During a members’ discussion, data and analytics leaders pooled their collective experience and approaches to outline a framework to starting a data literacy programme from scratch.
1. Structure your Data Literacy Programme
Start by creating bucket areas that can be separately managed but form a complete jigsaw when finally pieced together. Examples of bucket areas include:
Data and analytics landscape
Data culture and innovation
Specific training on specific tools
2. Include a Change Management Plan
A data literacy program must include a change management plan. To measure progress, it is important to diagnose the baseline maturity levels in each individual department, as well as the level of resistance to change and management understanding. Use the outputs to form a tailored training plan ranging from tool training to a leadership program, depending on the departmental needs and persona profiles.
3. Diagnose Data Literacy
Use an approach based on engagement with data rather than job profile. Define data personas based on how the person needs to engage with data, not the job they do. This helps identify gaps that feed into formalised learning paths. A recommended approach to “diagnose” data literacy is to ask yourself:
If we could describe this department as data literate, what would they be doing?
Data Leaders members can access a downloadable guide for data personas.
4. Delivery is Vital to Adoption
There is no one-size-fits-all for delivery. Mixed learning needs to be embraced. Self-paced, instructor-led, interactive classrooms; foundational courses, explainer videos, lunch and learns, show and tells are all in the mix depending on the audience and content. Telling stories using familiar data sets and solving familiar problems is powerful, especially when it’s made attractive, and users can ask questions and have their learnings validated. Train-the-trainers and champions are critical in providing support and leading learners to the right conclusions from their dashboards.
5. Celebrate Progress
A weekly 20-minute coffee session can become a compelling outreach tool. It can be used to show best practices, new features, or cool tricks in Power BI. You can also use it to reward good work with a free coffee or a quarterly free weekend hotel stay.
6. Consider “Data Wisdom” rather than “Data Literacy”
Some argue that “data literacy” sets the wrong expectations, and even runs the risk of patronising employees. Instead, we should be talking about analytical literacy or data wisdom. Data is more prevalent today than ever, and the ease with which the lack of those skills can be abused or misused is troubling. We should be thinking about interpreting data, which should be a life skill. While data leaders continue to advocate for putting people at the heart of their data strategies, it’s possible that we are moving towards an era of machine-led decision intelligence or the rise of Chief Intelligence Officers.
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