Human capital metrics: fueling smart decision making

By Keri Alletson

As companies reexamine their growth strategies, understanding and improving workforce productivity is essential. But to ensure they’re making the right decisions about allocating limited resources for the greatest impact, senior executives need reliable data ― the right data.

Leading multinational companies are turning to human capital metrics (HCM) and workforce analytics to provide crucial business insights. By taking five fundamental steps, they’re harnessing new technology and improved measurement methods to make complex decisions about people, gauge the effectiveness of their HR function, and assess the return on their investments in people and programs. Organizations that overlook human capital metrics and workforce analytics could miss an opportunity to sharpen their competitive edge.

No HR investment, no business benefit

This real-life story illustrates why HCM’s time has come. To start the process of improving talent retention, the chief executive officer of a multinational company in the financial services sector asked HR for data on employee head count, compensation and the “real” cost of turnover for the entire organization.

The HR leader said the project would take a few weeks. First, he’d identify ways in which the company’s 40-plus operations captured compensation data. Then he’d send out data requests, including directions for defining an employee, termination reasons and more.

Each unit would extract data from multiple incompatible systems, including custom-built databases, and enterprise resource planning and vendor-maintained systems. By pulling analysts from another project, HR could provide the report in three weeks. A caveat: The data wouldn’t be current, as the manual data-entry process was three months behind real time.

The project was destined to disappoint everyone. Staff members would spend days developing a static data set without context, and company leaders had no mechanism for analyzing the data in light of various business approaches they were considering, let alone for scenario planning.

An extreme example of an HCM-deficient organization? Actually, no. Unfortunately, many employers are overlooking the importance of top-notch data support in their decision making. When they do seek it, the process is cumbersome and, without adequate resources, the results can be disappointing.

To gauge their progress against strategy, today’s multinational companies need teams that can measure not only profits but also other aspects of business performance. And as staffing costs represent an increasingly larger percentage of overall operating expenses ― at the same time, new workforce and talent issues are coming into focus ― the staff, tools and processes for this higher level of measurement and analysis will be critical to profitability.

What does HCM success look like?

Some companies that have invested heavily in HR technology, processes and people are already performing sophisticated workforce analyses. For example, a global technology organization with fully realized HCM capability can generate reports instantly on any aspect of workforce cost and value. The HR leader of this organization could have responded to the CEO’s request in detail in a matter of minutes.

This capability allows the global HR and talent teams to focus on predictive analytics ― such as identifying high performers who might be retention risks. HR can also develop refined strategies for managing executive retirement risk, improving diversity-focused succession plans, strengthening workforce health and engagement, and meeting other talent-related challenges.

Another example of successful human capital metrics is a North American retailer that has long relied on HR’s contribution to the monthly scorecard to understand which employee behaviors affect sales and profits ― down to the individual store level. The data have helped the company make many changes, including redefining the store manager’s role. The HR analytics team is now working on providing managers with self-service capabilities for real-time reporting on various workforce analytics.

In both companies, HR leaders are using HCM to create a culture of talent accountability and better people management. And the data are enabling managers and company leaders to better understand what drives employee behavior change, with the goal of maximizing both individual productivity and the workforce’s alignment with the business strategy.

Getting started with HCM

Such examples illustrate why HCM implementation is a journey. Few companies have arrived at the final destination ― the full implementation of human capital measurements. Most are somewhere along the path, with some organizations and industries leading the way in successfully applying this tool to link HR services and bottom-line results. If your company is seeking data to guide its investments in practices and programs that will improve productivity, here’s how to get started.

1. Invest in foundational HR technology. Despite advances in enterprise resource platforms, cloud computing and software-as-a service, a number of companies aren’t yet using company-wide HR systems ― and therefore can’t effectively gather and use integrated workforce data. To address this challenge, some companies are making the case for more investment in HR technology, while others are developing processes to compensate for the lack of technology integration. Some are investing millions of dollars in global data warehouses, and others are building processes to compile data from disparate sources.

While no one solution works for every company, it’s clear that better HR technology is the right foundation on which to build measurement capability. The alternative is a patchwork of spreadsheets that use varying definitions and can give rise to incorrect assumptions. A good first step: Develop a business case for increasing investment in your HR information system or HR management system.

2. Build or borrow analytical competencies. Even in today’s advanced technology environment, some HR functions, faced with mountains of data, lack a critical competency set on the HR team: analytical skills combined with deep business and HR knowledge. Having mountains of data but no analytical resources can be just as challenging as not being able to gather the data. As a result, a number of senior managers are creating HR/workforce analytics centers within corporate HR or HR shared services. Others are borrowing analytical staff from the finance function.

3. Engage business unit leaders and senior managers. It’s tempting to staff measurement projects with only members of the HR team, but measurement efforts are most successful when HR leaders work collaboratively with their peers in corporate and line management. Cross-functional teams are more likely to develop models that reflect the human capital needs of the entire business.

After taking the above three steps, organizations arrive at a midpoint on their HCM journey: Measurement and workforce analytics are standard in HR and have been incorporated into general business management practices. At this point, leaders ask, “Is this metric good or bad?” and “How does our company stack up?” For insights and answers, look to comparative analytics and external benchmarking.

4. Understand which metrics matter. It might be easier to count what can be counted than what should be counted, but don’t fall into that trap. For example, HR often spends significant time on efficiency-related metrics, such as the time to fill positions or the cost per hire. But understanding other workforce dynamics ― for example, how engagement and retention affect new customer acquisition ― could be more valuable to the business.

HR leaders must understand the business strategy and what drives business value so they can identify pivotal roles with the greatest strategic impact. And management teams need to recognize HR’s ability to provide a unique perspective on topics such as leadership development and succession planning.

When managers understand how various workforce elements influence financial results, they can make the changes needed to affect behavior. Without proper context and actionable insights, managers will discount metrics and analytics. When it comes to making management-level decisions to achieve desired outcomes, the key is in knowing which metrics are actionable.

5. Focus on companies that count. Most large companies have access to overwhelming reams of data from academics, professional groups and consultants. They find it difficult to weigh the credibility of data sources that offer contradictory information or data that lack global consistency. These situations can make analysis daunting and often lead to “analysis paralysis.” To address this conundrum, we suggest companies think small. Rather than looking for mass-market metrics that could prove meaningless, conduct custom third-party surveys to glean selected metrics. Focus on a small set of companies that compare closely to yours ― those against which you compete for critical talent.

Companies beginning their HCM journey will find the above recommendations useful. Companies and industries that have moved further along are using lagging and leading indicators, and combining metrics to produce predictive analytics and periodic reports. And a small group is using technology to enable manager self-service around HCM.

No matter where your organization is on the path, HR leaders can contribute greatly to workforce productivity by developing the company’s measurement capabilities as far as resources allow. By investing in technology, finding strong analytical competencies, involving business leaders, measuring the right things within the company and comparing those metrics to the appropriate peer group, HR will become a vital partner in strategic decision making. And the multinational organization will sharpen the competitive edge it needs to succeed in an uncertain economic environment.

Keri Alletson is a senior consultant at Workforce Health and Productivity of Towers Watson.