As part of our exploration into the skills and competencies needed for data literacy, I’ve been interviewing data leaders in businesses to better understand how they are approaching the challenge of helping their organizations become data literate, as well as what skills and competencies they believe are core to data literacy.

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Many organizations are straddling various levels of knowledge and skill in this area. They have built up some good capabilities, but the evolution of machine learning and AI is faster than business leaders can follow and they are struggling to take full advantage of these new approaches. 

So where to start in developing the skills people need to have? Not everyone needs to know how to shape the insights we can generate with the likes of PowerBI, SiSense or Tableau. However, many of your employees do need to know how to use the insights. This could be something as simple as reading a time-series graph and applying what you see to decisions in your particular function , to a complex as understanding the limitations of a machine learning application and how it should inform decision making.

Using personas to define individual maturity in data usage is an excellent way to understand several aspects of the data literacy journey. Personas can guide data leaders in deciding who to engage with, as well as what skills need to be developed. Different personas will contribute to the value of data in different ways. It is not one size fits all. Role based competency models can bring this into focus and accelerate the speed at which people can begin to contribute.

In my recent conversation with Bob Samuels, Head of Data for Widen Enterprises, Bob explained how Widen is using personas to guide aspects of their data literacy journey. Widen is a Digital Asset Management SaaS company based in Madison WI. Understanding data about content, users and usage is critical to their business. At Widen, personas are used to align learning and development opportunities They are even used to gate access to key features of Widen’s business intelligence platform. Training completed and the groups a person participates in can determine what data and functionality can be accessed.

Widen Senior Data Engineer and Architect, Molly Vander Velde, came up with the personas:

Persona - The Data Consumer

These are individuals in the organization who don’t necessarily need to know how to shape insights, or manipulate source data to do so. However, they do need to understand the meaning of data once it’s been packaged for consumption, to use it to to make decisions, or to justify the development of new products, features or initiatives.

Persona - The Data Discoverer

These individuals are deeply curious, and naturally inclined to probe data for insights, but may only have the broad brushstrokes of a question they are trying to answer. These are the people in an organization who are rapidly evolving their ability to ask questions. They want to understand what the data tell them, and how to use data to answer questions. 

Persona - Data Designers

These are the individuals who shape the insights derived from source data. They help the other persona consume those insights, make decisions and take action. Data designers have a unique responsibility to ensure that the proper meaning of data is conveyed. This involves a deep understanding of how the data is generated and governed.

Data designers are also responsible for ensuring that everyone understands what Prashant Motewar, Head of Product Management and Business Engagement for Data/Analytics for Equinix calls ‘data lineage’. Particularly when source data has been used to create new metrics, it’s vital that the consumers of those insights understand the components behind those metrics, how they are weighted in calculations and how the origin of that data influences what kinds of conclusions one can drawfrom it.

By now, you can probably glean why personas are so powerful as a tool for guiding your organization’s journey toward data literacy. At Ibbaka, we’re looking at personas as a way of organizing competencies and skills into roles, which can then be represented in an open competency model for data literacy. Open competency models are skill frameworks that can be used and adapted by anyone, as long as they make proper attribution to the model’s source when using it. 

Widen’s data literacy personas are an excellent example of how people with different job titles in your organization can have roles that overlap, along with their accompanying skill sets. For example, within your C-Suite, the role of ‘data discoverer’, and the skills that go with it, may be widely shared. 

The Ibbaka Talent Competency Modelling environment allows organizations to design flexible competency models that can be used to define and combine roles together with their skills, competencies and behaviors. These can be reused across your organization to assess skill coverage and gaps, as well as to help individuals identify skills they need to be successful. To be part of our work in skills and competencies, subscribe to our blog. Or feel free to reach out to us for a conversation.

Other posts on data literacy

• Who needs data literacy? (This post)

• What skills are required for data literacy?

• Data Literacy and Skills: Asking the Right Questions

• What does data literacy do for you?