Technology knows me intimately. For example, Netflix knows what movies I like… but that’s old news. Netflix likely knows more than that. It probably knows my interests and hobbies, where I lean on the political spectrum, how I spend my time and my income level. It probably knows people with whom I’d be good friends and, perhaps at some point, Netflix will decide to introduce us. After all, artificial intelligence is all about large sums of data, computer processing power and human capabilities — the three forces driving AI.
So, if technology allows us to ‘know’ each other so intimately, why do we as compensation and benefits professionals continue enrolling people in the same plans as everyone else, assigning salaries based on well (or not so well) defined jobs and reviewing salaries once a year at the same time for everyone? AI is beginning to move beyond simple automation to self-teaching neural networks and, in turn, its power to profoundly change every industry is increasing. While we’re just starting to discover AI’s full promise, it’s becoming clear where we’re headed when it comes to the future of work: AI is eroding transactional jobs.
AI’s promise is that it will unshackle humans to concentrate on the activities most of us enjoy more, such as solving problems, expressing ourselves and interacting with others. And HR leaders recognize that human jobs (rather than ‘machine’ jobs) will need to shift up the value chain. 41% of respondents to Mercer’s 2018 Global Talent Trends Study said they believe that high-value jobs will focus more on design and innovation in the next three years, and this shift is reanimating some near-defunct sectors.
Consider the travel industry, which has a business model that was cannibalised by online booking sites. Many traditional travel agencies went out of business, and the ones that survived had to up their game. Beyond booking airfare, hotels and ad hoc tours, agencies today are designing integrated, tailored packages that allow travellers to have richer experiences in the locations they’re visiting. In this context, AI is the young startup compelling the traditional compensation and benefits (C&B) business to evolve.
Life was simpler when we focused on payroll and editing job offers. Then, the role changed to encompass strategic elements that required expertise, such as designing total rewards policies or benchmarking pay practices. As AI proves itself capable — as well as more reliable and affordable — at core C&B analytical tasks, where is our added value?
If the aspiration is to move HR away from process-driven systems to instead drive business value, then the challenge for us as C&B professionals is to provide a first-class service to employees. This isn’t about general perks (e.g., gym memberships); rather, it’s about paying close attention to your data, which reveals the benefits that would make each of your employees’ lives better. And the C-suite is just as eager for this to happen. When asked about their talent priorities, executives ranked ‘enhancing the employee experience’ high on the agenda, according to the talent trends study. And they recognise that rewards need a makeover: Nearly 60% of employers plan on revisiting their rewards strategy in the next six to 18 months, according to Mercer’s 2017 Total Rewards Practices Survey.
And in the next three to five years, AI will do more C&B analytical tasks. While only 9% of respondents to a WorldatWork survey of 364 organisations currently use AI in their compensation processes, 32% are thinking about doing so, resulting in tasks being done more quickly and accurately, and with greater granularity. The result is that, in nearly real time, companies will be better able to map external labour market fluctuations to internal business needs and compensate employees according to their true value.
AI will enable the personalisation of the comp and benefits process. This fits neatly with the shift to the ‘experience economy’.
Consider job matching as an example. Previously, this heavy-touch process of matching jobs to salary surveys to determine an employee’s pay and benefits package was time-consuming and required using significant resources and tying down people to do it. Today, companies are developing algorithms that read and match a job description to a market survey’s job library codes in seconds. Even better, the most powerful algorithms don’t even require a job description — they simply draw data directly from the HRIS system and use it to match jobs to external market surveys or other databases to allow comparisons. And the process can be repeated frequently, fuss-free. Even when AI errs (and it will), its mistakes are consistent and easier to correct — that’s more than what can be said for unpredictable humans. The upshot is better quality job matching done in a fraction of the time.
AI will also enable the personalisation of the C&B process. This fits neatly with the shift to the ‘experience economy’ seen in the past decade, wherein people have come to expect tailored recommendations. The era of the individual has disrupted even the disruptors; AirBnB suggests experiences (e.g., a salsa class in Havana) in addition to rooms, and the C&B world is catching up. For example, technology services and consulting firm Infosys has tagged AI to ‘push’ pay raise recommendations to managers to approve or reject. In the next three to five years, AI can help us personalise the quantum of pay raises to help deal with pay (in)equity as well as allow us to customise the timing and nature of pay increases, bonuses or new benefits.
For employees, this means C&B updates will be more in tune with their changing personal circumstances rather than an arbitrary annual process. Take two typical employees: One is a 53-year-old CFO who’s comfortable in her career. Meanwhile, her 27-year-old colleague is juggling wedding planning and an online master’s course. Perhaps the CFO would value time off to volunteer or a financial health checkup to prepare for retirement more than a pay raise. She also may only require a biannual check-in. In contrast, her younger colleague may value smaller but more frequent pay increases as his life changes rapidly — particularly as his new skill set becomes hot in the market.
Today, we review pay and benefits for employees at the same time, once a year as part of a standard process. But we actually hold enough data on our employees and can leverage technology to help us personalise the review process and have it aligned to employees’ needs rather than to the company’s process.
Thinking beyond the annual salary-review process, most management processes that have run on predefined cycles and served us so well during the economy’s industrial period will be challenged going forward. Those regularly scheduled processes have served the crucial role of adding discipline and fairness into management, whereas most decisions previously were based purely on executive discretion. But in a way, those processes hold us back today.
In sum, in the next three to five years AI could provide the intelligence to align C&B policies better with market dynamics as well as automate the processes by which these movements are matched with individual employees’ situations. And it will do so at scale, whether for one employee or a thousand.
In the longer term, as AI capabilities progress, the compensation manager’s role will focus more on complex and unstructured situations. The role may transform into something akin to a wealth adviser infused with marketing and communications capabilities, mixing portfolios of pay and benefits adroitly for different types of employees to deliver a premium workplace experience. This means C&B professionals will be required to have both data-science and analytical skills, not to mention expertise in design, marketing, communications and, above all, a customer-service mindset. It’s a challenging combination, but also an exciting one. It further implies that how C&B (and HR) departments are structured today will change to facilitate these new capabilities as well as to ensure they’re organised in a way that they can jointly offer that employee experience.
First and foremost, we need to put ourselves in our employees’ shoes when designing these new portfolios. Think of a theme park where different rides cater to different visitors. There’s the lazy river for the risk-averse and the vertical-drop rollercoaster for the daredevils. These rides segment populations into clusters based on their preferences, and there’s a ride to suit every type of visitor. People go from one ride to another as their tastes change. In the same way, we can draw on employee data to develop different workforce personas (based on attributes such as age, income, life stage, career level and so on) and design experiences that maximise the value of income and benefits allowances and align with their unique needs.
In this context, we also will need to up-skill to be adept communicators, clearly setting out the portfolio range and effectively advising managers on the different benefits. We will be managers’ go-to coaches for training in how to communicate compensation decisions to employees. And we will be key advisers to the business, using data to explain the effect of different benefits on employee retention, productivity and engagement. And we know this change is coming: As communication becomes more important, more than half of respondents to the WorldatWork survey reported expecting to hire and promote compensation candidates with a liberal arts degree in the years ahead. AI will take care of the calculations and produce outcomes, and we’ll need to make sense out of it.
This vision is not without its pitfalls. As compensation managers, we need to manage the tension between the call for more customisation and the imperative for greater fairness and transparency. If AI can eventually suggest bespoke C&B deals for every employee, how do we balance that with our responsibilities on pay equity and equal treatment? Ultimately, this raises legislation questions of how fairness and equity are defined and understood today. To enable the full power that AI combined with high-value human jobs can deliver, we will need more pieces to align — and legislation is just one key piece.
The C&B function may find itself in jeopardy, too. With so much of the employee experience sitting outside of C&B, do we need a stand-alone compensation unit at all? Will HR silos disappear completely, replacing industrial-era functional divides with a personal employee experience adviser assigned to each employee? Indeed, the best companies already are transforming HR professionals into employee experience (EX) designers who actively think about the whole employee journey, from hiring to outplacement.
We live in a transitional period. These are interesting times to live in, as the feeling that ‘everything is possible in the future’ drives so much of our creativity and energy. Humans have been notoriously bad at forecasting the future. But the mere exercise to try to shape an image of the future is useful, as it helps us uncover opportunities today. AI technology is still in its infancy, and there is so much that will happen in the years to come that we simply cannot imagine today. We also must acknowledge that AI is here today, and it’s creating opportunities for us to rethink how we deliver on our objectives.Back to top