Big data: the expression is overused. Smart data, or “sophisticated data analysis,” seems more accurate. Their wealth, volume, variety and velocity are such that many managers seem to be intimidated by the innumerable possibilities they present and remain paralyzed rather than seeking action. Others, on the contrary, want to act well but do not know where to turn, as if to get rid of this hot potato. Unlike start-up companies run by a younger generation with almost natural expertise with new technologies, on the other hand, companies run by the older generation still hesitate too often before jumping into the fray or taking no action.
The billion razor
Do you know Harry’s story? At first glance, this New York company has nothing fancy to offer: simple razors. However, by offering its customers to deliver them at home when they need them, this company has innovated where the big players are going in circles. Indeed, thanks to the knowledge of his clientele (intercepting potential customers in their browsing habits on the Web by taking advantage of key words), Harry’s piqued the curiosity of the behemoths of this world. As a result, Colgate Palmolive, a multinational corporation with a turnover of more than $ 15 billion, untied its purse strings and put its hand on Harry’s for a whopping $ 1 billion.
The famous case of UPS also demonstrates that diligent data analysis can sometimes be very cost-effective and can have a concrete impact. in the mid-2000s, this American courier and parcel delivery company surprised everyone by changing their vehicle tours to avoid left-hand turns that, on the two-way arteries, were causing waiting. Stupefaction of some, even derision on the part of some. Yet this mature business decision was based on a careful analysis of the data collected by the company’s GPS, which has nearly 100,000 vehicles. A few months later, this decision paid off. The reduction in turn-by-turn delays has resulted in significant savings in fuel (significant reduction in greenhouse gas emissions), a reduction in the number of accidents and a gain in productivity. The UPS profits of amount to several million dollars.
Pushing the boundaries of customer service
In the field of business travel, a company might one day push the boundaries of customer service through artificial intelligence, as Thomas H. Davenport pointed out in his book Big Data at Work – Dispelling the Myths , Uncovering the Opportunities, published in 2014. This company has designed and implemented an application that is not limited to booking flights and hotel rooms for you to attend a conference, for example, but who will reserve for you a table in a restaurant that fit your tastes and will invite friends and colleagues for you according to your agenda. The algorithm manages everything, regulates your expense report and even sends it to your boss without you having to worry about anything.
The Small and Medium Enterprises (SME) would gain from using big data to grow. Take the case of a wood seller who usually puts a sign on the side of the road indicating the price of his rope. Supposing, this producer can already earn a decent living … but let’s imagine for a moment that he collects data on his customers in order to know at what precise time of the year they need firewood. Thanks to this data, this farmer can now offer and deliver, without being wrong, the wood his customers need. What’s more, he can even try to sell them other products like tools for you fire place and soon new material with lower GHG.
These examples illustrate how enlightened data analysis can propel companies to new heights. However, you must be careful with the sound of sirens and not be impressed by the technological tools, which are not a solution in themselves. All the tools of the world can not suffice alone in this quest for meaning. Managers must first define an opportunity or a problem and then know what they are hoping to find, because it is impossible to search all the data, structured or not, of a corporation without a compass. Work must be done beforehand. What problems do we want to solve? How to improve processes or services to clients or citizens? What data is available and potentially useful? These three fundamental questions must be asked upstream.
Is there a chef in the kitchen?
Now think about the most beautiful cuisine in the world. Renovated at the cutting edge of technology, it has a new stove and refrigerator, trendy. In addition, the refrigerator and pantry are full of quality food. What will happen, however, if a person who has never cooked goes through the door and tells you that she wants to prepare a meal? Will you accept that she embarks on the adventure? Or would you prefer a rudimentary, minimalist kitchen, where there are only a few ingredients … but prepared by a great chef? Asking the question, is to answer it. However, the same problem arises when it comes to sophisticated data analysis. There is no point in acquiring extraordinarily powerful and costly tools if no member of the company knows what to do with them. Contrary to popular belief, data analysis is primarily a management decision and not a purely technological decision.
“Do not wait to be uberised! “
Despite the Airbnb and Uber of this world, which have disrupted entire industries, many managers still seem to be in complete denial of reality. however, rigorous, long-term data analysis can only take place within companies if corporate executives show a genuine willingness to do so. Boards of directors also need to spend time and money on them. HIPPO (Highest Paid Person Opinions) must use data analysis to support or not their intuition. A manager is much more likely to solve a problem if the solution he or she offers has been validated by intelligent data analysis. Inspired by the scientific cycle, managers must test their hypotheses to increase their chances of success.
It is not a matter of questioning intuition but rather of anticipating the return on investment of such a process in a factual way by determining if the company has the necessary data to validate this intuition. after delineating the problem and evaluating its potential impact, this exercise is essential. At this point, managers must exercise their power with conviction. In this case, a lack of leadership will put a brake in the process. What’s more, the team will suffer the repercussions.
This is why human resources have a central role to play in this regard. A competent team can be focused solely on data analysis, although this function can also be found virtually in many different departments. The right people have to be in the right place. Managers also have an obligation to be better trained in the use of data in decision-making. Middle managers need to educate line managers and employees about the importance of this work.
Front row marketing
It is no coincidence that the marketing world has grasped the importance of data analysis more quickly than others. Marketing has been able to quickly measure the benefits of data analysis because its benefits have come to mind. In particular, customer loyalty with the help of special programs was quick to play this role.
The multinational credit card companies have also updated their models on a regular basis. As proof, when you pay with your credit card, there is always a delay before the acceptance of the transaction. It is precisely during this short time interval that the algorithm determines whether a transaction is fraudulent or not, now a day it must be admitted at the outset that all economic spheres could take advantage of similar but adapted algorithm.
To achieve this, interested companies must first define the opportunities or problems to be solved, then use the data to tap into new knowledge and put the results into practice, hence the importance of raising awareness organizational structure. For example, a bank might want to determine which 20% of its clients contribute 80% of its profits by trying to study the profile of its clientele. An SME might want to avoid waste by getting to know its customers better and offering them to deliver their products to their homes at the exact moment they need them.
Two precious dollars
Two dollars is the average price a company has to pay to read and compile a comment from one of its customers. This amount may seem both derisory for an SME and astronomical for a large company that has tens of thousands. The vast majority of businesses, small and large, do not take the time to read these comments. However, these data may contain invaluable information that could help solve many problems within the company or, who knows, propel it to new heights. Perhaps we should be more interested in this informative material that is this flow of data? The key to innovation is probably there. Sometimes the answer to questions are often before the eyes of someone who knows how to look?
Authors François Labrie, CEO and Cofounder Ai Outcome and François Bellavance, PhD, Professor Department of decision sciences, HEC Montreal, written in collaboration with Francis Halin, journalist. This article was published in Gestion Volume 42, Number 1, Spring 2017 and was translated by François Labrie.