How did people analytics catalyze workforce productivity? A Chevron case study
Thursday, April 27, 2017 11:51:19 AM

The concept of ‘People Analytics’ being only an HR discipline is fading fast. Just like spreadsheets broke its long-touted ‘finance’ straitjacket and got assimilated into every aspect of a business, people analytics is now steadily becoming the mainstay of organizational activities. Organizations and businesses that have already started using people analytics are bringing it to the heart of their businesses in more innovative ways. Such a unique implementation of people analytics has been made by the US-based multinational energy corporation, Chevron. Going a step ahead, the company has been able to create a global, best-in-class analytics function.

Dwindling oil prices in the recent time has made Chevron explore new methods to retain its above-average profitability, along with revenue per employee. To meet this goal, the company leveraged analytics to gain in-depth insights into workforce productivity.

Chevron’s Journey towards the Innovative Use of Analytics

The organization set off its journey with a small and centralized HR analytics group. The group was provided with standardized people metrics and reports at the headquarters. Earlier, there was a significant lack of community sense among different HR specialty areas as well as business units, resulting in variability in their individual capabilities, operating procedures, and practices. Various areas of the business involved duplicating the collection of the data and analysis procedures to generate the similar reports.

To address these issues, the entire team redefined the very mission of the company: “to support Chevron’s business strategies with better, faster workforce decisions informed by data.” Such an extended vision encouraged the organization to reinvent the entire analytics team as an organization-wide community of practice and set up a global process to take care of all people analytics projects across the organization.

The community of practice was made up of 295 members across all the significant divisions of the organization, right from specialists, analysts, and HR business partners across the world. In the organization, it started offering a forum for all interested analytics professionals to virtually collect and discuss various data models, share data, show the latest technologies, create analytics programs, and design standardized metrics. Also, the core team came out with an in-house workforce analytics curriculum intended to create important analytics skills in HR as well as non-HR stakeholders. Since analytics comprises a wide range of skills—right from problem solving to data analysis to visualization to statistics—this curriculum assists team members in gaining a general level of understanding as well as capability.

Outcome

All these initiatives have led to a significant outcome. Within just two years after the revival of people analytics, the entire team has now gained the capability of conducting several analytics projects. The company’s people analytics practice has dramatically lessened the time to finish analytics projects and enhanced reliability for all its people-centric decisions. Chevron now has the standards reports throughout the business for every talent metrics. Further, the team provides consultation for various decisions on restructuring, recognition, and so on. Unlike the previous decentralized model, the latest one works at a comparatively lower cost. However, it results in 30 percent increased productivity, doing more work with a lower number of human resources in comparatively less time. In 2015, a business unit eliminated almost 100 hours of redundant reporting activities.

The Key Takeaways

Given the Chevron example, the following eight factors can be considered as ‘essential’ for a successful people analytics program:

Making significant investments at the senior level in people analytics

Setting up proper leadership

Giving priority to clean and trustworthy data across HR as well as the organization

Gaining an idea of the multidisciplinary nature of analytics

Enhancing analytics fluency across the organization

Creating a two- or three-year investment roadmap for various analytics programs

Giving emphasis on actions, apart from only findings

Integrating organizational, HR and external data