
Data is the new oil; to transform it into rocket fuel, you will need to teach your people how to use it.
With the evolution of Artificial Intelligence and other technological innovations, many companies neglect what remains the main asset of any business: its human capital. Humans generate data; data is the new oil; it is the new currency.
If you have the impression that you have heard it before… The phrase "data is the new oil" is not mine.. but it was said – and has been repeated since it was coined by the British mathematician Clive Humby in 2006 – to denote this value and power in the data in our business lives.
Data is not just numbers; they are texts, videos, images, audio, and all kinds of information encoded. Data are even people. The combination of millions, billions, and trillions of information make up what we call Big Data.

What is Data Literacy
Data literacy is a relatively new concept that emerged simultaneously in companies using business intelligence to make better decisions.
It’s the idea that everyone should know how to make decisions with data to perform their function fully.
Gartner defines Data Literacy as "the ability to read, write and communicate data in context, including an understanding of data sources and constructs, analytical methods and techniques applied – and the ability to describe the use case, application and resulting value."
Data literacy is a perfect analogy to a person’s literacy process in their mother tongue: it requires effort, repetition, reading, accompanying professionals in the field, and interest … But, once this step is taken, the process flows. And when people are literate, they read, write, work, communicate, think, reason, and argue in that language. Data literacy works the same way.
The data has no meaning in itself. You can take the data out of context, like a letter or a number, and make it almost meaningless.
A routine but straightforward example: a Google search with only the word "Plant." The results are disconnected and varied, mentioning: planting soybeans, planting a banana tree, planting a chip, and how to plant a tree … So, so it is necessary to contextualize and specify the searches so that the data found are more assertive and accurate.
Data – without the interpretation of people – has no meaning in itself. However, the combination of human reasoning ability with artificial intelligence generates some conclusions about the information. Although data analysis can provide a significant differential for the organization in several aspects, one must not lose sight of what is behind all this, precisely the people.
Data scientist and analyst Susan Etlinger speak in her TED talk: "We have the opportunity to give the data meaning by ourselves. Frankly, data does not create these senses; we do". And how can we create these meanings for the data?
_"We are not passive consumers of data and technology. We shape the role they play in our lives and the way we give meaning to them. But to do that, we need to pay as much attention to how we think about the way we code. We have to ask questions, tough questions, to move from the moment of ‘telling’ things to the moment of understanding them", according to data scientist Susan Etlinger._

Why Does it matter?
This ability to read, work, analyze, and argue with the data must be implemented in all functions and employees at all levels of competence.
A good data analysis strategy gives everyone in your workforce the power to make discoveries that lead to change.
That is why all organization members must be able to use data to drive results, reinvent business processes, understand customers more deeply, discover new sources of revenue, and better-balancing risks and rewards.
In the TED Talk below, you can overview how appropriate data literacy can help us decipher what is true and what is not without becoming data scientists or how we can use the information to make better decisions. Have a look:
Why everyone should be data literate | Jordan Morrow | TEDxBoise
The Data Literacy Project
Recently, Qlik and Accenture surveyed more than 9,000 interviews (with people from different industry segments, from C-light to beginners, in nine countries in North America, Europe, and the Asia Pacific) and produced a report about the current scenario of data literacy in companies.
The report brings a somewhat worrying reality: although managers consider that they are developing actions to be guided by data (data-driven), the breakneck pace of some changes is eventually causing anxiety, fear, overload, uncertainty, and even sadness among employees.
According to the survey data, 74% of respondents reported feeling unhappy (unprepared, insecure) when working with data.
The machines can process an increasing volume of data and information with more sophistication and agility, making thousands of combinations and even imitating human behavior, suggesting specific responses to a service’s users.
Thus, it is inevitable that they will be increasingly desired and used to automate various companies’ processes. However, it turns out that, as mentioned above, this has caused distress and overload for employees who have to deal with a daily mountain of information, updates, and new tools.
Even if they feel uncomfortable dealing with data, they recognize that it is an asset to the organizations they work for and believe that data literacy training would make them more productive.
Data literacy allows operations leaders to communicate success measures to the c-suite. It helps finance convey urgency when the sales function is not meeting quarterly and yearly targets.
Improving business data literacy positively affects gross margin, return on assets, return on equity, and return on sales, resulting in a $ 320 to $ 534 million difference in companies’ values that focus and do not focus on Data Literacy (data provided by The Data Literacy Index ).
The study also found that 76% of top business decision-makers do not trust their Data Literacy skills.

The impact of Data Literacy
Therefore, the critical point is to include people, involve all sectors in data analysis, break barriers, and overcome technical issues to democratize and demystify access to data. In this way, the company can benefit as a whole.
This also impacts relevant aspects of culture, stimulating the exchange of experiences and knowledge, a collaboration between peers, regardless of the area, and continuous learning.
Having a healthy and robust culture and preparing people to deal smoothly and efficiently with data-based decisions are strategic issues to build a more humane and pleasant corporate environment – characteristics increasingly valued by the market – and optimize results, including financial.
Dissatisfied and anxious employees may unconsciously contaminate the company’s culture and become demotivated.
When accounting for the slowness in the execution of medical processes and licenses resulting from stresses resulting from issues associated with data and technology, companies lose an average of more than five working days (43 hours) per employee per year.
Of course, changes in culture do not happen overnight, but it is a fact that it is in constant motion. Knowing this and how much this is a fundamental pillar, managers must always be attentive, seeking to share this responsibility to develop a fair culture based on values that make sense to the teams, in line with the organization’s interests.
Thus, digital inclusion becomes a less stressful process and with better results, since people will be more open and willing to incorporate new tools into their work routine, understanding more deeply not only the functionalities related to these technologies and data but the gains that she can have with this and, consequently, being more genuinely interested in analysis, data, etc.
Therefore, before investing millions in data usage projects, invest in people, as they are the key to Data Science strategies and other projects. If it is necessary to take a step back or slow down the implementation of the analysis to educate employees about data more cautiously, including making it attractive to these people – and not only those used to the data -do hesitate. The results in the medium and long term will be justified.

Conclusion
As we can see, Data Literacy is the idea that everyone should know how to make decisions with data to perform their function to the fullest.
It has a relevant impact on aspects of our business culture, stimulating the exchange of experiences and knowledge, the collaboration between peers, regardless of the area, and continuous learning.
Due to stress-related data and technology, companies lose an average of more than five working days (43 hours) per employee per year. The only way to reduce this stress is with data education and awareness.
Data awareness as a second language is necessary for the present, not just the future. Are you and your company working to make it happen? Tell me about it in the comments!
One more thing…
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