Our panel of HR Tech innovators – each a founder of a successful HR technology company – tackles 4 big disruptors shaking the workforce today. We talk about jobs going to automation, the skills gap, how to become more agile in HR, and what candidates & employees are saying about AI. Listen in for tips on how to navigate these disruptors in 2020!

Webinar Transcription

Webinar host: Briana Harper

  • President and CEO – Greg Moran
  • Chief Strategy Officer – Imo Udom
  • Director of Product – Adam Thompson

BRIANA: So, thank you for joining us today for a webinar, “Seeing Clearly in 20/20, What’s Ahead for the Future of Work.” I’m really excited about today’s presentation because I have three HR tech thought leaders on the call with me. Those are the voices you heard during our trivia game. We’re gonna to talk about four major disruptors that are shifting the workforce as we speak and provide some tips on how to navigate as we move into the new year.

Again, I’d like to say thank you for being here. I know you could be doing a hundred other things right now and you’re here with us, so I really appreciate it. I hope we can provide you with a chance to think, reflect, and plan ahead in spite of it being a really hectic time of year.

My name is Briana Harper, and I’m your webinar host. I’m also your resource for any questions you have about today’s topic. I’ll be taking questions throughout the presentation, so feel free to chat in any time during our panel discussion.

So, here are the thought leaders on our panel today. In fact, I’m calling this our founders’ panel because each of these gentlemen has founded a successful company — or multiple companies — in the HR tech space. One of the great things about working at Outmatch is we tend to collect really innovative people like this who, on multiple occasions, have seen opportunities to market and then build creative and workable solutions from the ground up. These guys have blazed trails in HR tech and because they’re so deeply rooted in this space, they are perfectly positioned to talk about workforce disruptors and the future work with us today. Let me quickly introduce each one of them.

Greg Moran is the President and CEO of Outmatch. Before Outmatch, Greg founded a company called Chequed.com where he built a software platform for automated reference checking and assessments. In 2015, Chequed merged with a company called Assess Systems, and that’s when Outmatch was officially born. Greg also founded two other companies, PeopleAnswers and Pinnacle Technology Solutions, and he’s a consultant, author, and speaker.

BRIANA: Awesome. Okay. Next in our panel is Imo Udom. He’s our Chief Strategy Officer. Right about the time that Chequed and Assess Systems merged to create Outmatch, Imo was founding a company called Wepow where he continued work on the video interview platform he began back in 2008. Imo joined us a year ago when Outmatch acquired Wepow, and his team is hard at work building video interviewing onto Outmatch’s talent intelligence platform. Imo’s earlier companies include Ovia and Inovaz.

Hi, Imo.

IMO: Hello, everybody. Looking forward to sharing again.

BRIANA: Awesome, thank you.

And then we have Adam Thompson. He’s the Director of Product at Outmatch. Before Outmatch, and for most of his adult life, Adam lived in Thailand where he founded a company called Thompson Bridge. At Thompson Bridge, Adam created a technology called Eureka, which uses machine learning and natural language processing to match candidates with companies. Outmatch acquired the IP for this technology earlier in the year and brought Adam on board as well.

Hi, Adam.

ADAM: Hi, and if there’s anybody Thai, sawadee-khap.

BRIANA: [Laughs] Thank you all three of you for being here today. I’m really excited about the conversation that we’re gonna have.

So, before we dive into our panel discussion, I’d like to give you a sneak peek at some of the other topics we’re going to cover in our future work webinar series. Next month, we’ll look at how to create feedback loops from pre to post hire, so you can better understand if you’re hiring the best possible people for your business. Then in February, we have a special Valentine’s edition on how to give candidates more love in the hiring process, and finally in March, we’ll show you how analytics can help you understand team dynamics and strengthen your internal mobility initiatives.

You can find all of our upcoming webinars at outmatch.com/webinars. You can also watch any of our past webinars on demand on our YouTube channel. Each presentation as well as today’s presentation is valid for one professional development credit for the SHRM-CP or SHRM-SCP. I’ll chat in that activity ID at the end of the webinar, so just look for that note from me.

Okay, and a quick overview of the topics we’re gonna cover in our discussion today, we’ll also save some time at the end for Q&A with our panelists, but feel free to chat in any time with your questions and we’ll just take those on as they come in.

So, we’re gonna look at jobs likely going to automation, the skills gap and what to do about it, the difference between ‘doing agile’ and ‘being agile’, and then AI in HR tech — what candidates and employees are saying.

So now you’ve seen the topics on our agenda, I’d like to know which of them is your highest priority or your top concern for 2020. So, let’s just do a quick poll and then I’ll hand it over to our panelists.

I’m gonna open this poll up to the audience, and then you guys can go ahead and start answering.

All right. I’m seeing lots of answers come in, and I will share this poll with everybody as soon as I close it out, but right now I’m seeing a lot of votes for the skills gap, that looks like the highest priority for most of you on the call today.

All right. I’ll go ahead and close that out and share the answers with everyone.

Okay, so as you can see it looks like 50% of you are most concerned about the skills gap, so that’s really helpful just to let us know, you know, how we wanna focus our conversation today.

GREG: Yeah, I — I mean, I don’t know about Adam or Imo. I don’t — not too surprising, right? For the conversations that we have, you know, with organizations around skills gap, we’re really trying to get multiple ways to kinda look at skills gap, right? And, you know, we really think about skills in two different ways, one is really a concept of, you know, that we refer to as enduring skills and, you know, they’re really, you know, around traditional hard skills, right? Hard skills being — hard skills really being around, you know, technology and, you know, you need. I don’t have enough people that can actually code in Ruby on Rails or, you know, whatever that is, right? And enduring skills really being more, you know, things that we would have considered more competencies, right? How do I — how do I get people that are more creative? How do I get people that are more innovative? You know, just a huge topic as we, you know, in an area where we have a labor market with, you know, 3.5% unemployment or something like that, you know, these days.

I mean, I remember earlier in my career when we used to think of full employment at around 4%. So, you know, today, we’re at 3.5%, it just keeps going lower and lower, right? You have to figure out a way to get more from the talent that we already have and that skills gap becomes a huge thing. So, I think, no surprise that that’s where, you know, most of our audience is. The one that — the one that actually is surprising to me and, I think, my guess is if we look at this maybe a year or two years from now, option A about jobs going to automation will actually become pretty large — will continue to become something that we’re thinking more and more and more about. We’re talking about it, we’re hearing about it today, but it hasn’t been in mass yet, it hasn’t affected those roles that maybe are around most of the people on this call today, right?

When we start to see financial roles or we start to see sales roles or more we’ve really considered to be more professional roles really starting to get automated, I think this is gonna very quickly rise from, you know, what I think was the lowest rank in there to probably the highest rank pretty quickly, but I think we’re probably a year or two ahead of that. I don’t know what Imo or Adam think about that, but …

IMO: Yeah, absolutely, Greg, and I think those things are tied as automation starts really pervading jobs and roles that traditionally have been done by humans. What tends to happen is that the skills and the knowledge and the information that we, as knowledge workers need to have, is gonna adapt and change as well. So, we’ll see those things going hand-in-hand the importance of enduring skills that help you work in a world where repetitive tasks are being done by automation, right?

ADAM: I agree largely. I think jobs going to automation is definitely going to be a big topic in the years to come. It’s no longer a question of if that’s gonna happen, it’s just — it’s a win now, but I think we should also be thinking about what jobs are gonna be augmented or changed because of automation, not necessarily, you know, they’re not gonna go away like radiologists are not gonna go away, but that’s probably gonna be one of the positions that are highly augmented by AI. And then there’s gonna be a whole list of jobs that are created that we, you know, gonna find it difficult to predict what those might be today, and all of that ties back to skills gap.

BRIANA: Yeah, absolutely. That’s really good insight. I think it’s a perfect segue into our first topic here, which is all about jobs likely going to automation, and it’s no secret that jobs have always evolved and changed with technological advancement, but I think what we’re seeing now is such a rapid rate of change that people are really starting to be concerned about job loss and future proofing their workforce.

So, I’ve got a question here that I wanna throw out to the panel: “How do you view automations impact on the workforce?” And, Adam, I think I’ll throw this one to you. I know you were just talking about this, but is there anything that you wanna add here?

ADAM: Well, I would just say let’s — I would not underestimate how big the impact is gonna be. I mean, we’re really at the start of a new industrial revolution. It’s already being coined to the Fourth Industrial Revolution, and that’s really AI and Big Data. If you look back at what our last industrial revolution was, it’s really the start of computers in the information age. Think of how much that changed the way that people went from working on assembly lines to everybody now, you can’t live your life without a computer. It’s a monumental shift in the way that we live, the way that we work. A lot of jobs, of course, were destroyed that don’t, you know, no longer existed after the computer age kinda came in, but it also created hundreds and hundreds of new types of jobs.

So, I would say, first of all, the impact is gonna be enormous and we’re at the very, very beginnings of it, and I would just again kind of overemphasize we should be thinking of some jobs are gonna be augmented, some are gonna be completely disrupted, and some are gonna be created by this. So, there’s my — that’s how I would start this conversation.

GREG: Yeah. If you look at, you know, just depending on whose data you believe, right? Anywhere from work for — you know, from World Economic Forum to a lot of the Deloitte’s and McKinsey’s and PwC, I think, have all done some work around this topic. You know, you’ll see numbers that range from somewhere between 5 million on the low end to about 20 million to 30 million on the high end of jobs being automated over the next, you know, five years, seven years, 10 years.

There are today, if you just look at the US alone, and I know we’ve got people on this call from all over the world, but if you just look at the US alone, right? There are about a hundred million-ish workers in the United States today, right? In the US labor market. If you start to think about that five, 10, 20 million, that level of disruption is like nothing we’ve ever seen before, right? So, what does that mean for an organization, right? And how do you start to — how do you start to — you know, I don’t know that I would say how do you prepare yourself because I don’t know how you — I have no idea how you do that, but how do you start to think about that, right? Well, it means that the people that we have in our organization today, if they’re in siloed fields that become — that are going to become targets for automation and, you know, I hate to say this, it’s probably, I mean, everybody on this call today including probably the four of us, right? I mean, are all — the way that we need to think about our careers going forward is really fundamentally different, and that’s why that concept of enduring skills, I think, becomes a really important thing, right?

How do we start to prepare ourselves and, therefore, how do we start to prepare an organization? Well, you do that by trying to expand that skill set beyond somebody who can, you know, work with spreadsheets, beyond somebody who can — my son about a year ago broke his leg skiing and the x-ray was done — there was an x-ray and there was an MRI, both of them were analyzed by somebody, I have no idea where they were. They were not — they were not anywhere in the hospital that we were in or anything like that, right?

So, you start to see, like, I mean, that was just that kind of that really early wake-up call. Well, when you start to look at siloed professions where really is about your ability to process work, that will be where the biggest impact is felt. So, how do you start to enhance those enduring skills? How do you start to enhance around innovation? How do you start to optimize around creativity? How do you start to optimize around those things that truly are enduring and they truly are gonna drive an organization forward? Because those are not areas that, you know, automation, that those type of skills are always going gonna be required. And I think for an HR professional standpoint, it’s really incumbent about educating our workforce is that these are the things you need to be thinking about, right? And how do you start to enhance your career both for ourselves individually and our organizations broadly.

ADAM: Yeah, it’s interesting. I saw a theme in the skill sets of the jobs that are most likely more safe than others when it comes to automation, and it has to do with jobs that require a lot of empathy, so really relating well with people, jobs like, you know, therapists or graphic designers, even nurses rank really high in that — on that, also jobs that have a lot to do with creativity or critical thinking. So when you’re not — you’re not facing the same type of problem over and over again, but you’re facing different types of situations on a regular basis, and it requires high critical thinking skills, those were the three top skill sets that are really enduring skills that would lead you to become a little bit more safe in the future.

IMO: And if we think about that, those two things that you’ve said, as we look at the future, some of how we look at people’s performance and rewards needs to shift, right? If we think about a lot of the old way of performance reviews or tracking success is really looking at things done of tasks accomplished. Well, in the world of automation, those tasks can be accomplished at a much larger scale much faster. So, when we think about having to make sure that we’re prepared, we need to now encourage people to be creative, to innovate, to be empathetic, create experiences because it’s those experiences that are going to really help companies be more successful, right?

Look at the retail world. You have two dynamics happening. You have the rise of Amazon and everything is going digital and online sales are being huge, but then you have people still having store footprints, but they’ve reimagined what that in-store experience looks like, so it’s more about the experience than the getting the item you need, right? So, we’re seeing that shift.

I think as HR, as we figure out how to encourage the workforce, reward the workforce, we’re gonna have to think a little bit differently.

GREG: Yeah, it’s definitely — I mean, this is not a political statement in any way at all, but it’s definitely not a coincidence that this — I don’t know if everybody’s been watching what the Democratic debates for US presidential race, but this has been a topic and I think every single one of the debates, a couple of candidates are a little bit, you know, more vocal about this than others. But, you know, regardless of where you are on a political spectrum, just the fact that it is actually risen to that level of attention today, I mean, it really tells you about, you know, I think where not only the US is going, but where the global economy is really going.

It’s huge, and just going back to that poll. That’s why, you know, I think if we went back and we took a snapshot in 6 months, 12 months, you’re just gonna see that trend line just going up and up and up because we’re not — we’re not feeling it yet in the way that I believe we really will be, right? We hear it when we’re dealing with trucking or certainly self-driving cars and impact on Uber and, you know, things like that, but we are not — we’re not hearing it yet in the world that most of us working on a daily basis, but we’re going to.

ADAM: Yeah, I’d be — I’d be really curious to know, Imo and Greg, what jobs do you think are gonna be kind of first up for automation and where we’ll see, you know, the really big first wave of disruption? You mentioned we’ve heard a lot about truck drivers. Did you guys — I don’t know if you guys heard, but there was this story where the first self-driving truck drove 2,800 miles from California to Pennsylvania just November, just last month through snow, through cities, through traffic, completely self-driving. Do you think it’s gonna be truck driving or do you think it’ll be something else?

GREG: I think it’s gonna be a lot of stuff. I think that’s gonna be — you know, I was in Europe last week and you go into — you look in any fast food establishment in Europe, there is not a single person working at a counter anywhere. You go in most checkout lanes and grocery stores and things like that in Europe today, you know, are fully automated. It just hasn’t quite made its way to the US yet. And I think, you know, that and I believe, you know, and Asia kind of the same issue, right? That’s, you know, extremely automated. US is actually lagging a little bit in that area. So, I think, you know, that’s gonna be a big area.

I also think, you know, like I said, it’s gonna shift into more professional roles as well and, you know, I think financial, you know, any kind of like back-end financial, this starts to, you know, hit the world that we all live in, I think, you know, with HR and you start to get into more the administrative functions of HR and that admin and things like that, I think, you know, are gonna be very quick kind of early movers there…

IMO: I mean, if you look at something like back-office finance, I think that’s a really good place where the automation is really augmenting what the individual can do, right? So, instead of having to do a lot of accounting, looking at spreadsheets, following up with clients for invoices, that part can all be automated, and then what the financial analyst can do is really look at that information to see where the opportunities for the organization to do things differently to gain more value.

So, again, you started this at the top of the hour, Adam. I think that automation is gonna impact different roles in different ways. Some are really just gonna be augmented by the automation, and I think that’s also a very interesting thing to look at. So that skill set you need is going to change. Again, so there’s a big correlation between the automation and skills gap or where we need to go skills wise. So, again, that’s gonna be very interesting as we evolve.

BRIANA: Yeah, I think that leads us really well into our next topic, which is all about the skills gap. And I know, Adam, you said that these two are closely related. And, Imo, I heard you just said the same thing.

Let me back up.

Okay. So, I just wanted to share a stat that I found from Gartner, 64% of managers don’t think their employees are able to keep pace with future skills needs and 70% of employees say they haven’t even mastered the skills they need for their jobs today. So, there’s certainly a skills gap as, you know, all of you just mentioned, but there seems to be a lot of differing opinions about what skills are most lacking. So, of course, we all just talked about automation as becoming a bigger part of our lives. We’re seeing augmented jobs or even jobs being replaced and then, of course, we’re gonna need more people with technical skills to manage all that automation, that’s pretty clear, but, you know, what I wonder is is that where the gap really lies?

At the HR Tech conference this year, Josh Bersin said that most college graduates today already have really good technical skills, so what companies need instead are behavioral skills like curiosity and creativity, and I know creativity already came up in the discussion, so we’ll look into a little bit more into that.

GREG: Yeah, I mean, if you’re — you know, if we’re thinking about where the biggest gap is, I don’t — again, this is — the technical skills gap has been extremely acute for a long time, right? We just simply don’t have enough skilled engineers on a global basis to keep up with the pace of change and really face with automation, the pace of change and things like that. That is a very acute problem. We’ve known that. We understand it. We’ve had it for — we’ve had it for a number of years.

When you look at — and that really influences. So, you know, if you look at some of the World Economic Forum stats from last year, you know, one of the things that they talked about is by 2025, there’s only one country in the world that’s going to have a surplus of talent for technical skills, and that is India. The rest of the world is gonna have a deficit of skills — of skilled talent. So, super acute. We’ve known it. We understand it. We all — anybody in HR we’re living it or certainly in technology, we live in this every single day, right?

But, I think, what Josh was talking about is a really good point because that soft skills gap or what we call enduring skills, that kind of — that need for somebody to think about their role differently is not something — when we operate in a more siloed, very technical skill, and again broad definition of technical skills, I don’t care if it’s technical skills in programming or if it’s macros in Excel if you’re in a financial organization or if it’s technical skills in HR or technical skills in sales or anything else, if the way that the impact I believe that we’re gonna be seeing over the coming years is really around how do we get — we talked about this earlier, but how do we get our existing workforce to think differently about their roles, right? And those are those soft skills, and that’s really more about creativity and innovation and empathy and all those other things that we talked about because that is really gonna define what makes a successful career in the future.

The technical skills, that gap will continue to close as we train more and more people and that’s known, it’s defined, and we understand how to get people there. Well, we don’t really have a great understanding of from an organizational standpoint typically is how to get people to think more creatively, how do you get people to innovate faster, how to create a culture of innovation within our organization. Those are the things that I think will be truly the biggest gap, you know, and again, I’m not talking — I’m not talking 10 years down the road, I mean, in the next — in the coming, you know, in the very near future here, right? Because that’s what’s gonna define competitiveness. And as we start to see more and more automated, the need for somebody to be able to think differently about their role is gonna be absolutely the case. I think right now, we really feel the technical skills gap. I think in the very near future, I think we’re starting to feel that soft skills gap, and I think that’s really gonna be what is the major problem in the workforce going forward.

IMO: Absolutely, Greg. I recently saw this headline, you know, ‘skills change but human capabilities endure,’ so that’s what we talked about those enduring skills, those capabilities, critical thinking, curiosity, aptitude for learning, learning agility, those things endure. And if you think about a world that’s changing so quickly due to automation, AI, again the world becoming interconnected, the ability to learn is gonna be an enduring skill, right? That’s gonna give someone an advantage not necessarily what they know today, but their ability to always be able to learn what they need to know for the future. That’s why it’s so critical. I like that you brought it up, Greg, where — if you were to ask me, those enduring skills, those human capabilities cultivating a culture for learning and improving is really what’s gonna set the organizations apart.

So cultivating, like how do we — in HR, how do we think of cultivating these human capabilities, these enduring skills, so that people are able to adapt as we need them to and as the organization or jobs demand on an ongoing basis.

ADAM: Yeah, I think it’s good to separate technical from soft skills. So on the technical skills side, one gap — you know, we always hear that the gap of not enough engineers and then I think a lot of us specifically mean programmers when we — when we say that, but actually two really big fields that have huge labor gaps at the moment, one are trade skills, I mean, plumbers, electricians, carpenters. I read a report from SHRM earlier this year, and I just kind of refreshed my mind on it this week in prep for this call, and there’s a 30% gap in the market for trade skills and not nearly enough young people going into studying those. So that’s massive, and we also know a lot of countries have aging societies at the moment.

If we look outside of the US, a lot of the world, the birth rate has dramatically dropped. If we look at Japan — actually, Thailand has one of the lowest birth rates in the world right now, and there’s gonna be a massive need for nurses, anybody in the medical space. So those are big technical skill gaps in areas where people would be really, really safe from automation.

On the soft skills side, two things that we haven’t really talked about much, I think we’ve alluded to it, but one is dealing with complexity and ambiguity. There’s gonna be so much change happening that training people to be flexible and adaptable is huge and communication. That leads us back to empathy, but training on communication skills, I don’t just mean language ability, I mean, how do you actually communicate your point.

BRIANA: Yeah —

GREG: Yeah, and I think — oh, sorry, Briana, go ahead.

BRIANA: No, Adam, you just — you make a really good point. And so my next question is whether it’s a trade skill or, you know, one of those human skills, do any of you have insight on how you might train those or maybe how you go find that in your candidate pool or in your existing workforce?

GREG: You can — I think there’s two ways, right? The way that organizations need to think about talent selection is gonna be different, right? And the way that organizations need to think about talent development is gonna be different. One, I think, from a selection standpoint, if — and, you know, just by the fact that we have some people on this call, I mean, obviously, this is a really big topic and organizations that are on here today, I’m sure, are — I mean, nobody would be here today if they weren’t really thinking about this, right? But it is an incredibly important thing when you’re thinking about talent selection that if you’re still in the mode of, “Hey I’m gonna go through this pretty subjective process. People are gonna apply. I’m gonna give them to a hiring manager. The hiring manager is just gonna figure out if this person could sell. If they can, we’re gonna hire them or we’re gonna give them a shot, or if this person can code, then we’re gonna go through some interview process really more based around technical skills.”

We pulled back the technical skills, right? We — you know, from an HR perspective, I think we’ll probably — I think we’re good at that and not doing that, but the moment we give, you know, from a talent selection standpoint, we just see this all — we deal with some of the largest companies in the world, right? Today, we’re running, you know, Outmatch is running somewhere around 15 million candidates a year through our technology and, you know, so we deal with — we just have this incredible position to deal with some of the most innovative companies in the world, but even those, you see hiring managers still kind of revert back to what we know, which is, “Hey, can they sell? Can they code?” Can they blah — whatever it is? Can they do the, you know, the journal entries if they’re an accountant or whatever it is, right? And then they’re — and that’s how we’re making hiring decisions.

They need to really get serious in the talent selection process where the most important thing that you’re screening for are those enduring skills that has got to lead the way. You can put some — and again, I’m not recommend- I know you couldn’t do this across. It’s a developmental organization for everybody, but you can train somebody in those technical skills. I mean, these are very often definable things that we can train into, but if somebody does not have those enduring skills, that has to be the point of the spear in the way that we’re thinking about how do we select talent. It’s got to infiltrate the assessment process, it’s got to infiltrate the interview process, it’s got to be throughout.

And then when we get into development, that need — one of the concepts that we talked about at Outmatch a long time with our clients is this concept of lifetime value of an employee, right? That we need to constantly be pushing the value that this person can create for organization, and you only do that by taking a constant learning approach with that individual.

Two things end up happening: Number one, you drive that value up over the life of that employee by helping them understand what are those enduring skills you need and how to acquire them. We’re all not naturally great at one versus another. And I can tell you, I’m not exactly the most empathetic guy on the planet, but I tend to be pretty creative, right? So — but that’s okay. I can learn empathy. I can kind of do these things, right? And we can provide that constant feedback to keep growing to value that organization. So that’s number one, it drives value to the company.

Number two, I can tell you right now, if you’re not doing it, you’re gonna lose the person. Quite simply, you’re just gonna lose the person, right? They’re gonna go somewhere else who’s going to make that investment because your candidates and your employees also understand what’s happening in the workforce around them. You’ve got to make that continuous investment in constant learning to continue to drive the value that that person can create. They wanna create it, and your organization needs it.

IMO: Right. There’s a study that that Bersin did last year — [clears throat] excuse me — they surveyed 700 organizations and found out that the average employee only had 24 minutes a week, 24 MINUTES A WEEK performer learning. So, something that HR can do is really encourage and reward continuous learning, right? So how do you encourage and reward continuous learning? Again, these kinds of rewards build habits, but you need to be able to make sure that people understand, that it — they should be taking the time to learn. Some of that needs to be self-directed. I think the traditional mindset or in the past, a lot of individuals feel ‘teach me, teach me, teach me.’ I think we can also shift that mindset to how to enable you to learn, how to create opportunities for you to learn, and again reward that learning, so that it’s reinforced within the individuals and the organizations as a whole.

The one thing that’s happening right now that I love, you know, at different levels, I interact with different people within the Outmatch family. In our CTO’s technical organization, they’re reading a book to look at team structures, right? And one of the things he proposes us in the product organization, why don’t we read the same book? Because our teams work very closely together, and we’re thinking about ways we can optimize and improve. It’s good for us to be on the same page. So that’s self-directed. That was really great.

On the product team, we’re also looking at other information, but we have teams encouraging each other to go out, buy books, and learn on our own, and then we create meetings to actually discuss our learnings and our findings and we’re putting them in practice in real time. So that’s an example of creating a culture of continuous learning, but also I think tactically, HR can try and reward those things on an ongoing basis.

GREG: Here’s a great — I had actually never heard that before about the 24 minutes is the average amount of learning. Here’s a great goal for everybody going into 2020, like really go hog-wild with this, right? Like go crazy with this and get a 300% improvement and learning across your organization, just give people an hour a week. Like, I mean, it’s a tiny piece of the time, right? And, you know, but you look at the, you know, the impact that that could really have, and again, this is — we’re talking about totally unstructured stuff here, but, you know, there are obviously ways to really optimize this and really drive continuous learning, but that’s just pretty — I had never heard that number before. That’s — that’s pretty incredible.

BRIANA: I love what you guys are saying about learning culture and even the learning philosophy kind of needs to shift within organizations. So that brings us to the topic of agile and this kind of self-driven learning is a key element of agile, so I wanted to shift this over to this topic.

Pulling another quick stat from Gartner here, 49% of HR leaders are unsure how to design the organization to be faster and more responsive, and that’s really what we mean when we say agile. I mean, that’s why this has become such a hot topic lately. But understanding the agile philosophy and adopting some agile practices, that’s really the first step in a much longer journey to becoming agile. Truly being agile requires not just changes in thinking, but changes in how your employees are managed and motivated and trained and hired.

So, I’ve got a question for the group here and Imo is our Head of Product or our Chief Strategy Officer, but leading the product team here at Outmatch. So, Imo, I’ll throw this one over to you since agile is really a software development term and it comes from the software world. So, what are some ways that HR can adopt some agile practices or principles?

IMO: Yeah, absolutely. So, a great question, Briana. You know, I believe that — again in HR, a lot of the traditional thinking and what has historically been asked for from HR is create control and alignment. It’s been all about control and alignment. Here are the rules, make sure everyone’s following the rules. Here are the policies, make sure everyone’s following the policies. So, I think that that naturally needs to shift and leaders — I mean, if you’re an organization where your leader is still pushing that alone, I think you need to push back a little bit there.

So, I think HR should think about creating opportunities and focusing on speed and responsiveness. So, again, we keep talking about the future of work. We keep talking about automation. We talked about people needing to learn and be more agile as an organization, and HR can really adopt that by taking a different philosophy. Silicon Valley is known for this, you know, don’t be afraid to fail. Maybe in some cases take that to the nth level, but it doesn’t have to be that far, but that concept of experimentation is what’s really gonna help HR be in more agile, not just talk about agility.

So, one of the big principles of agile is launch something, test it out, experiment, get feedback, iterate, and improve, right? So, if we think about that in an HR context, when trying to make a decision with little information, what tends to happen is we go research, research, research, research. Go in the room, create a workflow map, nail it all down, and then roll out across the entire organization. That philosophy is not agile, and that, you know, you’re putting way too much on the goal of getting this right and getting it out to everybody.

What we should think a little bit more about is how do we quickly launch something whether it’s a project or initiative, how do we pull in a cross-functional team, so when these ideas come from the front lines, how do we pull in people from the front lines to help us do the initial thinking. And think about it, you launch something, it works great, you scale it. So, launch, it works, scale. Launch something, it doesn’t work, no problem. Iterate, right? It doesn’t have to be right the first time. That’s a culture shift and a mindset shift, you know, creating an environment where it’s okay to fail, right? Creating an environment where you want to experiment, but I think that’s the key to HR agility or an agile HR practice or an agile workforce, just building that muscle of experimentation of launching things, being okay to fail, iterating and improving as we go.

GREG: If you look at agile and — you know, one of the things for everybody on this call, if you’re not — you may have heard the term agile before as it relates to software development, I would really encourage everybody on this call if you’re not — if you’ve just kind of heard the term but you’re not exactly familiar with what it really means, go grab a book, you know, jump over to your local book store or Amazon and get a book. There’s a million of them that explained the concepts.

The concept behind agile comes from what used to be the way that software was developed, right? And it did come out of Silicon Valley, and it was the way that software was developed. And previous to this, previous to agile, it was what was called a waterfall method, right? And if you think about the way of an organization, it’s very analogous to the way an organization tries to operate in many cases, right? Waterfall method is we have this vision for what we’re gonna do. Then what we’re gonna do is we’re gonna build this strategy that really kind of flushes out that vision. Then we’re gonna break up the strategy into a bunch of different parts and then those parts are gonna get broken down into a bunch of different parts. And now we’ve got a million different parts all over the place, and then we’re gonna start to assign out little pieces of parts to people all over the place. And magically, it’s all gonna roll up to this grand vision that we have. And organizations kept doing this and doing this and doing this, and then building software that didn’t work.

And because when you start to parcel it out down to such a micro level, Imo said the key word there, which was you are completely relying on the fact that you got it right, and I don’t know about anybody on this call. The amount of times that I actually get it right is about not, right? Now I might get parts of it, right? And I might get like a couple ideas, right? And I might have enough right to build on, but it was, you know, that’s really where it comes from.

So the agile method was really — the agile method software development was really about how do we do experiments, how do we take little pieces build something that’s isolated, and then how do we start to build on top of that something to just continue to iterate and iterate and iterate over time, right? And you start to see today and some of the most innovative startups in the Valley and even in larger companies today, that method of thinking about software development has now really kind of permeated down into the way that companies operate, right? Instead of saying, “Hey, there’s this.” I mean, we obviously all have a vision for what we’re trying to build, but then from that vision down to a series of experiments, how do we do something? And it doesn’t have to be right, it just has to be something that we can build on and build on again and build on again and build on again.

And suddenly what we see is it becomes a very customer-facing, customer-first type of approach that we take because we’re iterating based on the feedback from the market, right? Now, if you’re building a product, that market is external. If you’re building, say, you know, a culture initiative inside your organization or a learning initiative inside your organization, that market is internal, but the exact same process applies. Don’t have to get it right. We just have to start, and we’ve got to get pieces of it that we can start to build from.

BRIANA: Thank You, Greg. I really like the way you put that. It’s definitely experimental and it’s definitely about the people that you’re impacting with your decisions

Let’s go ahead and move on to our last topic of the day. I wanna talk about AI since it’s everywhere, it’s not going away. You probably have more tools in your tech stack using AI than not. There’s huge benefits to using AI, but we also can’t forget about the people whose lives depend — or lives and livelihoods depend on the decisions that AI may or may not make about them.

So, I found some reviews from candidates and employees that range from apprehensions to flat-out anger when it comes to employers using AI and some other processes. One candidate said, “Beware of robot recruiting systems. AI analyze everything you do from your pupils dilating to the tone of your voice.” Another asked, “How can anyone trust that? The system is biased.” And then someone also said, “I assume it won’t be long before Skynet is using this to determine which of us is part of the resistance.”

GREG: And besides all that, candidates love it.

BRIANA: Yeah, yeah.

So, Adam, I’ll throw this one over to you. How can we use AI responsibly or how can we ensure that we’re using it responsibly when we do use it, and how can we help ease some of these candidate and employee concerns?

ADAM: Sure. I think we just take a step back. All of us actually encounter AI every single day of our lives without even knowing it or at least machine learning. If you’ve ever used Google Maps, that’s machine learning. If you’ve used Grammarly to help you polish your emails, that’s machine learning. That’s AI, actually. If you shop on Amazon, well part of the way that they know how to stock their inventory is using AI. So you touch — AI touches your life every single day, every single day in tons of different ways.

Now, when it comes to you actually as a candidate applying for a new job, you don’t want to think that a robot is making that decision. You wanna — you want to think that a human is the one that’s ultimately look- reviewing your CV and you’re gonna eventually get in front of a human instead of a robot just making that call. I guess part of the way I think about it is if you are gonna go shopping at a grocery store and you are gonna — you picked something up out of the aisle and it had no ingredients on the back and it was a complete mystery of on what’s inside of this, you’re gonna be pretty apprehensive about buying that and eating that. Same thing kind of comes over to how a candidate would feel if they’re encountering AI inside of your selection process. If it can’t be explained to them how that AI is being used and what exactly it’s looking at, well it’s almost like eating that mystery item off the, you know, the grocery store shelf.

Some use cases for AI can feel really, really creepy, and I think that’s what some candidates are reacting to. Yeah, if it — there’s definitely AI that can read your facial expressions, look at your pupil dilation, how fast you’re speaking, where your eyes are looking, all of that, I think a lot of us inherently get a little bit of the heebie-jeebies. It’s kind of creepy.

There’s other AI use cases that are more about augmenting a recruiter instead of replacing a recruiter, and I think ultimately, if somebody knows, hey, HR is gonna use this tool to help prioritize which candidates to spend more time with or what kinds of questions to be asking a candidate, that’s a much better use case that doesn’t make anybody feel creeped out than an AI is gonna read everybody’s resume and automatically produce a shortlist.

GREG: Hey, Adam, can you —

ADAM: It’s just — yeah?

GREG: You’ve done a lot of — you’ve done a lot of writing and speaking around that concept of like different types of AI, right? Like, the black box method versus more transparent AI, can you just kinda talk about that for a second and how maybe people that are on the call today can be — when they’re looking at different types of AI technologies that may bring into — maybe consider bringing into the organization that they can think about that and in and around those different methods.

ADAM: Sure. So, AI is essentially statistics on steroids, that’s really what it’s doing. There’s two main approaches to building an AI model, a prediction model, one of them is black box where you basically throw in all the data they possibly can to try to predict something. In a black box method — and by the way, black box are the majority of the use cases that we see out in the market today. You can’t explain how it works. So, it goes back to that grocery store analogy. You have no idea how those ingredients are stirred up and that’s where a lot of bias can creep in, and that’s where people get freaked out.

So if, for example, we took that facial recognition concept and it was used in a black box way, we wouldn’t know or be able to show, for example, if somebody who was a burn victim or had a stroke or has a scar, are they being impacted because they can’t smile or have facial gestures the same way that other people can? That’s a — so that’s really I think something to be really conscious of if you’re gonna make a decision to use a black box tool, and those are types of questions that you really need to be asking, how can bias be creeping into this?

Whereas with black — glass box approach or it’s in the AI lingo, everybody calls it explainable AI, you are able to see exactly how that model is working, what is being used to predict. Possibly cutting out things that are popping up is bias, and you know that they’re popping up because you can see it, you can visually see it. So, we’re doing some early things with natural language processing here at Outmatch and some of the things that we’d be able to see are, here are the types of words that when somebody uses them in a video interview are predictive. Well, if something pops up in that prediction model that we don’t like, we can cut it out and we’ll actually be able to see it with our eyes.

IMO: Yeah, you hit the nail on the head there, Adam. Right. I think solutions are the future as providers like us build these things. We really need to think about how do we break things down to smaller components so that the user, you know, in our context it is HR or talent acquisition users can actually understand what’s happening, right? Let’s use the predictive models, let’s use the automation on the lower-level pieces, present those recommendations at the lower level, and then the decision can be made by the person that has that information at their fingertips, right? So, and, you know, the way we’ve been seeing it and the way we believe the future will be is how do you bring the information that everyone needs, make it clear, and put it in their fingertips, to then make the final decision there. So I think that’s critical when it comes to organizations thinking about using or adopting AI within technology to help.

The other thing that I think is just important to think about and, again, this is why we’re seeing some pushback, the AI revolution or machine learning revolution has felt almost like an arms race. You know, you hear organizations or even leaders saying, “What are we doing in AI?” You know, “What’s our AI strategy?” And I think that that can be very challenging especially when it filters down to different groups where the focus is so much on AI as opposed to the outcome you’re trying to achieve and then how potentially machine learning, natural language processing, robotic process automation is helping to achieve those outcomes.

So if you in your role are getting pressure from leadership to be more innovative, to adopt artificial intelligence, the first thing I really think about is what outcome am I trying to achieve and then is there a way that the solutions were using leverage machine learning to help us achieve those in a better way or in a faster way or in a more consistent way. Those are some suggestions I would give for any of you who are listening today that are having to do with this on the job.

ADAM: I just think a good — a good rule of thumb is, can that solution — could you be able to sit down with a candidate and explain to them how a decision was made? If the answer is no, probably not a great solution.

GREG: Or if your answer is, well because the technology didn’t think you’re a good candidate, that’s a really bad answer.

ADAM: That’s a bad answer.

BRIANA: Yeah. We have several resources actually on how you can — some things you can do to vet technology that uses AI, so I’ll share that out after the webinar. And if anybody on the call has questions even after we break today, please feel free to email me and I can help answer a question or I can get you in touch with any of our panelists if you wanna speak more with them.

I wanted to quickly show. At Outmatch, we developed some ethical AI principles, and this will be in the deck as well in your follow-up materials and you can also use this as like five steps to using AI ethically and responsibly. So, these are our principles, but it’s also a good way to kind of help check the box when you’re looking at new technology, so be sure to look at that after the webinar.

And before we wrap up today, I just wanted to go around the panel and have each of you give maybe a 30-second recap or maybe the top takeaway that people on the call should start doing today as we approach 2020. Greg, let’s start with you.

GREG: Constant learning. You’ve got to be thinking about learning on a micro level and it’s got to be something — if you’re learning, if the way that you’re thinking about learning is, hey, we’ve got this LMS system that people can access and it’s got tons and tons of tons of content, you got to be doing more than that. And it’s really — it’s not about having the right technology in place to do that, it’s about facilitating that constant — that constant learning around those enduring skills. I think that’s the biggest takeaway, you know, just in listening, not only participating, but just listening today, I think that’s one I think is something that we can put in place immediately within the organization.

BRIANA: Yeah, thank you, Greg.

Imo, what would you say is the top takeaway or the number one thing that listeners can start doing today?

IMO: Yeah. So, since Greg stole mine, I’ll have to recommend something else, so I think, again, Greg has already said that, I won’t say too much longer, but that continuous learning is really important. I think that’s critical. I think the second thing I’ll just come up with this, just think about outcomes or when it comes to any of these initiatives or this AI whether it’s how am I gonna help with enduring skills, what outcomes am I trying to or are we trying to achieve, and how do we create experiments — experiments to test out whether those outcomes can be achieved with something and be comfortable with iterating. You know, sometimes you can come up with why — if you’re rebuilding your onboarding process, why not come up with two or three potential onboarding processes and test those out with different groups and see what works, iterate. So that’s what I’ll give, iterate, test outcomes, experimentation. That’s about it. Thank you.

BRIAN: I love that. Thank you, Imo.

Adam, over to you, your top takeaway.

ADAM: Sure. I would just say huge change is coming. It’s gonna be a complete new industrial revolution Jury’s out on when that’s gonna hit, but it’s coming soon. I agree with Greg, focus on the enduring skills, empathy, communication, innovativeness, and don’t believe that AI will be a panacea for all of your candidate recruitment needs, and definitely don’t —