Many companies have either already established people analytics teams or are seriously considering developing a people analytics capability.
There is an increasing recognition that intangibles are the primary component of companies’ market value—up to 90% according to some estimates. Beyond the traditional sources of intangible value—software, intellectual property, “goodwill” from acquisitions, etc.—is the latent value within individuals, teams, and organizations that people analytics can identify and unlock. People analytics helps firms understand the sources and nature of this value, enabling its preservation and growth.
But do different industries think about people analytics in different ways? And does this variability influence the relative pace of HR’s adoption of people analytics across industries?
While there is no specific research on this topic, I’d like to share some thoughts based on my experience in people analytics leadership across financial services, healthcare, technology, and retail e-commerce over the last 20 years, as well as some of my academic research on transforming HR into a more data-driven function.
Finance and technology lead the way
My recent doctoral research on people analytics adoption is based on a unique global data set of almost 200 founding people analytics leaders. These are organizations’ very first formal people analytics leaders. They play a critical role in their organizations’ adoption of people analytics.
The financial services and technology industries tied for the highest proportion (21% each) of founding people analytics leadership roles reported in the underlying survey. They are followed by the healthcare (13%) and retail e-commerce (8%) industries.
In other words, financial services and technology lead other industries in people analytics adoption.
Driving people analytics adoption is arduous and invariably an exercise in change leadership and change management, regardless of industry. However, I found it relatively easier to launch people analytics in financial services than in the other industries I worked in. I have also noticed that my financial services clients are readier for people analytics than those in other industries. I might be looking through rose-tinted glasses at my very first founding people analytics leadership role at a global investment bank many years ago, and others’ experience may well be different.
Being a founding people analytics leader
While leaders at the global investment bank I worked at were surprised to see analytics emerge in HR, they were instantly supportive, eager for insights and recommendations, and refreshingly quick to act upon them.
The bank’s ready adoption of people analytics is partly attributable to the financial services industry’s perpetual and insatiable hunger for increased returns on invested capital to build and sustain competitive advantage—the alpha, if you will—in the industry. While all firms in all industries are competitive, the relentless focus on financial performance is unmatched in financial services, in my experience.
Alpha, the elusive excess return beyond what the market delivers, distinguishes the winners in the financial services industry. If HR can deliver competitive advantage through data-driven talent management, bring it on!
Using my empirical labor econometrics training and consulting experience, I was able to identify opportunities to manage costs, reduce risk, and improve the firm’s reputation in the talent market. For example, examining attrition through the lens of survival analysis, I was able to identify costly turnover occurring roughly two years after hire. As a result, HR put incentive and retention programs in place to manage undesired turnover.
I built a regression model to identify factors that predicted success at the firm. The model’s results prompted, among other things, a change in the schools that the bank recruited from and a greater emphasis on internships since graduates of second-tier schools and employees with financial services internships (regardless of the company) were more likely to succeed at the bank. Both initiatives improved diversity outcomes, too.
Using Markov chain analysis, I was able to help the investment banking division avoid over-hiring in its analyst and associate programs. Differentiating itself from other Wall Street banks did wonders for the bank’s reputation in the talent market. Using the investment banking division’s success as an example, I persuaded other departments to be more intentional about their size, labor cost, and organizational design, hastening the advent of workforce planning.
It wasn’t a hard sell at the end of all this to persuade my manager to allow me to start and lead a new “HR Strategy and Analysis” department. We were one of the earliest people analytics teams in the world!
3 reasons financial services companies succeed with people analytics
There can be some general advantages for financial services firms adopting people analytics.
1. Human capital is part of your economic value
The world of finance is inherently data-driven. As a result, models such as the capital asset pricing model (CAPM), the Black-Scholes option pricing model, and discounted cash flow (DCF) analysis are widely accepted and employed. This familiarity paves the way for the “human capital” paradigm of human resources. Human capital refers to the economic value of employees’ knowledge, skills, and abilities. It can also include employees’ networks and associated social capital.
Viewing the workforce as human capital turns HR thinking on its head; workers are an asset to invest in rather than a resource to be consumed or a cost to be minimized. The human capital paradigm resonates within the financial services worldview and has played a prominent role in elevating HR from “personnel” to human capital management (HCM). For example, Goldman Sachs’ HR function is known as HCM and is highly regarded within the firm and across the financial services industry.
People analytics teams should use the paradigms and language of their industry and organizations to frame their models and communication as they persuade stakeholders to adopt people analytics.
2. Measurement made easier
Measurement matters in financial services, whether abiding by the Financial Accounting Standards Board’s (FASB) generally accepted accounting principles (GAAP), the Securities and Exchange Commission’s (SEC) reporting requirements for public corporations, or the Federal Reserve’s stress measurements for large banks. Beyond regulatory compliance, financial services companies emphasize measurement for optimizing investment and operations.
Human capital or talent-related metrics are a natural extension of the principles of measurement and accountability and, therefore, receive due focus in financial services companies. For example, the SEC’s recent human capital disclosure rules reflect the notion that human capital is a substantial driver of companies’ value and therefore requires disclosure in the form of human capital metrics.
People Analytics teams should take advantage of the emergent board and leadership interest in human capital metrics to advance the adoption of people analytics more broadly across the organization.
Sound financial planning and analysis (FP&A) is vital for all organizations and arguably more so in financial services organizations. It’s not a giant leap to be concerned about HR’s parallel accountability—organizational planning and analysis (OP&A). The two activities complement and complete each other.
The synthesis of the two is an integrated approach toward strategic workforce planning. I define workforce planning as a business process that uses the discipline of FP&A to optimize the workforce on three dimensions—capacity (e.g., number, cost, availability), mix (e.g., type of worker, location), and capability (e.g., expertise, skills, experience)—to execute the long-term business strategy. Integrated refers to the need for HR and Finance to partner in the exercise (to a “you complete me” extent).
People analytics teams should engage actively in workforce planning and align Finance and HR in this vital work through a platform such as Visier, integrating data, analytics, and planning.
Going beyond Finance
Financial services companies have certain advantages—in my experience—in the adoption of people analytics: they chase alpha any way they can, are measurement oriented, and are familiar with frameworks, models, and modeling.
Each industry is different. What can you learn from other industries’ experiences? What aspects of your industry’s particular features and paradigms can you leverage for accelerating the adoption of people analytics?