All Blog Tracking Survey: THE IMPACT of COVID-19 on the DEVELOPMENT SECTOR in INDONESIA
Saraswati applies a comprehensive approach to knowledge management. We view knowledge management as a combination of: 1) systems & processes; 2) technology; and 3) people. As such, our support ranges from developing Monitoring, Evaluation, and Learning (MEL) frameworks and tools to building online Management Information Systems (MIS) and training development partners in data collection and analysis to promote data-based reporting and advocacy.
While our three elements of knowledge management are all important in ensuring a continuous learning process, there is increasingly a lopsided interest towards technology. Why? Tech solutions can be touched and manipulated by the user. It is easy to see the direct consequences of merging datasets and aggregating data for an instant overview of the information available to the organisation. And because tech manifests itself as a material tool, it is external to the business of the organisation. Therefore, it is ‘easier’ to develop tech solutions than reform organisational business processes or people’s work habits. Consequently, ‘innovation’ refers to a constant search for new, shiny technological features rather than addressing the issues of knowledge transfer and skills building.
So, how to ensure that your efforts in support of knowledge management contribute to organisational sustainability?
Understand your data structure. Most of the time, organizations are so caught up in collecting as many datasets as possible. However, they tend to overlook fundamental questions: “Do we need these data? If so, why?” As we formulate research objectives, these end goals guide us in deciding appropriate data and data collection methods. Similarly, we have to determine the specific aims and outcomes of our program, then trace our way back to key data and information needed. This way, we have a clear map of what data are to be collected, where to find them, and who is responsible—a basis for an organisational logframe. The logframe is crucial in MIS design, as we have to program the system to understand the relationships and correlations between data. Otherwise, the system will not provide any benefits in automatic data aggregation.
Train and empower your team. Having an MIS in place encourages decentralisation of organisational knowledge, as information in the system flows from the lower levels up. This means that every team member will contribute her or his share of data and knowledge to support higher level decision making. As such, the process of developing and maintaining an MIS requires organisations to trust and continuously improve the capacity of all their team members—from field staff to senior management. This does not mean that you should train your whole team to be data scientists; instead, they need to be aware of your organisational data pipeline, including their roles and responsibilities in each step of the flow. While the MIS can automate many steps in the data processing flow, human resources are still crucial for data input, validation, and analysis. Some actions—for example, managers’ validation and approval—are required before the system can progress to the next step. Therefore, another crucial element in your training is to build your team’s habit to update regularly into the system. This ensures a continuous flow of information and timely data aggregation that contributes to sustainable organisational learning.
Gain and share insights from your data. The synergy of your system and your team results in aggregated data, a summary of your collected raw data. The MIS may generate some visualisations of this aggregation, such as tables, graphs, charts, and maps. Such visualisations are useful to provide a quick outlook of your current organisational or programmatic situation. However, the real value of data aggregation is to encourage deeper analysis to contextualise the situation at hand. But not many organisations uphold this practice. Data insights become interchangeable with data visualisations, eliminating the narratives crucial to tell stories, offer alternative theories, and provide recommendations. Improving your team’s writing skills—in addition to data awareness and capabilities—will be beneficial to maximise the use of your data to influence program design and policy.
Saraswati provides technical assistance in overall MEL framework design, developing online MEL platforms that improve data aggregation and analysis, as well as training development partners in data analysis and data-based writing. For more information, contact us at info@saraswati.global.
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Tiara Permadi is Project Manager at Saraswati. She manages multiple projects with complex DFAT-funded programs to design and develop online knowledge hubs and data management systems, as well as leading on innovative programs to engage the private sector, social enterprises, tech firms and communities.
