How Accenture transformed its recruitment using contextual analytics
Analytics is enabling the human resources function to truly speak the language of business. At Accenture, a number of experiments were being conducted on contextual analytics across India, Philippines and North America to help ease the talent acquisition process. Unmesh Pawar, Global Managing Director Human Resources of Accenture said: “When we first decided to take action, we made the choice of using design principles to put the candidates at the center instead of automating basic processes.” This meant asking questions like ‘what’s the most optimal experience that we want to create? How much time would be needed to create this experience? What kind of analytics support would the company need to put in place?’
The exercise also helped to define the role of the recruiter – which was that of a talent spotter who is able to identify high potential candidates for the organization. The focus on experience also required that the recruiter spend more time with candidates on a one-on- one basis, provide them with high-touch experience, and identify areas within the company where the prospective candidate would be most useful. Accenture partnered with Spire Technologies and Solutions to leverage technology in this journey. This partnership enabled the company to teach machines to help identify the right candidates quickly.
The first step was to create a mechanism to filter “renege” candidates – those who accept the offer but don’t turn up on the joining date.
“When we wanted to hire some 20,000 people for our technology business in India, we received over 300,000 resumes,” says Unmesh. Since the capacity of the recruiting team was finite, the company did not want to load the team with tons of CVs, which would have resulted in a deteriorated employee experience and increased the probability of hiring a bad quality candidate. To address this challenge, they built some tools using contextual analytics principles. The first step was to create a mechanism to filter “renege” candidates – those who accept the offer but don’t turn up on the joining date. Certain attributes were identified of people who seemed to have high “renege” probability. The next step was to identify what a high performer looked like using the ‘High-Quality Hiring Index’. Added to this was a filter to identify people who had a high chance of getting selected in the organization. When all these things were put together; it helped the organization in many ways:
- The analytics engine helped to narrow down to 200K resumes from 300k resumes.
- In addition to the above, it allowed the company to prioritize 60,000 interviews as against 200K interviews which they were doing before.
- It also enabled an increase in the engagement levels of both recruiters as well as of the prospective employees.
When organizations grow in scale and size, it is issues around discipline, data behavior, data gathering, and management that crop up. And the impact of legacy systems and old practices adversely impacts candidates’ experience. Reorganization requires capacity building and a lot of cultural shift. Accenture took almost took 10 months to a year to carry out this entire process. Here are some key outcomes:
- The hiring time was reduced by around 60%
- The company could identify 70% fit candidates just by virtue of technology
- Candidate happiness score also went up drastically.
Hyper-personalized experiences are what drive engagement today. Organizations need to create that by using contextual analytics to ensure business as well as people impact. And analytics is the train that makes the digital machinery move: Contextual analytics and machine learning will make lower level decision making redundant which will free up the capacity of HR to engage in a high-value content work.
Companies need to prioritize strategic decisions and prepare their ecosystem to act quickly. They need to understand that people analytics journey is not entirely an HR journey. It takes a number of stakeholders across multiple functions and external parties to make the change happen and to truly understand the power of analytics. The crux is that the entire organization needs to come together to drive the change.
(This article includes insights from a session on contextual analytics at TechHR 2016)