As these authors write, “Analytics does not have to be a whip used to increase the stroke count associated with extracting more from individuals. Rather, it can provide the opportunity to build a more effective, empowered and engaged workforce that increases the value of the larger organization.” They identify and describe six steps for achieving this in the article that follows.
According to a newly released study of over 1,700 CEOs from around the globe, human capital was cited as the most important factor in maintaining competitive advantage. (see Figure 1).[i] Other traditional sources of advantage, such as access to raw materials and physical assets ranked far lower on the scale.
These findings highlight what many of us who have worked in the human capital field have known for years: people are essential to the long-term success of the organization. Yet, organizations have not applied the same rigor to understand this critical asset. Compared to functions such as finance and supply chain management, HR has not had a traditional depth of experience in making fact-based decisions. Another recent IBM study of over 700 Chief Human Resource Officers highlighted that only slightly more than one-third felt that their organization was able to use analytics to effectively make strategic decisions about their workforce.[ii] Given the importance CEOs are placing on their workforce, could there be a disconnect between the value of the workforce and the ability of the organization to apply fact-based decisions to managing it?
One reason organizations fail to use workforce analytics is the lack of a simple paradigm that informs how analytics help businesses better compete. In fact, there is a general sense in many organizations that workforce analytics is simply measurement: head count, labor costs, turnover, and so on. In fact, one of the questions people ask us most is, “Which workforce metrics are most important?” as if there were a universal truth that all organizations could follow. This is not the case. We believe that workforce analytics is not about:
- Simply counting “heads.” Instead, it is about knowing how “heads” can be organized and utilized most effectively.
- Reporting turnover. Rather, it is about understanding what skills are being lost, what skills are most valuable, and how to retain those that are essential.
- Building a catalogue of employee knowledge, skills, and abilities. Workforce analytics, in contrast, identifies sets of competencies that managers can use to rapidly select and deploy capable workers at the right time, cost, and place to achieve critical business outcomes.
- Reporting engagement scores. Workforce analytics seeks to understand which aspects of employee satisfaction may lead to high performance and what can be done to improve them.
- Buying “analytic software” It is not about buying technology and looking for a way to use it, but rather being attuned to the workforce issues that interfere with company success. After identifying the problem, it is about adopting the processes and tools necessary to implement the right solution.
In short, successful workforce analytics involves modeling data (both qualitative and quantitative) to understand the past, present and future drivers of organizational performance. It is a rigorous and systematic approach to defining workforce problems and testing successful solutions. It informs what tools and processes the organization should put in place to achieve its highest potential. Finally, analytics is most successful when applied to an immediate and pressing business problem whose solution is critical to competitive success.
Another reason why workforce analytics has not been widely applied in companies is that many executives often see getting access to the needed information as too difficult and time consuming. Executives often rely on their own intuition and seek to avoid “analysis paralysis.” Analytics often means challenging the fundamental assumptions that form the foundation of their intuition and requires a disciplined approach to solving problems that some executives find uncomfortable.
Meaningful analysis almost always requires the integration of data from financial, operational, sales, and human resource systems; unfortunately, these systems are often set up to support their separate owners, functional silos, and administrative processes. Each function worries about the security of the data and how it will be used; in many cases, each system has different definitions of common concepts and different levels of quality and refresh cycles. This pattern of data ownership and system silos makes rapid, as well as continuous integration of data frequently challenging.
Still other companies have a cultural bias against adopting a disciplined analytics approach to people, believing that people are not inanimate parts. For some, analytics is often thought of as a cold, heartless way to manage a workforce — a Tayloristic approach to reducing individuals to cells on a spreadsheet. However, we argue that companies can use workforce analytics to make more justifiable decisions and prevent arbitrary actions that can have a negative impact on individuals. As John Boudreau highlights in his book, Retooling HR:
“Is it because people are not widgets, and out of respect for their free will and humanity it’s unfair or wrong to use the same logic for workforce decisions as we use for decisions about more inanimate objectives like inventories and machines? No. In fact, it’s arguably more unfair and disrespectful to employees and job applicants to make important decisions about where to invest in their development, performance and careers in less rigorous ways than those applied to more traditional resources.”[iii]
Analytics does not have to be a whip used to increase the stroke count associated with extracting more from individuals. Rather, it can provide the opportunity to build a more effective, empowered and engaged workforce that increases the value of the larger organization.
Using workforce analytics to make more strategic decisions
Having worked with a range of clients in industries as diverse as airlines, pharmaceuticals, retail and manufacturing who have wrestled with strategic workforce issues, we have identified four critical areas where organizations can focus their time, energy, and resources to more effectively use analytics to improve workforce productivity and capability. Answering these questions is critical to demonstrating how the human resource function can add substantially to the strategy and operations of the company.
- Based on the organization’s strategy, what is the work that needs to be done, and are the processes, structures, and roles designed to efficiently and effectively accomplish it? This analytic approach shifts the focus of executives away from simply reducing head count and costs to understanding how an organization can become more productive and competitive—knowing where to invest in their organization and workforce and what the benefits of these investments will be.
- Is the human capital supply chain filling those roles with people capable of doing the work at the quantity, quality, and cost required of the business model? This question moves the focus of workforce decisions away from the cost of hiring, training, and developing workers to one that addresses how best to meet the demand for labor required to execute the strategy of the company.
- Once in place, is the workforce fully engaged and motivated to meet or exceed performance standards? This analytic approach migrates from quick and narrowly defined performance management fixes to ask a broader but basic business question: what do we expect from our workers and what do we need to provide them to meet those expectations?
- Finally, since change is ubiquitous, how can we detect the need for change, test innovations and disseminate those throughout the organization? This approach focuses on understanding how organizations and people can share insights and innovations that allow them to be more productive, while reducing the risk of poorly designed or executed change.
The answers to these questions will have a profound effect on the competitive success of an organization. However, obtaining these answers requires applying the scientific method, coupled with sound financial analysis and operational realities. The combination of methods allows an organization to translate the findings of the research into profitable action.
Six steps for maximizing the value of strategic workforce analytics
We have identified six important steps that successful organizations use to apply workforce analytics in solving important strategic issues:
Step 1: Frame the Central Problem
While it may sound obvious, taking the time to understand the real issues confronting the company is essential. Line managers and executives are very good at recognizing the immediate issues they face and usually eager to take action with the information they have at hand. Unfortunately, they often take those actions without fully understanding the underlying cause or which additional problems might result from their uninformed actions. However, without settling the immediate issue the company faces in the larger context of the business, any analysis will be focused on confirming an executive’s hunch instead of thoroughly examining and solving the problem.
Step 2: Apply a Conceptual Model to Guide the Analysis
This requires formulating a model that identifies which factors may tell us what is going on in the company, and how we go about understanding whether these factors are driving performance. Those involved in workforce analytics run the risk of becoming lost in the accumulation of data that companies have available, while at the same time finding themselves stymied by the seeming lack of critical information. Analysts need a way of determining what data are important and what they can do without, as well as some basis for understanding how missing data may limit the interpretation of their findings.
Step 3: Capture Relevant Data
This step is all about quickly getting the best data available to analyze. Too often, companies get lost in finding data that is not needed and/or cleaning data beyond what is required for analysis. As mentioned earlier, most companies are rich in data and poor in information. Useful analysis depends on collecting and constructing measures that can be clearly tied to employee productivity and corporate profitability. The necessary information usually resides in different databases that must be integrated, and even then, the data is often not in analyzable form. Analyzing the effect that the workforce has on company success almost always requires the integration of finance, sales, operations, and human resource information, each with its own definition of organizational relationships, head count, and costs.
Step 4: Apply Analytical Methods
This step is not only focused on solving the problem but also addressing it in a way that is practical and relevant to the business. There are many statistical techniques available to perform organizational and workforce analysis, including simple cross-tabulations, regression, stochastic process modeling, factors analysis, cluster analysis, survey research, and experimental design. All have their appropriate applications; all have their strengths and weaknesses. Knowing which to apply to which questions is critical to producing valid findings.
Step 5: Present Statistical Findings to Stakeholders
Translating the analytical findings into action requires that management can understand and relate to the results presented. Otherwise, it will resist the information and the necessary changes implied. Regression equations, process models, and factor and cluster analyses do not immediately speak to the non-statistician. Results must be presented in a way that is consistent with the management philosophy and language of the company. Engaging stakeholders and inviting dialogue that connects analytical results with business experience are essential. The stakeholders’ responses to the presentation of analytical results breathe life into the statistics and enrich the understanding of the data. Such engagement is the key to finding the best solutions and obtaining commitment to transformative actions.
Step 6: Define Action Steps to Implement the Solution
This step provides a clear business case and roadmap for action. Identifying the relationship between particular workforce actions or attributes and company profitability is not enough to accomplish change. The analytical process must translate proposed solutions into a sustainable action set that supports and monitors the desired outcomes. This entails determining what processes and tools will be effective in supporting new actions by managers. The tools often need to be embedded in the managers’ existing routine to provide appropriate alerts, content, and actions that are linked to targeted events.
Putting it together: Making workforce analytics work for your organization
From our experiences in the organizations we have worked with, we have found that embedding workforce analytics into the fabric of a company requires the following important elements:
- Integration of data that are timely, accurate, and crosses traditional organizational boundaries. Too often, the data required for HR analytics are found in a range of systems, from HR systems that address recruiting, compensation, performance and learning to those that are geared towards sales and operations. For a host of reasons, these systems often house data that can be incomplete or are based on conflicting collections practices and assumptions.
- A flexible and responsive set of processes and technical infrastructure that can routinely and easily extract, clean, transform and integrate the information as well as react to the constant changes in the data and needs of the organization. This requires building an effective information supply chain that pushes actionable information to managers and employees where and when they need it during the execution of their normal work. While this data can be collected manually to address the needs of smaller scale projects, organizations looking to incorporate workforce analytics into their normal course of business need to look at more robust approaches to building, maintaining and analyzing this data.
- Individuals who have the functional, statistical and business oriented skills needed to interpret the results of data and work with internal audiences to use the information most effectively to drive organization change. We are seeing many organizations that are either developing these skills within the organization or drawing from analytic talent that exists within disciplines such as finance, marketing or customer service. Individuals with these capabilities need to be integrated with the IT developers who build analytical systems and the IT operational workers who maintain the source systems from which the data are drawn.
- Governance structures that allow stakeholders from different functional and operational groups to voice their needs and prioritize enhancements. This includes representatives from HR, IT, Finance, Sales, Operations and other groups that have a stake in how human capital data is applied throughout the organization. This process will allow the analytics organization to flourish even as budgets and membership in the governance structure changes.
We have often said that analytics is the connective tissue between vision and action – not an abstraction or set of tools looking for a problem. That connective tissue, the sinew and muscle of an organization, can enable the organization to realize the value of the workforce. It gives a company a powerful tool that allows it to create new ways to compete based on how they organize and deploy their workforce.
[i] Leading Through Connections: The IBM 2012 Chief Executive Officer Study
[ii] Working Beyond Borders: The IBM 2010 Chief Human Resource Officer Study
[iii] Boudreau, John, Retooling HR (Boston; Harvard Business School Press, 2010), p. 10.