Wouter Neef
5 minutes
Data literacy is a container concept for a lot of different skills. To understand if your data literacy program is creating business value, you should look at data literacy program indicators. Two concrete examples of these indicators are the number of course completions by your employees or the average assessment scores for the completed data literacy training. These program indicators give you high-over insights on whether your data literacy program is being completed by learners.
While it is difficult to directly assign a monetary value to completing data literacy courses, it is an early indicator of how your data literacy training program could enable value from data-driven working. For example, by measuring the number of completed data literacy courses or the average assessment scores over time, you can link them to other important business metrics such as revenue growth, customer retention, or revenue per employee. If you measure this before and after rolling out your data literacy program, you can get a quantifiable estimate of the value created.
Measuring the number of course completions is rather easy and can be done for almost all data literacy programs. However, there are also more sophisticated KPIs that may be harder to measure but may be more suited for your business to quantify the value created.
To measure if learners not only complete the data literacy training but also change their way of working, you should measure tool adoption rates. By measuring tool adoption rates of e.g. Tableau, Power BI, Google BigQuery, or Thoughtspot, you have a tangible way to quantify the effectiveness of your data literacy program in changing work behavior.
Ideally, you would like to measure the adoption rates, pre-training, and post-training so that you can accurately tell if, and by how much, the tool adoption rates have changed. KPIs that could be good to options to track as measure of tool adoption rate are:
The weekly or monthly average number of users of tools will show you what percentage of people use certain tools, and how often. This will give you better insights into what tools are used most often. And if the tools are fully utilized. Also, the number of queries or quantity of data queried will give you more insights into how much data your employees are using for their work. And the number of people with access to dashboards will give you more insights into how many employees are using descriptive analytics. For example, to track certain business objectives or to make more data-driven decisions.
In the end, you can relate all these metrics back to the business performance metrics of the entire organization or specific teams. For example, is there a noticeable increase in revenue when sales managers are using dashboards more (frequently)? Or is there an increase in marketing ROI, when marketers use data tools more frequently? These associations can give you a better understanding of how your data literacy program is influencing business metrics through tool adoption rates.
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