Organizations focused on managing and analyzing their data for decision making are 23 times more likely to win customers when compared to those that still follow the traditional paths of collecting, analyzing and developing strategies based on quality information.
The projection is from the McKinsey Global Institute, one of the main business consultancies on the planet.
The statistic, confirmed by other international consultancies, should be carefully considered by entrepreneurs and executives in the current scenario of high complexity and increasing competition in the markets. Awareness of the strategic importance of data reaches a greater number of managers, who are realizing the need to leave theory and adopt practice in strategic information management.
Thanks to the growing digital transformation of businesses and enterprises, we have more data in abundance than ever before, helping decision makers in ways few would have imagined a little over a decade ago.
It is natural for you to question: what changes now? After all, data analysis has been around for a long time in business management, finance, sales and production.
What does data science add to analysis and strategic decision-making processes?
How does artificial intelligence help to better understand data?
How does this actually change our day-to-day in terms of decision-making in the company?
Why is it important?
The evolution of medical treatment
To answer the questions, let's make a comparison with the evolution of the routine diagnosis of human diseases.
At the beginning of the last century, a doctor's examination depended on the ability to feel a patient's organs to identify an abnormality. As well as the anamnesis, the interview in which the person describes what he feels.
The best clinicians could make all the difference, depending on specific skills and little data. The evolution of medicine was, in fact, enabled by new sources of information. Over time, the professional began to have more data about what was happening in the body, with blood tests, image analysis, radiographs and CT scans, among other increasingly accurate resources.
Today it is practically impossible to imagine a doctor making decisions about a clinical condition without bringing a little more of this data about what is happening in the body to define the best diagnosis. Even if it is not only about data, but also about listening the patient, it is not possible to practice without data anymore.
Evolution in companies
Something similar is happening right now in the business environment. Even today, the prevailing model provides somewhat limited sales and financial analysis. As if companies were still using mechanical microscopes from the middle of the last century.
Today, with the technological leap, there is greater access to details that were imperceptible in traditional data collection and analysis systems and information generation. The visualization framework, based on digital systems, has the power to identify small signals.
“The new technological resources, big data and Artificial Intelligence, indicate how the company generates revenue. We were able to look in detail at the interconnection of the gears of business operations, thanks to in-depth analysis of operations from a huge volume of data”. Arian - Founder and CEO DdF.
We are seeing the times when the recording and generation of indicators in electronic spreadsheets are not sufficient. In the routine that is becoming in the past, companies defined growth strategies based on insufficient criteria. “Can we grow faster than we are growing?” the top executives would say.
More like a wish than a well-founded conclusion. Sales teams experienced the anguish of achieving goals at any cost only guessing strategies. They had to answer the questions:
How are we actually going to grow?
How can we get into this sales operation and better understand where the opportunities are?
How and where to direct expansion business?
With the data available, how is it still possible to find out what we will do differently with our customers and to acquire new customers?
Discovery: Big Data, Artificial Intelligence and Machine Learning
Answers include the realization that systems based on artificial intelligence and machine learning expand the discoveries about the levers that generate revenue in the system. For example, it is possible to understand who the customers are and why some are not buying from me (churn). What is my most profitable segment. What is my best product/service to put the sales effort into.
What are the main characteristics of the customers (profile)?
Which ones bring more value to my business?
For whom is it possible to give discounts or make different strategies?
What will be our next best action to bring in more sales?
What is our optimal pricing strategy?
A foundation favors the efficiency of marketing science. The Discovery platform enables a deeper analysis of operations that can generate greater customer retention and loyalty, and deepens sales opportunities.
More than a CRM or even a BI, Discovery makes it possible for any company to give meaning and value to its data. Data are necessary for a better understanding of events and the generation of information for the definition of business strategies. It improves the focus on the best indicators about operations, like a GPS, they become a guide to improve sales.