Data literacy - is it being sidelined as we rely on BI-solutions to save us?

The implementation of BI solution in companies has always been and will continue to be a business project first and foremost. Successful implementation should enable the company to learn more about its customers, find new revenue sources or optimise certain business processes in order to increase revenue or cut costs. However, the implementation of BI solutions in companies is often reduced to one type of technology replacing another or to a modern dashboard replacing an obsolete one, while barely quantifying any concrete advantages for the organisation.

Data literacy in companies

For years, BE-terna has successfully marketed a modern, flexible approach to BI solution implementation by utilising next-generation tools that are technologically superior to traditional BI tools. Although modern BI tools are paramount for meeting the business objectives indicated in the introduction, they are hardly sufficient.

Companies often tend to neglect the other key component of these projects, namely people and their knowledge, which allows them to derive the maximum benefit for the company from those tools. Data literacy is a concept that is overlooked today by most companies and is based on the assumption that the so-called soft skills are a prerequisite for the user to transform raw data or information into knowledge and business decisions.

The importance of soft skills

A large number of people with the role of analysts or controllers invest their energy in achieving personal growth and development when it comes to technical competencies, while at the same time neglecting soft skills, which are pivotal for making successful business decisions. When discussing soft skills, we primarily think of basic soft skills, such as communication or teamwork. Other slightly more important skills should also be noted, such as creativity, curiosity, problem-solving and using storytelling as a skill to present analysis as a clear and easy-to-read story or report in order for the listeners to receive the message more easily.

You are unlikely to make a quality business decision looking at a pivot table showing sales up to the current day and making a comparison with the same period last year. 

You will make a quality business decision by being curious enough to meticulously analyse the trends by customer category and the diverse packaging of your own products and by being creative enough to compare the data with market data, market shares and specific economic indicators. For example, this can help you realise that your top-selling items generate low margins, while the bulk of the profits in the said market segment is derived from XXL packaging that you do not even own at the time in question. This realisation will ultimately allow you to make an effective and attention-grabbing 5-10-minute presentation for your superiors and make a joint decision on the marketing of new packaging that will compensate for the lost profit. The process described in the previous example is simplified, but not intuitive and people frequently lack the training to solve a problem this way. 

90% of the successful companies spend more than 50% of their investment budget on the so-called "last-mile" activities

Learned behaviour

Companies often take the easy road when solving this problem by trying to find a person that has acquired all the aforementioned skills. BE-terna's market experience shows that it is very difficult to find a person who possesses a full skill set and that it takes 2-3 people to completely solve a single analytical problem. 

Data modelling, business knowledge, data analysis and storytelling play a crucial role in the process. 

BE-terna tackles the aforementioned problem by including the required user training pertaining to the development of knowledge and skills in the segments of decision-making, data reading and analysis, as well as the segment of data literacy as an integral part of the implementation project.  

How to take a step forward

Data Literacy is a training programme that Qlik, one of the global leaders in analytics, marketed with the aim of training various types of users who deal with data analysis in operative business for high-quality problem-solving. The aim of the training is to equip users with specific soft skills in order to facilitate the employees' decision-making, which will ultimately benefit their company in terms of business.

Training consists of several steps:

• 1. The first step is the assessment of the company's data maturity via a simple questionnaire in order to determine the maturity of the company with regard to reading, writing and making an argument using data.
• 2. The second step comprises user training in certain basic data operations, such as aggregation, distribution or a general understanding of basic visual displays.
• 3. The third step includes the revision of key statistical analyses that the users require in order to make a decision with a certain degree of certainty.
• 4. During the last step, the training deals with the decision-making process and analyses the guidelines and techniques on how to objectively approach decision making without falling into the psychological traps that often limit us in this process.

A different approach to BI solution implementation projects

The first generation of projects implementing analytics tools emphasised data modelling, warehouse building and a few other activities hidden far from the view of the end-user. Today, it is the complete opposite, mostly due to technological development, business operation speed and the training of end-users. 

Less time and money is spent on data modelling in BI projects, while more time is given to user interface development, its intuitive design and the training of end-users, 

enabling them to transform data into knowledge using the applications and make better business decisions.

The aforementioned changes are most noticeable in projects pertaining to the implementation of artificial intelligence in the company operation. The results of one of the most recent surveys on AI adoption, conducted by the McKinsey consulting firm showed that out of the 1000 surveyed companies, the biggest difference between those that successfully implemented AI-based operational changes and those that never got past the pilot project implementation stage was that 90% of the "successful" companies spent more than 50% of their investment budget on the so-called last-mile activities, such as business process redesign, end-user training in communications, decision-making etc., while only 23% of the "unsuccessful" companies spent the same budget amount.

Criticall skill in new 20s

This survey by McKinsey is perhaps the best indicator of the market direction in which clients' needs are headed and clearly shows that people are paving a critical path involving success in all data-based projects. The technological development with the cloud at the forefront has made advanced algorithms accessible to almost everyone and everywhere, but only humans can reap true benefits from the projects in question, provided that they transform this information and data into knowledge and successful business decisions. The culture, business climate and market (under)development have all, to a certain extent, contributed to the fact that we live in an environment in which the learning, growth and development of employees is not a top priority. Companies that wish to emerge stronger or simply emerge from the upcoming technological wave will have to change their climate and data literacy will be a central factor in these changes.