10 Transformation


Are you ready for change?

Jordi Perramon

Historically, education has been a key variable for younger members of society to adapt to their environment and learn to bring value to it, being economically rewarded in exchange for the time and effort dedicated to a specific function.

There have been many studies that have found a correlation between higher levels of education and higher salaries. It stands to reason that the more difficult it is to acquire a skill, less people will be able to do it, there will be less labor competition, and thus the salary will be higher. Among other reasons, this is a key variable for which a surgeon, with specific skills and knowledge that are difficult to acquire, will receive a higher salary than a waiter, a role requires general skills that are in reach of the majority of the population.

This mindset, in which we have all grown and developed, could be about to change. And the change could be as drastic as what happened two hundred years ago with the Industrial Revolution, when we moved from a rural economy based on agriculture to an urban, industrialized economy.

According to a study by Carl Benedikt Frey and Michael A. Osborne, from the University of Oxford, this change could even destroy 47% of jobs in the United States over a period of between ten and twenty years. And, as you can see in Figure 1, it would affect practically all areas of knowledge.

Probability of job destruction by area of knowledge

Figure 1: Probability of job destruction by area of knowledge.

Before explaining the causes and consequences of this change, as well as signaling how we can best adapt ourselves to the challenge, we need to understand a concept that will help us to frame the problem and propose a possible solution: the black swan.

The black swan

A black swan is a highly improbable element that has a large impact on a group, or on the whole population. Although the black swan theory, developed by Nassim Taleb, is far more restrictive, I will use it throughout this discussion in a broad sense, in order to make the key points that I develop more understandable.

Decisions, both from a business point of view and a human one, consciously or unconsciously support themselves on the concept of probability, which helps us to operate in our daily lives. This creates a bell curve, where the vast majority of events are focused in the center of the curve. This helps us to keep making decisions, the results of which return to the center of the curve. Thus, reality is created on the basis of a highly stable and secure system of collective normality. This reality is our black swan. For every hundred thousand swans we see, ninety-nine thousand nine hundred and ninety-nine will be white. But reality is complex, and it keeps rolling the dice, day after day. And one day, when nobody is expecting it, the black swan will appear. As you can see in Figure 2, the black swan is located on one end of the spectrum, as it is a highly improbable event. Thus, we should take it into account that a high percentage of the population is unprepared to see the black wan, given that their mindset has only been molded to see the white swan. This will transform the way their see reality and, if they are not prepared for it, it can have a very negative effect on how they adapt to their new environment.

Probabilities related with the black swan

Figure 2: Probabilities related with the black swan

From my perspective, and although I am making a free adaptation of the concept, there are two kinds of black swan appearances: the abrupt kind (this would be closest to the purist concept), and that which, despite having the same effects, would hit society at a slightly slower pace. Regardless of the modality, the majority of black swans, once they have been seen, shift the bell curve and create a new reality that we have to adapt to. And evidently, those who adapt fastest are those that acquire the largest share of new value to exploit. There are many examples of black swans that have appeared in our lives and which we now consider to form part of reality. The Industrial Revolution radically changed the concept that was already established around the economy and value creation, the fall of the twin towers changed our concept of security, antibiotics changed our concept of illness, the internet changed the way we consume, the housing crash changed the way we value investments, mobile phones changed the way we communicate, etc. All of these changes destroyed realities and created new ones.

The philosopher David Hume indirectly planted the dilemma of the black swan when highlighting the case of ‘Russell’s turkey’:

‘The turkey found that he was fed every morning, and, after several months of such observations, he concluded that there was a universal law: “These kind humans must love me dearly, given that they feed me generously each day”. On the day of Thanksgiving, it turned out that these ‘kind humans’ sharpened their knifes and cut its throat, demonstrating that the turkey’s universal law was worth very little.’

Clearly for that turkey, Thanksgiving was its black swan. We all have our own.

I will use this concept of the black swan and the shift in the bell curve to expose the challenge that we will be facing in a near future.

But before I discuss the challenge itself, I will discuss the conditions that, as people, we must have in order to face it.

What brings us success?

Throughout the majority of the nineteenth century and at the start of the twentieth, it was believed that what differentiated people who were successful from those that were not was their IQ. According to this vision, intelligent people are those that find good jobs and are capable of developing professionally, and those that are not intelligent cannot compete.

This vision has been turned around over this past decade thanks to studies, primarily, by Angela Duckworth, of the University of Pennsylvania, and other academics that followed her line of investigation. They studied the discrimination of success and failure among groups in various professions considered to be highly competitive: strategic consultancies, doctorate studies, military academies, high finance, auditors, etc.

In all of these professions, they observed a variable that vastly increased their probabilities of success. And it was not IQ. Nor was it good looks, health or the purchasing level of their parents.

The key variable in all of these studies was ‘grit’. That is to say, that a crucial element to success in any project that we undertake is to have courage. To have a gritty attitude is to set long-term objectives, to be firm enough to not falter, and to have enough stamina to endure tough situations. It is treating life as a marathon, and not as a sprint.

Other studies have not only been consistent with these conclusions, but have also been progressively dismissing IQ as a variable of success. In the current environment, characteristics such as enthusiasm, curiosity, motivation, self-control and optimism are much better predictors of achieving professional success than IQ.

Therefore, whatever the future holds, it would be a good idea to internalize these attitudes. And this is also particularly valid when you consider that the person you spend most time with in life is yourself. It is far better if we can tolerate ourselves.

Knowing how we should be in order to face the challenges of the future, we are now going to discuss why our jobs will be destroyed, and why, during this academic year, it is important for you to transform the way you normally see reality.

The future

There are two lines of investigation that have been advancing simultaneously fur several years, and which, having met, are creating the conditions required for there to be a black swan in the job market. On the one hand, we have artificial intelligence, where we have been able to create computers, some of which robotic, that evolve and learn by themselves through algorithms, without having been specifically programmed to do so. This threat would not be a threat in itself, given that computers need data to learn. And here is where the second variable comes into place: big data and the digitization of information. At this moment in time, we have all turned ourselves into machines for creating, experimenting and disseminating data every time we search for information on Google, buy things on Amazon, use our mobile phones or publish information on social networks. Furthermore, much of the information on paper has been digitized (invoices, CVs, clinical files, bank accounts, etc.), which makes it susceptible to processing and analysis.

These two lines of investigation have created the perfect conditions for the automation of a large part of professional work. And this transforms what was a highly improbable scenario a few years ago into something that is far more likely today.

Let us look at a few examples to illustrate this premise:

1- McKinsey, one of the most important strategic consultancies in the world, receives hundreds of thousands of CVs each year from candidates who want to work for them. Last year, they put artificial intelligence to the test to determine the reliability of machines to select the best CVs. The process was as follows: after going through all past results, they selected 10,000 CVs received in an office in North America and put a group of machines and a group of humans to work, working simultaneously and without communicating between them, with a view to select the best candidates. They found that the algorithm used by the machines matched the results of the humans by more than 90%… the only difference being that the computers did it in a matter of minutes, while the humans took several weeks to sift through the CVs and select the best candidates. In analysing the differences between both processes, they observed that the machine had not discriminated according to gender, race or age, which are variables that can be susceptible to biases from human beings.Introducing artificial intelligence into the recruiting process could save millions for a company like McKinsey, at the expense of the highly-prepared professionals that have been in charge of the process up until now. What will stop them from directly sifting through the curriculums on LinkedIn, to go from 100,000 potential candidates to just 500? And once this process has been set up successfully, what will their competitors do to not lose profits? And the most important question: What will happen to those companies and professionals that, up until now, have dedicated time and resources to the initial screening process?
2- Deloitte, in collaboration with Kira Systems, has created a tool known as ‘Argus’, which is capable of extracting accounting information from any document (invoices, receipts, leasing contracts, loans, etc.), processing it and analyzing it. The next natural step for Kira Systems will be to develop a programme that directly accounts for this information in the system. In this case, the potential savings on costs for companies would be hugely significant. And of course, accountants are not likely to be too satisfied with this.
3- Another: KPMG, one of the Big 4, has recently aligned with IBM to apply artificial intelligence to account auditing with an objective to automate some daily tasks. This helps to increase the analysis sample (in many cases there won’t be a sample, but rather they will process 100% of cases), increase the speed of the audit and reduce costs, thus improving the efficiency of the job.
4- And one more: Let us take a look at the health sector. It is expected that computers will have access to millions of health records. Computers will process the information to determine the patient’s illness, the most effective medication and chance of survival. Now, companies like Kaggle, after having gone through thousands of medical resorts in the system, have managed to match, or even improve, human success in diagnosing illnesses. The difference is that our health system takes weeks, even months, to generate a definitive result, involving specialists from different disciplines, and using up system resources and patients’ time. An ophthalmologist can see 50,000 eyes over the course of his or her career. One computer can analyze millions of eyes in minutes. And its effectiveness is increasing as it obtains more and more data. The good news is that health spending is the main item in any state of wellbeing, and artificial intelligence has the potential to save huge amounts of money in this field. However, once again, we have to ask ourselves where these health professionals will work once machines have managed to improve and universalize their performance.

Anyway, hopefully these last examples won’t cause you to drop out of your Master’s course. That would be a bad idea.

The situation we will be facing is the following: We will not be able to complete with machines in frequent, high-volume tasks. Think of calculating invoices, analyzing a bank’s insolvencies or the volume of incidents that large insurance companies manage. The vast majority of these operations can be found on a very steep bell curve, and are very repetitive. Given their high volume, there is a lot of data that can be processed using a computer. Furthermore, given that they are repetitive, they take up resources, and thus it is cost-effective to invest in technology to save on expenses.

One of the most interesting points of this transformation process is analysing the new circumstances that this future scenario will offer us: Computers will not differentiate between highly qualified tasks and low skilled tasks. They will simply automate highly repetitive tasks of a high volume.

The good news is that there are many tasks where computers will be unable to compete with us. Computers, using artificial intelligence, have made no significant progress in facing new situations, i.e. those that they have not faced before. Machines cannot face scenarios that they have not already dealt with many times in the past. The toll of artificial intelligence is that, prior to making a decision, they have to process millions of pieces of data. Humans, on the other hand, are intuitive; we can face new situations are good at connecting points together to create and interpret new realities.

And therefore, there will still be a need for accountants, doctors and auditors. There will still be a need for financial experts and human resources managers. And it is likely that they will be much more productive than they are now, thanks to the support of computers.

Nevertheless, they will have to differentiate themselves from computers, being specialists in specific matters, being creative and staying in touch with new situations, as well as with the evolution of the state of the art and their area of specialization. That is to say, people will need to be at the cutting edge of their profession, meaning that they are in touch with advances and science, in order to be at an advantage when repetitive, resource consuming tasks are eliminated.

Humans will be the ones designing the business plan. Humans will be the ones bringing in new audit clients, designing risk maps, analyzing results and deciding whether or not to introduce caveats. Humans will be the ones planning the acquisition of companies, inventing strategies to improve profit margins and deciding how to create added value for the shareholder.

So, if you want to protect your future, be human. Create and think.

It’s not about getting a Master’s to have something (a qualification or another line on your CV), but rather to be something. You should prepare yourself, personally and academically, to face this future scenario.

And the good news is you are in the right place to achieve this.

Jordi Perramon

Jordi Perramon

Academic director of the Master's Degree in Financial Management and Company Auditing at the UPF Barcelona School of Management

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