Effective teamwork and collaboration are critical to the success of modern business. However, are recruiting functions using the right approaches to build great teams? How do great teams work together and is there a role for technology in their recruitment and development?
To help me answer these questions, my guest this week is Alistair Shepherd from Saberr. Alistair has a considerable amount of experience in understanding team dynamics and consequently has some great insights to share.
In the interview we discuss:
• The increasingly collaborative nature of work
• Why recruiting isn’t geared up to build great teams.
• The importance of shared values and levering diversity
• The art and science or recruiting and management
• Using consistent platforms throughout the employee lifecycle
• How humans and AI can work together
• The potential power of predictive people analytics
Alistair also shares his thoughts on team-based performance management and tells us what is on his radar for the future.
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Transcript:
Matt Alder [00:00:00]:
Support for this podcast comes from the HR Technology Conference. HR Tech has been the industry leading independent event for more than 20 years and it’s the place to be 9-11-13th to gain the innovative strategies needed to drive business success today while preparing for tomorrow. This year’s agenda includes sessions focusing on innovative ideas in recruitment, marketing, using technology to remove unconscious bias, debunking myths around talent acquisition trends, and much, much more. At the Expo, you’ll get to see the first hand offerings of more than 400 vendors, including many in the recruitment space. To find out more, go to www.hrtechnologyconference.com and you can use the discount code ALDER300. That’s a L D E R the number 300 to get an extra $300 off your ticket price.
Matt Alder [00:01:17]:
Hi everyone, this is Matt Alder. Welcome. Episode 140 of the Recruiting Future podcast. Effective teamwork and collaboration is critical to the success of modern business. But are recruiting functions using the right approach to build great teams? How do great teams work together and is there a role for technology in their recruitment and development? To help answer these questions, my guest this week is Alastair shepherd from Saberr. Alistair has a huge amount of experience in understanding team dynamics and has some great insights to share.
Matt Alder [00:01:55]:
Hi Alistair and welcome to the podcast.
Alastair Shepherd [00:01:57]:
Thanks Matt.
Matt Alder [00:01:58]:
Brilliant to have you on the show. Could you introduce yourself and tell everyone what you do?
Alastair Shepherd [00:02:03]:
Yeah. So I’m the founder of Saberr. We’re a team development and technology company. We build software to design and coach teams so that they reach the top of their game.
Matt Alder [00:02:15]:
And could you sort of give us a bit of background as to sort of you came to set up that company and what your vision for it is?
Alastair Shepherd [00:02:23]:
Yeah. So the company has been around for a few years. I think it’s about five years old now. And my, my background is not the traditional route into hr. My background is as an aerospace engineer and I spent a long time designing systems and engineering systems before becoming increasingly interested in human systems. And people often say, you know, it’s not clear the parallels between engineering and hr and I actually think there’s quite some quite good parallels in engineering. Your job is to understand a system well enough to the point where you can design it to be better. And there is no more interesting system than a human system, particularly human systems that do work, meaningful work that makes, you know, lives of people better, be that medical teams or be that technology, teams creating tools for the future. And so what I wanted to do was to say, well, can we apply some of the engineering mindset to make human systems work a little bit better? And that’s been the vision and the mission of Saberr ever since is very much how do you get teams of people to perform extremely well together all of the time? And how can you understand the levers that drive performance within teams? The goal for Saberr, I guess, or the vision for Saberr, is really to continue that theme. How can we build the very best technology platforms that are going to help teams perform at their top of the game? Increasingly, that means using artificial intelligence and using new technologies to strike conversations up between people that have lasting impact on the way that they do things.
Matt Alder [00:04:12]:
Now, I’m really interested to explore a little bit later on this kind of the relationship there between technology and artificial intelligence and people, because I think that’s a fascinating topic. But just to, I suppose, back up a bit before we do that. What’s your view on the sort of the current state of recruitment? Because you sort of, you know, obviously, big focus on. Big focus on teams and collaboration. Do you think that the way recruiting works at the moment is conducive to, you know, to sort of producing great teams that can work together?
Alastair Shepherd [00:04:48]:
I don’t think it’s. I think the way recruitment gets done almost out of necessity isn’t. Isn’t to build great teams. It’s often to fill particular roles. And so it’s taking a more individual slant on, you know, recruiting people. How do we get the best individuals into the business? And there’s real merit in that, you know, getting people with excellent skill set who you think could be transformative to the business or, you know, just fulfill a really important role to a very high standard. That’s a really worthy goal. But I think we could do a lot more in terms of thinking about how performance happens within organizations. And work these days in the modern workplace is increasingly collaborative. I often share a really great sort of statistic about how many people have shared the Nobel Prize since its inception. So in every category, and I think there’s about six or seven categories, the number of people who have shared the Nobel Prize each year is increasing. So in the beginning it was won by one person. In recent years, it’s being increasingly shared by two or more people, sometimes three or four people have been sharing the prize. And I think that’s indicative of the challenges that we try to solve today. The hardest problems of today are not only more easily solved by collaboration, but actually require collaboration in order to be solved. So when we think about that in a work context, often the people that we are hiring into the business aren’t going to be working in isolation, they’re going to be working collaboratively in order to get things done. And we all know that brilliant people can perform a lot better or worse when you put them with other brilliant people. And there’s famous examples in history of great partnerships going down the pattern. And we have all sorts of cliches like a team of B players can beat, can beat a group of A players, that sort of thing. So our interest is really how can you make recruitment more team centric and less individual centric?
Matt Alder [00:07:07]:
And I think that’s very interesting because one of the, the arguments that seems to have sort of raged over the last 10 years is this kind of, this whole kind of art versus science in recruitment and I suppose in management and leadership as well, that you know, that on the one side of the, of the fence you have, you know, technology and analytics and, you know, predictive analytics and artificial intelligence and, and all this kind of stuff. And then on the other side you have, you know, this view that actually, you know, human to humans and you know, a good recruiter is a good recruiter because they have, you know, this, this kind of human skill and experience and you can’t replace that with, you can’t replace that with, with, with sc. But obviously it’s kind of causing a problem when we’re sort of thinking about how you sort of build and manage successful teams. Where does sort of technology and data fit into this? And how do you kind of sort of square that argument between art and science?
Alastair Shepherd [00:08:16]:
I mean, I think the answer is it’s both art and science. It’s neither one nor the other. Data should be a very useful tool, but it isn’t an end in itself. And ultimately what we’re trying to do is use data to help human beings work better with each other. So if you totally remove the human from that process, then you’re just left with machines, which is obviously not what we’re looking for. We’re trying to get human beings to work better with each other, but there’s very sort of crucial things that you can do with data that would allow you to do things that you otherwise wouldn’t be able to do as a human being. For example, it is too time consuming to get the views of everybody that a potential hire might have to work with. But you can use data and technology to make that process a lot easier. So you can Profile the people that you’re going to, that you’re thinking about interviewing. You can profile the people that they are likely to work with and you can use the data from those two surveys to get a fit score, for example, between potential candidates and the team that they’re going to have to work with. Now that isn’t the only data point that you would use in the recruitment process, but it would become a very useful data point to say, okay, we’ve looked at their cv, we’ve looked at their skills, we’ve interviewed them and we’ve also considered how well they’re going to fit with the team that they’re working with. So it’s about adding together all of these different data points and then making a decision based upon a range of data points rather than trying to automate the system too much.
Matt Alder [00:10:05]:
And how, from your experience, how have you seen that working in practice? How does it work practically? And what kind of results and value are people getting from that sort of data technology driven approach?
Alastair Shepherd [00:10:23]:
I mean, the biggest thing it gives people is just a sense of confidence that they’re making the right decision. Ultimately it’s very useful to leave the decision down to a human being rather than leaving it in the hands of a robot. And in Europe at least, there’s new regulation that says gdpr, says that individuals must have the ability to question an algorithm and repeal against any algorithm made decision. But it’s very useful to be able to say, okay, well these are the data points that we used to make this decision and this is what it says. And if you’re building fair algorithms that are genuinely looking at, you know, the right metrics, then we shouldn’t be scared about, you know, using them to give us confidence that we’re making the right decision. So when we’ve worked with, with particular clients who in the past might not have been able to use culture fit assessments, they’ve been able to, you know, ask questions of their candidates using technology, ask questions of their existing employees using technology, and then use our algorithms to, to get a fit score between the candidate and the potential team.
Matt Alder [00:11:38]:
I mean, that’s, you know, that’s kind of really interesting, really interesting stuff. And I suppose, you know, without asking you for the precise details about how your algorithm, how your algorithm works, you know, what’s kind of going into that fit score? What’s the thinking, you know, what’s the kind of, the thinking behind it? What’s it looking for?
Alastair Shepherd [00:12:00]:
Yeah, it’s looking for really human things. We’re really not trying to reinvent psychology. We’re not trying to reinvent teamwork. It’s as old as the hills. And when you do try to reinvent it, you either end up back at what everybody already knows, the conventional wisdom, or you’re wrong, generally speaking. So the things that we look for are things that have. That we all know to be true already, that diverse teams, teams that have got a diverse perspective on how to solve particular problems generally are more capable at solving these problems. But then also, if you have diverse values within a team, any other diversity can be destructive rather than constructive. So essentially, what we end up looking for within teams is people who can bring a broad range of perspectives to the team, but are likely to be able to see eye to eye and have very frank, meaningful discussions without it descending into sort of destructive conflict or conversations. So we look for people who share values. And values are sort of these deep intrinsic motivators that help us decide what is right. For example, I might be pro risk trying new things, and you might be pro security and making sure that things don’t break. Now, those are two very different motivations. And so we are going to find it difficult to see eye to eye about how to solve a particular problem. If you and I both shared the same motivations, we both agree that it’s very important to minimize any chance that this project could go wrong, then we can have a really good debate about the approach that we should take. But the goal is common to both of us. Make sure nothing goes wrong. And so that’s the sort of thing that we end up looking for, is people who can work very effectively together and leverage the diversity within their team rather than see that diversity create unnecessary conflict.
Matt Alder [00:14:18]:
One of the things that I find frustrating about recruitment and HR technology is that, is that it kind of very, very much operates in, in silos. So you get great technology for, for recruitment. And then as someone becomes an employee and moves into a company, you know, they’re dealing with different parts of the, the HR setup and different technologies and, you know, perhaps, you know, lo that transition. Now, I know that you guys, you know, work on the recruiting side, but you also, you know, you also work on the kind of the team, the team management side of things as well. What kind of advantages have you seen from being able to, you know, use this approach throughout the kind of employee life cycle rather than just sticking with the recruitment part?
Alastair Shepherd [00:15:13]:
Yeah, it’s actually the sort of team development is really where our focus is as a company. So getting the right people into the business in the first place is an important step. It sets a right foundation. But we all know that teams need continual development. They need continual training. This is something that applies to all types of teams, be it sports teams. Sports teams are a great example of people who have dedicated coaches to help that team reach the top of their game. And the same is true of workplace teams. But generally speaking, only the senior most teams within the business receive dedicated support or coaching about how they can work better as an individual or as a collective. And what we think technology could provide is a way to scale the learning, development, training, and coaching aspects that are currently only reserved for senior teams and make them available to everybody within the organization. And that, for me, is the exciting promise of technology. It’s not that you could do something radically different. It’s just that you could make things, you know, high quality training available to more people.
Matt Alder [00:16:31]:
So what are the key learnings that you’ve taken from that? How do humans and artificial intelligence and technology, how do they work well together? What are your sort of key findings?
Alastair Shepherd [00:16:44]:
Yes, it’s a good question. So we’ve got a product called Coachbot, which is a digital coach for teams. And its job is to see if it can help teams improve the way that they work with each other. So it sounds like an easy enough goal, but it becomes quite a difficult challenge when you try to get technology to do that process on its own. And one of the things that we learned is that human beings really don’t like to be judged. And so any performance management system or coaching system that grades people tends to see disengagement. For example, if we’ve got a digital coach, which is trying to evaluate how good we are at setting and sticking to our goals, if we grade the team and say, hey, you guys are a 4 out of 10 in terms of goal setting, that’s quite a demotivating statement. And it is demotivating regardless of where you sit on that spectrum. So if you’re a 10 out of 10 across the board, you’re good at goal setting, you’re good at communication, you’re good at decision making, and you’re good at defining and sticking to norms of behavior within your team. You’ve got well defined roles and responsibilities. Let’s say you’re nine out of ten across the board. What you really want to know as a team is, okay, so we’re a good team, but what can we do to be better? Conversely, if you’re a 2 out of 10 across the board, you know you’re one of the worst teams in the business. You don’t need to be told that you’re the worst team in the business. What you want to know is, okay, what’s the one thing that we can do to be better? And so one of the lessons that we learned early on in the development of CoachBody is when you’re using technology to coach and develop teams, it’s extremely beneficial to simply phrase it in a development setting. So rather than saying, hey, you guys are terrible at goal setting, we could say, teams like yours typically find it useful to re evaluate their goals fairly regularly. Tell me, how do you feel that you’re doing against achieving your goals? And then we can help teams have a conversation around that. So the way it typically works is we gather little bits of information from people during the week, we send them an email, ask them a couple of questions, and then we use the data from all of those questions to figure out, okay, what’s the most important thing that this team should be talking about? What’s the elephant in the room that this team all know on an individual level but haven’t collectively spoken about? We can use technology to gather that information. Then we can present it back to them in their next team meeting to say, hey, it seems like it would be a great time now to reevaluate where you are against your goals. And here’s a framework for doing that, and you can have a discussion about that in your next team meeting. Then the other key thing that technology can do is check in with you to help make sure that any actions that you set are being adhered to. It’s that stickability piece. One of the things we spoke to coaches about when we were designing this in the beginning was what is the, you know, the thing that human coaches struggle with the most? And often it is when they leave, they’ve delivered a great coaching session, the team arena really, really fired up. And then they go away, the coach goes away, and the team goes back to work. And then work happens and they forget all of this great stuff that they were taught in their coaching session. And so technology can keep that coaching session alive. And it can say, hey, we set some goals last week. Just want to check in. How do you feel your progress is towards those goals? Just those simple reminders can really make behavior change last.
Matt Alder [00:20:24]:
There’s a huge amount of talk in HR circles at the moment about the power and the potential of predictive people analytics. What’s your view on that? I mean, obviously looking for a company that’s collecting a huge amount of data on people and performance and values and all that kind of stuff. Can that data accurately predict the future and help people make decisions based on what might happen?
Alastair Shepherd [00:20:57]:
It absolutely can. So our profiling product base can, with a reasonable degree of accuracy, predict the performance of a team simply based upon cultural fit. So if you’re thinking about hiring somebody, the base scores that you get can predict the performance of that employee. Now, the question is not is the prediction accurate, but is the prediction useful? And often human beings don’t like to feel that they’re not in control of situations. So it’s about using the intelligence, it’s about using the predictions in a way that is going to be beneficial for the people who have to make decisions off the back of that data. So if you predict that this team is not going to perform so well, it is about phrasing that prediction in a way that gives them control and agency over doing something about it, rather than just judging them and saying, hey, looks like you guys aren’t going to do so well. We’re going to report that to your manager. That’s a very disempowering use of predictive analytics. So, and this was articulated, I think, really clearly in a sort of statement that I heard at a conference that was actually called the Art and Science of People Analytics. And it was a very senior member from the automotive industry on the panel, and he said, if you show fair data to fair people, they will make fair decisions. And I think that’s true if you’re designing an engine, you know, make the exhaust nozzle a little bit bigger rather than a little bit smaller, and you’ll get better performance. But when you show fair data to fair people about people, they’ll make emotional decisions. And this is the thing that the analytics community, I think, will struggle with. As our predictions get better and better, it is not going to be simply good enough to be right. It is going to be more and more important to be useful.
Matt Alder [00:23:02]:
So, final question. There’s obviously a huge amount of change going on in the people space at the moment. What’s on your radar for the next 18 months? What do you think the biggest shifts or biggest changes are that we’re going to see in the short to medium term?
Alastair Shepherd [00:23:22]:
Well, the shift that we are really trying to promote and actually are really pleased to see is starting to happen is a shift towards team based performance management. So companies are realizing that the performance in their organizations is being driven by the unit of the team rather than individuals. And they’re starting to say, okay, how can we start to build structures that would leverage this how can we do team based performance management? How can we do team based reward and recognition? And that is something that we’re really excited about seeing more and more of because we think it will make a tangible difference to organizations and we think technology, like the technology that we’re building at Saberr, is something that can really promote that.
Matt Alder [00:24:11]:
Alistair, thank you very much for talking to me.
Alastair Shepherd [00:24:13]:
Thank you very much, Matt.
Matt Alder [00:24:15]:
My thanks to Alistair Shepherd. You can subscribe to this podcast in itunes or via your podcasting app of choice. The show also has its own dedicated app, which you can find by searching for Recruiting Future in your app store. If you’re a Spotify user, you can also find the show there. You can find all the past episodes@www.rfpodcast.com on that site. You can also subscribe to the mailing list and find out more about working with me. Thanks very much for listening. I’ll be back next week and I hope you’ll join me.
