Data and Decision-Making: The Measure, Fix, Prevent Approach
October 17, 2023 by Steve Goll
In today's data-driven era, government agencies and departments play a pivotal role in shaping their community's future by harnessing the power of data. From local initiatives to statewide programs, the importance of effective data collection, analysis, and management cannot be overstated. In a Tyler Tech Podcast, Franklin Williams, president of Tyler’s Data & Insights Division, shared his expertise on making informed decisions using data.
The Three-Step Continuous Improvement Data Approach
Based on Williams’ insights, one aspect of data-driven decision-making in government that stands out is the three-step process of "measure," "fix," and "prevent." This continuous improvement approach underscores that data’s true value in government comes not just from its mere presence, but from its iterative use in decision-making processes.
- Measure: This initial step focuses on understanding the current challenge. What’s going on? What needs to be improved? Whether it's high crime rates, response times, or recycling effectiveness, the first step is to gain an accurate understanding of the situation. Once the data is collected and key performance indicators (KPIs) are set, it lays the groundwork for improvements. Without accurate measurements, you won’t be able to know if you’re making improvements.
- Fix: After gaining visibility into the problem, the next step is to address it. Using accurate data to identify the root cause and subsequently implement solutions is paramount. For example, an analysis might lead to the insight that high crime rates are happening in areas with low street lighting. Once identified, solutions like increasing street lighting can be rolled out and their effectiveness monitored by tracking crime rates in those areas.
- Prevent: The ultimate goal is to ensure that once a problem is fixed, it doesn't recur. Predictive analytics plays a crucial role here. For instance, when Pierce County noticed a rise in the number of positive COVID-19 cases among 20- to 29-year-olds, they used data to reallocate funding to target this demographic and change their behavior.
Williams also highlighted the significance of interdepartmental data-sharing. Coming from an era where data was initially all about transparency, the focus has now shifted to internal sharing and collaboration. Residents don't live in silos, and data shouldn't either.
Bridging the Interdepartmental Data Gap
When considering data-sharing across departments or jurisdictions, recognize that for residents, challenges don’t stop at a department line or a program line. The public views government as a single entity, not a complex organization with different resources and systems. Solutions to residents’ challenges demand a collaborative approach, and this collaboration is fueled by shared data.
To foster interdepartmental data-sharing, governments can start by addressing two prerequisites:
- Clear Objectives: Instead of just sharing data for sharing’s sake, governments should have clear objectives in place. Creating data-sharing agreements that outline what will be shared, its intended use, the recipients, and the benefits can pave the way for smooth collaborations.
- Right Tools: Ensuring that stakeholders have access to tools that integrate data from various sources, old and new, is essential. With the right tools, stakeholders can easily access consolidated data and use familiar tools to make informed decisions.
As governments continue to navigate the complexities of public service and a surge in data from their services, having an agile, data-driven approach is more critical than ever. The power of measuring, fixing, and preventing problems — enabled by the right data management tools — holds the promise of better performing government.