What should every data scientist be able to do?

5 reasons why you should train non-technical workers in data skills

Know-how in data is often only required by data scientists. But what if companies started teaching other employees at least basic data skills? It is actually a necessary step to bring a company into the age of digitization. The digital transformation is not just a gigantic transformation project, but the continuous development of an organization.

You have probably heard the quote: "Data is the new oil". Almost every organization and service provider collects data. Some see them as their most valuable resource. However, regardless of the sector, the collection and handling of data is usually managed solely by a relatively small team of data experts. While data scientists are still in high demand and difficult to hire, in most cases the reason for small data teams is actually unintentional. Organizations manage their data skills in a departmental vacuum, even if the information resulting from the data would have to be available and used company-wide.

You may be familiar with these issues:

  • Data scientists often get frustrated working with colleagues from other departments who lack basic data knowledge and understanding. Also, data scientists often do not receive the necessary support, neither with data collection nor with the expertise of colleagues.
  • Corporate stakeholders are dissatisfied because data requests take too long or questions are not answered adequately.
  • Management is dissatisfied because they are not getting the numbers and insights they need to develop or validate strategies.

Often, one cause of these problems is insufficiently efficient communication due to a lack of data expertise.

Data literacy is the basis of the fourth industrial revolution.

Data literacy means the ability to read, work with, analyze, and argue with data. Or to put it more simply: Everyone who takes part in the modern world of work must be familiar with the handling of data.

Implementing data literacy across the enterprise is the foundation for developing a digital mindset and culture for a successful business in the 21st century. Contrary to what some might think, ubiquitous data knowledge doesn't make data scientists and their expertise obsolete. Instead, it encourages them to work more efficiently and effectively and to concentrate on their core competencies.

With that in mind, here are five reasons every employee needs data literacy training, and even your company should be considering it.

1. In the fast lane to a digital and data-driven organization

In order to achieve the target state of a data-driven company of the 21st century, company-wide data knowledge is required. People in very different roles need data literacy to get the most out of various tools and large amounts of detailed data. In addition, the increasing automation of business processes requires employees in more traditional business roles to understand how data is collected and processed and how this affects their roles and responsibilities.

A recent study among chief data officers classified poor data literacy as the second biggest success blocker (source: Gartner).

As organizations become more data-centric, poor data literacy becomes a drag on growth and ultimately a bottleneck. On the contrary, giving everyone access to the data and the ability to interpret it can accelerate the transformation of a company into a digital company. Ultimately, it makes operations more streamlined and efficient, as those who can gain insights from the data themselves no longer have to wait for data scientists to decipher the insights. The bottleneck has been eliminated.

2. Everyone needs to make smart, informed decisions based on reliable information

After all, data collection is worthless if not used knowledgeably. Data needs to be translated into insights. Making smart, informed decisions in any organization requires widespread use of data.

Numbers bring light into the dark. Data helps to underpin ideas and strategies, to gain objective insights and ultimately to give employees meaning. In practice it can look like that you identify cost savings, find (in) efficiencies and find out how you can work more effectively at your workplace.

Data is a valuable asset, but it must go through people and refinement to gain value.

3. Make insights accessible to everyone: translate and visualize data

To really get the most out of the data it collects, every organization needs great data translators. They efficiently formulate requirements for data scientists and visualize information in order to make it easier to understand for everyone involved, but above all for decision-makers.

Data visualization is one of the most sought-after technical skills in 2020 (Source: Northwestern University).

Let's just illustrate a few examples of how data translation and visualization on a non-data team can improve any business:

  • Use objective evidence to convince prospects to buy your products
  • Manage production efficiency
  • optimize employee performance

Actually everything is measurable and can be used to adjust the KPIs. So far, all data that computer systems and tools collect only occupy storage space unless it is regularly viewed, interpreted and shared with others.

4. Jump to a customer-centric company

The use of data enables a dedicated customer-oriented business: Understanding user data and using it for product modifications and the development of new products.

As with tech giants Netflix, Google, and Facebook, you can leverage user data to improve your customer experience. This is not limited to R&D departments or market research teams, but applies to everyone who comes into contact with the product or product-related services.

Training for sales, marketing and customer support to become familiar with the data and how to use it to understand the user data leads to a better understanding of the use cases, problems and needs of the customers.

5. Data literacy is the new standard business capability

Microsoft Office used to be a must that every employee had to master. For the 2020s, these are “must-have skills” data - for all types of professional activities, from sales managers to clerks.

To the extent that companies and entire industries develop and use digital products, services and complete business models, every workforce must grow together and be retrained if expectations and requirements change.

Research suggests that the loss of productivity due to the skills gap in data literacy costs companies around the world $ 200 billion each year (Source: (Accenture and Qilk).

Employees should be able to use data to influence their day-to-day activities and far-reaching decisions. When used correctly, they can help any employee achieve personal goals, get work done better, and contribute to overall productivity and business performance.


A lack of data literacy is one of the major barriers to digital transformation success and a company's ability to grow. While investments in big data and the hiring of data analysts and data scientists increase, it is still estimated that one in two companies lacks the data and AI literacy to achieve sustainable business value.

Data literacy is as important today as literacy was a century ago.

Data will drive momentum and success. Now is the time for everyone in an organization to understand why it is important to improve data literacy - and then act on it.

Do you feel inspired to introduce your employees to the data? Find out how - contact us.