Three organizations share how they use people data and analytics to amplify business strategy.
By Marta Chmielowicz
“People analytics” has been a hot catchphrase in the business world for years, with data promising to revolutionize recruiting, talent management, and myriad other HR processes. But while organizations have embraced data collection and reporting, data analysis remains in its infancy for all but the most sophisticated companies.
LinkedIn’s 2020 Global Talent Trends study of nearly 8,000 talent professionals reports that 73 percent of leaders view data and analytics as a major priority for their companies in the next five years, but 55 percent say they “still need help putting basic people analytics into practice.”
Furthermore, the LinkedIn survey notes that while many companies use data to measure employee performance (68 percent), few are using analytics to their full potential in areas such as predicting candidate success (19 percent) and identifying flight risks to improve retention (37 percent). The research shows that descriptive analytics may be here, but predictive and prescriptive analytics are still far on the horizon.
At a moment when data is accessible to all, understanding and capitalizing on analytics is quickly becoming a must-have skill in HR—one that is critical to identifying and solving business challenges.
Here, three companies share how they are integrating data analytics into their talent management strategy for real business results.
American Tire Distributors (ATD): Developing Learning
Prior to 2017, ATD did not have any systems in place to collect and analyze workforce data, says Chief People and Communications Officer Rebecca Sinclair. But over the past two and a half years, the company has built a powerful ecosystem of technology that connects its geographically dispersed workforce with a shared user interface, strengthening culture and engagement while collecting analytics that reveal insights about the business and its people.
The new talent management system features an HRIS integrated with advanced learning tools that leverage artificial intelligence, machine learning, and data science to link individual performance to business results. The resulting data is used to guide management strategies, develop personalized learning programs, and enable the company’s people-first culture.
“The advanced talent management capability allows us to create on-demand, leader-accessible talent dashboards using blended insights from our talent management system, HRIS, business outcomes, and analytics dashboards. This robust data is in turn used in organizational design conversations,” Sinclair explains.
ATD’s system has a personalized development insight tool that provides managers with valuable metrics about their and their direct reports’ performance, helping them more effectively engage, motivate, and manage their teams. Some key metrics include:
- correlations between knowledge growth and sales efficacy;
- correlations between knowledge growth and safety performance or incident reduction;
- the impact of onboarding completion on time-to-productivity rates;
- progression of leadership knowledge development; and
- associate progress in understanding overall business transformation.
“This also has a unique capability of providing leaders with an understanding of their team dynamics and producing tips to improve communication and their ability to flex and engage with the team as a whole,” says Sinclair. “These insights are a great tool for people leaders to use when completing performance reviews, delivering feedback, or learning about their team.”
But the data has improved more than just management practices; stronger connections have been forged between talent and learning teams, strengthening knowledge sharing between departments. ATD’s managers are able to work with learning associates to align development activities with quarterly talent goals, which enables proactive succession planning, internal candidate sourcing, high-potential mentorship programs, and more.
One benefit is the ability to create targeted learning programs for employees. By consulting the data, leaders have insight into their employees’ skills gaps and can create personalized micro-learning plans according to each individual’s personal learning algorithm. This drives reskilling and upskilling, which leads to sustainable behavioral results that enhance business performance.
These personalized learning programs are monitored through a performance management process, which uses defined metrics as a basis for quarterly talent conversations that outline clear, targeted goals aligned to each business unit.
Another way that learning and performance data come together to enhance ATD’s business strategy is through workforce planning initiatives. For example, the company used turnover data to develop on-demand, guided career advancement plans for associates in its warehouse.
“ATD created a position in between entry level and driver to allow for greater career progression and development, as well as flexibility within the business. Overtime reduction and courier reduction were two operational metrics that were positively impacted,” says Sinclair.
Thanks to these initiatives, the company has seen marked improvements in individual performance as well as career mobility. Since 2017, 15 employees have been promoted to positions of director or above, and in 2019, 45 percent of all leadership roles were filled with internal talent that was identified through talent analytics.
Symantec: Back to Basics
Symantec‘s data strategy has evolved over the past five and a half years to become more practical, strategic, and pragmatic. When Amy Cappellanti-Wolf, former senior vice president and chief HR officer, first joined the organization, the HR analytics function was doing sophisticated work, but having very little impact on the business. While the data team was reporting predictive, forward-thinking metrics around leadership transitions and retention, they were neglecting the basic information that business leaders needed to run their day-to-day functions.
Cappellanti-Wolf decided to take a more practical approach, working with IT to build a data warehouse that could house the information gathered from the company’s Workday platform in a centralized location. She began the transformation with a listening tour of the company, reaching out to managers and business leaders to understand what kinds of metrics were needed and what their sophistication level was in analyzing the data.
The analytics team then optimized its Workday functionality and began gathering data that was critical to business function, including:
- attrition and retention data;
- information related to market-based pay;
- time to fill positions;
- average cost per hire;
- internal versus external requisitions; and
- employee census data, including diversity, tenure, gender, and position.
The company also invested in a survey-based listening tool that would reveal employee sentiments—where employees feel engaged, disengaged, and supported by management. The results of these pulse surveys were immediately reported to managers to address gaps quickly.
The two major goals of the revamped data strategy were simple:
- create a single source of truth that aligned both finance and HR metrics, and
- implement a standardized process by which business leaders could request reports.
To that end, the analytics team created a data ticketing request process through ServiceNow, the tool used to manage their workflows, which allowed them to monitor requests and respond to inquiries more efficiently. To make reporting more consistent, they also introduced a dashboard that business partners and the global services team could use to consult their business.
Cappellanti-Wolf recently left the organization and she also left her mark. “We had a really robust data strategy for how we reported data, spanning everything from monthly attrition and retention reports to predictive analysis on what you could expect at the end of the year,” she says. “We knew when there were specific times that people would come and go. We did studies to figure out why females were leaving at a higher rate than males. We also took a look at choke points in terms of our D&I strategy to understand why people were leaving, when they were leaving, and why they are not being promoted to certain ranks.”
Importantly, these metrics were not isolated—they were integrated with the broader business cycle in order to lend meaning and context to the trends. For example, the organization found that attrition tends to rise in June right after the company pays out bonuses and equity vests, and the sales team tends to leave at the end of the second quarter once they know they won’t meet their annual quotas. These moments of truth became revealed in the data, allowing the organization to take steps months in advance to get people reengaged and avoid predictable attrition.
Another people analytics success was in the management of the sales team. According to Cappellanti-Wolf, the HR team worked in conjunction with the sales operations and compensation teams to determine which sales professionals were most effective in selling Symantec’s wide, complex suite of security products. This study was critical as the sales team was experiencing an uptick in turnover and management was seeking to understand how the loss of tenured sales representatives would impact potential revenue.
“This was a terrific opportunity for the sales operations team and HR to partner together and consider several factors for analysis, such as sales and quota attainment, employee tenure, efficacy of year-over-year sales plan management, and management continuity,” she says. “The analysis revealed that the highest performers had between two to four years in tenure, consistency in territory assignments, success in selling some of the more complex security solutions, and higher engagement survey scores.”
This information helped the sales team to focus on territory management, sales training, and manager development. “We then spent time with the highest quota bearing folks to analyze what makes them more capable and then wrapped these attributes into our training program. Sometimes leaders have a point of view that when coupled with data, can get to the heart of the issue faster.”
Chipotle Mexican Grill: Mobilizing Managers
Over the past two years, Marissa Andrada, chief people officer of Chipotle, has reinvented the company’s data strategy to drive significant business growth, resulting in an incremental climb in sales compensation and stock growth of over 200 percent.
How did she accomplish this feat?
Andrada partnered with the operations team to identify and solve one key business problem: stability at the general manager (GM) level. “We believe that if you have stability at the restaurant manager level, meaning the same person in the GM role for at least a year, that it will drive growth. That has been at the foundation of our growth and transformation strategy. They are the most important role for us because they run all 2,600- plus of our restaurants,” she explains.
The analytics team evaluated both hard data and anecdotal feedback, examining each restaurant’s turnover, transfer, and promotion data alongside reports from general managers and employees about the guest and employee experience. They found that the organization was frequently transferring managers between restaurants, causing each branch to cycle between two or three different managers per year. Based on this feedback, Andrada formulated the hypothesis that transfers at the general manager level were driving the highest amount of turnover.
She then set out to validate that hypothesis with actual behavioral data, reaching out to business leaders to evaluate why this was happening and listening to employees on the ground to understand the impact it was having on their experience. In addition to in-person conversations, Andrada implemented employee engagement pulse surveys to get more frequent feedback.
The leadership team was then able to introduce new programs and policies to reduce turnover among the GM population. This included a new process to decide how managers would be transferred from one store to another.
“The core of that is that we weren’t developing talent fast enough,” says Andrada. “We had to create the right success profile, arm our leaders with the ability to assess talent against that profile, select and promote talent into that profile, and then develop them. Just looking at transfer and turnover data informed a lot the strategies we implemented to create GM stability. Now we’re seeing consistency in the guest experience and consistency in the employee experience, and that is driving business results.”
Chipotle also introduced two other changes to improve the employee experience and gain better ROI from its perks programs. The company reduced the eligibility time frame for tuition reimbursement from one year to four months. It also decided to offer a bonus of an additional week’s worth of pay per quarter to every employee in the system. While these initiatives marked a significant financial investment, data from the company’s Workday HCM platform showed that it was important to incent and benefit employees in order to improve retention and drive growth.