It’s War: Intuition vs. Data

“It is really difficult to design products through group interviews. A lot of times people don’t know what they want until you show it to them.” Citing Steve Jobs after his enormous success with Apple seems like a guarantee of success and a lapidary way of closing a debate. However, the conflict between intuition and data is more alive than ever in the business world. The rise of Big Data seems to increase the weight of numbers in business decisions, but instinct claims its own place as an essential tool in business.

If you had to make a momentous decision and the data advised you one course but his intentions recommended another, what would you do? A multitude of people and businesses face this dilemma on a daily basis, trying to decide when to get carried away by one or the other. According to a study by the Intelligent Economy Unit-APT, almost six out of 10 senior executives believe that they make decisions based on data. However, more than seven out of 10 of them also assure that they trust their own intuition when choosing a course of action. So what happens?

Do you have to choose between intuition and data?

For Roei Ganzarski, CEO of BoldIQ (a data analytics company), it’s not a matter of choosing between the two. “Analytics is an additional weapon that allows you to do things that the human mind simply cannot do. We are here to improve your ability to make decisions”. And it is that, in this same line, most experts advocate the synergy between instinct and figures.

However, a part of the businessmen resist their precious intuition giving up space. Many of them built their companies without analytics comparable to what they have today, and they had to use their instincts to make their businesses prosper. Accustomed to the fact that it has served them faithfully for years, they are suspicious of the arrival of numbers.
The limits of data and instinct

The best news is that in this confrontation, where the skills of one seem to falter, those of the other shine. It is clear that the power of today’s computers to work with numbers far exceeds the capacity of our brains, but data has not yet managed to learn how to start companies from scratch.

For example, in the world of Transgesa, that of logistics, the development of Performance Indicators -fundamental to know the operation of companies- is closely related to the improvement and evaluation of processes. Where does instinct come in then?

“In data science, intuition and analytics work together in tandem, each informing the other,” Steven Hillion explained in a TechCrunch article. “There is an attitude that you just have to apply enough math or enough machines to a data set to get the best models. But it is absurd to think that only with numbers you can achieve the answers that a business needs to take the lead.

Hillion explains it with an example. A bank asked his company to create a model for him to find out which customers were most likely to cancel their accounts. His team studied the request and saw that the data did not show a clear indicator that could allow them to get ahead of customer cancellations.

But as they were going over the numbers, one analyst had an insight: Maybe there was a type of customer who borrowed unusually high, who were long-time customers and who owned small businesses. And it turned out that it was.

The key was in the analyst’s presentiment that this type of client could be using personal loans and/or their credit cards as a way of financing their businesses. This discovery allowed the bank to address these customers in order to offer them appropriate financing means for their business, preventing them from using inappropriate products that would surely put their future relationship with the bank at risk.

It is important to realize the limits that, in turn, the human mind has. Let’s imagine a sales team leader who leads a relatively large group of salespeople. As much as this boss, after years of experience, has a great instinct to sniff out the problems that his team may be having, the opportunities and niches to attack commercially or the strengths and weaknesses of his employees, he will need help of the figures.

Statistics on new sales, on the markets in which they are having more and less success, the type of products that is best fitting each client, the performance in the different geographical areas, number of new contacts per client and day, percentage of success in closing new accounts… All very valuable data that when making decisions and drawing up strategies will allow us to go from “I believe” to “the data indicates”.

In addition, when we want to present new plans and projects for the company in which we want to involve employees and/or convince other departments, using statistics will always make things easier for us, since we will start from common and objective knowledge, which will be easier to involve others.
Intuition as a guide

Many authors agree that intuition is essential to know how to focus the figures, to give meaning to everything that we can collect today. They argue that exclusively based on figures it is difficult to decide the positioning that a company wants or needs. Decide if we have to be a company focused on price, service, being recognized for our closeness, standing out for our exclusivity, etc. But once these objectives are set, the data can be very helpful to know how to achieve it.

Another limitation is its ability to project into the future, since the data is necessarily based on the past. That is, they can allow you a good prediction about what could happen in the future in a given scenario as long as its variables do not change abruptly. But, how could the analysis of sales in the world of laptops have been correct before the release of the Ipad, which has influenced the sector so much?

These authors argue that if we only have data from the past, we may be able to better understand what the leaders in our segment did well, but it will be more difficult for us to know how to draw the future and lead the next big change in the industry. How are we going to anticipate tomorrow if the data we have is about what likes or works today?

Logically, this aspect is not so relevant in those sectors in which the products or services do not require a high level of innovation and are closer to being “commodities”. And it is that not all companies need to change the world with their next product or anticipate a very changing market.
How to combine intuition and data

The coexistence between instinct and figures seems the best recipe for the success of companies. To achieve this reconciliation Jeanne G. Harris, director of information technology research at Accenture, proposes five measures:
Invite executives to the analysis party

Harris is committed to making it clear to executives and the CEO that decisions will be based on data and its analysis. But ensuring at the same time that the experience of these senior officials will be an integral part of the process of analyzing these numbers.
Ensures good two-way communication

It is necessary that executives know how to appreciate the virtues and advantages that the analysis of figures brings to the company. Similarly, analysts must be able to understand the language of business and express themselves using it.
Build an analytics ecosystem

Make the presence of numbers natural in the company, having trained personnel who work with them and

using them normally on a day-to-day basis and in big decisions. This will help to reduce that unnecessary tension in the debate between numbers and experience.
fosters creativity

Promote initiatives that reward new ideas. This will make it clear that intuition and the courage to launch ideas will continue to be valued in the work environment.
Embrace data caps

Data is a support for decision making. Harris argues that good leaders know when to trust their intuition and how to bridge the art and science of business decision making.
For an approach between intuition and data

We have seen how intuition and data are forced to understand each other. Their virtues are complementary and when they reach their limits they need to turn to each other for help. Proof of this is that companies are increasingly investing more money both in talent and in data collection and analysis. The meeting of both concepts will be key for companies to make better decisions for their future.

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