Data Storytelling: The Great Schism of Business Intelligence
For many years, Business Intelligence (BI) exploration tools have proven themselves by equipping experts with data. The purpose of these tools is to explore the data and then return it to share with decision makers. Only one new category has emerged in the world of business intelligence: data storytelling.
What is data storytelling?
Data storytelling is a pedagogical answer to recurring questions from the business and operational sectors. They often have neither the time nor the training to handle hard-to-access tools and complex data sets.
The problem of traditional exploration tools is that they are addressed only to information experts such as data scientists. Training is time consuming and expensive because the features of these software are innumerable.
There is a real distinction between the exploration scenarios for analysts and those of direct consumption of their data, intended for operational and business decision-makers. These operational performance data consumption scenarios did not exist before, today we call this category data storytelling .
Data exploration tools are for analysts
These tools are intended for an individual trained to use a tool, for several days over several weeks. This person has several hours a week to use and compile data, and knows how to access most of the company’s data and has access to it.
This data expert then carries out explorations from database before communicating to another person. In summary, this is the scenario of Excel and the majority of Business Intelligence tools. It is the exploration of a database, to answer complex questions.
An example: a retailer tries to understand the number of women between 25 and 35, who belong to the loyalty program, who have bought in the last 23 days, a product in the butcher’s department and a chocolate bar of a mark given in reduction.
This level of precision is often linked to an extremely precise demand from a business that wishes to access unique and punctual information. This is the scenario of the analyst.
The purposes of data storytelling tools
The tools of data storytelling are intended for operational and business decision makers
These tools are for individuals who are not trained in the use of a data visualization tool and need to learn how to use it in a very short time. This concerns the neophyte of the data. This one will use the tool a few minutes every week and must find only how to implement it immediately but also the decision makers. The need for these is to make the data actionable. From the teachings of these figures, the person sells, manages, finances, markets, buys or directs.
This is the scenario of a sales representative, a human resources manager, a financial manager, a marketer, a buyer or a company executive. For example, for a distributor, it is immediately know his turnover per day, per week and per month, compared to the same period the year before, by radius. This need is recurrent. It is then the performance indicators that make it possible to control the activity of the distributor.
This operational population has other issues besides the population analyst. That’s why data storytelling tools focus on features like mobile and connectionless data access. The trades must therefore be able to access their data in the elevator, at the airport, etc.
These tools allow regular access to the main business stories. In this case, the information is clarified, hierarchical. This is the scenario of data storytelling. Business stories are told through data visualization applications. The data is then contextualized, scripted and actionable.
