Data Literacy — A Must have Skill for All
In today’s blog we will understand the term data literacy and what makes this skill so important in data-driven business organizations and how one can become a data literate. Organizations need people with the ability to interpret data and to draw insights that improves business performance.
We will be seeing the definition of data literacy, why it is important, what the challenges are, how to overcome them and what kind of mindset and attitude a data literate person needs to have. There is more to this skill that encompasses — data governance, data security, data analysis, data storage, data visualization, data storytelling, data ethics, etc., which depends on what role one is in the organization. For example : a data analyst needs to be more knowledgeable and skilled at data analysis and visualization then an account manager but both need to be able to talk in terms of data and have understanding of what analysis is being done and what is shown on the dashboard, so that both can interact with it and have a conversation.
What is Data Literacy ?
Before we define data literacy let’s define what literacy is and expand that definition to data literacy.
Literacy can be defined as the ability to identify, understand, interpret, create, communicate and derive meaningful information from printed or written words.
Data literacy can be defined as the ability to derive meaningful information from data, by reading, analyzing, speaking and thinking critically about the data.
We don’t need to be data scientists to understand or work with data , but all of us do need possess and be confident in our data literacy skills, i.e. — the ability to effectively read and comprehend the data and information that is presented to us. We need to analyze the data to find the insight within. With good actionable insight, we can make data-driven decisions and empower people. Finally, we need to develop skills to communicate effectively with data.
To derive meaningful information from data, we need to look at the data and understand it. Data Literacy gives the ability to question the data quality, data integrity, the analytical methods or formulas used that led to the result and to question the statistics behind it.
Asking these kinds of questions, assists us in developing curiosity towards our data that will be consumed within or outside the business organization. We need to have a critical eye towards the data and the answer provided for the questions asked and its usefulness.
Data literacy is a skill that helps us to answer following questions that assist in delivering high quality data that is truthful to its nature.
Do you trust your data ?
- Data Literacy is the ability to question if my data is accurate.
2. Data Literacy is the ability to question if my data is useful.
Do you trust what you see ?
- Data Literacy is the ability to understand how aggregations were calculated.
2. Data Literacy is the ability to understand basic statistics.
Do you trust what you create ?
- Data Literacy is the ability to use facts to communicate complex ideas, without misleading your audience.
2. Data Literacy is the ability to use all the facts, including missing data.
Why do data literacy skills need to be developed across an organization ?
In today’s era of data and digital transformation, the responsibility of skills development has shifted from academic institutions to business organizations, where various development programs are flourishing. Companies like Bloomberg, Guardian Insurance, and Adobe now have data science and digital academies that are focused on helping employees in all disciplines learn how to analyze data.
By 2023, data literacy will become essential in driving business value, demonstrated by its formal inclusion in over 80% of data and analytics strategies and change management programs. — Gartner
Challenges
- Dismiss data because they are unable to comprehend it.
- Cultural Challenges.
- Complexity ( human thinking ).
- No common language.
Data is a language that anyone can learn to read and speak. We need to start seeing data as the beginning of the conversation, not the end — Engage in thoughtful dialogue. It’s a new language we all need to be fluent in.
Data Literate Person
The qualities that a data literate person needs to have are : curiosity and creativity.
Curiosity helps us to have a healthy skepticism about the data and to ask the required questions that help to understand and uncover hidden trends and pattern present in the data.
Creativity allows us to explore and fiddle with the data, keeping the business objective in mind and coming up with multiple solutions which might be unique/creative/different/optimal to the business use case.
Both these qualities combine the art and science of data and assists a person to make sense of the massive amount of data (big data) involved in creating dashboards and interrogate each story that relies on it.
As we become more data literate, we cultivate an alertness about the data and become truthful, logical and bring value to it and at the same time protect the integrity that the data has to offer.
Lets consider an example of Rental Car business in an Online Travel Company:
Performance of any business can be measured in terms of monetary value i.e. sales, revenue, or in terms of total transactions made, etc.
The below dashboard shows a sample data of rental car business for a single day, we can see Total Price value and the input among different rental partners and fare types.
A person who understands the business and data related to it may ask a question like
Q. What is the metric chosen to measure the performance of rental car ? or Is Total Price the right metric to measure the performance in terms of monetary value ?
Rental car business measures its performance using of Total Net Value and not Total Price.
Total Price is calculated as partner revenue + merchant (OTA) commission + taxes/fees, whereas Total Net Value (TNV) is calculated as post no show, post cancel commission/margin + insurance margin + ad revenue etc. It does not include taxes and fees.
It is important to understand the business and how it measures its performance and success and leverage the data analytic tools to process and present the data in a most intuitive way.
After selecting the right metric, let’s look at the below dashboard. Upon observing the dashboard we see that the TNV value shown considers only confirmed reservations.
Q. Is it the true/right representation of performance of rental car business ?
To get the true or right performance value we need to consider the reservations that were booked as well as reservations that were canceled, to get a correct understanding of how the rental car business is performing overall.
A data literate person who has a good understanding of business, data and technology will ask questions about the analysis done and shown. Having a curious mindset will help (in this example) a dashboard to become an outcome driven dashboard i.e. it provides insights or actionable items
for various teams when they engage with it.
At the end, data literacy isn’t just about visualizing or understanding charts, it’s much broader than that, it’s how we think about data and it’s about people, it’s how we arouse the curiosity and ability to ask questions.
Recommended Learnings
- Data Literacy video — Tableau.
- Data Literacy Program by Arizona State University.
- Tableau Learning Program.
