Data management can be tricky, with many not-for-profit organisations struggling to collect data or find meaning in the data they collect. However, when data management is done right, it can help you improve the way your organisation operates, make more informed decisions and take smarter strategic actions. But, what are good data management practices? This blog describes the steps and actions you can take to get better at collecting, managing, and using data at your organisation, easily remembered with the notion of the 4 A’s to Data Management – Accumulate, Analyze, Apply and Act.
The first step to good data management is to accumulate data so that you can use it. While data accumulation is relatively easy, accumulating data for the sake of it, isn’t useful. You need to collect “good” data that is clean, consistent, of quality and most importantly, is relevant to your organisational goals.
So, keep it simple and accumulate “good” data by implementing these tips:
- Determine what data is valuable to your organisation and collect that data.
- Define how you will accumulate relevant data and what tools you will use.
- Set-up data entry standards and create data entry manuals for your organisation.
- Manage data quality with operational controls and data quality reports.
- Support users responsible for data entry with training and guidance.
Unless you do something with data, it is relatively useless. This is where analysis comes into play where you will consolidate and aggregate your data, provide some context to your data, and format it in such a way that it is more meaningful. Although analysis may require some maths, interpretation, and deep thought, it can help you uncover the hidden meaning behind your raw data and provide the empirical evidence needed to make informed decisions and take smarter actions.
Analyse raw data by implementing these tips:
- Create reports with data that is relevant to your strategic objectives.
- Run reports on a standard schedule so analysis is a consistent practice.
- Ask questions like: what is the data telling me, what data am I looking for, and is the data what I expected?
- Confirm your analysis by reviewing your conclusions with others.
Data management is about taking data and making it practical. You therefore need to move beyond questions like “What is the data telling me?”, to questions such as “What does this data mean for our organisation?”. This means applying any insights or learnings from your data to your organisation so that you can make changes to your programs to ensure that you are continuing to make a difference to the lives that you service.
You can apply your data by implementing these tips:
- Compare real outcomes evidenced by data to your goals or objectives.
- Find discrepancies or alignments between expected and actual results.
- Contextualise trends, patterns, and single metrics in time.
The last and most important step to good data management is action. Data informs and data empowers, but it is essentially a tool that needs an operator to “act” on the data by applying the data to a real-life situation. If you aren’t using data to take action, then you are probably collecting data that is not relevant to your organisation.
So, act on insights from data by implementing these tips:
- Develop action items from insights gained during analysis and application of data.
- Use insights from data to define new goals, new strategies, and new tactics.
- Position data as a motivator for continuous performance improvement.
- Take action on a consistent and timely basis.
- Communicate and reinforce strategic decisions and actions with empirical, data-driven evidence.
Thus, although data management can be challenging, if you implement these 4 key steps, you can ensure your data is practical, useful, and actionable in your daily work, thereby making a significant contribution to your organisation and those you serve.