Episode 2 – Turning Talent into Competitive Advantage
Oct 29 9:00:00 am
Welcome to the “hello, Human” podcast, a show about AI solutions, advancements in technology, and about the leaders in the tech industry. In this episode, we’re going to explore the building blocks to developing a resilient digital core, and how automation helps businesses manage through a crisis. With me today is Kamal Ahluwalia from Eightfold. Together we are going to explore the current state and future state of turning talent into a competitive advantage for companies. People are really the backbone for any organization, and it’s not an accident when we talk about the golden triangle of people, process, and technology that people are first.
Employment is the backbone of our society, and everyone deserves the right job. Today, you get the job based on who you might know and not what you are capable of doing. Tomorrow, AI-enabled technology will transform how high-performing companies acquire and manage talent.
- Who is Kamal Ahluwalia and what does Eightfold do?
- How can AI technology help veterans?
- Can AI technology help with unemployment?
- Social justice, diversity and inclusion and how AIs can remove bias
- AI and remote work and school
- Transformation fatigue
Full Episode Transcript:
Jon: Kamal Ahluwalia, the President at Eightfold joins us today on the hello, Human podcast, where we discuss the latest topics in artificial intelligence and how it’s being applied in the real world. I’m Jon Knisley the host of hello, Human and a longtime technologist working at the intersection of business and emerging IT applications.
A big thanks to FortressIQ for sponsoring the program, and be sure to subscribe wherever you listen to podcasts.
In this episode, we’re going to explore the current state and future state of turning talent into a competitive advantage for companies. People are really the backbone for any organization, and it’s not an accident when we talk about the golden triangle of people, process, and technology that people are first.
Welcome, Kamal, to the program. As you may be able to tell, I’m excited about this conversation, so let’s jump right in. First off, congratulations to Eightfold on the recent selection as the grand prize recipient of the Veterans’ Employment Challenge. That’s quite an honor and validation of the platform.
Although veterans are some of our most dedicated and talented individuals, that transition to civilian employment is known to be challenging. Can you tell us a bit about the Eightfold platform for folks that may not be aware, and how it will help the military community specifically?
Kamal: Great. Thank you, Jon, and thank you for having us and making time for us. Thanks for the congratulations, we’re actually very proud of being able to help. Especially, in my opinion, I think the best-trained workforce in the world. If you actually double-click on the role that veterans play, it’s not just while they’re in the military service. Today, they do represent at least 6% of our workforce.
There are about 20 million veterans in the US right now. I think we haven’t done enough to make it easy for them when they transition. The reason why we got involved with this is we have built an AI platform for all talent. Single platform for hiring, retention, internal mobility, diversity, and inclusion, and all of that. The mission is to apply our expertise to provide the right career for everyone in the world.
As we got going three years ago, the thing that we kept looking at was okay, how do we do it at scale? The thing that dawned on us was if we are going to solve this thing quickly, in the next few years. We have to start with the largest employers and the largest talent pools. Veterans are definitely a very large, very capable talent pool.
When we got this opportunity to participate in this Department of Labor, Department of Defense, Veterans Affairs challenge. That brings your best technology to bear in helping our veterans’ transition, it didn’t take us long to jump into it. What we have done is this. We have a capability matrix in our platform, and that is geared to learn from all the people in the world, and all the publicly available data to understand what they are capable of doing, and it all depends on the context.
Resumes and all that stuff are all backward-looking. What people are looking to do, and what we want to use our AI expertise is to allow the hiring companies to hire for potential. With veterans, that is the problem. They are very well-trained. Most of the time they are working with technology that most of us won’t even see for another decade. And then all the soft skills that people ask for—leadership skills, ability to perform under pressure, ability to work in an ambiguous environment in this entire year as ambiguous as it gets.
This is the workforce that is best trained to actually thrive, and yet in April, when COVID hit, 8000 veterans transitioned straight from military service to unemployment. That’s a travesty. Yes, everybody’s suffering, but that’s what we want to do to help. When we go back to the capability matrix, what we have done with our data-driven platform is that we should be learning from all the skills and capabilities that are out there.
Focus more on learning ability, not just what you’ve done in the past, understand the context, and evolve every time so that you are accounting for the latest greatest things. With veterans, in particular, there are two tracks to solve. One is understanding what they have done when they were serving in the military.
Some of it is captured in their military occupation codes. Some of that is in their […], which is essentially their equivalent of the resume, but then there are two things there. One is translating what they know into a civilian role, but then a lot of them have very different aspirations. It’s not like they want to continue doing what they were doing in the military service versus whether it was logistics, transportation, or IT services.
In that case, we are actually looking to provide them the opportunity. When I was in one of the sessions, one of the veterans wanted to pursue a career in performing arts in Florida. A few of them wanted to go back to school and learn new things. A couple of them wanted to become state troopers—one in New York, one in Chicago. Another one wanted to move to a different part of the country.
All of these combinations we should be able to account for and with the AI we can. In light of this is what we are building with them and why I think we were chosen was a very intuitive and easy way for veterans to find a career of their choice. If they want to pursue a career of which requires them to learn new things, give them a solid career path so they can get there, and essentially make it easy so that this transition should not be filled with anxiety. It should be filled with promise and confidence. That’s essentially what we’re looking to do for veterans.
Jon: That’s great. Congratulations, again, on the recognition. I spent some time at the Defense Department’s Joint AI Center and talent management was definitely an area of interest, so it will be great to watch Eightfold’s contributions in the coming years.
Turning to a topic that’s been top of mind for many this year, I want to explore social justice and Eightfold’s potential to address diversity and inclusion challenges. Each week, there seems to be a new story about someone being rejected a half dozen times from an organization until they disguise their gender or their ethnicity.
Can the platform help remove that bias and provide greater accountability? Do you have any real-world examples that you can share with us?
Kamal: Absolutely, and I’ll share a few. What we were talking about a few minutes ago about how to hire for potential and how to use the capability matrix, that essentially is the only way to solve for diversity and inclusion. Because if we keep looking for people who have already done it before, clearly, we haven’t given enough opportunities to people of diverse backgrounds and people who don’t have the same privileges we have had.
This applies to pretty much every segment. In fact, it applies even more so to women in particular because our whole system is stacked against them. The way to get out of that is one, when people are applying, we have to look at the whole thing holistically. No one is asking us to do them a favor, no one wants that. All they want is a fair shot, and that’s the equal opportunity part.
Our algorithms don’t take into anything into account, whether it’s sex, background, ethnicity, pedigree, any of those things that factor into the match score when an individual is being compared to a particular job. So that when we are presenting these few people are a great fit for this role, it is only based on what they’re capable of doing.
Then we can even help the company create better job descriptions that are all geared for what you’re trying to do versus leaning one way or the other. Because we comply with equal opportunity algorithms, all these things are taken into account. Even though a company’s data set may still be skewed towards one side, we are able to course-correct right there.
Secondly, when you create the job description, you are able to see that what does my talent pool surface? How many people would fit this profile? Who is likely to respond? And how many of these people are of diverse backgrounds? If you’re asking for requirements that skew the talent pool against a particular diversity segment, you can do the course-correction right there.
I’ll give you a simple example. Of all the data scientists who know R only 30% are women. Of all the data scientists who know Python, only 15% are women. If you write a job description and the hiring manager says I want to hire someone who knows both R and Python. By definition, you have stacked the deck against women. You only have at best 10%, 15% representation. And invariably, it’s 1/9, so highly likely that you’ll hire someone else. One or two years later, we look back at the group and say, hey, how come there are no women here?
Those are the things it’s all data-driven because we bring a global data set to you so that you know whether such people are out there or not. If they are out there, then we make it easy to find them.
The second part is addressing how do we widen the talent pool because a lot of our customers are taking those steps? One of them actually went back and looked at how many people had applied from Howard University, and it turns out 700.
There were plenty of candidates available who would fit the profile. Then some of our customers have improved the diversity from 18%-33% for women. One of our customers, Micron, has recently been sharing that they are able to identify the ethnic background for 77% of the candidates. That enables them to take affirmative action if they choose to, but at least become more and more diverse.
Even other customers have seen a 90% reduction in time to discover and engage with underrepresented candidates. In all aspects, the number one excuse that is often used is that we looked, but we couldn’t find enough capable people of diverse backgrounds. We want to use our AI to show that no, you didn’t know how to detect the potential, and we are here to help you.
If your intent is there, we want to make sure that you can find the diversity candidate that you want to bring in and make your workforce more inclusive. The last thing I’ll share on this one is on career sites, when we use our matching algorithm, we also bring transparency.
Here, people don’t have to figure out on their own on which job is a good fit for them, but we are able to tell them that you’re a great fit for these two or three roles, and here’s why. That allows them to apply with confidence, and we are seeing a tremendous uplift of 30%-50% improvement in diversity applicants applying to the right roles where they are likely to be a great fit.
That’s changing the dynamics for our customers who want to solve for diversity, but earlier systems or technologies would simply not be able to do that, and we are absolutely loving the opportunity. Unfortunately, it’s always because of these adverse news items that come up and how individuals are being targeted, et cetera, but we’re hoping that this time people stick with it and actually make a difference. I think we are seeing more and more companies stepping up.
Jon: I think having that information and then transparency enables those companies to stand up and do the right thing, which is great. The other major shift that we’re seeing this year with the workforce is the transition to remote work, which is appearing to be more and more permanent trend that we need to adjust for.
As a leader in that talent management space, what’s your expert opinion on this issue? Is remote work here to stay, or in two, three years are we going to be back in the traditional office environment? Who benefits? Is this an employee benefit, employer? Do both sides of the equation benefit from the transition to remote work?
Kamal: I think COVID, unfortunately, will change a lot of things and accelerate a lot of things because what we are seeing is very clear that all of us are being forced to work remotely. Even though we thought that this is not the way to work, we are all seeing that, yes, you can get stuff done.
The second problem that’s emerging, unfortunately, and we see this and I think we’ve all gotten used to enjoying it. Now kids are also at home. They’re also learning if they’re younger, they need retention. Even if you have both the parents working, that’s hard to juggle both the school and the work.
If you’re a single parent, you have my best support and wishes because it is so difficult. What that’s leading to is, yes, kids will go back to school. They also need their environment, but I think some of these things are requiring us to step back and think very differently. I do see a couple of very clear opportunities here.
One is that we will cast a much bigger fishing net because the talent is there. We’ll all get adjusted. We can hire in cities where we never went in before because we didn’t think they were close enough, or we didn’t have an office there. Well, guess what, we don’t need an office in every city or wherever people are. As long as the talent is available, it will allow us to cast the net a lot wider.
Secondly, if that leads to 5%, 10%, 20% improvement or increase in your talent pool, then you need AI to go through that very quickly to figure out who are the best people to bring in. You don’t need to do anybody a favor. You simply have the ability to hire from more diverse backgrounds.
McKinsey did a survey with us using our data on how to help people who did not finish a four-year college on how to get them on a career path so that they are making more money than they’ve done in the past.
The key to that is identifying what enabled them to succeed in the past and then providing them more and more opportunities to get into such roles. Using AI and data to provide better opportunities to others who are not presented. That essentially reflects this in remote work.
Then the third element is how it helps the company? Maybe you are now back to thinking in terms of running multiple shifts or hiring people for specific time zones. As long as people are interested and willing to work at different hours, you can continue hiring them according to that. And that, by the way, has happened with call centers.
A lot of companies that used to run these in offshore environments, in Eastern Europe, or other parts of the world. The math was that to run a 24/7 call center, you need essentially 5.4 people for every role, and that would give you enough staffing to have a fully manned properly staffed role to account for holidays, vacation, sick leave, and all of that stuff.
Some of that rejiggering of how we think in terms of our workforce is needed. Then the other element is do we have the managers who know how to manage a remote workforce? That oftentimes is not a requirement—some have done it, some have not—but now that becomes a necessary part. If you’re going to be leading a team, you need to know that some of them will be remote, and could be anywhere.
I think the COVID is actually having us rethink, and I’ll give you another example. Event recruiting or going to campuses to hire for early talent. Guess what, that’s not available, but a lot of the companies are still running their business.
With our stuff, you can run a virtual career fair. You’re not limited to just going to 30 universities, you can go to all of them. Get all the resume books in, see who you want to talk to, schedule the interviews. And instead of being limited, it’s giving you more opportunities to hire from colleges that you never went to.
I think this is forcing everyone to step back and think about how do I leverage this? Yes, it’s not comfortable, and clearly, we need to get past the health crisis and then the unemployment crisis. I think it’s here to stay. I think things will get better because it’ll force us to accelerate everything.
Jon: Certainly, my son can attest to the challenges of remote school, and hopefully we can get the children back safely into the school soon. I appreciate those comments. Talking with business leaders and a lot of the organizations that I work with, there seems to be transformation fatigue that’s starting to settle in a little bit.
I see more and more eye rolls when the transformation word gets mentioned. Some people say hey, don’t even bring it up. It’s not going to go anywhere. That said HR and talent management, in my mind, still seems very ripe for transformation, especially given the advancements in automation technology.
They can shift human work from low value to higher-value activities, increased productivity, and increase that employee experience. In some ways, I think the pandemic may have increased awareness, but you hear all these dire predictions about robots taking everyone’s job.
I personally don’t buy into that vision and think worker augmentation should be seen as a net positive. What’s your worldview on the impact of AI on the future of work?
Kamal: I love how you phrased it, worker augmentation, because I think what will come up is a better balance between the stuff that can be automated and can be done by someone—basically a machine. Oftentimes, a lot of this menial work or repetitive work is not the fun part of anybody’s job. If some of the stuff can be automated, we should automate it.
The second thing—I like how you phrased it as transformation fatigue. The thing that’s emerging for us is a lot more focus on people and employees because before this, there was a lot of this thing, hey, we’ll just go out and hire. Now, as more and more people are being forced to rethink their business, and there is more need for digital scales, data scientists, and all of that stuff. People are realizing that it’s not like all these markets are littered with that talent, so let’s focus more on the employees.
What we have been focused on is how do we get the rescaling and upscaling going? How do we help companies foster and build a culture of learnability so that people are always looking forward to doing stuff?
The thing that a lot of our customers are saying is that look, it’s not just classes because most companies have subscribed to a lot of classes. But most people when they are in a job they learn 70% of their new learning comes from actual experience. About 20% comes from people and mentors, and only 10% comes from taking a class.
What we are using with our AI platform is how do we provide a talent marketplace or a project marketplace where the company can post projects? The important part is how do we get some of the rock stars to participate, and how do we find the experts so that we start building this self-service environment where people want to be appreciated, they want to learn more, or they want to learn from others who are recognized in the companies as being experts?
How do we create that environment, and we are now seeing tremendous success with a lot of our customers were both internal mobility, rescaling, employees wanting to learn new things, and then how to work together as a team. This thing is manifesting itself in a lot of use cases, for example, when you’re doing an M&A.
You’re going to bring two companies together. You want to actually preserve the best talent on both sides, and how to bring them together so that they start working together integrated as a single team. The project marketplace is a great way to do that.
Secondly, we also run hackathons now. Our first one during COVID was actually across three continents was very successful. The fun part was that everybody even got to vote on the projects. By default, they were picking the things that were interesting and things that were not interesting.
There’s a lot of simple ways of actually personalizing the experience. What we are doing a lot is how to change the user experience. One, the individual and employees feeling empowered. That hey, if I want to explore other opportunities within the company, how do I do that?
To me, it is transformational, but I have no issues if we don’t use that word and simply say this is all about empowering the individual to pursue a career of their choice within the company. Focus on learnability, applaud everyone that’s learning new skills and building new strengths, and get it to be aligned with the company direction. When you do that, it is magical. We won’t use the transformation word. Let’s use the word magical because that’s what it is. What do you think?
Jon: I think that’s a great point to end on. To recap today’s conversation with Kamal Ahluwalia the President at Eightfold. Certainly, one of the market leaders in the emerging technology-driven talent management space, really helping companies gain incredible insights into their employees and candidates.
Employment is the backbone of our society and everyone deserves the right job. We heard about the exciting work Eightfold is doing to support our veterans. Today, you get the job based on who you know, and not necessarily what you’re capable of doing.
Tomorrow, thanks to companies like Eightfold, AI-enabled technology will really transform how high performing companies can acquire and manage talent.
Thank you, Kamal, for joining me today. I want to give you an opportunity to make any closing comments or provide any final insights, but I also have one final question for you. I am a bit of an information junkie and always looking for the latest and greatest resources. My question to you is what resource—website, newsletter, podcast, email blast, anything at all—do you rely on most to be successful and knowledgeable in your role?
Kamal: That’s a tough one. Everything else was easy. Apple News is what I rely on every morning. Funnily enough, even Google Alerts. I’m trying to get off social media and somebody else determining what I should be looking at. The other part is, in the last two years, the content that’s interesting to me is changing and is becoming more and more focused on the individual.
How would people learn? It’s very different. It’s more about how to influence, change management because we are seeing a tremendous opportunity to get people to think differently. More than anything, that’s what I’m looking for and I’m interested in learning more and more about it. I think my sources are different now than they used to be.
Jon: That’s great, and I’m a big fan of Apple News myself. I get a lot out of that $9.99 subscription every month. For reference, my resources episode that I can’t miss is the First Look daily email from CIO. I’ll date myself a bit and admit that I used to get the print version of CIO magazine back in the day when we actually had magazines.
They have a great article today on low-code platforms and how companies like Toyota and Conoco are leveraging them to drive business value. We’ll be sure to put a link to all the resources recommended and the article announcing Eightfold’s recent award as well in the show notes. That is a wrap on today’s show. Thank you, Kamal, for joining me and FortressIQ’s sponsorship. I’m Jon Knisley, and this has been hello, Human.