How to develop team-based data literacy in your organization

“They are just navel-gazing,” my boss told me. Many years ago, I heard this term after a meeting where most of the attendees acted like the meeting did not apply to them.

If you are in ancient Greece practicing meditation, navel-gazing is the proper way to describe the position of your head. In modern terms, it means the “useless or excessive contemplation of a single issue at the expense of a wider view.” (Google dictionary)

Data literacy in the corporate world has a navel-gazing problem. Not everyone, but most. This is how you can tell if you do, too.

• Using “I-measures.” Your data literacy program has an impressive dashboard showing the contribution of disparate activities, workstreams, or functions, not the whole. They reinforce the idea that I measure what I am responsible for.”
• No R.O. But you track Investment. (Also referred to as vanity metrics and success theater, terms coined by Eric Rese, “The Lean Startup.”)
• You look at data literacy program metrics in units of Individuals,” e.g., how many have been trained, have a skill, or got a certification.
• You define a data literate Individual as someone with the ability to read, write, and communicate, etc.”.

Do any of these describe what you do?  If you are still not sure, click here for more telltale signs.

When actions are excessively focused on the individual, you miss the wider view - the view that shows how data literacy benefits your business and the leaders and employees you serve in the data literacy program. To be effective, data analytics must have a wider view.

Give this definition some thought: 

A data-literate organization (not an individual) is one that creates new business value through data. 

What changes with this definition? The data literacy program and metrics become very actionable.

First, data literacy happens when skills are put into practice during hands-on, end-to-end data analytics. Do you have a data analysis process for non-data experts? If not, then you are not aware of the analytics process skills they have or might be missing. That is a big gap in your assessments and training. 

Second, the definition means teams are core to your data literacy strategy. If you think about it, data analytics has never been an individual effort. Teams comprise business people and data people working together on a specific business problem and who have the relevant mix of skills needed to solve it.  Do you assess team-based competence ?

Third, the definition should cause you to ask questions about business value. Data analysis can be a journey of a thousand questions. That is why people often feel like they are drowning in data. The first questions should be about the potential business value and how it can be unlocked. The answer is most likely sitting in Product, Marketing, Risk, Operations, or HR. Not in the data function.

Every successful team engaged in data analysis has these three characteristics:

1. Functional business leaders provide the team with the strategic context behind the problem or opportunity and empower the cross-functional team to work on it. They know how to engage with the team throughout the analysis process.
2. The team has collective accountability for coming back to decision-makers with actionable recommendations backed up by data that deliver impact. 
3. New ways of working (NWoW) that fit team-based data analytics and change mindsets. These are practical, hands-on working agreements. Not vague concepts, models, or a list of principles. Working agreements are tied to business impact. (similar to how product management is tied to value delivery.)

What does it take to get a wider view of your data literacy strategy?

Work with senior leaders to define a few key data analytics projects. Train leaders to champion the data analytics process and engage with the teams at critical moments during the project. Then ensure each team has the assessment and training needed for their project.

The assessment needs to cover more than charts, stats, and storytelling. Training is not the typical learning path that is given to individuals. Training is relevant to what they need to solve the specific problem.

Once you get leaders and team members aligned, trained, and working together, you will quickly see a significant shift in mindset. 

Continue reading , for more details on developing organizational data literacy through teams and how to convince leaders to do it.