Knowledge-what we know basic awareness of anything i.e. technology,product,process,methods.

by sudhansu sekhar pallei

The process of effectivelly manageing the Knowledge asset of an organization is called Knowledge Management.

Advice to the knowledge manager
Three questions are central to the business case for any performance improvement program, including knowledge management:
1. Value Proposition: What are the expected business or organizational benefits?
2. Cost: What resources will be required to realize the benefits?
3. Time: How long will it take to realize the benefits?
At the end of the day, your KM program must produce easy-to-understand results that answer these questions. Measurement is a means for demonstrating progress and sustaining stakeholder support. It is essential for understanding what is working, and for determining what should be changed to ensure that the expected benefits are realized.
Measures fall into three classes:
1. Input Measures (or Cost Measures): These include expenses to create and support the program (e.g., consultants, direct staff, IT) plus the time of participants.
2. Process Measures (or Activity Measures): These are measures of the level of participation in the KM program. Examples include: number of lessons learned, number of project teams using KM approaches, Web page views, number of CoP members, and perceived utility of KM processes and technology in improving the daily jobs of participants.
3. Output Measures (or Outcome Measures or Results Measures): These are the measures of progress in delivering on the value proposition. They may be traditional "hard-dollar" business metrics like: revenue growth, improved productivity (e.g., revenue/employee for a service business), improved efficiency (e.g., return on capital employed for a capital-intensive business), reduced capital or operating expense, improved quality, reduced cycle time, or enhanced innovation (e.g., percentage of revenue from new products). They may also be "soft-dollar" measures like: success stories, cost avoidance, increased customer satisfaction, improved skills and competencies, decreased time-to-competence, and improved ability to attract talent or capital. Organizations often expect the KM program to influence their overall Key Performance Indicators and integrate its results into a Balanced Scorecard.
Input and process measures are called "leading indicators", whereas output measures are called "lagging indicators." Because different stakeholders need different data to take different decisions, sustainable KM programs employ a blend of leading and lagging indicators.
The measures that make sense for your KM program depend on the culture of your organization. Begin by asking around to understand what long-term success means to the different stakeholders (e.g., senior managers, operational managers, colleagues, individual contributors, customers, suppliers) and what data they will need to be convinced. Prime these early discussions by going over successes reported by other organizations in benchmarking studies. However, be prepared for a vigorous discussion. Reported successes are usually greeted by healthy skepticism ... from all stakeholders.
Following are some familiar objections, together with some ideas on how to respond to them.
• "We're different." The results don't apply to our organization.
o Of course, this may be true. It is best to find results from organizations that are close to your own (perhaps competitors, customers or companies that use similar business processes in a different sector) or where the differences can be shown to be immaterial to the case for KM.
• "The knowledge manager can't claim all the credit."
o Organizational performance results are indeed based on a number of factors. Focus on results reported by line management and play down those reported only by a knowledge manager.
o Be aware that organizations typically do not attribute results to a particular functional group (KM, IT, HR, …). For example, Schlumberger reports these results for a specific KM program (InTouch): queries resolved 20 times faster and $200 million/year revenue created or saved.
o This kind of reporting is consistent with the way companies attribute revenue to new products. They don't carve up the revenue by function (R&D gets this percentage, Marketing gets that percentage, and so on). Of course, the analogy to KM isn't perfect because company accounting systems track revenue for individual products, whereas they typically don't track cost savings by program with the same rigor.
o This leads to a caveat when measuring the results of your own KM program: Avoid percentage credit negotiation. In this approach, a functional group (like KM or R&D) engages business managers in a kind of negotiation about what percentage of the revenue or cost savings for a particular program should be attributed to their efforts. Experience has shown that this is a waste of time and reduces the credibility of the group doing the negotiating.
• "It is easy to measure progress in a business, but much harder for government or non-profit organizations."
o It is true that "hard dollar" output measures are less obvious for a government or non-profit organization. Concentrate on "soft dollar" measures like customer satisfaction, cost avoidance, not making the same mistake twice, providing quick access to correct information, etc.
Use what you learn to select a small set of measures for each pilot project:
1. Measures that are meaningful to management. For these decision-makers, the most useful are likely to be a combination of input and "hard dollar" output measures, but be sure to include some anecdotal measures (e.g., success stories) and process measures in the mix. While "hard dollar" measures are the most useful for senior managers to decide if the program is producing the expected benefits, they are often the most difficult measures to obtain.
Measures that are useful to you as knowledge manager. These are primarily process measures that help you assess overall program health, measure the utility of individual KM processes and technologies, and guide next steps.

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