Modern Analytics help in defining more accurately which incentives work with each employee segment
With Analytics, we cannot only mine huge amounts of data, we can also offer more granular, customized solutions, including more flexible responses
Diane Gherson is Senior Vice President, Human Resources for IBM. In her 13 years with IBM, Diane has had extensive experience leading organizational transformations. She was named as one of the 2015 Fifteen Most Powerful Women in HR by HR Executive. In this Big Interview, we talk to Diane about her journey leading the HR function in one of the world's leading technology companies.
You have had a diverse career history; tell us a little about it.
I have always been fascinated by organizations and people. In my undergrad days, I did political science and economics. I was really influenced by a book written by an economist Albert O. Hirschman, titled “Exit, Voice and Loyalty”. The book was about three models in consumer marketing: “exit” – when customers switched between products for a better price, “loyalty” – when customers buy because of a brand, and “voice” – when consumers buy the product because it gives them a voice. It was brilliant because it spoke to me about how businesses could be run and the culture that a company could build. “Voice” was about quality of work life and having participatory management.
When I went to Cornell to study Industrial Relations, they assumed the “exit” model founded on the belief that there needed to be an adversarial relationship between the management and the employees. Under this model, an employee leaves for a small increase in salary because there is no cultural sticking power. I wanted to explore this more. So I went into consulting and had a really interesting time there. One of the biggest things I learnt while consulting was having a consulting mindset – learning to listen, to probe, to present alternative solutions and to be more outcome-oriented. People within HR tend to be more process bound and tend to look at HR as a product that needs implementation. It’s an exciting time to be in HR, because “voice” is really the secret to IBMs success.
What is that one experience that you think would have better prepared you for your role?
I think it’s immensely important to know your products really well. In my consulting career, I did get a chance to sell, be accountable for sales and learned how to run a P&L.
When you reflect on new paradigms, what has changed in your approach to people management?
A great example of a new approach is our new performance management system. Instead of having a task force and coming up with the correct answer, I blogged about the need to upgrade and asked our employees for feedback and input. We got thousands and thousands of people working on trying to understand what works and what does not. We did a series of multiple polls and we debated topics as part of the exercise. We got a lot of insights on the design, and we are still working on them.
At IBM, our focus has been on providing flexibility and empowerment to our managers. We have observed that managers are more comfortable in reviewing performance and giving feedback throughout the year, instead of a periodic review at year end. If we look at performance management, we are looking at five elements: skills, performance, responsibility, innovation and client success. It not only opens up the aperture for a much richer discussion between a manager and the employee, but it also reduces one summary reading for an individual. It also avoids the pressure on managers having to conform to a bell curve model.
Working for a technology company, what are you most excited about in technology for HR?
Well, I think its Analytics. So much of HR was built off intuition, and Analytics just changes the discussion. With Analytics, we cannot only mine huge amounts of data, we can also offer more granular, customized solutions, including more flexible responses. Using outcome data like revenues, productivity, hiring yield, individual performance, or employee engagement, we can understand the probability of success of certain decisions.
I had the exciting opportunity, just last week, to share the impact of our employee development program with senior management. We were able to show that for employees with managers who had attended our new management program, there was an eleven point difference in engagement compared to those whose managers had not attended, So instead of begging people to go to management development, as we have done traditionally, we now have an argument and data to prove that if you don’t, this is what happens. So it’s that kind of Analytics that enables you to have a very different conversation.
What kind of clusters do Analytics create?
In 2009, when we had a salary increase that was not competitive in India, we had a high level of attrition. It was clear that we were spending more on hiring replacements. So I went to the CFO and asked for some funding. I basically guaranteed that I could retrieve that same amount back. So we went back and found employees who had a high propensity to leave and gave them a salary increase. Over the past few years with this program, we have saved about US$300 million. What Analytics can do is that it can identify certain characteristics with certain clusters, it could be as simple as people having the same manager since their college days, or they have been working in a certain location, or having a new manager.
What does HR do with that data, what kind of action points do they need to take?
If we look at the example of a cluster of people who have a high propensity to leave, the action is not always a salary increase, although in India, the trigger point seems to be pay. People leave for very little pay increase. So, it could be a place where you can start. There are many steps that can be taken, even with respect to work environment opportunities, it could be career interventions or even global experience.
Why have companies and HR not adopted these technologies yet?
The first reason for that is unavailability; most tools are still not commercially available. Secondly, people drawn into HR are not people whose strength is Analytics, although this is fast changing. The third reason is that people reject Analytics for people-related items. When we predict that an individual has a propensity to leave, managers working with them are often surprised, despite the fact that they themselves have been working closely with the individual and still did not see any cause for concern.
How does this change the nature of work for HR?
Let’s take recruitment as an example: now we have software that can both read and filter candidates. Then there are competency tests and personality tests. Of course you also need better HR people who can assess what a successful candidate would look like, so that data can be incorporated into the system. So, the focus is going to be on a more continuous process – whether it is recruitment or in talent management.