funds a new startup, we'd like to get an alert about it. We'd like to know about it when a person on our list changes employers or forms a new company.

• Rapid prototyping and testing service. We'd like to be able to test new tools and techniques with our own staff and our peers in other organizations. Will a new product feature eliminate costly content conversion, reduce the cost of custom application integration, or enable non-technical managers to assume more control over their information environment? What problems and opportunities do our peers in other companies see?

• Access to interdisciplinary research and case studies. Will a new line of research in ethnology, sociology, or linguistics have an impact on information productivity? Will a new development in academic libraries affect corporate information services? What's going on and what does it mean?

• Publishing services. All practitioners, but especially those in the information disciplines, have a responsibility to disseminate their findings and assist their colleagues — i.e. publish and teach. But often they lack the time to write, edit, index, and distribute their know-how. We'd like a service that could convert a Powerpoint presentation into a handbook, training guide, or article suitable for publication.

None of the items on our wish list is particularly new. All are offered by other organizations catering to specific disciplines and industries. But no organization offers these services in the context of information productivity and performance from an interdisciplinary and practical perspective.

Since 1998, we have been researching, writing, and interviewing members in all these areas. In the Lab, we've experimented with Google and Amazon Web services, blogs, XML, metadata repositories, and auto-categorization software. Results have been published in the Digest, Montague Institute Review, and Member Q&A articles. Our courses have evolved from lecture-demo sessions into project-oriented work with a Web-based lab and one-on-one mentoring.

But we have just scratched the surface in terms of tapping member expertise, providing contact with experts and information pioneers through face-to-face and virtual meetings, testing and reporting on new software and services, developing and sharing the capabilities of our learning materials and lab. We have formed a small advisory group to help us develop ways to better leverage our resources and those of our members. We are looking at adding more services and opportunities for collaboration to our enterprise membership as well as ways that individual members can receive additional benefits in proportion to their contributions — e.g. as authors, compilers, and roundtable guests.