Unlocking Big Data: A Strategy for Workforce Analytics

By Brian Kelly and Wendy Hirsch

AMA sat down recently with Mercer’s Brian Kelly and Wendy Hirsch who work with clients around the world on workforce analytics and planning solutions.

Brian, a lot  has been made of workforce analytics and the era of big data.  Why should business leaders care about these topics?

When we talk with clients, we sometimes hear that they’re absolutely overwhelmed with data, metrics, and analytics. Senior executives are confused at what key indicators to look at and manage. In the rush to implement analytics or “big data” initiatives, companies can easily experience this sense of being overwhelmed.

It’s no wonder. Properly planning for current and future workforce needs is not easy. While many companies collect workforce data, far fewer possess the process and capabilities for turning that big data into useful and actionable intelligence that can drive strategic business and people decisions.

The ramifications of missing the mark are substantial. Some companies will discover they have lack of talent to execute successfully their business strategies; some will find themselves throwing misspent dollars at the problem, buying talent on the open market and playing catch-up; and some companies will simply miss opportunities by becoming less relevant in their respective industries.   

OK, so let’s say organizations start down this path. What type of results should they come to expect?

From our perspective, workforce analytics and planning is a required business process and an indispensable part of being competitive within any industry. It enables a company to analyze its future workforce needs against internal and external labor market trends, identify potential shortfalls and/or gaps, and outline strategies to successfully bridge such gaps.

In fact, the research we have conducted in conjunction with the World Economic Forum indicates that CEOs and boards of directors are hyper-focused on this issue. Klaus Schwab, the founder and executive chairman of the WEF, said: “The success of any national or business model for competitiveness in the future will be placed less on capital and much more on talent. We could say that the world is moving from capitalism to ‘talentism’.”

The organization that can get it right—that is, harness big data, analyze current and future human capital requirements, segment the workforce, and make sense of internal and external labor markets—will be positioned for success.

How do companies get started, Brian?

I’ll give you a client example. Jim at ABC Company was concerned that his organization’s analytics and planning Center of Expertise (COE) was not the game-changer his leadership team expected and hired Mercer to assess this belief. We learned that the company started out, like many other companies before them, by first figuring out its data landscape—gathering what it has  data on and asking if the data are complete and relevant. From there, it assembled a menu of the people metrics it could track and manage—categories like “talent,” “compensation,” and “turnover.” Finally, it assembled weekly, monthly, and quarterly reports, occasionally consisting of an executive summary, and distributed them to HR. 

One month Jim asked his analytics specialist, who compiles and sends the monthly reports, to hold off sending the report to gage reaction.  Do you want to know what they heard back…nothing! That's right, not a thing. People did not send Jim or his team an email asking why the reports were delayed; the HR leaders had not grown to depend on the report’s insights to make decisions or adjustments.

We suggested that ABC Company had an efficient data smog generator and advised that the company  instead flip its thinking around by asking: What’s the impact we’re looking to have? What’s the question we’re seeking to answer? Do we have the data we need to answer it?

In other words, start with the impact you want, that is, the question you want to answer. Then choose the metrics you’ll use to assess the impact. Then collect the data you’ll use to generate your metrics, report your findings, and assess whether you had the impact you desired.

This may seem overly simple but, for most of us, it requires a major mental shift. Starting with the end in mind means that:

1. You understand the organization’s business goals and people strategy (where you want to be).
2. You understand where the business is now.
3. You understand the road you’ll have to take to get to your goal, particularly from a people perspective.

Wendy, what should companies measure?

The right metrics are those that matter to the business—not to HR. If you choose to measure something, it should speak to impactful outcomes for employees and your business; it should not be because a measure can be benchmarked or everyone else is measuring it.

Just a few metrics are ideal. First-generation dashboards failed in part because they included everything. One solution is to include access to a lot of data via dashboards but keep the top-level “views” clean, simple, and focused on the right few metrics and business objectives.

Remember that impact means different things to different companies. For some organizations just being able to establish accurate headcount and start to analyze basic information on their global workforce could have huge impact, offer insights, and provide improvement if they hadn’t been able to be do so in a repeatable, consistent, and high-quality way in the past. For other organizations, being able to quantify the cost and root cause of turnover in a critical workforce segment might be the most important thing to focus on, since so much money is spent sourcing and developing this talent.

Given this business focus, what resources should run with this type of initiative?  I’m guessing that many may be concerned that their HR team does not have the ability to do this type of stuff.

In a recent cosponsored study with WorldatWork, we learned that the majority of participants have one to two full-time employees responsible for HR-related analytics, so, not a huge set of resources.

Creating an Analytics and Planning Center of Expertise (a “COE”) that has the right capabilities requires a team with extensive skills and knowledge in the areas of leadership, partnering, work-enabling, and functional and technical skills. As you alluded to in your question, this means that the COE, even one located within the HR function, includes non-HR specialists who understand the needs of the organization’s lines of business. Examples of functional technical competencies include the ability to analyze and interpret data and identify trends and correlations, as well as be comfortable with leveraging sophisticated technology platforms.

Of course, there is always our AMA training courses that are designed to give staff the skills needed to make strategic workforce planning process a reality.

What can organizations do, Wendy, to accelerate their time to success?

Good question.  We’ve worked with companies over the past 20 years in this area and have a few lessons we’ve learned about using metrics and analytics as a business tool.

• Be patient, stick with it: It can take years to build metrics and analytics capabilities. Don’t try to do everything at once.
• Continually update and refresh your metrics: Don’t assume your first set of metrics will be your last.
• Use what you’ve got: Leverage the data you’ve been collecting. Start your dashboard with what you’re already measuring.
• Align your metrics with the business’s strategic goals: HR drives human capital management but it’s the business, not HR, that owns human capital management.
• Don’t cut and paste: Benchmarks are the keys to someone else’s success. Go beyond what others are measuring and look inside to determine what the right, few measures are.
• Tell a story with data: Don’t inundate senior leaders with pages and pages of data. Don’t become a reporting function. Know your audience, match the data with the person, and make sure you tell a story with the data.
• Avoid some key pitfalls: Ensure the function is adequately staffed and that expertise resides in more than one or two people. Don’t let data credibility concerns keep you from starting down this path. And, finally, prioritize work so that day-to-day queries don’t drive out longer-term strategic activities.

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