Knowledge Management System

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Contents 1 Introduction 2 Knowledge Capture 3 Operating Culture and Staff Oversight 4 Managing Knowledge for Results via Learning Loops 5 Footnotes 6 Navigation

Introduction

Implementing a program using a value chain facilitation approach presents a range of challenges in collecting, analyzing and using information required to achieve objectives. The approach requires a complete re-think of project management based on comprehensive knowledge management. The process of moving from an almost stove-piped reporting structure to an integrated management process includes not only the way data is gathered and reported, but the way staff are managed and information is used, analyzed and communicated throughout the project. Developing a knowledge management system that can deliver both the reporting requirements and real time knowledge of behavior change to inform resource allocation decisions is essential and requires a combination of data capture techniques and staff management methods.

Knowledge Capture

There are two types of information that need to be captured. The first is tacit information that is held within a person (i.e., staff, value chain actor, etc.) but not communicated in any formal way. Tacit information is the result of someone observing and learning a great deal, but transmitting very little of what they see and learn. Understanding and planning methods to capture more of this rich information is critical. The second type is explicit information that is pre-defined as important and required to be reported.

• Tacit knowledge capture. To capture tacit knowledge value chain projects can use five different qualitative methods:

1. Operating culture: An operating culture has to ensure that incentives, whether in the form of bonuses or kudos, are supportive of staff actively sharing information and questioning why they are doing a specific activity. This is an ongoing process that is rooted in the value chain approach, but which requires constant internal monitoring.
2. Teams: Using teams to foster social cohesion and joint responsibility among staff can be a highly effective means of sharing knowledge.
3. Staff-to-staff or project-to-project exchanges: Exchanges can be effective in fostering change among local actors or improving the performance of staff.
4. Internal small group workshops: Having management and staff design and present participatory training modules to each other on an ongoing basis to extend learning and increase staff-to-staff interaction and learning can be very effective as a capacity building and knowledge sharing tool.
5. Regular all-staff meetings: When facilitated well, regular all-staff meetings foster knowledge flows in a project. They can be conducted with staff or on occasion by an outside consultant.

• Explicit knowledge capture. Explicit knowledge typically focuses on the process of capturing monitoring data for management and reporting purposes and can include the following methods:

1. Tracking reports: Such reports are directly linked to pathway observations as a means to better track key indicators against expected behaviors.
2. Quarterly and annual reports: While quarterly and annual reports typically have specified data requirements that are taken from the tracking reports, they often require additional data sources such as lead firms, key informants and external sources (government, research organizations, associations, etc.).
3. Targeted evaluation: Conducting more formal evaluations of secondary effects using quantitative and qualitative methods is an essential component of managing a knowledge-based facilitation project.
4. Formal impact assessment: This is the only way to determine with a reasonable degree of certainty the impacts of a project.

Operating Culture and Staff Oversight

Implementing a market facilitation approach is dependent upon a management structure that actively pushes information from the ground back up to managers and then back down to field staff. Field staff must have the capacity to read and react to local market signals and understand the fine line between facilitating an action and directing an action. Empowering field staff with the knowledge and skills to fulfill this role is critical and highly dependent upon staff having ownership of the project’s strategic objectives and belief in the approach. At the same time, most staff in development projects come from a hierarchical management structure with specific predefined activities and with job performance criteria based on simple operational indicators (i.e., number of people trained, number of meetings held, value or volume of sales, number of microenterprises receiving a loan, etc.). While not necessarily bad, these indicators and the incentives around such management structures run counter to the foundations of a value chain facilitation approach, as they enforce the perspective that the indicator frames the goal rather than signifying something that needs further investigation in terms of its contribution to increased competitiveness.

Managing Knowledge for Results via Learning Loops

Capturing data, whether explicit or tacit, is only as useful as the processes set up to analyze and push the new learning back into efforts to adjust ongoing facilitation activities. Projects should therefore develop management processes that intentionally foster learning loops emanating from all interventions. The initial set of project activities should initiate an ongoing process of comparison between the anticipated and actual responses of local actors to opportunities and threats catalyzed by the interventions.

After the initial pre-defined activities have been implemented, the knowledge management process can drive follow-on interventions within the context of keeping local actors in the industry, support markets and enabling environment moving along the pathway toward improved performance over time. Implementers can lay out a range of contingent activities that might be needed depending on the knowledge gained from the various tacit and explicit capture methods. The data captured on actual observations will be assessed against expected observations in the pathway.

Example: In Liberia a USAID-funded project^[1] facilitated promotional events at which input providers discussed products, handed out some samples and also made sales. Farmers were observed repeatedly buying small quantities of inputs, rather than purchasing the larger packages and saving money. Discussions with the farmers revealed that they were afraid to buy the larger products lest family members and/or neighbors saw them, realized they had money, and asked them for it. The project recognized that a less public forum was needed for the sale of inputs.

Footnotes

1. ↑ Agriculture for Children’s Empowerment (ACE)Project, USAID/Liberia

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