Why do I need data? OR What will I do with data?

Determining the why and what of data are essential components of storytelling. They establish a baseline to assess change; set the performance goals which enable measurement of success; aids in organizing the information to be collected and combine to tell a convincing story through examination of trends and patterns.

What story must data tell?

Assessing good or bad depends on the story we tell. The same is true for determining urgency or a call to action. Data is often used as a call to action. As a result, it must be strategic and relevant, include examples for audience to visualize the why, be intentional with visuals to distill data, and be communicate with the action needed. In sum, data visualization with compelling narratives help to comprehend data and act.

Who must know about the outcomes of data?

If data must move the audience to action, knowing the audience is as essential as reporting the result to stakeholders. Therefore the outcomes must be communicated to those from whom the data was taken, those who must take action, those who will benefit from the action, as well as those who will monitor the change. Data is only as good as what it communicates and who it impacts.

Where must the data come from or be stored?

The location from which the data comes dictates its accuracy and effectiveness. Though we may retrieve data from student information systems, local state departments, from students and teachers, or even from community, the best place to get and store data is from a system where all variables impacted or will be impacted or may change can be added and assessed. Everything you would want to know must be collected in variable form. This will change overtime therefore the system must be able to accommodate the change.

When do I need data and how often?

Data needs change all the time. Despite data collection occurring in regular cycles such as every month, every semester, or as the states requires; it should be collected as often as available but best assessed semi-annually or annually. This is important because data must be collected around interventions or organized changes. The outcome is the ability to spot patterns and trends so when compared we are aware of where and when to intervene. In addition to create change, we are aware of where old variables must be complemented or swapped out for new ones.

How do I know the data answers my questions?

Data can be used to answer any question. The key is, can it answer your question. As such, playing a role in data collection or siphoning data from one place to use elsewhere requires early attention. Not everyone must be on board with what you collect but you must create a hypothesis with the questions you hope to answer. This is the only way you can be sure the data will answer the questions you have.  Identifying a hypothesis is a way of listing your problems and identifying the solutions you anticipate.

What actions do I plan to take with data?

After collecting and assessing data, action is necessary for it to have meaning. Revisiting the hypothesis can give direction but data users must take action by informing stakeholders, defining  benchmarks, assessing if goals are being met, and planning for change. Most importantly, data evaluators must identify the areas where they would want to introduce intervention or new variables for the best impact from data action. The actions can be targeted and specific to what change you want to see, within the timeframe you have identified within your system.

How do I monitor change from data?

Monitoring change, resulting from data, is simple when we run trend analysis at regular cycles. Monitoring at the start and end of each cycle ensures accuracy and timely variable change. A cycle is defined as a period for collecting information determined by the data collector. Its best to establish your own monitoring plan with all stakeholders who collects, stores, and assesses data. The goal is to use what you collect to set benchmarks, confirm hypotheses, and run trend analysis.

What interventions can facilitate change?

So, you want to use the data to facilitate change? Any intervention can facilitate change; albeit negative or positive but its best to have variable-specific interventions. Intervention success is not dependent on the number of persons impacted or the cost but, on the change anticipated by the hypothesis. In fact, intervention success is dependent on the problem to solve. If there is a match between the problem and the solution, interventions are often effective to facilitate the desired change.

How do I report on and sustain the change?

To complete the cycle, we must share the findings with all stakeholders especially those who identified the problem. Determining what to share is as important as where to share. Sharing on social media, in written or online reports, and annual general meetings are good places to start.