Using people analytics to get to High-Impact HR


Posted by David Fineman on Nov 1, 2017

High-Impact HR refers to an HR function that helps the business excel in key areas—adapting to market changes, introducing new products and services faster, being more responsive to customer needs, operating efficiently and cost-effectively, and beating the competition. People analytics, which is really a subset of business analytics, is a key enabler of High-Impact HR. Deloitte’s 2017 Global Human Capital Trends report tells us that 71 percent of surveyed executives see people analytics as a high priority, and are applying it to talent challenges, as you might expect, particularly in recruiting and also in performance measurement, compensation, workforce planning, and retention.1 But it’s not just about HR—people analytics addresses business issues, too.

Consider a few of the areas in which people analytics can support the business:

  • Sustaining revenue growth by predicting talent requirements, focusing attention on the highest-value current talent sources, and identifying potential new sources to support growth.
  • Driving revenue in new and existing channels by mixing labor data with customer and pricing data to enhance the development and deployment of human capital.
  • Protecting the organization’s ability to retain top talentby proactively predicting attrition risk and identifying cost-effective interventions.
  • Enabling profit growth and cost reduction by providing granular analysis of labor spend and ROI by combining labor, compensation, and finance data to track specific business outcomes.
  • Enabling strategy execution by anticipating potential leadership gaps and proactively developing a pipeline of top talent.

Delivering high impact—Start with believable data

Getting to high-impact analytics relies first and foremost on accurate, believable data. Without accurate data, metrics and operational reporting may as well not even exist. Potential HR data issues include validity, duplication, outliers, and poorly defined or inconsistent calculations or definitions (for example, not considering all of the costs associated with an organization’s “cost to hire” metric). These limitations can make interpreting metrics difficult for key stakeholders and those who use the insights gained from the reports to make decisions.

The following illustrates levels of sophistication and capability of people analytics. When this model was introduced a few years ago, about 80 percent of organizations studied were in the lower two levels (about 56 percent in the Operational Reporting level and another 24 percent in the Advanced Reporting level).2 What we believe has happened over time is that the 80 percent figure has stayed relatively constant, but more organizations have moved into the Advanced Reporting tier.

Source: Bersin by Deloitte, Deloitte Consulting LLP

Organizations have been able to increase their analytics maturity by implementing data governance programs, prioritizing focus areas, standardizing reporting intake and delivery processes, and upskilling analytics acumen.

Solve a real problem

While there are many potential areas to apply people analytics, one of the first questions HR should be asking is “What does the business need?” In other words, what challenges is the business facing that people analytics could address? For example, predictive attrition measurements to uncover individuals who may be a flight risk aren’t particularly helpful if the organization doesn’t have an attrition problem. To deliver high impact, the analytics should be focused on a particular challenge and have a sponsor in the business working with HR to address it.

Deliver data that matters to the business

HR tends to be good about reporting within a specific talent area, such as talent acquisition. While that data might be essential to running an effective talent acquisition function, some of it, such as the number of requisitions a particular recruiter is handling, probably doesn’t interest a business leader. Instead, that business leader might be more interested in how successful new hires are.

Measuring that could require knowing the source of the hire, and the new-hire’s six-month salary increase, performance rating, time to promotion, and operational effectiveness. Greater insights can be uncovered when data from multiple talent (and non-talent) functions are combined. This type of multifaceted analysis requires that the organization raise the level of analytics maturity from Level 1 to Level 2 and potentially higher.

As a case in point for business-driven problem solving, a global manufacturer we worked with was concerned that it might have a retention issue and believed it could use analytics to pinpoint the problem areas and identify which talent management programs could be created or enhanced to improve retention. The first step was to analyze where voluntary turnover was occurring, considering variables such as length of service, location, organizational level, function and business level, manager tenure, and organizational layer.

The analysis painted a picture of which groups in the organization were at highest risk of leaving, i.e., younger groups and those with less than 5 years of service; finance and sales functions; employees reporting to less experienced managers, and the like. This led the company to implement a variety of talent initiatives for reducing turnover among these groups, such as expanding onboarding programs, establishing cohort-specific advisory councils, and introducing a development program for new managers. Business leaders were specifically asked for feedback and recommendations and to provide sponsorship and support for HR’s ongoing efforts and next-step efforts. The company believed so much in the work that the executive team had specific goals for the next fiscal year for talent development and retention based on the analytics work the team completed.

Use the data to drive meaningful change

Insights from people analytics data can be used to drive change. Consider how one organization we worked with applied analytics to succession planning. After perceiving a leadership gap within a particular region, it sought to identify the attributes of a successful global leader and determine whether its current workforce possessed those attributes.

The company developed a scoring model to identify the attributes of success for a role based on historical data, then identified and scored current employees using that model.

Source: Deloitte Consulting LLP, 2017

Next the company determined the top reasons driving the individuals’ scores, used that information to identify a set of data-driven improvement opportunities, and implemented targeted development programs and stretch assignments. At the same time, it educated key executives on the importance of consistent and transparent development of high-potential talent.

Need help getting started (or going further)?

People analytics is still a work in progress—the percentage of companies correlating HR data to business outcomes, performing predic¬tive analytics, and deploying enterprise scorecards barely changed between the 2016 and 2017 Global Human Capital Trends reports.3 But not all issues require advanced analytics: most organizations can begin to make progress starting right where they are, and it is advisable to use the least sophisticated approach to achieve your objectives.

You can read more about the role of people analytics in High-Impact HR in Enabling business results with HR measures that matter and evolving your organization’s analytics capabilities in People analytics: Recalculating the route.

1 Laurence Collins, et al., “People analytics: Recalculating the route,” Rewriting the rules for the digital age: 2017 Deloitte Global Human Capital Trends, Deloitte University Press, https://dupress.deloitte.com/dup-us-en/focus/human-capital-trends/2017/people-analytics-in-hr.html?id=us:2el:3dc:dup3824:awa:cons:hct17.

2 Josh Bersin, Karen O’Leanoard, Wendy Wang-Audia, High-Impact Talent Analytics, Building a World-Class HR Measurement and Analytics Function, Bersin by Deloitte, October 2013.

3 Laurence Collins, et al., “People analytics: Recalculating the route,” Rewriting the rules for the digital age: 2017 Deloitte Global Human Capital Trends, Deloitte University Press, https://dupress.deloitte.com/dup-us-en/focus/human-capital-trends/2017/people-analytics-in-hr.html?id=us:2el:3dc:dup3824:awa:cons:hct17.

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