The Race Is On: Winning Analytics Fitness

Analytics seem to be invading every corner of our world. The word has come to mean many things to many people — Google analytics, sports analytics, operational analytics, social media and crowdsourced data, big data … the list goes on. The most all-encompassing definition of analytics is “the discovery and communication of meaningful patterns in data.”

The persistent message from the media and many leaders is “analytics everywhere, all the time, for everything.” Most organizations invest in analytics capabilities piecemeal where they see potential for the highest impact on business outcomes. In fact, only 33 percent of businesses in the U.S. and Western Europe are aggressively adopting analytics across the entire enterprise. It’s simply an issue of prioritization. While it’s clear that analytics are critical to business success today and are the engine for innovation in business tomorrow, it’s unrealistic to think that organizations can — or even should— invest in analytics tools and capabilities for every aspect of their business right now.

In fact, business competitiveness is rooted in achieving the right level of analytics fitness in the right areas as part of an enterprise analytics strategy. Given current global workforce dynamics and the inordinate cost of labor, organizations should consider their workforce one of the most critical areas in which they should be analytically “fit” right now. 

Four key elements contribute to workforce analytics fitness: a workforce analytics strategy; workforce priorities based on business objectives; workforce analytics tools; and workforce intelligence advisers.

Those of us who run races, regardless of length, know that athletic fitness is defined by the race and the athlete. Runners choose to enter the race that meets their strength and long-term goals and adjust their training schedule to match.

Like an athlete’s physical fitness, the level of analytics fitness required by an organization varies based on the organization’s competitive strategy. All companies achieve some combination of managed costs and accurate projections, product and service quality, productivity of people, speed to market and process efficiency.

However, like an athlete’s training plan, the right balance of focus and investment in each of these areas is defined by the organization’s unique business strategy. Investment in analytical tools and capabilities in the highest priority areas enables an organization to successfully compete by ensuring leadership has the information and insight required to make the best decisions in these areas.

Many organizations are now turning their analytics focus toward people: managing people costs, projecting people needs and improving people productivity. Key global workforce dynamics are placing increased pressure on organizations, particularly multinationals. These dynamics include emerging market growth in China, India, Eastern Europe and South America; the dawn of the so-called free-agent nation in which employees are increasingly acting as free agents in the labor market; baby boomers retiring creating succession planning and knowledge-transfer challenges; and colleges and universities not turning out business-ready graduates at a pace to keep up with demand. This pressure — in addition to workforce costs comprising over 50 percent of most organizations’ expenses — necessitates predictive and actionable intelligence about the workforce.

Elements of Workforce Analytics Fitness

Achieving fitness in workforce analytics begins with understanding the organization’s goals and its competitive pressures. A human resources analytics strategy should build on insights across HR domains, incorporate internal and external workforce data, and prioritize investments based on their ability to achieve organization goals. And it’s the real-world challenges of aggregating and integrating workforce data from fragmented HR systems — without the ability to connect people data with other business data, or to incorporate external market information — that justifies the need for an integrated analytics strategy.

If you’re producing reports from your workforce data, you might think you’ve got workforce analytics figured out. But using workforce data only for reporting is essentially standing still while your competitors in the race move on without you. Only when you’re able to measure how your organization is working, and predict changes, are you really in the race. To help assess your workforce intelligence fitness, ask yourself these questions:

• Can you identify, from a workforce perspective, how your organization generates profit and creates value?
• Do you know the three to five factors most critical to achieving operational success? Are you measuring them?
• Do your current workforce reports tie people data to organizational outcomes?
• Do you have a fact-based perspective on turnover in critical parts of your organization? Do you know the people who are most likely to voluntarily leave next?
•  Do you have an understanding of which talent management programs (pay, training, etc.) are most valuable to employees?

The more of these you’re able to answer with “yes,” the more competitive you’re likely to be.

In order to plot the course ahead, organizations must tie talent needs to business objectives. The focus of workforce intelligence is understanding the key people-related factors that drive an organization’s profitability or value, and how the interrelationship between those key factors can continuously improve organizational success. 

Organizations should find the right level of “analytics fitness” across operational imperatives, including:

• Cost management and projection accuracy
• Product and service quality
• People productivity
• Process efficiency

Business objectives need to be prioritized and cascaded down to people-related objectives. An organization’s talent management programs (e.g., recruitment/retention, pay/rewards and training), must be aligned with the factors that influence business success. Organizations also need to understand the most effective ways to deploy their human capital, because dynamic use of human capital (e.g., moving talent laterally in the organization and creating growth opportunities for high potentials) drives better organizational performance. Finally, objective prioritization based on business objectives and “road mapping” is important in laying out how and where workforce-related investments should be made.

Unlike the runner who’s likely already trained on the course on which he or she will compete, organizations have a very limited perspective of the road ahead and few tools to anticipate changing conditions or to spot hills, valleys and potholes. Both the organization’s workforce and competitive environment are dynamic and produce extraneous, noncritical information. For the runner, for example, the critical factors in the race are surface, weather conditions and level of hydration. The scenery — whether trees, mountain vistas or urban traffic noise — is immaterial to the race. Similar organizational “noise” when trying to develop and manage a workforce intelligence road map can thwart progress. Organizations often benefit from a coach that can help them discern what internal and external (market) workforce data are critical for the road map, and then provide experienced guidance as the organization starts its run toward true workforce intelligence.

What Winning Looks Like

Data-based evidence and predictions help set your organization’s talent management strategy through:

• An optimal operating modelby identifying revenue-generating roles and evaluating the need to centralize, decentralize, share or outsource.
• A targeted development strategy and proactive recruiting strategyby identifying required skills for current and future organization needs, evaluating the current and future workforce supply, and understanding the flow of talent within the organization.
• A performance-based compensation strategyby understanding which total rewards elements are most critical to keeping staff engaged, based on benchmarks, feedback and turnover trends within the organization.

In execution, a workforce strategy should go beyond just measuring data; it should prescribe action. Consider the following hypothetical example. An HR manager at a large employer views their workforce analytics solution and sees that there is high turnover in a critical division with high growth potential. They also see the skills within this division will be in high demand in geographic markets where this division is located.

On average, every employee who leaves this division costs the business $30,000 in lost productivity and costs to hire and train a replacement. The HR manager then has an evidence-based business case for specific actions such as adjusting compensation to meet market demand. The end result is prescriptive action with a measureable outcome and tangible value for the organization.

Financial planning and budgeting processes have historically been separate from the (sometimes optional) workforce planning and head count budgeting process. The separation of these two highly interrelated processes creates challenges: multiple sources for head count projections, errors and duplication of effort. Today’s workforce intelligence tools allow organizations to predict, model and build workforce plans aligned with the financial planning process, and with collaborative inputs from hiring managers, HR and finance.

Organizations with workforce plans rooted in predictive and prescriptive analytics are able to:

• Develop business cases and budgeting for workforce investments.
• Substantiate HR programs and processes to support workforce needs (recruiting, training, development, compensation/benefits, etc.).
• Determine the workforce implications of entering new markets and locations.
• Support workforce growth and contraction decisions based on costs and talent needs.
• Establish an ongoing and business-aligned process to review and address workforce gaps and challenges.

Integrating data that would otherwise remain stranded within disparate systems is a necessary condition of workforce intelligence. Consider the hypothetical example once again. This time, the HR manager has learned from a workforce planning solution that a certain skill is needed for the critical division and the employees that are leaving share this skill.

Remember, the attrition cost to the business is $30,000 per employee. And, while adjusting compensation to market demand is one option, training employees to develop the skills in demand is much less costly and has the secondary benefit of increasing employee retention. This kind of insight can be gained only by integrating three data sets (HR, finance and training) that are typically hosted in separate systems. The HR manager now has two options for an evidence-based decision and can take actions with measurable outcomes.

Staying the Course and Staying Ahead

Organizations that are analytically fit when it comes to their workforce are able to make sense of multiple integrated sets of talent-related data (e.g., turnover, performance, location, tenure and strength of external talent market), predict talent trends (e.g., availability of skills the organization will need in five years in the external talent market by ZIP code), and prescribe action based on the data. With these insights, they are able to align their most expensive assets (people) and their people-related investments (talent programs) to business imperatives.

Successful athletes don’t train for a race without a plan, clear goals, the right equipment and knowledge of the course. Your organization shouldn’t either.

Rebecca Atamianis the director of people and performance and career practice at Buck Consultants at Xerox Corp. Travis Klavohn is the director of human capital analytics at Xerox Consulting and Analytics. Comment below or email editors@workforce.com. Follow Workforce on Twitter at @workforcenews.