What is business intelligence?

In this era of digital transformation, the amount of information produced is growing at an exponential rate and the list of connected objects continues to grow: phones, tablets, watches, machines of all kinds, cars and even homes! Combined with virtually unlimited processing capacity as well as storage, we now have access to a ton of data, from our surroundings, at our fingertips. This creates several opportunities, but also several challenges.

The field of business intelligence refers to a set of methods and technologies aimed at integrating, structuring and synthesizing this data in order to transform everything into knowledge allowing to support business decisions. Here are some examples of questions that can be answered by a business intelligence model:

  • Who are my best clients?
  • Which sectors of activity are the most profitable?
  • How can I increase my sales?
  • What are the impacts of my cuts?
  • How can we improve productivity?
  • Which products have the greatest growth potential?

 

Concretely, the implementation of a business intelligence solution therefore aims to:

  • Bring together currently fragmented data in several separate systems
  • Ensure centralized standard information
  • Have a cross-sectional view of data on the different professions
  • Make information accessible to appropriate stakeholders
  • Make quick and efficient decisions

Companies adopt strategies called “analytical” in order to better understand their customers and suppliers, to reduce operating costs, to stand out from the competition or even to develop new markets.

Not only is it possible to do descriptive analyzes that aim to understand what happened and why it happened , but also predictive and prescriptive analyzes to understand what will happen and what should happen to achieve a certain goal.

For example, the company Netflix uses its data to forecast demand as well as the probability of success of its next films, which gives it a competitive advantage over the competition. We can also note the example of Starbucks which uses analytical solutions to personalize the customer experience, launch marketing campaigns based on the preferences of its customers and determine the best location for its next point of sale.