Although digitalization resulted in generating more data than our previous generations, Covid has highlighted the need to understand data at a rapid pace. Whether it is hospitals trying to staff based on local virus outbreak or companies trying to sustain business due to global supply chain disruption, pandemic has presented some unique challenges to get better at consuming and interpreting data. But not all data is created or understood equally.
Why is data literacy important now?
There is no shortage of data we collect and store but we have an insufficiency of people able to understand the data. Data by itself hardly has much meaning attached to it. It is the people who give it the meaning thereby using it to achieve business outcomes.
There are several definitions of data literacy if you google and it is an emerging area with people coming up with their own versions of it. My version of data literacy (DL) is getting a certain proficiency and comfort with data usage in both personal and professional lives. It is no different than financial literacy which has been around longer. Just earning a paycheck with no budgeting or investing will result in an uncertain future. Similarly collecting data and not planning a way to use it will soon lead to losing competitive edge in the current market.
"My version of data literacy (DL) is getting a certain proficiency and comfort with data usage in both personal and professional lives."
Without an enterprise level data literacy initiative, it is like giving a person all the needed ingredients to bake a cake without understanding their baking skills. Just creating dashboards and investing in technology solutions will not result in business value. There is a data understanding gap between people in technical and non-technical fields. Purpose of data literacy programs is to narrow and eventually close such gaps.
Anxiety around data
With the volume of data collected and increased expectations from teams to use that data to make decisions is creating stress and anxiety. Most of the working population did not get a formal data literacy education as part of their schooling and hopefully it will be addressed by schools for future generations. Everyone is not confident to step out of their comfort zone to experiment with data. There is a fear of failure in the unknown territory which is holding back teams from utilizing the self-service analytics capability the company built. Common myth about data literacy is it being a bunch of training or being able to code in R and Python or becoming data scientists. Hence launching a data literacy program and hoping everyone to follow along is not a realistic expectation.
Below are some tactics to lead a successful enterprise data literacy program:
Tactic #1 Get leadership buy in
Data literacy should be driven by leadership and not handled as an IT push. Leaders should be aligned and appreciate the value of data for enterprise data literacy to attain success. They should be active participants and willing to invest both time and money.
"Data literacy should be driven by leadership and not handled as an IT push."
They should level-set high level expectations by functional/job roles related to usage of data. This will ensure a clear vision and roadmap for data literacy over the years.
Tactic #2 Start small
Every organization’s data literacy journey is unique and to succeed it is vital to start small with a pilot project. Create a small user group of people, demonstrating value of data towards their day-to-day operations. DL is an iterative process with feedback loops to improve prior to enterprise level roll out. Other team members will become more engaged when they see quantifiable outcomes.
People learn at different speeds and make mistakes during the process. Create a small safe learning environment to eliminate fear of failure thereby others wanting to come onboard.
Tactic #3 Approach data literacy as a culture change
Any organization consists of data doubters who will question the value of data and prefer using their legacy knowledge over data. Not everyone is equally curious and excited to start using data and for data literacy to win it is essential to acknowledge it.
Cultural change is complex and requires persistence to shift to a new direction. If data usage was not a common practice in the organization without a single source of truth, it will require significant effort to change this mindset.
As the famous saying by management consultant Peter Drucker goes “Culture Eats Strategy for Breakfast", any data literacy strategy will miserably fail without cultural change.
Some organizations make the mistake of starting data literacy too soon without a clear idea of how to give data access. This shuts down the users before they start.
"Any organization consists of data doubters who will question the value of data and prefer using their legacy knowledge over data."
Tactic #4 Pick the right tools
It is not always picking the fanciest tool available in the market. Try to gauge the current skill level of the teams and pick a functional tool to suffice keeping the learning curve to minimum. Everyone’s creative and analytical skills vary with one overpowering the other skill. During the tool selection process, it is fundamental to have some sense of collective team skills and select tools that the team can easily follow. There are several no-code tools available which allows users to engage with data without any coding training. Also try to stick with one unified tool when possible instead of confusing users with several tools.
Tactic #5 Define what success means to you
Success could mean different things for various organizations. It could be getting real time data in the hands of most team members helping them to come up with better solutions. It could mean less errors or production issues or better customer service. It could mean no data breaches.
It is a prerequisite to define what success means to your organization in 3, 6, 12 months and years to come. This will enable staying on the forward looking path of improvements. Define success with an understanding that it is impossible to timebox data literacy by saying “We will be data literate in 3 months.” DL success is a gradual progression over time and celebrate the small wins in that direction.
Data literacy is an evolving area and every organization’s need differs. These tactics will drive and foster enterprise-wide data literacy.
