NO MORE LIFELONG EMPLOYMENT：
There was a time in the US when people went to work for companies and remained with them for their entire careers. There was a psychological contract between employers and employees that was based on long-tenure and loyalty – employees would often have lifelong employment and companies would in turn be loyal to – and take care – of employees into retirement, with pensions and other benefits.
The work environment and psychological contract between employers and employees has changed over time, however. Today, there are no longer promises or expectations of lifelong employment on the part of either employers or employees. Employment is a much more temporary arrangement – even to the point that increasing numbers are becoming “gig” workers who engage in free-lance, contract work with multiple customers rather than becoming employees.
The reason for these changes stems from several factors. Companies today exist in an environment of unrelenting change and hyper-competition. Technology advancements are leading to disruptive products and services that are changing entire industries. The competitive challenges are so intense today that 50% of the Fortune 500 are expected to cease to exist within 10 years.
With this fast pace of change and competitive threat, traditional companies have been under strong pressure to change how they operate. They need to innovate, recruit new talent, and learn how to behave in an agile and resilient manner. Companies are also under pressure to continually grow and show higher levels of profitability. These conditions do not support the kinds of stable, long-term employment arrangements that have existed in the past and, in fact, they have given rise to new employer-employee relationships.
There are labor shortages in the US at present. Unemployment is only 3.6% currently. There are fewer qualified workers than job openings, which leads to high competition for talent. Job candidates often have the upper hand with employers and the current labor situation has driven salaries up in several job categories. This gives workers more leverage against companies than has been the case in the past.
Millennials are also showing up for work with different demands than prior generations. They expect robust development and learning experiences. They crave feedback and attention, want to work for companies with a strong purpose and values, demand work-life balance, and put pressure on companies to behave more candidly and authentically. Having workers en masse that come with these expectations has driven companies to make changes in response to millennial expectations. Millennials do not have the same loyalty to their companies as workers in the past – they think nothing of picking up and pursuing better job opportunities or even taking time off work to travel or pursue their passions – they feel secure they get another job when needed, which has contributed to the changed employer-employee relationship.
However, I do not see the emergence of flatter organizational structures stemming from employees as much as from the competitive pressures organizations face. Technology advancements are creating disruptive change and hyper-competition, which is forcing organizations to shift from traditional “control-oriented” management models to more agile, responsive approaches. Traditionally, organizations have been hierarchically structured and work has been performed in functional silos. Organizations have been moving to flatter structures with more cross-functional work to enable them to behave in a more agile manner. Connecting product and service delivery end-to-end allows organizations to absorb change and adjust rapidly in response to change and competitive threats. So it is these environmental factors that have led to flatter organizational structures more so than employee demands.
With only 3.6% unemployment in the US currently, the majority of people can find jobs who want them. There is always some proportion of people who choose not to work or cannot work for various reasons so there will obviously never be 100% employment.
Some people have expressed fear that robots will take over the majority of the work that people perform today and this has led to some concerns about what people will do in the future. But others believe there will simply be new jobs created as technology is used for traditional work, so there will not be shortages of gainful employment for those who want it.
I don’t have a crystal ball or strong insight about how things will evolve. However, as a psychologist, I believe it is an inherent part of human nature to do productive things – so my belief is that we will continue to create useful work for ourselves even as technology is leveraged to do more things. But time will tell…
CHANGE IN PERFORMANCE MANAGEMENT SYSTEMS：
In terms of how people are evaluated, most companies use formal performance management (PM) systems to evaluate employees on job behaviors and results. Typically, expectations and goals are set and employees are held accountable for delivering against these. Performance reviews are conducted at least annually and in many cases more frequently. These are formal meetings in which managers provide feedback to employees on their strengths and development needs.
However, decades of research has shown that these formal PM systems do not work well. Managers are hesitant to rate their employees accurately, so everyone tends to get very high ratings. The feedback employees get is not very useful, and review sessions have not proven to be a positive, value-added experience for managers or employees. So while US companies have formal performance management systems in place, these have not been shown to have a meaningful impact on individual or organizational performance.
If companies get to a point at which they need to separate under-performing employees, there are separate systems that enable doing this. Sometimes companies will eliminate jobs. In other cases, companies will initiate formal performance improvement plans that put people on notice that their performance is sub-standard, and individuals are given an “opportunity period” to improve, after which the employee can be terminated if the performance issues are not satisfactorily addressed.
The specific laws that govern employment vary state-by-state but in general, companies can separate employees who are not performing well, and we have seen downsizing and lay-offs more regularly in the US, especially higher paid, longer tenured employees that are more costly for companies to retain. This is a result of the pressure companies are under to show continually increasing profitability, which sometimes triggers cost reduction measures. Not only are poor performers are separated but even good performers can be let go when cost cutting plans are implemented.
There are more protections afforded to European than US workers in general, but laws vary country by country and thus can afford more or less protection.
AI INTO EVALUATION：
AI certainly has the potential to provide greater insights and more robust data for all talent management processes – selection, progression, performance management, development, and so forth. However, AI applications in talent management are in their infancy – they are relatively new and limited in their adoption, although some companies are early adopters that leverage AI applications quite extensively. In my view, we do not have enough experience with AI applications, especially in post-hire talent systems, to have good sense about employee’s happiness with them.
The use of AI to date has been more prevalent in pre-hire applications. AI is used to help companies find employees who have the skill and experience profiles they are looking for, assess their competencies in passive ways, and target people to recruit. But even with these, there is not broad and full use of the AI capabilities that are available. We have seen less use of AI in post-hire - performance management, succession, and development, although there are increasing tools coming into the market in these areas. No doubt more will be coming. Companies in Silicon Valley are likely be earlier adopters of such technology.
Like any system, the outcomes and effectiveness of AI will depend on how the systems are used, their accuracy, and whether employees feel that decisions from them are fair. One concern is that the algorithms programmed into AI systems can end up hard-wiring biases into talent management processes. We have seen evidence of this, so it is something we need to be cautious about. I personally believe there is more positive than negative that can result from AI talent applications but the success of these will hinge on fair and proper use.
Companies do indeed invest in their top talent, with strong incentive packages, development opportunities and other strategies to retain them. As a CEO who is operating in an extremely competitive market for talent, we take significant steps to retain top talent. This is especially important today because top employees are targeted and recruited by competitors – using AI applications.
Yes companies can mis-use data in AI systems intentionally or unintentionally, and we do need to be concerned about things like biases being hard-wired into AI applications. In the US, there is more ability for companies to collect and use employee data than elsewhere. For example, the EU’s GDPR requirements put protections in place that we do not have in the US. I do not know the extent to which similar protections will be adopted in the US over time. However, data protection is a significant issue overall, not just for talent management systems but in numerous applications that collect personal data – from social media to medical records systems to financial records and so forth. This is obviously an area with broad-reaching implications for which policies, procedures, laws and so forth will need to continue to evolve.
While technology may be available that allows performance data to be automatically collected, this has not yet been broadly adopted, although I believe the time will come when more individual performance information will be automatically collected and used for evaluation.
The PM technology that most companies use today simply facilitates passing information back and forth from managers to employees and compiling PM information provided by humans. For example, employees usually input draft goals into an automated system, managers review and edit these, employees may input self-appraisals, managers may then review these and provide final ratings and justifications. Hence, the systems mostly facilitate information collection and storage.
As I mentioned, there is strong potential for AI to enhance the PM information collected and analyzed on individuals but until this gets fully tested and broadly accepted, I don’t believe companies will rely on AI alone without manager judgment in determining evaluations. We need to be able to prove that AI applications lead to more objective, accurate, and fair evaluations. Until people can become comfortable with the results of fully automated approaches, use of these especially for post-hire decision-making will proceed cautiously.
I do not believe technology is the answer to work reforms deeply steeped in culture and tradition. Culture change needs to happen within and across human beings. Leadership needs to believe changes are needed and they need to be able to articulate what changes are needed and why. I believe the motivation for change may eventually become a self-correcting problem for Japan, like it has in the US. In today’s global economy, it is hard to protect against the significant forces that are impacting the ability for companies to compete successfully. In the US, what drove change is disruption and competitive threat that made change a matter of survival.