Imagine yourself as a new data leader. You’re a strong believer in raising data literacy to help organizations make more informed decisions. But after a quick assessment, here’s what you find: 

  • Data literacy is minimal across your company
  • There are few (if any) sanctioned data literacy programs or pathways to learn the language of data
  • Best endeavors are undertaken across the organisation to yield insights from data
  • Data analytics capabilities are rudimentary at best
  • Strategic organisation priorities that could be transformed by data are not being capitalised upon

My first word of advice is, don’t despair! Here are seven steps we followed in defining a data literacy program at RBS International that may guide your success as well:

  1. Start with a strategy. To keep any data literacy program on track, you’ve got to have a strategy. With my team, I established one in the form of a North Star direction that described the ambitions of our data program, expressed in a way that was believable to the organisation. What we found is that having a well-defined strategy and a data literacy framework helped secure early champions who jointly can create the momentum behind data transformation.
  2. Benchmark existing data literacy. Creating a sample benchmark across your organisation gives you a solid baseline to build from and helps you create the next level of data champions who are eager to learn more. 

    The good news is, finding your volunteers need not be an arduous process. If you present the benchmarking to employees as a free diagnostic to help them score their own data literacy, I predict that you’ll create a lot of interest. It took me less than two days to hit our quota of ten percent of our workforce. In fact, we were oversubscribed. Clearly, there is interest and appetite out there for people to know the state of their data literacy so they can identify where improvements are necessary.
  3. Create learning pathways. Ensuring that the world of data is accessible to employees at every level is an invaluable piece of a successful data literacy framework. We created three pathways to address literacy levels, from curious to expert. This included a mixed set of materials covering topics from the basics of data security, data engineering, and data quality, to data insights, visualization, and master data management. Offer a broad set of topics to give people what they need to develop this new language and vocabulary and they will find their level. 
  4. Provide immersive learning approaches. These can range from hackathons to show-and-tells. Both have terrific potential to demonstrate the value of new technology, help people from across departments collaborate better, and encourage prototyping of dashboards and other data visualisation tools that the organisation may end up embracing. 
  5. Establish a learn, test, and reflect structure. Focus on doing the basics brilliantly in data literacy training. That means practices, methods and techniques that are simple, repeatable and robust, and that let your employees build their knowledge, evaluate it frequently, and see where gaps may still exist. 
  6. Build out your core data team. In conjunction with reaching colleagues who have a thirst for learning, focus on building out your internal data capability. Having the right core data team in place is essential. It has taken us two years, but we now have a full squad of data engineers, data scientists, and data analysts. They work as an internal center of excellence that continues to drive our data efforts forward. 
  7. Invest in a platform and services. A big piece of the puzzle is investing in data analytics and cloud platforms as well as services. This will help you move even faster in providing insights to your colleagues across the organisation, and to do monitoring and continuous integration and delivery.

 

As a final note, once you are up and running it’s a good idea to establish an internal data marketplace that you can share and make readily available for the business to see what sort of data sets are available. And because this marketplace should be part of your overall strategy, provide data insight services as well as self-service analytics that users can draw on themselves. 

Also remember that a good data literacy program always helps people to push their own boundaries. Case in point: at the beginning of our program I wrote a handful of articles to set the stage. As the program grew I said, “Okay, the entry level to join now is that you write an article and I will then help set some parameters around it.” I wasn’t quite sure what to expect, but we saw non-technical businesspeople who had never touched analytics or data analytics before creating some fantastic articles with a bit of coaching, a bit of guidance, and a few research links.

It's success stories like these that remind me how far we’ve come. Build a strategically sound data literacy program and you’ll soon be collecting your own.