With the advance of the digital economy, an increasing number of companies are facing changing business characteristics. As the uncertainty and complexity surrounding technological trends and the global situation grow, risks are increasing for business strategies that depend entirely on traditional business models. As a result, companies in infrastructure and smokestack industries have also started to invest in new businesses which were previously unfamiliar to them, and are eagerly engaging in open innovation and business partnerships.
Changes in business characteristics alter the optimal personnel management system. For example, let us define two simple different business categories which we call "Guardian" and "Star" businesses (Barron and Kreps 1999). Figure 1 shows the distribution of corporate profit for the two. Let us define businesses whose upside potential is limited, but downside risk is significant as "Guardian businesses." Typical examples include infrastructure companies, including power generation, communication and transportation companies. On the other hand, for "Star"-type companies, downside risks are limited, while their corporate value may rise much higher than expected if their business proves successful. Platform companies as represented by GAFA (Google, Amazon, Facebook, Apple) and other companies that have the potential to create new markets belong to the "Star" type.
The personnel management systems that are optimally suited to these two types of businesses are entirely different. As shown in Table 1, whereas a flat organization that enables prompt decision-making is desirable for star type businesses, a multi-layered organization that reduces the risk of making mistakes is necessary for guardian type businesses. For Stars, a bonus system that encourages risk-taking—namely a system that rewards employee contributions to profits but does not penalize them for failures—is desirable, because risk-taking raises the option value of the business. For Guardians, the best pay system is a penalty system which punishes mistakes in order to discourage risk-taking. The two types of businesses also need individuals of different talents. Stars need workers who have high growth potential but may lack track records and workers with diverse backgrounds (let us call them "risky workers"), while Guardians need workers with such qualities as stability and reliability ("safe workers") and shun diversity, which is considered to hamper smooth coordination (Lazear 1998).
Table 1: Business Category and the Optimal Personnel Management System
Optimal personnel management system
Tendency to Overvalue Safe Workers
Although the advance of digitization may be increasing the share of Stars in the economy as a whole, it appears that many companies have largely maintained the same hiring policies and practices and still refrain from hiring workers with diverse and uncertain profiles.
I have many years of experience teaching at Japanese and U.S. business schools, and have noticed that MBA students' attitudes toward hiring differ significantly between Japan and the United States. For example, when given the hypothetical choice of hiring Job Applicant A who has a 100% chance of generating financial value equivalent to 10 million yen (safe worker) or Job Applicant B who has an even chance of generating value equivalent to 20 million or zero yen (risky worker), around 80% of U.S. MBA students would choose Applicant B, the riskier choice. However, around 80% of Japanese students would choose Applicant A, a safer choice. What is the reason for this difference?
Let us look at Table 2 in order to systematically examine the difference. The decision-making matrix contains two right decision possibilities and two wrong decision possibilities. In the case of deciding whether or not to hire a job applicant, the applicant may be either able or unable to make positive contributions to the prospective employer's business performance, and the prospective employer cannot know for sure which of the two possibilities is right. In this case, the right decision is (1) to hire the applicant if he/she is able to make positive contributions and (2) not to hire the applicant if he/she is unable to do so. The wrong decision is (1) to hire the applicant if he/she is unable to make positive contributions (Type 1 error, or false positive error) and (2) not to hire the applicant if he/she is able to do so (Type 2 error, or false negative error).
Table 2: Two Wrong Decision Possibilities Regarding Hiring
Applicant A contributes to the company
Applicant A does not contribute to the company
Type 1 error False positive error
Type 2 error False negative error
Japanese companies prefer safe workers because they want to minimize the risk of making a false positive error. Underlying this tendency is the lifetime employment arrangement which is pervasive in Japan and which makes it difficult to fire workers once they have been employed even if the worker makes no contribution to the company. In short, the cost of making a false positive error is high. In contrast, in the United States, workers who do not contribute to the company can be fired more easily, so there is a stronger tendency to place more emphasis on applicants' potential than on qualities like stability. Another reason is that, unlike U.S. companies, where front-office managers typically have the authority in hiring decisions, Japanese companies give the human resources department centralized authority over hiring. When front-office managers have found hired workers to be useless, they blame the human resources department for making the wrong hiring decision. To avoid the blame, the human resources department makes conservative hiring decisions.
However, amid the growing perception that there is a shortage of capable young workers due to the low birth rate and the value of "risky workers" is increasing due to changing business characteristics, the cost of making a false negative error is steadily rising.
Factors Aggravating the Problem
Even if companies plan to hire workers with diverse profiles or workers with higher potential for innovation, it is difficult to implement hiring according to the plan in many cases. One of the reasons is the use of multi-stage interview system used in Japan (typically, three to four stages for large corporations). In order to narrow down the long list of applicants, companies use this system, under which only applicants who have successfully passed several interviews are hired. The problem is that typically, only two interviewers at most—one interviewer in many cases—handle each applicant in each stage, and thus a single person could prevent a particular candidate from hiring. so personal biases of the interviewers have significant consequence on the types of workers who receive job offers (Sah and Stiglitz 1986).
There is a psychological tendency for humans to be biased or lack objectivity in evaluating other people (Hoffman, Kahn and Li 2018). Let us assume that a company interviews an applicant with unique characteristics. In Japan, workers who stand out tend to be the source of personality conflicts that distract other workers from the main mission of the office. The multi-stage interview system is highly likely to eliminate applicants with unique profiles and favor "reliable" applicants who are viewed favorably by many interviewers but typical of the company.
To change this status quo, it is essential to re-organize the interview stage into a process whereby a team of interviewers screen applicants based on a structured interview approach with increased involvement of front-office personnel and increase the diversity in recruitment channels and screening criteria.
Another problem is the method of using aptitude tests. As it has become possible for employers to utilize online aptitude tests at low cost, many companies use these tests as a means of narrowing down the pool of applicants. However, when many companies use ready-made aptitude tests from a limited number of vendors in order to narrow down the pool of applicants, undesirable consequence could follow. For example, applicants tend to be divided into two groups—people who consistently succeed in advancing to the interview stage and people who are consistently eliminated before the interview stage. This presents a new "statistical discrimination" problem—applicants whose predicted achievement levels are low are not allowed to move on to the interview stage.
It might still be a necessary evil if aptitude tests were effective predictors of future performance. It may not be the case, however. In the data science workshop for HR managers the author organizes, we had the participants analyze which applicants actually received job offers (including those who decline the offer) at the end of the interview process. They calculated how much of the difference in the probability of receiving a job offer between successful and unsuccessful applicants including those that failed in the initial test screening can be explained by the differences in test scores on the aptitude tests. According to the analyses, no economically significant difference was explained by the aptitude tests. Not only is the accuracy of aptitude tests not very high in predicting which candidates will receive final job offers, but also online tests pose other risks, such as the possibility that applicants may ask other people to take the test on their behalf or that they may not answer questions truthfully.
The presence of these problems does not necessarily mean that companies should not use aptitude tests. In the case of large companies which handle a huge pool of applicants, it is inevitable to narrow down the pool somewhat through paper-screening. The important thing to do is to customize screening test measures by clarifying the kind of skills and qualities they need from workers instead of only using ready-made indicators prepared by vendors. Ideally, companies should design multiple such measures to attract diverse skills.
As has been made clear above, many companies appear to be adopting flawed recruiting methods while complaining about a shortage of workers. It is essential to take necessary steps, including ensuring that the hiring policy is understood and followed by the recruiting team, making selection based on a team approach and through structured interview, and developing unique measures for initial screening based on aptitude tests and other information on the application form.