This blog is excerpted from an original post on the CapacityPlus blog.

As a knowledge management (KM) practitioner, I ask others to spend time sharing knowledge on a daily basis:

• Record data
• Share results
• Archive documents.

Today, I am a victim of my own systems. My enthusiasm for sharing hasn’t waned, but it’s often buried beneath heavy and competing demands on my time. My own griping about time versus knowledge management underscores the value that KM can bring to the table. All organizations and projects use, capture, and share knowledge—they’re doing KM already. But without the intention to prioritize knowledge management, KM doesn’t happen systematically. It happens, but it gets buried in the day-to-day.

Furthermore, the knowledge that is shared becomes skewed. Personal habits and over-packed calendars feed a tendency to share only the positive aspects of our work and influence what knowledge becomes more widely available. That worked well—promote it! That failed—forget it ever happened!

When KM systems are articulated and participation expected, they’re harder to ignore and should provide better results. In the development context, we have an increasing bank of anecdotal evidence to support KM’s effectiveness, including the 47 case stories gathered and synthesized for the KM Impact Challenge, but we must do a better job of strengthening and sharing this evidence-base.

Beyond web statistics, it can be difficult to count knowledge’s use or effects, but we can assess our KM practices. It is imperative that the KM community continue to demonstrate the value of KM.

To that end, I was particularly inspired by these three techniques presented at the recent KM Impact Challenge unConference:

• Participatory and iterative monitoring and evaluating methods, like the Most Significant Change Method, can help to reveal the hard-to-predict and quantify impact of knowledge and learning initiatives.

• Organizational network analysis provides unique tools for visualizing, describing, and diagnosing information flow, partnerships, and other typically hidden relationships.

• Innovative mobile data capture methods, such as EthnoCorder, combine mobile technologies with videos and surveys to facilitate on-the-spot data capture and tagging without the need for an Internet connection or a time-consuming coding process.

KM is about learning from what is already known, making informed decisions efficiently, and performance. Yes, it’s about knowledge capture, synthesis, sharing and use, and those frameworks we KM people like to share and talk about—but most importantly, in the health context, it’s about improving and saving lives.