How IBM puts the right person in the right job
With 380,000 employees globally, it makes sense for a tech giant like IBM to leverage technology to keep workers productively occupied. One way it does so is with “Blue Matching,” a tool that links IBM employees with potential new job opportunities within the company. Anshul Sheopuri, IBM’s chief technology officer of Cognitive HR, has been at the center of that initiative. He recently discussed the program with Employee Benefit News. Edited excerpts follow.
Employee Benefit News: Tell me about the Blue Matching initiative.
Sheopuri: We were thinking about what employees really want to do professionally, and our needs as an employer. At any time at IBM there could be tens of thousands of jobs open. Many employees were trying to understand what their next jobs should be, and what they should be doing to get to that job. We did some workshops to try to understand how employees could be helped to take the right action. That was the genesis of Blue Matching.
We launched an MVP [minimum viable product] of Blue Matching in 2015 to deliver personalized job recommendations to employees who decide to opt in. They would receive personalized alerts based on their job history, and that of people with a similar job history, the employee’s performance, location preferences, and skills. All those things together help us deliver personalized job recommendations. It’s all voluntary, and about 15% of our employees have opted in to use the service.
EBN: How do you assess the program’s success?
Sheopuri: Our success metric is how many job placements we can enable. Since the launch of Blue Matching, we have been able to measure about 1,000 job placements that have resulted [because of] Blue Matching. If people don’t opt to use the system, it could just be that they are happy with where they are, and not any concern about Blue Matching. We’re excited about the results so far.
EBN: Do employees who opt in just have to wait to receive notifications?
Sheopuri: No, it’s both push and pull. Let’s say that today you decide that you’re looking for a job. You can go in and look at everything at this point available to you so that’s a pull trigger. And then there is also a push trigger where every week you receive personalized summaries of jobs that are relevant to you in your email or on your mobile app.
EBN: Can employees specify search result parameters, such as geographic job location?
Sheopuri: Yes, but it’s not a search tool in the normal sense. Think about it more as an intelligent agent that learns what is best to pick for you without your needing to identify parameters. It is really about learning from career trajectories, skill sets of other individuals and bringing that insight to you to help you on your career journey.
EBN: What about specifying compensation parameters?
Sheopuri: Compensation is not directly a factor in this, but we do have a level of expertise in position in the job. So if you are somebody who has an expertise level which is, let’s say, number five, we won’t be recommending jobs that are level number one. We’re recommending those that are commensurate to your level of expertise. And compensation is related to levels of expertise.
EBN: Does Blue Matching help people make successful transitions to jobs they might not otherwise have been on their radar screens —something quite different from what they were doing?
Sheopuri: Yes. The key value proposition is the ability to learn from other transitions that occur and skillsets that can then be learned or inferred, and matched against your description. If you have things in your resume that you haven’t paid attention to or you don’t think are important, with Blue Matching you could wind up somewhere you didn’t expect to be.
EBN: For example?
Sheopuri: Take blockchain technology. If you’re working on that in one division, and now it’s being used in finance. If you’re not in finance, you might now know where you’d fit in with that expertise. Blue Matching can facilitate that.
EBN: Does Blue Matching get smarter as it gains experience?
Sheopuri: Absolutely. First, if your resume gets updated, you’ll get more intelligent matches and more recent matches. And second, if new trends begin to emerge, let’s say if five people make transitions from certain jobs to other jobs, or even if only one does, then that trend and that insight informs what matches other people might get. So both things do occur.
EBN: Are there other sources of information about employees and their aspirations than what’s on their resumes and job history that can be used to advance their careers?
Sheopuri: Yes. We have begun to incorporate a lot of other digital footprints, like blogs. So if you write a blog on, say, security, and its applications from an AI standpoint, that blog will then be used to employ your expertise. So different types of internal digital footprints have been used to infer expertise and that capability has been added.
EBN: Anything else?
Sheopuri: One of the things that we learned after an internal hack-a-thon was that employees tend to think about their careers very holistically, and they’re thinking about learning they may need to do, not just what’s the next job. They think, ‘Maybe I’m not eligible for the job right now because I don’t have the skills, but maybe if I do a bit of learning in this area, then I may have the skills to move to that job.’ So we’re incorporating that insight into new iterations that we have begun to deploy.
EBN: Do you believe any employees resist using Blue Matching out of a concern that their supervisors will learn that they’re thinking about making a move, and that this could hurt their working relationship?
Sheopuri: This issue is part of a culture change we’re trying to drive within the company. It is a very conscious and intentional choice to give this information to the employees. And I think the way we think about it is it is better for the employees to find jobs within the company that are more subject to their skillset because that means that the employees are more effective there, and they are progressing. And an important outcome is this is reduced voluntary attrition.
EBN: You have tracked that metric?
Sheopuri: Yes, and it’s making us confident that this is the right thing for the employee. It’s a journey, and we’re certainly not at a final destination, but we’re moving in the right direction.
EBN: Can this initiative be leveraged to help identify positions for people who are currently not working at IBM?
Sheopuri: We’re not there yet. We’re evaluating opportunities for more solutions with AI embedded in it that touches multiple experiences, that will help candidates who apply, or people who are not even looking for a job, but maybe there is a job within IBM that we can recruit him for.