When it comes to developments in artificial intelligence and other technologies, the narrative isn’t always positive. But instead of unnecessarily focussing on the negative, why not concentrate on the positive? Like how technology can help us bring the best out of teams for example. Or how it can make us have conversations about matters we otherwise wouldn’t have discussed. I spoke about this and more with Alistair Shepherd, the founder of Saberr. Here’s his expert insight.
NV: Your view on the age-old employee engagement issue:
AS: Getting humans to engage, getting them to work well with each other is a problem that is as old as the hills and the same fundamental reasons haven’t changed. At the heart of most employee engagement issues sits their desire to have a meaningful purpose, their desire to get better at something in order to improve their abilities, and their desire to have the freedom to act autonomously.
At the moment, we see two big changes. On the one hand, we see purpose-led organizations trying to create a purpose that their employees can really get behind. On the other hand, we’ve got the incumbent organizations that are facing quite a challenge as to how to reinvent themselves or how to give themselves a purpose that a new, younger workforce can really connect to. The good thing is that a lot of them are succeeding really well. They are truly transforming the way things get done. Or even transforming their industries.
Another challenge that organizations are facing is how to give autonomy to their people while at the same time keep them accountable. That is the big thing, how do you balance autonomy with accountability.
NV: How can technology be of use?
AS: We think that technology can play a really big role here. Over the last sort of 50 years, the real focus has been either on the individual level or on the organizational level. Particularly in the US, the mantra is very much if you work hard you will be successful. As an individual. Forget everyone else, back yourself. The other focus has been at the organizational level which is all about the company goals. What can we do organizationally, what’s our strategy, what’s our vision, etc.
Increasingly though, all of the productivity is coming from teams, so you have to collaborate in order to solve these complex problems. You have to work in a small team in order to get anything done and the productivity and efficiency of work is really actually driven by the team now. So if you can start to focus on performance, measures, and support to teams – not individuals or organizations – then I think we’ll see a big change.
Technology such as our Coachbot program can help teams learn how to work better with each other. It can assist them in setting and tracking their own goals, their own progress, their own feedback cycles. Rather than it being a top-down performance management system or a central engagement survey where HR is quizzing you, it’s kept within the team.
As such, the technology helps teams identify and solve their own problems and I think that is a great way to give teams the autonomy they desire and keep them accountable at the same time. Because being accountable to your own goals is actually incredibly motivating. If you feel ‘I’m the one that set this goal, it’s mine,’ and you hold yourself accountable or your (close) colleagues hold you accountable to it, the sense of achievement you get and the sense of motivation you get when you reach that goal is extremely high.
I think that is a big shift we’ll see and I think technology like ours is going to be the driving force behind this shift, pushing it down to the local team levels rather than leaving it at the top level of the organization.
NV: How exactly does this work?
AS: The whole purpose of the technology is to get teams talking about the issues within their team. To have conversations about things that otherwise they wouldn’t be having conversations about.
The technology focuses on 6 key areas of teamwork.
So, the general framework that we’re working towards is that all teams need to have particular things. They need to have clear goals that are shared amongst the team, they need to have a motivating purpose, they need to collectively decide on their behavioral norms to which they are all going to agree to, etc.
Our job is to figure out how we get teams to have all that. So, practically what Coachbot does is it will send you an email during the week and it will say ‘Hey Neelie, you set a couple of goals last week and I just want to get from your perspective, do you think you are on target to hit these goals and what are the activities you think you should be starting/stopping or continuing in order to help you reach that target?’ And then it might ask you a different type of question like ‘Hey, you guys collectively agreed that it was really important to keep meetings on schedule, is that working? Do you feel like you’re achieving that norm or that everyone else in the team is achieving that norm?’
It will do this with every employee in the team and then it will generate a report based on the discussions with everybody. In your next team meeting, it will present that information and it will say ‘Ok, based on the conversations I’ve had with each of you this week, these are the most important things you guys should be chatting about.’
Let’s say it identifies that we are really behind on hitting our goals.
Instead of saying ‘You guys are terrible at hitting your goals, it’s looking bad,’ it will say, ‘Typically teams like yours or teams in your context will find it useful to review the activities that you are doing in order to reach your goals. Do you think that will be a useful thing for you guys to do?’
The technology is trying to use the intelligence of the people in the room, it’s not trying to solve our problems for us. It’s trying to get us to have the conversation because that’s what’s going to solve the issue.
Based on the answers of each team member,
the technology shows where the team is doing well and what areas to work on.
NV: Conversations you wouldn’t have had otherwise…
AS: Exactly. Once we’ve had those conversations, the final piece – and this is one of the most important pieces – is that the software will check in with us to say ‘Hey guys, you had a conversation in your last meeting, do you think anything has changed?’ It will ask a couple of follow-up questions to keep us accountable for what we were chatting about. And then it will repeat the cycle.
Some teams have meetings every week, others every quarter, we just use all of the information that we’ve gathered between your meetings. Whether that is a quarter’s worth of information or a week’s worth of information.
NV: How do you use AI?
AS: Where we use AI is to better understand what people are saying. For example, if we want people to discuss what they think their priorities are. If we hear from me, you and one other colleague and two of our responses are the same or very similar and one of them is different, we will group them together so that we end up saying ‘Ok, these three people think this particular thing, have a conversation about that.’
You can use natural language processing to understand the sense of what people are saying so you can start to group it and make the conversations flow more naturally. Rather than having to go point by point and realizing that you’re discussing one theme here, then you skip to another theme and then you’re back to the previous theme. If you can start to group the themes together you can make the conversation far more efficient. That’s what we’re trying to do with the AI.
And then there is a learning part to it, which is to say we start to learn what types of things typically happen in what types of teams. In a remote team, we’re starting to see a pattern of the issues that typically come up in remote teams versus the issues we see that come up in co-located teams. Or the issues that crop up in cross-functional teams versus functional teams.
This means that we can start to use that intelligence to probe for those particular things. We can say we typically find that cross-functional teams have more difficulty in setting goals but in functional teams, they find it harder to define roles and responsibilities. We can start to use this information to probe for the things that we think are going to be a problem.
AI can be used to better understand
what people are saying.
NV: What are the main results organizations experience?
AS: There are 3 levels of success our client see. The first level is all about employee engagement. Employees are happier and they feel more in control of what they’re doing. They feel more aligned with each other, they feel like they better understand each other, and they feel more motivated. There is a lot of employee engagement stuff that you see an immediate benefit in. You suddenly get clarity about what’s going on and there is no longer this big elephant int he room.
That’s the first thing that we hear from organizations: we are working better as a team, the air has been cleared. And we can see those results after a very short period of time.
The next series of results is about operational outcomes. As a result of the team working more effectively and the air being cleared, organizations are now hitting their targets better or they are seeing this metric change. It typically takes longer before you see these results. It might not be after six months that you start to see an impact on operational outcomes. In healthcare that might be about reducing staff absenteeism rates. It might be about reducing the number of serious incidents that happen. In commercial organizations, it might be about more success in hitting their sort of financial targets.
The third one is return on investment. As a consequence of coaching your employees, we are now seeing that there has been a significant financial return on investment based on those previous two combined. We got a happier and more engaged workforce that is having an impact on our operational outcomes and that is hitting on our bottom line by this and that. So the range of outcomes is quite broad, varying from things like staff turnover is lower through to more operational stuff like we’re on budget, we’re ahead of our budget, or we’ve delivered this product on time, that kind of stuff.
NV: What does the future hold?
AS: There are two ways we want to take this. We have this unbelievably granular understanding of what is happening at team levels that is going to blow engagement surveys out of the water. We’re going to build to give organizations a really clear understanding, not just of what’s going on in the organization but also on what they’re doing – and what’s working – so we can start to help the organization with more strategic workforce planning decisions. That’s direction number 1.
Direction number 2 is we want to get down to the individual level. We want to say ‘Neelie, we know a lot about you. We know how you’ve been interacting, we know what makes you tick. Let us coach you as an individual.’ You can then have your personal coach not just to take into work every day, but perhaps between jobs. So we can say ‘Hey Neelie the situation you are talking about, remember two years ago in that other company, it’s very similar to that, remember how you dealt with it?’
But really it’s about learning about helping people learn how to work with each other and helping people learn how to get the most out of each other when the background narrative is that AI is going to replace everything. It is never going to replace the need or the skills that we need to have in order to work better with each other and understand each other.
We’re always looking for interesting HR technology stories to feature on Digital HR Tech. If you know – or are – someone who’d like to share their insights with us, send an email to firstname.lastname@example.org.
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