Power to the people - the irony around HR analytics, according to Bersin by Deloitte's David Mallon

Profile picture for user jmilne By Janine Milne November 18, 2019
HR analytics needs to escape HR if it’s to be truly useful.

Bersin by Deloitte
David Mallon

The irony about HR analytics, according to David Mallon, Vice President and Chief Analyst at Bersin by Deloitte, is that it really shouldn’t limited to HR personnel. People data needs to be out in the field and used by managers who daily need to make decisions about their teams:

The single biggest trend is the value of all this being something that is being used by the supervisor and the employee rather than just HR. More companies are trying to put dashboards in the hands of team leaders, so they can see both the performance and business data - the widget-making or sales - and the people data

Not only would front-line managers have details of sales and operational data, but also training, development, sentiment, engagement and retention and other people data, argues Mallon:

It gives supervisors a calibrated view of the health of the team, so that day to day they can make better decisions about their team. That is the future of all this [people analytics].

But for this to happen requires a shift in mindset by HR professionals. Instead of looking for systems that only give HR people the data they need to have better conversations with business stakeholders, they must also think about what team leaders throughout the business need. They must decide what they put in the hands of managers or even individual workers themselves that can help them draw their own conclusions.

While Mallon is clear that people data needs to be with the masses rather than the few in the HR department, the decision about which solution to choose is less clear-cut - analytics buyers are simply spoilt for choice.

There is a host of pureplay analytics vendors to choose between. Equally, there are many HR platforms, such as talent acquisition or application tracking systems, which have analytics capabilities embedded.

There’s also an explosion of point solutions tackling specific problems, such as network or relationship analytics, looking at communication flows, organizational network analysis and how you might look at the networks in the organizations to improve the business.

Big deal 

People analytics is not a single thing. It’s on a spectrum from companies simply reporting to the holy grail of prescriptive analytics and Artificial Intelligence (AI), says Mallon:

Vendors in the recruiting world are probably the ones who’ve gone the farthest and fastest at putting both traditional reporting automation technologies as well as more bleeding edge, cognitive, aritificial intelligence and so on into their platforms.

Some vendors are very good about helping companies with this and are not just purveyors of technology, but sources of extending the capabilities of your in-house team. Others take a more DIY approach, handing over the platform and leaving it for customers to decide what they do with it.

Decisions about which people analytics platform to buy need to be based not only on the capabilities of the software, but the capabilities and mindset of the managers, he adds:

You may have a C-suite that’s cutting edge and using data all the time and have middle managers that don’t quite know what to do with it and who make decisions based on experience and relationships.

The democratization of HR data is part of a wider trend for employees to become more data driven, says Mallon:

One of the things we see in our research is this notion of overall data literacy….Everyone in the HR function and more broadliy everyone in today’s companies shouldn’t be entirely put off by a chart.

Data-driven decisions need to take place broadly across the company and not just in finance or sales or other pockets of the business.

Whichever flavour of analytics companies choose, it’s essential to have an overall data governance strategy:

You have to have a sense of what data you have, where do you get that data from how do you ensure it’s as clean and up to date and viable as possible.

Keeping on top of data privacy and regulatory considerations of where the data resides, who owns it and how it’s being used are key, but most important is the ethics.

Mallon suggests thinking of it as a Venn diagram of you could do and things you should do right and looking at where they overlap. New tools will give you greater insights, but you need to think of the implications of that data and be clear about how you are using data to drive impact rather than be driven by the data. Otherwise, observes Mallon:

You could get yourself in trouble even with the best of intentions.