Power of People, The: How Successful Organizations Use Workforce Analytics To Improve Business Performance (FT Press Analytics)

by Nigel Guenole

Workforce analytics is a discipline that is increasingly needed in organizations. This growing demand can be attributed to the following: • The continued need for increased business value and market competitiveness • The requirement for information and data in real time from managers and executives, to help them run their operations more efficiently and effectively • The move toward a consumerized working environment and the provision of personalized services using workforce-related recommendation engines • The deconstruction of traditional business models and the proliferation of the gig economy and independent workers • The ongoing explosion of Big Data from devices such as wearables and sensors that will expand the amount of available workforce-related data

Taking into account all of these points, the most descriptive and accurate name for this function is workforce analytics. This term best describes the broadest set of workers that contribute to organizational success and the fullest responsibilities of the function both now and in the future. Other experts concur with the use of the term workforce analytics as the best description of the function. Most notably, the SHRM Foundation, the research arm of the Society for Human Resource Management (the professional body for the HR profession in the United States), uses the term workforce analytics in its report “Use of Workforce Analytics for Competitive Advantage,” undertaken in partnership with the Economist Intelligence Unit. With the name of the function in mind, we can define the work of the function as follows: Workforce analytics is the discovery, interpretation, and communication of meaningful patterns in workforce-related data to inform decision making and improve performance.

The leader of the workforce analytics team need not have followed a specific career path before taking on the leadership role, but certain approaches, attributes, skills, and experiences will provide a better platform for success: • Have the workforce analytics leader report directly to the CHRO. • Clarify the role of the workforce analytics leader and the specific responsibilities for success. • Develop business acumen by continuously learning about the internal operations, metrics, and key performance indicators for the business. • Build external awareness by learning about the marketplace, competitors, and other external factors. • Improve financial and numerical literacy. • Develop leadership attributes to challenge the team, develop a cohesive team, inspire team members for success, and drive to achieve. • Create a workforce analytics team that has a blend of the Six Skills for Success (see Chapter 12) and ensure familiarity with the team’s areas of specialization.

Discovering, interpreting and communicating meaningful patterns in workforce-related data demands a robust methodology. Whether for a short project of a few weeks or a longer one that spans many months, methods need to be straightforward and complete. Successful workforce analytics projects follow these main methodology recommendations: • Consistently apply all eight steps of the purposeful analytics model to your analytics projects. • Start projects by defining the business question and building strong hypotheses. • Use the most appropriate technology and methods for your analyses to ensure robust results. • Get the point of your analytics projects across to your sponsors and stakeholders through clear visualization and storytelling. • Help your business translate project recommendations and decisions into action and evaluate the results. • Choose your sponsors wisely, with an eye toward strong, consistent support throughout the entire lifecycle of your projects, from request to implementation. • Familiarize yourself with the common reasons analytics projects fail, and throughout the eight steps, ensure that potential problems are avoided or addressed.

Analytically curious HR professionals, and certainly all members of the workforce analytics team, should understand the basics of analysis so they can have sensible and informed conversations. • Select research designs that are appropriate for the business questions you are trying to answer and know how to interpret the results. • Learn the objectives that quantitative analyses aim to achieve: explore, associate, predict, classify, reduce, and segment. • Use qualitative analysis to generate a hypothesis, interpret results, and contextualize findings by adding color to quantitative analysis. • Consider the use of unstructured data for both qualitative and quantitative analysis. • Familiarize yourself with conditions under which statistical modeling or

machine learning is more appropriate. • Be clear about the tools and skills you have at your disposal for advanced analyses such as analyzing unstructured data. • Scrutinize your analyses for their potential to produce adverse impact, bias, or unfairness, and take corrective action as needed.

The expert analytics professionals in these case studies undertook their projects with focus and intent. The organizational challenges and the techniques used to address them varied across the cases, but the following factors were common to all: • The problem to be addressed was clearly articulated and linked to the overall strategy of the organization. • Sponsorship of the project by an influential person positively impacted all stages, from initiation through implementation. • Hypotheses were clearly understood and testable (and, in some cases, developed iteratively). • Data gathered and analyses undertaken were appropriate for the project. • Insights and recommendations were clear and precise. • Communications to various stakeholders were well planned and developed with the help of expert communications professionals, when needed. • Projects were designed to provide business impact and were evaluated for

success and learning. • Internal or external partners contributed expertise to the team to ensure success.

These key steps set the direction for workforce analytics in your organization: • Pause, listen, and think before you dive into your first analytics project. • Talk to the person who appointed you, or the most senior person in your functional line (for example, the CHRO), to clarify the scope of your role. • Identify prospective project sponsors for interviewing and ask them about business challenges. • Identify which of the Seven Forces of Demand are driving the primary need for analytics in your organization. • In a memorable vision statement, describe the desired future impact of your function on the organization. • In a memorable mission statement, describe your objectives and how you will address them. • Use the vision and mission statements to communicate your function’s identity to your team and the wider organization, and to prioritize your projects.

Working effectively with stakeholders is essential for workforce analytics success. Relationships are needed with a wide variety of people throughout your organization. Approach the task of stakeholder management thoughtfully and systematically, with the following actions: • Identify the various stakeholder groups, taking into account those served by the analytics team, those you are dependent on, and those whose working lives might be affected. • Determine your stakeholders’ perspectives on analytics and adjust your communications accordingly. • Be cognizant of data privacy and security requirements, and seek legal expertise to successfully navigate the requirements. • Create, execute, and maintain a communications plan to structure your interactions with stakeholders, including key messages and discussion topics for each. • Help stakeholders understand and fulfill their roles and responsibilities. • Bring value to your stakeholders; make them more successful, acknowledge their contributions, and listen to and address their concerns. • Plan for the end from the beginning: Think through and discuss potential analytics results and recommended actions, as well as how you will evaluate actions that you implement.

Selecting your first workforce analytics project can be a difficult challenge, but taking a systematic approach to considering both complexity and impact ensures that you make the most appropriate choices. In particular, remember the following guidelines: • Spend enough time planning your project to address all the hurdles you expect to encounter, but be prepared for the unexpected hurdles that will invariably arise. • Identify potential projects that relate to the organization’s key performance indicators. • Classify your projects according to their complexity and their expected impact, and go for a Quick Win that is low-to-moderate complexity and

moderate-to-high impact. • When rating the complexity of the project, consider the following factors: politics, skills, data, technology, and ease of implementation. • When rating the expected impact of your first project, remember that the project should deliver a sufficient return. The benefits should also be realized in the short to medium term and should offer a greater net return than investing in any other workforce analytics project.

Data are essential building blocks for workforce analytics, and relevant, high-quality data are needed for quality results. The following guidance helps you strike the right balance between ensuring data quality and progressing the workforce analytics agenda: • Build relationships with data owners to facilitate data access and learn the details of the datasets (such as allowable data values, methods for interpreting the data, and ways to spot errors); utilize data profiling technology to assist with data checking. • Check data for missing values, determine reasons for the missing data, and take appropriate corrective action (drawing on expertise as needed). • Verify that you have the most current and complete version of the data needed for the analysis. • Determine whether you can create the data you need from the data you have, or find a proxy for the data you need. • Consider a full spectrum of data sources and choose those that best answer your questions. • Take the time to establish data governance processes, including data steward roles, to ensure ongoing data quality. • Participate in online forums and user groups to stay current with the latest views on data challenges and solutions. • Hire or partner with a data scientist to assist with data decisions; an intern can be a cost-effective approach. • Recognize that data collection and analysis will be iterative and that you will refine and improve as you go.

Decisions about technology are among the most important ones you will make in workforce analytics. To make the right decisions, you need good

advice from Information Technology (IT) and HR Information Technology personnel and from your data scientists. To prepare for these discussions, take the following steps: • Decide on the appropriate mix of technology by understanding what you have now and what you need to perform the required types of analyses in support of your workforce analytics vision and mission. • Get familiar at a high level with the basic components of workforce analytics technology, including the benefits of cloud technology. • Consider whether and when cloud-based services will work in your organization. • Understand the breadth of technology required for a workforce analytics technology system: the HRIS, the HR data warehouse, reporting and business intelligence technology, analysis and data integration software for advanced analytics, cognitive solutions, and visualization software. • Decide whether to share, subscribe to, or own your technology, based on ease of access, financial cost, and your degree of concern over how the technology ages.

Building the analytics team or function is a critical task in the early phases of workforce analytics because the capability of your team is an important determinant of your success. This can seem like a challenging task, but taking a structured approach and following the principles outlined in this chapter sets you on the path to success. Be sure to cover these tasks: • Ensure that you understand and have access to the Six Skills for Success, whether they are on your team or are easily accessible elsewhere. Configure the skills in your team and its size based on the expected workload and nature of projects.

When deciding whether to hire new staff or develop existing staff, be aware of the pros and cons of each approach, such as whether skills developed in another area transfer to a workforce analytics context. • Remember the fundamentals of personnel selection. Cognitive ability and certain personality traits, particularly conscientiousness, are important in all roles and can be tested with standardized psychometric testing.

Establishing a workforce analytics function does not necessarily mean staffing a fully skilled end-to-end in-house team. Although that is certainly one option, collaborating with partners (either internal to the organization or external providers) could be the best path to success. Consider the following when choosing among your options: • Understand the options for bringing together the needed workforce analytics skills (in-house, in-source, outsource) and the advantages and disadvantages of each. • Determine the availability of needed skills in the local labor market. • Assess the time required for sourcing, hiring, and training new team members relative to timing expectations for project delivery. • Estimate the cost of hiring versus outsourcing, given the skills needed.

Assess the organization’s perception of HR, to determine whether the credibility typically associated with external experts will be advantageous. • Determine whether the required skills reside elsewhere in the organization, and assess the feasibility of partnering with those functions to execute your initial projects. • Investigate whether any people in other parts of your organization have undertaken their own workforce analytics efforts; if so, seek opportunities to collaborate. • Consider all the factors (including budgets, skill availability, time, organizational expertise, organization size, perceptions of HR, and the need for third-party objectivity) to select the best option for your circumstances.

A well-planned operating model drives efficiencies and allows the workforce analytics team to focus on the work at hand: successfully implementing analytics projects that improve business results. Following are the key actions for establishing your operating model: • Confirm your vision and mission, incorporating the renewed perspective that comes with experience. • Understand data privacy legislation, regulations, and policies for all countries in which your organization operates, and adhere to them at all times. • Understand the sensitivities of HR data; rely on local HR expertise to guide your analysis and ensure that you operate within policies and guidelines. • Request broad permissions for data use when embarking on a new data collection effort, and encourage employee participation by applying the FORT framework (gathering feedback, opting in, recognizing contributions, and ensuring transparency). • Ensure that the reporting structure provides access to the CHRO. • Manage your team’s scope and configuration to ensure that analytics does

not get displaced with metrics reporting activities. • Clearly define the roles and responsibilities of your team and the people you interact with to execute your mission. • Agree on a decision-making process that will serve your team well, and use an advisory panel as part of your process. • Adopt a consultancy approach to project management, with clearly defined activities and checkpoints during project initiation, execution, and conclusion. • Build a business case at least annually that contains a comprehensive view of investments and benefits, to demonstrate return on investment and obtain commitment for funding. • Agree on and implement your own outcome and proximal metrics to hold your team accountable for delivering value to the organization.

To reap the most benefit from workforce analytics and achieve the widest impact, the broader HR function within an organization must embrace and demonstrate an analytics mind-set through their words and actions. The following recommendations will help you enable an analytics mind-set in your HR function: • Understand the variations of analytics literacy among your organization’s HR professionals and categorize them accordingly: analytically savvy, analytically willing, or analytically resistant. • Customize communications and enablement based on the analytics literacy categorizations: • For the analytically savvy, provide training on the latest analytical techniques, tools, and methods; encourage them to connect with community forums. • For the analytically willing, demonstrate and coach them on familiar data and tools, and have them attend basic statistics courses. • For the analytically resistant, win them over by using analytics to provide insights that will make them more successful. • Identify HR business partners with the right analytical mind-set and skills

to perform the important translator role in workforce analytics. • Understand your leaders’ views of analytics, leverage their support fully, and form a coalition of additional supporters as needed. • Encourage an analytical mind-set in leaders through one-on-one coaching and involvement in projects that are directly beneficial to them.

Efforts to bring workforce analytics to an organization are sometimes met with resistance. For almost any reason offered for why workforce analytics “won’t work here,” an appropriate counterargument can be made. The following tips can help successfully overcome resistance: • Understand how your organization views the value of analytics. • Identify the sources and the nature of resistance by spending time listening to others’ perspectives. • Determine the underlying cause of resistance, such as skepticism, perceived threat, lack of trust, lack of understanding, perception of insufficient skills, or unwillingness to invest. • Choose how to overcome the resistance; possible actions include educating, demonstrating value, partnering for skills, starting small, keeping it simple, making your case, and helping the resistor succeed.

The art of storytelling and visualization with data requires technique and practice. Effective storytelling increases the retention rate of the messages and the likelihood that action will be taken as a result. Visualization helps to create an understanding of the insights and recommendations, and a good understanding of your audience helps you tailor communications to maximize impact. For these reasons, storytelling and visualization are skills that workforce analytics practitioners should practice. Following are the main points this chapter emphasizes: • Ensure that your stories follow these principles: Educate, don’t fabricate; enlighten, don’t overwhelm; and convince, don’t confuse. • Create effective workforce analytics stories by providing context, creating emotional impact, revealing the conflict, and conveying a memorable message. • Construct visualizations that show the intent of your analytics by clarifying the message of your visualization, designing it appropriately, and testing it before you use it with your selected audience. • Understand the different types of audiences (newcomer, enthusiast, scientist, or master) and tailor your communications accordingly. • Get help from others in preparing your communication materials if you need it, and strive to keep things simple.

Workforce analytics is an essential organizational capability and experts believe its impact on business performance will only increase. By taking the following steps, you can position your function well to capitalize on the opportunities:

Familiarize yourself with emerging data sources in workforce analytics, such as worker digital footprints, sensors, and wearable data. • Ensure that your function is ready to utilize new and emerging technology that blends reporting and predictive analytics using open source technology, all deployed with artificial intelligence and cognitive technology. • Decide on the appropriateness of data sources for particular purposes based on the scientific evidence, legal context, and social implications of using the data. • Prepare your team to evolve its skills, particularly the ability to lead in a complex environment, with privacy as a specialty and using data scientists who can learn new methods and techniques quickly. • Learn why workforce analytics is important for tomorrow’s business and prepare to embrace the road ahead.