“Without data, you’re just another person with an opinion.” That’s a quote from W. Edwards Deming, and was shared in a presentation on metrics by Ryan Kohler, CEO of ApplicantPro, at the Society for Human Resource Management’s annual conference in Chicago.
The conference had an impressive track on analytics, which tied in with a larger theme around strategic HR and ensuring HR has a seat at the table. Every business leader will claim their people are their greatest asset, but too often people experts are left out of key decisions. This year’s presentations armed HR practitioners with skills around speaking the language of the C-suite to best apply their expertise, along with how to build an analytics function that stands up to scrutiny.Business leaders say people are their greatest asset, but people experts are left out of decisions Click To Tweet
Here are some key learnings around HR analytics that will resonate, no matter if you’re scaling or just starting your analytics program.
Too Much Data Isn’t a Reason Not to Start
Where does human resources data come from? Some is collected and managed by human resources, but often it also comes from finance or IT. If you have 1,000 employees and 10 systems with 50 data fields that adds up to 200 million data points. Making it actionable means cross-referencing data sets from different parts of the business. Sound scary?
With today’s digital tools, most organizations have too much data. But Giovanni Everduin from Boston Global warned, don’t let that stop you. He shared a delightful anecdote of a man walking through the desert for days without water who comes upon a lake, then pauses. Another man asks why he doesn’t drink, and he replies, “I won’t be able to finish the lake!”
— Raychel Lee (@RaychelY) June 19, 2018
HR analytics can be a glass of fresh water for your organization. But before you can extract insights, you need a data model with clear definitions that is agreed upon by multiple parts of the business.
— David Shepherd (@oldshep) June 18, 2018
It’s About Distributing Metrics to Enable Managers
The annual engagement survey is a common source of data points for many HR teams. But too often, this enlightening information never leaves the department, or gets stuck in the C-suite.
SEE ALSO: Ultimate Guide to Employee Check-Ins
“If you don’t know the score, you’re not a player,” Shane Yount of Competitive Solutions, Inc said in a presentation on HR metrics.
Every team should have a tool that’s accessible and will tell them daily if they are winning or losing — meaning, how they are progressing towards metrics that are tied to business results. Think of this scorecard like a Nest thermostat. Decisions should be reactive to the current situation and the display should always be up to date.
Metrics Must Drive Towards a Business Result
It’s bad news when your C-suite views your program as an HR project. So, change your terminology, advised Suz Graf O’Donnell. Talk about increasing performance, not talent acquisition.
“If you are always focused on reducing costs, you will be seen as a cost center,” Ryan Kohler added. “Throw the word revenue in — ‘We can see an increase in revenue by a specific time by increasing our NPS score.’ “
— J. Gilardi (@GilardiJulie) June 18, 2018
— Stephanie Vasquez (@HRXennial) June 19, 2018
Kohler shared an example from Virgin Media. The company relied on subscription revenue and the goal is to grow subscriber base.
To determine proper alignment, start with the leading indicator and work through to the lagging indicator — and set metrics at each step. To drive results, swap the order: Start with the lagging indicator and work up to the leading indicator. Cancelled subscriptions are a lagging indicator, while a complaint about bad customer experience is a leading indicator.
What Virgin Media found was that 18% of job candidates were existing customers, and 7,500 canceled 30 days after the hiring process, adding up to $4.4 million in lost revenue. Improving the candidate experience had a direct impact on revenue. An agile way to start might be adding a real person’s name to job rejection emails – and track those metrics.
You Can’t Do Predictive Analytics Without Descriptive
“How many people work at your organization?” Everduin asked the room. About 20% of the room raised their hands.
There are two types of HR analytics: Hindsight and foresight. Predictive analytics are making a big splash, but you can’t get there without getting descriptive analytics right. If you have your HR data in silos — recruiting, performance, training, core HR — it needs to be organized first.Predictive analytics are making a big splash, but you can’t get there without getting descriptive… Click To Tweet
If you have three people with three definitions of attrition, you aren’t ready for prescriptive analytics yet. But, take a small victory, like identifying a department with above average absenteeism and determine the impact on revenue that would come with fixing the problem. This will give you a business case to move strategies forward.
When you have metrics, you have a seat at the table.
“Use metrics in meetings to set the tone so personalities don’t have to,” Yount said.