Nowadays our life is driven by data! Almost everything is turning around data! Not only our daily working life, but also our private one. To bee able to suceed in this data driven society, people, companies and workforce need to be able to understand, interpretate and mainly speak data as our new second language. The so called data literacy era!
What is Data Literacy?
Data literacy is the ability to read, understand, create and communicate data as information. Much like literacy as a general concept, data literacy focuses on the competencies involved in working with data. As data collection and sharing become routine and data analysis and big data become common ideas in the news, business, government and society, it becomes more and more important for students, citizens, and readers to have some data literacy (ref: https://en.wikipedia.org/wiki/Data_literacy). Data literacy is the ability to derive meaningful information from data, just as literacy in general is the ability to derive information from the written word.
The complexity of data analysis, especially in the context of big data, means that data literacy requires some knowledge of mathematics and statistics. To deal with that complexity, many organizations are hiring specialists called data scientists or data engineer, who have advanced analytical skills. But this is for sure not enough. Nowadays all people within the organization should have at least a common understanding of their data, of their daily business to be able to take decisions, to share ideas and knowledge to be able to grow faster in a data driven environment.
What are the key factors for a data literacy culture?
– Knowing and using the right data for the right business case
– Interprating reports, data visualization such as graphs and charts in the right way
– Thinking in an analytical way
– Understanding tools and methods and apply them in the right moment for a specific use case
– Creating a collaborative working culture
– Sharing information about data and their insights to pople lacking data literacy (well known as Data Story Telling)
– Empowering employees with the right tools
Why a collaborative plattform?
Once employees have access to data, they need to be able to view, add, manipulate them with the purpose to share results with colleagues.
During my working experience I recognized that Excel is still a religion in the daily working life, which of course is not bad as Excel is a great tool for small daily tasks, but still confining data to a desktop application is limiting in a lot of aspects (last but not least the limit of size), leads in many cases to inconsistencies and missinterpretations and creates dangerous data islands within an enterprise . Out-of-date data, conflicting results even when people within an organization supposedly looking at the same figures, which leads to discontent, dissatisfaction and confusion.
On the other hand having a common platform for viewing, analyzing, and sharing data is helpful. It provides a single source of truth, ensuring everyone has access to the latest information. It’s also much easier to set policies around security and governance, which nowadays plays a crucial role and goes hand in hand with legal and regulatory compliance.
My personal experience says that one of the key points of introducing such collaboartive plattforms is to guarantee and ensure the end-user that he is still the owner and in full control of its own data. If this is not the case the introduction of a data literacy culture and way to think and work won’t succeed.
Don’t stop on the surface, dive deep
Analytics are only as good as the underlying data, and employees must learn to think in analytic and critical (still constructive) way about appropriate use of the information they have. Data can be out of date, incomplete, or insufficient to draw meaningful insights from. Acting and deciding on the wrong data will lead to bad decisions, which means waste of resources (time and money).
And what if we turn it in a game?
Gamification has nowadays emerged as a new trend. Using motivational techniques like those the videogame industry has put to such effective use. Who has not spent some hours on their own, trying to get to the next level of their favorite game. We love to challenge ourself, regardless if in sport, games or work. This is our human nature! As gamers love to match their skills against others and to compare notes on how they’re doing
Both gamification and big data are big business buzz words today. It might be surprising to some that these two separate concepts actually work well together. Gamification can be a helpful tool to gather data, and in some cases, it can also help analyze that data and at the same time will increase statisfaction, motivation and productivity of employees.
Gamification for sure won’t replace the data mining and other traditional tools of big data analysis, but under the right circumstances, gamification can have an appropriate place in the data analysis toolbox and data literacy culture.
In my role of BI Consultant I have encountered plenty of cases where business people thought they know everything about their data, but ended to show big gaps in their understanding and their usage. Most of the time I encountered cases of uncomplete data, lack of knowledge of own systems and available interfaces, lack of time to understand own data, missing 360° view of company processes and data, missing or wrong tools to put data together and last but not least wrong culture in the workplace and ethics to a data driven society.
The biggest challenge nowadays is to “eat” and speak” data as our second language.
The emergence of data and analytics capabilities and technologies, including machine learning, artificial intelligence and deep learning requires people to “speak data” as a common language. Data and analytics leaders must champion workforce data literacy as an enabler of digital business and its transformation by empowering enterprise company and their employees with the right tools. On the other hand organizations must take steps to educate professionals who are involved in creating data-driven solutions and services. They must make sure those steps achieve the goal of teaching all relevant employees to speak data as their new second language, as well as developing and feeding communities where people can share data, discuss results and ideas, and take winning decisions for their own business in an agile and light iterative process.