The Use of Big Data in HR - Where Are You Today?
Are you an Early Adopter, Early Majority, Late Majority or Laggard in the use of Big Data in HR?
I first spoke passionately about this topic at the Chapman Networking Session held at Mondelez International APAC HQ office in April 2014 and the use of Big Data is still widely discussed today in many HR discussion forums. Clearly - it is an area where some companies have embraced it while others have adopted a wait & see stance.
At the Chapman Networking Session, I made the comment that it is important to correctly position and communicate the use of data in a HR Business Partnering approach. For example, in the FMCG industry, it is possible to use the language of the business when we present big data in HR for the business. For example, we could report HR analytics under the themes of 'Buy, Make and Sell'. What do I mean by that?
a. The functions and big data that falls under Buy? - think Procurement.
b. The functions and big data that falls under Make? - think Supply Chain, Research & Development, Innovation Team, etc.
c. The functions and big data that falls under Sell? - think Sales, Route to Market teams, etc.
Make Big Data so intuitive that business leaders can relate quickly in a fun and direct way! One of my personal belief is - No 'HR talk' with the Business please. Talk business with the Business.
Recently, I also shared another Big Data example at the ThriveInAsia HR Gathering at LinkedIn APAC HQ office in Singapore on the 10 March 2016:
Most companies report monthly attrition rates for their business leaders (Factual Analytics). Some companies take it a step further by projecting the anticipated annual attrition rates based on past monthly trends (Predictive Analytics). However, I want to push the thinking further beyond predictive analytics. And I call this Business Analytics. Let's use the attrition example again. HR leaders can and should link people data to a specific business outcome.
For every attrition vacancy, did you replace with an internal transfer or expat assignee?
Did you recruit directly or via a recruitment agency?
Or did you eliminate the vacancy completely and delivered an overheads/headcount saving for the company instead?
All these actions have a direct impact on the operating income of a company which contributes directly to the bottom line of the company's financial performance. Linking attrition rates (a HR big data) to a business outcome (in the example above) makes the case 'very real'. It could even serve as a reminder to the business to take attrition seriously (if they don't) and start taking measures to improve talent retention & engagement!
Another key is to ensure consistency in the use and communication of Big Data to the business. Don't go to the business with Big Data in Jan and then go back to Gut Feel recommendations in Feb. Be consistent - tell a story with Big Data every month. Consider reporting your Big Data in 3 key themes - Capacity, Capability and Culture.
Under Capacity, perhaps look at the health status of your Region's Top 100 roles? In these roles, how many of them have leaders who are newly appointed? How many of them have ready-now successors? From there, work closely with your business leaders to deepen the succession pipeline if necessary.
Under Capability, track your ROI in your Learning & Development initiatives. Who has attended training programs? What functions are represented? Who can benefit more in the next run?
Last but not the least, we have Culture. Track your total diversity scores. Is Gender diversity a key to your company? Or how about Nationality diversity? Co-own the accountability of diversity targets with the business by reporting total diversity scores in a consistent manner and regularly. Overtime, you build rhythm and rigor!
The discussions, debate and fervor behind Big Data in HR will continue. Regardless if you're an early adopter, early majority or late majority, I encourage HR leaders to link people data to a business outcome, and in a direct way.
Someday, your business leader may come to you and say, 'Thank you for sharing this data point with us. You're not a HR Business Partner, you're a vital part of the business. Your data helped shape the decisions made!'
This article first appeared on LinkedIn.