Episode 20 – Rebooting Talent Acquisition with AI
Dec 02 7:24:10 am
Today, Jon Knisley (the host of hello, Human and a long-time technologist helping companies adopt and utilize emerging digital solutions) talks with Jessica Zych, the Vice-President for Strategic Partnerships at FortyOak, the go-to firm for talent first automation strategy. Jessica, like Jon, keeps an optimistic perspective on the human and robot/AI partnership in the future, where both humans and AI can work together. Today, through her optimistic lens, she shares her opinions on the increase of AI adoption in the HR talent space, how to create a high-performance automation team, and what the future holds for the hybrid workforce.
The Great Resignation is here and it’s real. The last several months have seen a tidal wave of resignations. Job transitions among Gen Z are up 80% year-over-year, and they’re up by 50% for millennials. To help handle the uptick in transitions, AI-enabled technology solutions are delivering productivity, efficiency, and accuracy to the traditionally human-centered process. Using AI frees up recruiting teams to spend more time on the work that humans are best equipped to handle: conducting phone screens, building relationships, compiling offers, and guiding stakeholders through the process. AI can be deployed to simplify interview scheduling, screen resumes, and identify passive candidates. At the end of the day, AI is helping companies hire better and faster.
A big thanks to FortressIQ for sponsoring the program and be sure to hit the subscribe button whenever you listen to podcasts.
- The elevator pitch on FortyOak
- Jessica’s AI background and her journey to FortyOak
- How companies are infusing AI into their business processes
- The increase in adoption in the HR talent space
- The importance of monitoring and eliminating the bias in AI output
- Process and technology considerations for recruiting
- The recipe for creating a high-performance automation team
- Jessica’s vision for the future of the digital workforce
If you enjoyed this episode, subscribe and check out our series at fortressiq.com/podcast. Thanks for joining us today on hello, Human.
Full Episode Transcript:
Jon: Jessica Zych, the Vice-President for Strategic Partnerships at FortyOak, the go-to firm for talent first automation strategy, 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 helping companies adopt and utilize emerging digital solutions. A big thanks to FortressIQ for sponsoring the program. Be sure to hit the subscribe button wherever you listen to podcasts.
The great resignation is here and it’s real. The last several months, I’ve seen a tidal wave of resignations. Job transitions among Gen Z are up 80% year over year, and they’re even up 50% from millennials.
Tell pandal the uptick in career moves. AI enabled technology solutions are delivering productivity, efficiency, and accuracy to the traditionally human-centered process that typically has involved lots of swivel chair activities across multiple systems. We are fortunate to have an industry leader give us her perspective and insight on the exciting uses and future of AI around automation in the emerging digital workforce.
Welcome to the program, Jessica. Thanks for joining us on hello, Human and bringing your knowledge and expertise to the program. To get started, it would be great if you could give us the elevator pitch on FortyOak for listeners who may not be familiar and your experience that got you to the firm. I teased the talent first automation strategy tagline. But how do you spend the FortyOak narrative?
Jessica: First of all, thanks, Jon, for having me. I’m really excited to be here. As you said, I lead the Strategic Partnerships for FortyOak. Talent first automation strategies, what does that mean? We have a few different verticals that we function in. A lot of our clients are struggling to make sense of Intelligent Automation and artificial intelligence, and how to take control of their programs.
We offer advisory solutions to our clients as to how to build and scale their automation or AI teams and initiatives within their organization. On the other side, we also offer talent acquisition and resource strategies in terms of building out a complete center of excellence, and progressing those strategies and solutions to be a fully sustainable program within the organization.
Jon: How about a little bit of your background? How did you get to FortyOak?
Jessica: My background, I’ve been in talent acquisition, staffing, recruiting, all of the different ISMS, if you want to call it, for the past 10 years. I started in technology recruiting, moved into a managed service provider role, where I was working with a client and implementing their vendor management solutions, then moved into a recruiting process outsource organization where I was sitting on site with clients.
At firsthand, knowledge and in-depth look into how companies are either excelling or really struggling within their talent acquisition and HR function. I brought all of that experience to FortyOak. About two years ago, we saw a need in the market where there was a huge talent shortage. Companies were really struggling to hire the right people to propel their programs. I married my background of talent acquisition, my interest in Intelligent Automation and AI, and everything that fits under that umbrella. It brought me here.
Jon: I think that’s great. As you can tell, I’m excited about this conversation. I think it’s exactly on point. The importance of people today doesn’t get enough attention. We could probably spend a whole episode on this. In today’s environment, in a lot of software categories, especially the more mature ones, there’s not a ton of differentiation in technology platforms.
The people in the process dimensions (I think) have lost the focus a little bit. I’ve argued a lot that that’s part of the reason why transformation successes is so challenging. There’s been too much focus on technology over the past year. Looking at processes, how are companies infusing AI into their business processes today?
Jessica: It’s interesting that you say that. I think that going to your point, there’s not a lot of focus on people. At the end of the day, we’re not getting anything. Although we’re talking about AI and bots, we are bringing that human component, i.e., hello, Human back to the table. Every day we’re working with large and mid sized companies and we’re trying to find solutions to the problems that they want to automate or enhance via AI or Intelligent Automation.
We’re seeing everything, finance, invoice processing, financial analysis, huge uptick in NLP and OCR. In IT, a huge rise in chatbots. I think most interesting to our context is in and around the HR and talent acquisition area. It’s proven to be a huge focus area throughout the pandemic. Obviously, you mentioned earlier the great resignation and everything that’s going on in regards to that.
There are shortages in talent. All companies are now, after 2020, on the rise to hire people. So how are HR and talent teams really driving and differentiating themselves from the competitors? We’ve seen, like I said, a huge uptick in that area in terms of using AI to simplify the interview scheduling processes, screen resumes, identify passive candidates, and really opening up a broader and a lot of times a more inclusive candidate pool.
Jon: I’m so glad to hear you move on beyond the typical financial and accounting practices use cases. I think too many in our industry are stuck on that, order to cash and procure to pay. I get it. The structured data is fairly easy to work with. But in all honesty, I’ve been catfished into a number of webinars by a leading process mining company that will go unnamed, but they’ve promised industry-specific details.
There was literally one line about the biopharma space. The other 35 minutes was this generic demo of order to cash. I’d like looking beyond those traditional use cases.
You mentioned seeing an increase in adoption in the HR talent space. What use cases have you seen to be most valuable in that area?
Jessica: I think when we’re talking about use cases, it’s important to look at historically where there have been challenges. The pandemic threw in infinity more in terms of HR and talent acquisition. Obviously, the pandemic force companies make some really difficult choices. Some of them took the biggest hit. We’re in HR and talent acquisition teams, and now we’re seeing companies that had to scale all the way down to zero in terms of their talent acquisition, and recruiters that are now rebounding, and really driving hiring initiatives.
In an unsurprisingly twist, companies are trying to do more with less, which is a lot of why we’re here. The two main areas that all HR and talent acquisition teams are concerned with are hiring top talent and retaining that talent within their organization, their high performers. AI is definitely being used to drive the efficiencies in both of those areas, which is leaning into a positive candidate experience and an employee experience.
Going back to what the pandemic has shone light on is that a lot of people had a lot of time to really think about what’s important to me and in my job. What do I want to be doing? This war on talent has never been more competitive. Candidates are looking at the interview and onboarding experience overall as to what they can expect when they’re an employee of a company.
Any long arduous interviewing processes, how long it takes for them to get a response from when they initially apply to when they’re having a phone screen with someone, just the ability for someone to have an interaction with someone at the company or who they perceive to be someone at a company. The increase that we’re seeing is certainly in candidate sourcing and screening, implementing AI, and really infusing AI into that process.
Obviously, AI has the ability to process data at a huge scale. With most recruiters, they’re working anywhere from 20–30 jobs at a time across all different kinds of disciplines. So it’s nearly impossible for a human being to be an expert in all of those areas. What AI does is it allows a broader reach. It can scan and crawl millions of profiles online pretty quickly.
You’re sourcing intelligently through social media, job boards, online resumes, LinkedIn profiles. It’s really bringing more accessibility and really driving that pipeline. If any talent acquisition or recruiters are listening right now, they’re saying, how are we going to do this? How do I drive more people into my pipeline that are going to close these roles?
Another way that it’s really reaching out is going through all of the profiles that are there. I said, recruiters are typically working 20–30 jobs. When we’re looking at it in terms of applicant status, you typically have hundreds, if not thousands of people that are applying to each job, which is obviously daunting for one human being. Most talent acquisition and HR teams are handful at that and they’re responsible for driving the best talent into the organization.
If you have someone who is sorting through each and every one of those profiles, it’s no wonder that hundreds and hundreds of people are not being responded to. It’s just impossible for a human being to go through that many per role. Again, we’re seeing a huge uptick in these HCM and ATS Intelligent Automation and AI programs that are going through. They’re able to actually score different resumes in terms of how applicable they are to the position.
Where we’ve seen an uptick (I guess) or how they’re starting to implement is looking at people not just what they’ve done historically but also where there is potential for that person. A lot of times, with historical algorithms that have been in place previously, it was just keyword matching. I’m looking for a Java developer. Here’s Java on the profile and now we’re matched.
Artificial intelligence can actually look at more of a component. It has the deep learning component, specifically with machine learning, for example. It’s looking through millions of data points, analyzing trends, and can really bring a really diverse area of talent, not only that matches really what we’re looking for but also can look to see who’s still going to be with the company within a few years. So it goes beyond from a talent acquisition perspective, and now we’re floating over in retention.
We’ve also seen some programs be we to assess which candidate traits correlate with long-term success in a specific role. Then it allows the program to then go back and look for candidates that fit into that particular profile set. That’s from a talent acquisition perspective and how it’s been applied in that space. That’s been a huge focus area there.
In terms of HR, HR teams are constantly bombarded with employee questions. We’re talking about holiday schedules. Where do I find my W-2s? All of these repeatable, very time consuming, if you’re replying to all of them individually questions. There is a growing adoption of natural language chatbots, and HR, HCM software. A lot of users are very accustomed to interfacing with those types of information.
The change management component from that perspective has been very minimal. It’s been really increasing again. We go back to the candidate experience and the employee experience. In a lot of instances with organizations, the long-term success of someone or how long they’ll stay with an organization can be directly correlated to the success of their onboarding and their hiring process. For those that went through a negative or wishy-washy interview and onboarding process, the likelihood that they’ll stay on longer is significantly less than those that went through a stellar process.
So again, we go back to a lot of those questions coming into HR from new employees. Where can I find this information? How do I get to it? Again, just going to improve that employee experience.
Those are a couple. I could go on and on. In HR and talent, there are infinite ways that it can be applied, but those are the ones that we’re seeing the most of recently.
Jon: You are truly the expert in this area. Again, the whole topic is really fascinating to me. Getting ready for this session, I read somewhere and I wish I would have written down the source because it’s one of those numbers that I really liked, but speaking of candidate experience, it was like, best practices around initial contact through offer was like four days.
I actually went back and looked at it and I’m like, hang on, was it a typo? Was it supposed to be four weeks? No, it was four days, which was miraculous to me to think that that today is considered best practice and how quick you go from first contact to offer to really get the quality of candidate that you’re looking for in this crazy world that we’re living in today.
Jessica: Just going back to that point, this market has changed considerably. We have seen every candidate that we’re talking to right now has multiple offers on the table. The speed to response and the time to hire, you have to move very, very quickly in order to be competitive. If you’re coming in after a week of that person having applied, you’re probably not going to win that person and add them to your team.
When we’re looking at some of those things, we’re looking at the candidate experience because it affects retention. We’re looking at the time to hire because it affects the offer acceptance ratio and the quality of the hire. So all of those things are coming into play. Specifically, that’s where AI can really make a huge difference in the success of a program and bringing the right people into the organization.
Jon: I think the whole Intelligent Automation ecosystem, from the process discovery to the RPA, to the DPA and analytics, and everything else in between the AI and the machine learning, it’s really one of those cases where it’s the exponential benefit that you’re getting out of it. It’s a case where one plus one equals three.
Individually, all these solutions drive value at their own level, but when you combine them together, that’s when you can really get the speed to value, accelerate the time to value that you’re looking for, and put you in a place where you can make those hiring decisions in four days, which a couple years ago would be absolutely unheard of.
You mentioned algorithms a little bit. Ethical AI is coming up in conversations more and more. What’s the impact of ethics, explainable AI, and recruiting? When the technology starts deciding who does and doesn’t get screened or hired, I assume the scrutiny of AI models jumps significantly. Can AI help non-traditional candidates get a look?
Jessica: I think you definitely can. Again, it’s accessing millions and millions of data points and it’s looking for trends. Some people who don’t have the traditional profile, it’s identifying as a match for a role or it goes beyond that, and it suggests to that person that has their profile posted somewhere is open to new opportunities, and they’re bringing those job positions to that person so that they can apply to it. It is targeting. It can allow a more diverse candidate pool, and it can drive the not obvious person for the role to that organization or to that program.
Amazon had the hiccup or the mishap in 2018, some of their developers looked into the 10-year history of hiring. They created a program to find great candidates that were similar to what they have hired previously, but all of those profiles were predominantly male. They inadvertently discriminated against all of the female engineers. They were only looking for those specific things.
I think at the end of the day, we have to look at this as, AI has to have some input in order to receive an output. If the input is biased, in Amazon’s case in 2018, that it has since been […]. It was very, very quickly recognized and cut down just so that we’re clear, we don’t get in trouble with anyone there.
They found the issue and they nixed that initiative. If the input is biased, so will the output. If we’re looking at it, companies are looking to increase their candidate pool to diversify it and to work to eliminate the bias. That said, it’s something to definitely be conscious of. Companies are using tools, but they’re liable if discrimination is your output. It’s important that these systems are closely monitored. That includes audits and things like that.
Reverting back to earlier, we were talking about sourcing and AI, specifically. The candidate pool can be increased with AI to include non-traditional candidates that otherwise would have been overlooked by maybe an overworked or an inexperienced recruiter. They may not see that you have a background that is purely applicable because you don’t have the keywords that they were typically looking for.
Inexperienced recruiters are playing a little bit of a matching game until you get some years under your belt, you can read between the lines and see the nuances of someone’s profile and candidacy. That’s where AI can really make a big difference.
Something that I was reading about recently was that New York City is considering requiring employers to inform job applicants, if and how they’re using AI in hiring decisions and requiring AI vendors to perform audits initially after it’s been implemented.
I think that that could be something that we start to see. That would, I think, bring more trust into organizations in terms of ensuring that they’re not, again, inadvertently discriminating against a protected class. Something that Salesforce did recently is they hired a chief ethical and humane use officer. I guess recently is a relative term. It was about two years ago that they hired her.
I think that that could continue to be a trend. Looking at development strategies to make sure that this technology is being used in an ethical and humane way, and to really continue to build that trust. HR and talent acquisition can typically, like you said earlier, be an overlooked area for this type of technology. I think it’s because the crux of that business is people. There’s a knee-jerk reaction of distrusting artificial intelligence. If we have some of these programs and initiatives in place, I think that that would go a long way of ensuring that we don’t have any inadvertent discrimination or bias that’s afoot within the program.
Jon: Time is all relative these days. So yes, recent can fully qualify a year or two ago. I think it was in that same time frame, maybe even earlier, Google had their first meeting of their data and ethical council around ethical AI. I think it had to disband after the first meeting and they had to retool how they set it up.
These are tough issues, but I think ultimately at the end of the day, organizations aren’t doing this maliciously. It’s more just, okay, I had bad data going in, so I’m going to have bad data going out. As long as we’re aware of it, keep an eye on it, and make adjustments, ultimately, as we get more data, we can make better decisions.
That’s one of the other arguments that I tend to make. Data-driven organizations tend to win and we can be more data-driven. We can do more things, do better things, and do it faster, so all makes sense.
Switching gears a little bit. Beyond recruiting, FortyOak provides advisory services to companies looking to build their automation capabilities and expertise. Every organization is obviously unique, but what are the key components that companies need to consider to win in this space? It obviously goes beyond just the people. I assume there are process and technology considerations in there as well.
Jessica: Definitely. There are a few that I’ll highlight, obviously. One thing that we highlighted in FortyOak is there’s not a one-size-fits-all approach, although there are tried and true ways that we found to be successful and some pitfalls that we’ve seen with other early adopters that we try and steer clear from. Although they’ve since righted the course, it does go beyond just people.
You definitely do need specialized talent to get your program off the ground. Some of the early adopters were getting to a point where they’re self-sufficient. But anyone getting started needs an infusion of talent and process-oriented thinking to really meet the expectations of the speed that’s associated with these products.
In terms of process, again, going beyond people, but if we’re thinking about it from a hiring process because we’re still in the talent acquisition in HR, it is important to think. If you’re typically taking months and months to hire the right resource to propel your program and there’s an expectation that a digital worker will be productive in one to two months, there’s a disconnect there that needs to be resolved. That’s one, but we also have to look at the governance, approval, and oversight. Those things need to be addressed to ensure that there’s agility and controls are maintained.
I think it goes without saying when we’re talking automation, that it’s also important to evaluate your processes and improve the process prior to automating. I can’t tell you how many leaders that I’ve talked to that have gone down an automation path, looked up and said, probably should have optimized that process before we automated it. So they’re having to peel back that onion. Never automate a bad process is definitely a word of advice, number one.
In terms of technology, obviously, we all see that these new products have huge advantages. We also have a huge technical debt and systems that are really hard to let go of in a lot of cases. Non-digitally native companies have all of those legacy systems that are fully embedded into every piece of the organization. With today’s AI, it’s often very configurable and multiple, sometimes fragmented.
It doesn’t always paint a clear picture of how it will support an entire business process, which in some cases, can create complexity and dependence on some of the existing systems that aren’t as advanced and can lead to either expensive solutions or it leads to an immature solution with gaps. It’s really looking at your organization holistically and not relying on one product to fix all your problems.
We really have to look at all of the technology, and all the considerations, and see how each of these products working with what you have in your existing tech stack can enhance the organization. Sometimes, that takes an objective view, which obviously we offer, but sometimes it is able to be handled in house. So those are a couple of the considerations there.
Jon: You hit about a half dozen of my favorite buzzwords, so I don’t know where to even begin here, including technical debt. But again, we’ve seen a ton of organizations with what I call the ready-fire-aim approach. It’s so critical too. We say, look, you got to do your discovery, you got to do your optimization, and then you got to automate at the end of the day. It’s got to be in that order. You need all three of them and it’s got to be in that order.
I think the other piece that I’d add on there is I saw an article. Again, last week or two, but could be four or five weeks ago given the time frame these days. It was on a COE for a bank Intelligent Automation program. I was struck by the numbers. They said they had 20–25 process optimization experts. They had, call it 30–35, data engineers, RPA engineer type people, and then 20 data scientists.
When you’re looking at driving that kind of capability in the organization, that struck me as, okay, the ratios are important but also just the sheer scale to get the numbers that you’re trying to impressed me a little bit.
Your team does a lot of work in the automation space, obviously. One of the key challenges facing company is scaling programs across the enterprise, as I just talked about a little bit. Is there a recipe for pulling together a successful automation team? What’s the talent mix that you found that’s needed to create these high-performance teams?
Jessica: Definitely. The recipe for the automation team, there are a few balances to strike. As with any recipe, if you’re building or if you’re baking a cake, for example, you may find that, Jon, you like a little more salt in it and I like a little more sugar, so they’re all customizable, but there’s the underlying, we’re going to need a crust, we’re going to need some filling. These are some of the things that we take into consideration.
The balances that I think need to be struck right off the gate is the domain experience versus the technical experience. Automation requires both. There has to be an intimate understanding of the business process and knowledge of the automation tools and technology. You can’t just go in. Like you said, we have this process. Let’s automate it and not understand how it’s going to affect the entire organization, if it will.
We have a webinar coming up on the rise of a microbot and how you can automate these really tiny, little bitty processes. That is not going to affect the entire organization. It’s just that one little sliver. So again, a few different ways to do that.
The other balance that needs to be in consideration is the internal experience versus external experience. So both are required again. Again, enough knowledge to navigate relationships within the organization, but enough detachment to actually challenge the status quo. You have to be able to navigate governance and the budget process, but also be willing to change.
The challenge of the way we’ve always done it is going to be there. Especially with Intelligent Automation and AI, there’s a huge change management effort that has to occur in most instances. Without someone in the program that’s going to be an evangelist of sorts, you’re going to be fighting a little bit of an uphill battle in most cases.
In terms of the types of roles that we see in an automation team, regardless of the way that resources are brought in, program manager, leader, typically these are going to be your change agents. We often call them a catalyst, depending on the size and complexity. The existing adoption of disruptive programs in the organization, these people can really make or break the effort. We typically see a solution architect, an analyst, a developer, and a support function.
These are not groundbreaking roles, but having those folks that have especially the ability to communicate the benefits of artificial intelligence or Intelligent Automation and how it will enhance people’s work is critical in order to get that off the ground. In terms of company profiles that are coming up, you have to look at it holistically. There are some companies that are looking for solutions that are straight out of the box. Want to add minimal headcount? Consulting option is great for them.
We have companies that recognize that their business processes are going to change in a meaningful way. They want full transparency and control, but they’re not really ready to commit to full time employee hiring. So contingent workers work great for them. We also have companies who recognize processes are changing, want to have full control, and they want to bring on more headcount. So that would be a full time employee engagement.
There are a few different ways that this can shake out. Again, blending those models, sometimes they’ll hire a full-time program manager and add in some developers from a contingent workforce perspective. Again, it depends on the size, complexity, and where you’re seeing the adoption within your own organization, I would say, really affects what that recipe really is going to be.
Jon: I’m going to steal that concept of microbots. I love it. Again, I’ll go back to all the information sources I take. It was Harvard Business Review a month or so ago. It talked about, you’re not going to find dollar bills sitting around on the factory floor. But if you look, there are 10,000 pennies sitting there. At the end of the day, I’d rather have 10,000 pennies than a dollar bill. I think that that idea of microbots is pretty cool.
You gave us the development team side of it. Looking at it from the other angle, let’s talk a little bit about the digital workforce. Employees see oftentimes automation as a job killer and leadership sees it as operational efficiency. I think that’s a bit too narrow of a view.
I tend to take a more Utopian view of the opportunity that technology presents. For me, the digital workforce isn’t a humans versus robots issue, it’s more of a hybrid outcome. It’s humans and robots. What’s your vision for what the digital workforce of the future is going to look like?
Jessica: I tend to be more optimistic in nature. My view sounds like it’s pretty similar to yours. Obviously, in my industry, AI and automation are enabling humans, in most cases, to be more human. In terms of what we talked about today, AI and IA frees up recruiters and talent teams, HR organizations to do more work that only humans can do. So conducting those phone screens, building relationships, and really getting to know people as a person to person, and alleviating a lot of the things that can cause frustration and burnout. There’s a ton of inefficiencies that can lead to that.
When you have employees that are running into that fatigue and burning out, obviously, your attrition rates are going to go through the roof. So wrapping it all up into a nice little bow, again, we’re getting back to the pandemic. Employees are looking at this great attrition, the great resignation if you will. It’s important to really look at the quality of your work. We always talk about work-life balance, but what is the quality of your work?
I read an article recently that workers are saying they’d be willing to forego 23% of their entire future lifetime earnings in order to have a job that was meaningful to them. So finding meaning at work, employees are happier, they’re more productive, they’re absent less. The attrition rates of those companies are going down.
The way that I look at it is very similar to yours—it’s humans and robots. We’re taking away the mundane, repetitive, mind numbingly boring or extremely daunting in certain situations, tasks from people. We’re maybe somewhat ironically because we’re using AI putting the human back in human resources. We’re employing the AI to allow us to do that. I think that it is that hybrid way of using the bots to enhance the human experience. I think that that’s hopeful and exciting in my opinion.
Jon: That’s great insight, Jessica, and a great point to end on. It reminds me a little bit, a couple of years ago, I saw there was a Swedish company that was renaming HR to humans and robots. Your comments reminded me of that.
To recap today’s conversation with Jessica Zych, the Vice President for Strategic Partnerships at FortyOak, AI enabled technology solutions are delivering productivity, efficiency, and accuracy to traditionally human-centered processes, especially in HR.
Using AI frees up teams to spend more time on the work that humans are best equipped to handle, and helps address the current talent crunch that companies are struggling with. Infusing AI into their business processes require unique resources and strategies for applying AI. Managers need to be prepared to deal with the challenges.
That’s a wrap on today’s show. Thank you, Jessica, for joining us, and FortressIQ for sponsoring. If you enjoyed it, be sure to give us a like or a five-star review on whatever platform you’re listening to. I’m Jon Knisley, and this has been hello, Human.