Guide to Distributed Knowledge Management

Submitted by admin on Mon, 09/26/2016 - 11:35

Knowledge management can be defined as the “management of organizational knowledge for creating business value and generating a competitive advantage. Knowledge management enables the creation, communication, and application of knowledge of all kinds to achieve business goals (5).” This resource guide is loosely based off a framework established by Amrit Tiwana in The Knowledge Management Toolkit, and modified to fit projects of a scientific nature.

This idea of knowledge management (KM) can be translated and adjusted to fit the needs and goals of those conducting team science, in order to promote more effective communication and information sharing across teams, as well as allow increased access to different materials used to findings discovered by different parts of those teams. Implementing a knowledge management system (KMS) is far from a general practice, whether a team is working for the same organization, different organizations in the same geographic area, or in a geographically dispersed team. While much of the research behind effective creation and utilization of KMS is rooted in business or industry, the takeaways related to knowledge sharing and the leveraging of knowledge to enhance creation and sharing of knowledge can work for team science as well.

Phase I: Infrastructure Evaluation

Step 1: Assess and audit existing knowledge economy.  

  • Determine what knowledge is being created and saved within your team, as well as how it is being shared.

  • Consider how your methods facilitate knowledge sharing. What decentralized methods are already being used? How can you include these practices in with your KMS?

  • What knowledge is tacit in your group, and what is explicit? Consider knowledge sharing methods that ensure you are effectively sharing tacit knowledge.

  • What is missing from your knowledge base?

  • Consider issues of remote scientific collaboration: Do dispersed teams have access to each other’s knowledge base? Is one team using proprietary software? Is the funding agency or the organization responsible for information or knowledge that needs to be accessed?

  • Section sources: Gibb; Horibe; Inkpen & Dinur; Osterlund; Olsen (Ch 4); Raub & Von Wittich

Step 2: Align knowledge management strategy and strategic goals of utilization.

  • How can you leverage your knowledge, or the efficiency of your knowledge sharing, to gain an advantage in gaining grants or funding?

  • Ensure your knowledge sharing methods are generating value, and optimized for value extraction.

  • Align KM with with contribution from key functional units to increase effectiveness of knowledge collection and sharing.

  • Section sources: Horibe; Maier & Remus; Pan & Leidner; Raub & Von Wittich

Phase II: KM System Analysis, Design, and Development

Step 3: Design the KM infrastructure.

  • Consider infostructure over infrastructure, think about desired formatting and interface. (Tiwana)

  • Customize the architecture to your organization, select the necessary components, and incorporate UI considerations. (Tiwana)

  • How is this data going to be used, and who is going to use it? (Olson, Ch 1)

  • What kind of tools need to be included for this particular audience - i.e. data tools, searchability considerations, visualization capabliities? (Olson, Ch 1)

  • How do you map your actions around what is being produced? Is information about your KM process being incorporated? (Osterlund; Maier & Remus)

Step 4: Audit existing knowledge assets and systems.

  • Is your team capitalizing on existing tools through your institutions or the funding agency through which you are able to perform the work? Can you? Will you both have access to all of the same materials if so, or are there permissions limitations imposed? (Olson, Ch 1)

Step 5: Design the KM team.

  • identify stakeholders, expertise, balance constitution of team (expertise & skill), consider team sizing issues (Tiwana)

  • Will you outsource the build after designing the infrastructure? Do you have the resources (money, time, ability) to do it yourself?

  • Note: If you’re outsourcing the actual building of the system, consider how the built system will be managed in terms of knowledge adding and updating in order to build the team.

Step 6: Develop the KM system.

  • actually put it together; remember when working with CS, they will want to do something new, but maybe not always what’s most effective (Olson)

Phase III: Deployment

Step 7: Deploy new KMS. 

  • Given your team size and location, will a pilot release or beta testing be effective? (Tiwana)

  • Have you incorporated communication practices with KM to ensure full adoption and support? (Osterlund; Raub & Von Wittich; Pan & Leidner)

Phase IV: Evaluation

Step 8: Evaluate performance and incrementally refine the KMS.

  • What is your method and frequency of getting feedback? How are you implementing this feedback? (Tiwana)

  • How are you implementing quality control in the face of multiple users? Can you use best practices from other aspects of the organization in this regard? (Osterlund; Maier & Remus; Horibe)

  • In your case, does it make sense for one person to be in charge of changes?

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