Where do we start? We start with intentional Data Management. As the culture for evidence driven reports strengthen, the need for effective data management systems will continue to grow.
Data Management is the process of consistently collecting, storing, organizing and maintaining the data created within an organization. This is way more than simply filing with a very detailed filing system. Realistically, as your organization grows, the time spent sifting through paperwork will not exist. As needs increase and data expands a system of quickly accessing the specific data points becomes extremely important.
Considering, your data is the most essential piece to your organization and more specifically your project/program, it needs to be treated with the utmost care. Some time ago, we briefly illustrated a data management process on our Instagram page. https://www.instagram.com/p/CL92pSnB6T-/?igshid=mbxwxcm6krjp
Let’s dive into greater detail!
● DATA QUALITY ASSURANCE: This refers to consistent measures put in place to establish strong data quality. Within these realms we can pay specific attention to the Validity, Reliability, Precision, Integrity and Timeliness of your data.
● DATA FLOW: This step of the process speak to where the data comes from, where it needs to go and all the small things in between. Who collects the data? From where/whom? How often? How are data accumulated and stored? How is the data analyzed? How and when will the data be used?
● DATA STORAGE AND RETRIEVAL: This point aligns right within DATA FLOW ...they both require each other to produce good data quality and excellent data management
● DATA PROCESSORS, ANALYSIS AND REPORTING: This speaks to our outputs. How is the data interpreted? What does the data say? And, after we have determined what the data says, how will we communicate that to our audience?
We have seen the impact of effective data management systems in the outputs produced by organizations and programs. We look forward to hearing your feedback and are available for consultations if you would like to explore more efficient data management systems to suit your needs.
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