Data analytics helps with resource allocation and time management. Data analytics tools empower districts to focus on areas of need, while minimizing time spent on areas requiring less attention. Whether it is monitoring trends or analyzing comparable data of similar districts, these tools improve decision-making and save time.
Written by: Tim Raymer, Retired Assistant Superintendent, Forest Hills Public Schools
What are Some Practical Applications?
What is the real history of enrollment, revenues, expenditures, and fund balance? Deal with, and document, the real trends as opposed to perceptions that develop over time and frequently have limited connection to reality.
Data Driven Decisions
Decisions based on data have a sound foundation, are easier to explain, and defendable when necessary. Focusing on trends and peer district comparisons results in discussion and decisions that maximize perspectives and minimize short-sighted thinking. Trends are especially important as they relate to sustainability–critical to any decision.
Refuting Inaccurate Assertions
We are frequently confronted with inaccurate statements that need to be clarified quickly. This is common in negotiations and the budget process. When someone makes an assertion about where dollars are spent, it is helpful to respond with accurate data comparing the district to similar peer districts. As Charles Darwin said, “to kill an error is as good a service as, and sometimes even better than, the establishing of a new truth or fact,” or the shorter version–An attack unanswered is an attack believed.
Communicating effectively with the Board, employees, and community is critical. Sound data is the foundation of any communication, but effective messaging improves the entire process. Numbers, tables, and budgets are enhanced significantly by self-explanatory graphics and key comparison measurements.
If you aren’t analyzing your data, you are subject to someone else analyzing it. The position of “the analyzer” is preferable to “the analyzee” any day of the week.
Data Analytics is Not an End Product,