People Analytics: Here With A Vengeance

4. Data and analytics literacy has become an imperative for HR professionals.

I remember a meeting with a CHRO several years ago where he told me “I’m tired of hiring HR professionals that don’t know the difference between a median and a mean. I’m thinking of asking all my HR teams to take a course in statistics.”

Well that dream is starting to become a reality. Our new research shows that one of the biggest factors that predicts success in People Analytics is not just the skills of the analytics team – it’s the skill set of the HR business partners, analysts, and staff. In fact we found that level 4 companies have a sharply higher set of skills among their general HR population than those at lower levels of maturity – and I’d venture to say that this is a new “bar” they have raised for their teams. (Level 4 companies report that 63% of their HR professionals have strong analytics literacy, vs 20% in Level 1 companies.)

So HR professionals out there: it’s time to become data geeks!

The reason for this is simple. In the world of People Analytics today, the power of the analysis is not always the line manager looking at a dashboard to figure out why someone is likely to leave their group (they don’t have the time or inclination to do this). Rather it’s the HR business partner, HR VP, or HR consultant who comes to the senior leader and shows him or her data which points out that their team has bias, poor work practices, weak skills, failing culture, or other problems that can be proven with data.

Most business people have learned that data is key to their success: they will not listen to an HR professional waving their hands about how bad the “culture” may be or how “biased” or “unfair” the organization has become. They want data to prove what is wrong and they want data-driven recommendations for improvement. If the HR professional cannot make that case, show the data in a clear and understandable way, and defend their analysis, the line leader simply will not listen.

I know that in my case as a business leader I always ask people to give me a data-driven explanation for why they recommend a course of action. If they can’t show me the data I always wonder where they came up with the advice. This has now become the new world of HR: if you can’t put data behind your work, business leaders just will not pay attention.

So the problem is not just “having the data” but “knowing how to use it” and understanding how to explain itvisualize it, and put it into action in front of a business leader. And the business leader may have an MBA or background in statistics and is very likely to ask you “where did this data come from” and “how did you come to that conclusion.”

HR teams are not there yet – I still hear continuously that HR business partners are not analytic enough. But if there’s one thing you should think about in 2018, it’s “energizing your HR organization” with a good set of courses, programs, and exercises in statistics, data analysis, and the effective communication of data-driven recommendations.

In our research we detail the program Chevron developed to build global HR skills in analytics: it has been extremely effective in their organization, and serves as an example of how important it is to take data literacy seriously within the HR function.

5. AI and Machine Learning have arrived – and People Analytics teams are using these algorithms to partner with the business

The final change I’d like to point out is the fact that advanced statistics, neural networks, and other forms of machine learning have arrived. LinkedIn just published a study[3] that shows skills in “machine learning” are now the hottest in the marketplace, and a new study[4] by a team of AI leaders shows that courses in AI are exploding in popularity. These professionals are now in the workforce and they are itching to look at interesting data problems in business.

(By the way, if you dig into machine learning, you find that it’s essentially a lot of math. People Analytics teams are going to be able to develop or use these algorithms from public domain APIs, so this technology is available to any company.) 

I’ve now talked with HR departments who are looking at attrition patterns, prediction models for performance and retention, models for employee absence and grievances, and analysis of many other forms of employee productivity – all based on the People Analytics data available within their organizations. These companies are starting to correlate this data against data available from external social networks and can now learn things about their companies they never before thought possible.

One vendor, for example, now has a tool that reads comments from bi-annual engagement surveys and automatically recommends direct behavioral changes to managers to help improve the engagement and productivity of his or her team. Another company has built a machine-learning algorithm that identifies the behavior of their best sales people to help understand how to train others to perform at a higher rate. Many professional services firms are looking at communication patterns and travel schedules for the highest performing consultants to figure out what others can learn.

We used to think the secret to productivity at work was “skills.” Now, through the use of machine learning, we can understand that the secret is also “behaviors,” “habits,” and “patterns” that highly successful people adopt. Many of these are unconscious by the experts, but can be analyzed and understood by software.

Our research shows that the highest-performing people analytics teams are now partnering directly with the business, serving as internal consultants, and bringing their analytics expertise to bear to focus on productivity, performance, safety, and direct facing work related problems.

As the head of analytics at a large technology firm put it:

“I am not in the curiosity business. We need to know the relevance to the business before we spend time and energy to work on a problem.”

This is the new mantra we see taking hold.

This has been a long journey, and it continues.

Let me summarize by saying this has been quite a journey. I’ve been studying this domain for almost 20 years now and the domain of people analytics has reached the C-Suite. We still have many issues to address:  Who owns employee data about location, health, and work habits?  What are the privacy policies we should put in place?  How do we best inform people about the data organizations are collecting?  How do we make sure all this data is used for positive purposes?

While these are new and daunting questions, the time to invest is now. 2018 should be your year to consider investing in these technologies. I look forward to hearing your stories and would love to help any organization understand how to take advantage of this critical new business imperative.

 


Josh is a published author on Forbes, a LinkedIn Influencer, and has appeared on Bloomberg, NPR, and the Wall Street Journal, and speaks at industry conferences and to corporate HR departments around the world.

You can contact Josh on twitter at @josh_bersin and follow him at http://www.linkedin.com/in/bersin . Josh’s personal blog is at www.joshbersin.com .

As used in this document, “Deloitte” means Deloitte Consulting LLP, a subsidiary of Deloitte LLP. Please see www.deloitte.com/us/about for a detailed description of our legal structure. Certain services may not be available to attest clients under the rules and regulations of public accounting.

[1] Sierra-Cedar 2017 Human Capital Technology Survey

[2] https://aws.amazon.com/alexaforbusiness/

[3] https://economicgraph.linkedin.com/research/LinkedIns-2017-US-Emerging-Jobs-Report

[4] http://aiindex.org/2017-report.pdf

[5] Bersin by Deloitte High-Impact People Analytics 2017

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