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What we watched this week...How big data and artificial intelligence will shape your 2018 talent acquisition strategy

ThePeopleSpace editorial director Siân Harrington watches the HR videos so you don’t have. This week – after a lot of hype, HR is finally feeling the benefits of big data and now artificial intelligence is starting to bring additional benefits. But it’s all about augmenting, and not replacing, your recruiters

HR is at an inflection point where much of the hype around the use of big data and artificial intelligence (AI) in talent acquisition is becoming reality and showing strong outcomes, agreed speakers at a Human Capital Institute webinar that gave sound advice and examples of practice while warning of the potholes HR can fall into.

The intersection of big data and AI is accelerating speed and accuracy and unlocking capacity in organisations, said Geoff Dubiski, executive director at consultancy EY. But the biggest benefits come from working with stakeholders across the organisation while one of the major potholes is the failure of HR to look at data through a wide-angle lens.

“There’s a tremendous correlation in analysis that shows strong candidate experience reflects positively or negatively within your brand management. Sit down with your marketing and PR folks to do the correlation. Your efforts can double or triple by bringing in some of these stakeholders, but you can also share costs. Human capital data permeates every stakeholder in the enterprise,” he said.

Sankara Viswanathan, senior vice president and chief information officer at Day & Zimmermann, agreed that it is always more effective when multiple functional leaders collaborate when dealing with data.

“If we don’t partner together it will always be challenge. If a big data solution is considered by HR and they do not have a good partnership with IT or with those consuming the technology, then it’s a nightmare.”

Shelia Gray, global talent acquisition leader at GE Appliances, pointed out that she has always collected metrics around the performance of recruiting and information around candidates. However, her ‘aha’ moment came when she realised how one could take candidate data and use it to turn those candidates into consumers and vice versa, such as by looking at the buying patterns of candidates.  

Potholes to avoid with big data

Common potholes are data hygiene, information overload, cross-border legal and IT issues and unconscious bias.

“You need to look at how your house is in order today, how that will be impacted by new data and how to contextualise data. I often hear people saying they need best practice benchmarks but we must caution ourselves and lend a contextualise lens to this,” said Dubiski.

Gray added that it is important to think about how to interpret the data. “Each data point is unique. We have the opportunity to use it to expand our horizons or to fall into the pothole of unconscious bias. Data is rich and great but we need to break down some of the barriers.”

Big data and potholes

At EY data from real estate, environmental health and security has been analysed to discover how people are using space, for example their duration in a particular area, and how they are using collaborative spaces versus office space. Dubiski said this has enabled the company to adapt space differently, resulting in significant savings per square foot, but such data could also be used to think about where people should work when you are recruiting.

Michael Dachenhaus, director of RPO operations and technology at webinar sponsor Yoh, said talked about personalising the job message to an individual, noting that a millennial on the West Coast  may react differently to a type of communication to someone in 15 years into their career in the Mid West.

All speakers agreed that AI was an exciting development that would bring benefits to talent acquisition. Gray views AI as ‘assistance intelligence’, helping recruiters to be more predictive in areas such as quality of hire, candidate communication and scheduling. “It’s about looking at what happened in the past and how it can be applied in the future to make different decisions,” she explained.

Dubiski gave the example of a bot at EY that was triggered when a global win was settled in the business. This bot notices when it is a global deal so members of the team will need to travel. It contacts everyone in the relevant team to ask if they will or will not be travelling and if the answer is yes, the bot triggers relevant workflows, such as visa requirements.

Path to select and implement artificial intelligence

Gray explained the path she takes when considering AI technology:

  1. Business strategy – where is the organisation trying to go and how does talent acquisition align with this?
     
  2. Ask what is not working in this space that technology could help with?
     
  3. What’s the return on investment – how long will it take to implement, who will the implementation impact and what is the cost and time resource?
     
  4. Do we want to look at technology that currently exists or spend time working on some emerging technology that could be customised?

Path to select and identify artificial intelligence

Finally the panel warned of the folly of expecting automation and AI to be the silver bullet that solves all problems and that the last thing you want is to automate a bad process.

“If you have no data then you have no need for AI. If you have bad data, then AI will rapidly increase the creation of bad data,” said Viswanathan.

He suggested thinking about something that is not easy to do from a human perspective if you are considering an AI project, for example the use of unstructured data such as social media to complement humans and enable them to make better decisions.

Gray agreed: “When technology is taken out too far it becomes a weakness. Applicant tracking systems became a weakness when we lost the personal touch. AI technologies should be an extension of our own approach and not a replacement.”

Identifying and overcoming artificial intelligence potholes

 

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