Companies with a higher data literacy rate can leverage data to better understand their customers’ needs and product usage. This insight allows them to develop better products and create a delightful customer experience. It then drives greater revenue and accelerates business growth. But, what does data literacy mean?
What is Data Literacy?
Data Literacy is the ability to read, digest, and interpret data toward meaningful discussions and conclusions. It is one of the four pillars of developing Data Culture in your organisation. The other three being: Data Maturity, Data-driven Leadership and Decision-making process.
Understanding Data Literacy
Now that we know that data literacy is important for an organization, how do we ascertain if a company and its employees understand and interpret data properly?
Let us consider an example:
- Campaign A had a conversion rate of 46%, while campaign B converted 74,000 people
- Campaign A had a conversion rate of 46%, while that of campaign B was 38%
- Campaign C converted 21,000 people, while campaign two converted 74,000
Which of these campaigns performed better?
If employees of a company are asked this question, the answers would normally vary. On the basis of their answers, the employees can be categorized into seven data literacy personas.
Different Data Literacy Personas
- Data Skeptics — They are employees who are most likely to ignore the data available to him. They will make decisions based on their own understanding or intuitions.
- Data Enthusiasts — They consider the data available to them, show interest and acknowledge its importance.
- Data Literates — They have a better understanding of the above-mentioned scenario. However, they are likely to be not able to ascertain which of the scenario is better.
- Citizen Analysts — They are able to follow a structured process for analyzing the campaign. They will be able to conclude which campaign converted better.
- Digital Citizen Analysts — They possess the same skillset as a citizen analyst except that they can design and analyze A/B tests.
- Data Scientists — They are able to employ more advanced methodologies to take the learnings further.
- Data-driven Executives — They can interpret the results their teams present and make positive decisions.
It is important to understand that developing Data Literacy in an organization does not necessarily mean that every employee needs to be of a data scientist persona or above. In fact, having so may backfire.
Data Literacy calls for all members of the organization to have a certain level of understanding of data depending upon their job role and the decisions they need to make.
A company that has 75% of its employees data literate or above is considered a data-driven company. In such organizations, decisions are taken using a structured process based on data, facts and/or assumptions. The employees know what to look for and when to look for them. They understand the driving factors of the business.
Five steps to develop Data Literacy in your organization
One of the most important things needed to develop data literacy in an organization is to have a data-driven leadership. The leaders of the company first need to champion the nuances of Data Literacy. Following that, they can lead the path in making the company data-driven.
If your organization has a data-driven leadership, Here are the five steps to build data literacy:
- Defining Data Literacy in the organization: The first thing to do is to define what data literacy means for your company. You will need to ascertain the level of data literacy of each of your employees.
- Data Culture Assessment: Now that you have information about all your employees, you will need to evaluate the data to understand where the organization stands in terms of Data Literacy. With a clear picture, you will understand the changes you need to achieve your goal.
- Planning a stratified learning solution and success metrics: At this stage, you would need to develop a stratified learning plan for your employees to push data literacy in the organization.
- Communication and Execution: As a Data Literacy project is essentially a change-management process, it is important to create and execute a cohesive communication strategy. The company’s DNA should be incorporated when doing this step.
- Evaluation and Improvement: As with any projects, it is necessary to evaluate the progress. You should gather reports on a monthly or quarterly basis. This would allow you to tweak the project to better meet your goals of achieving data literacy.
Data Literacy Framework
Following a structured approach when working on any project makes it simpler to do and the results more effective. Here’s a tip: Similarly, using a recipe-based approach will help you gain progress easier and faster. One such example is BADIR, Aryng’s structured analytics framework.
BADIR enables actionable hypothesis-driven analytics and ensures that the right problem is being solved.
- Identify the Real Business Question – The process of analytics starts with clarifying the Business question as a problem well stated is a problem half-solved. The Business Question framework gives the ability to get to the real question, i.e., what exactly are we trying to solve?
- Layout a hypothesis-driven analytics plan – Plan before you act and make sure all the key stakeholders agree with it. A hypothesis-driven approach enables accelerated discovery of insights toward the problem at hand.
- Pull relevant data – BADIR propounds using hypothesis-driven plans to winnow down the exact data needed to answer a question. This makes reaching insights in the fastest manner possible.
- Convert it to insights – BADIR has an exact recipe to follow for every methodology you will use. Also, it has clear guidelines on which method to apply for different kinds of problems. The insights recipe provides accurate analytics and the fastest results with early check-ins with stakeholders priming them up for action.
- Make recommendations to drive impact – With BADIR, we have the exact science to make winning presentations loaded with actionable recommendations that drive dollars and influence.
Every company has big rocks and KPI that they genuinely care about. Every project that the company works on should tie up to those numbers. The projects should be decided based on how it moves these top metrics. The question is how to identify the critical analytics projects your organization should be working on, i.e. how to lay the organization’s analytics agenda. We have a structured framework for that. Please email us at email@example.com to get your copy.
Aryng is a Data Science consulting and training company. We are a unique partnership of analytics professionals with decades of experience in Fortune 100 companies, conducting analytics, building and managing Business Intelligence and Analytics teams, and delivering cumulative results in the $100s of millions.
Aryng’s SWAT Data science team is uniquely positioned to get guaranteed Rapid ROI because of our proprietary hypothesis-driven BADIR framework, which aligns the stakeholders to a standard problem definition, rapidly brings to an actionable solution, and preps the stakeholders toward actions and dollars.
Aryng’s proprietary and unique BADIR framework drive ROI with training. We have industry-ready, immersive, hands-on training that delivers impact. We have role-based training from citizen analysts to data scientists. Our training uniquely covers Data Science as well as Decision Science that takes insights to decisions and then to dollars. Our applied learning ensures that the data culture is established through live projects from their work.