Episode Notes
Episode Notes
Are you or your team clocking long hours at work? Or often twiddling your thumbs? Turns out Goldilocks was right: the balance needs to be just right. In this episode, Professor Andrew Neal discusses how bosses effectively (and ineffectively) manage workloads and what the risks are when they get it wrong.
[Start of recorded material]
Female: When I first started the job, she gave me a whole extra fulltime job on top of the fulltime jobs that I had already been appointed to do. So, there had been no mention of this extra job anywhere in the ad, during the recruitment process or at the interview. I was just expected to do it once I started.
Male: Over my time working for this bad boss, my workload doubled, but he refused to recognize it.
Female2: I had this boss once. He said to me on 2 o’clock on a Thursday afternoon we need six training courses written and completed by the following Tuesday. So, I thought about it and I said [01:00], “Okay, I reckon I can probably do three or four. Which are the most critical?” And he said, “No, they’re all equally critical. They’re all equally important. Get them all done.”
And then Monday afternoon rolls around, of course, after me working frantically, and the boss says to me, “These courses aren’t needed anymore. Why are you working on them?”
Ginger: It is just not an effective way to manage an organisation. In fact, it’s not even a cost-effective way to do it because the more a person has on their plate, the less they are able to focus, plan and strategize and it’s also a massive safety issue.
Professor Andrew Neal: When people experience overload, they’ve got too much to do that exceeds their capacity to do it, you get poor quality work, you have an increased likelihood of accidents and incidents, and errors. People experience elevated levels of stress, fatigue, and if people are exposed to chronically elevated levels of workload, ultimately those effects [02:00] accumulate over time and lead to poorer physical and mental health.
Ginger: That’s Andrew Neal by the way. He’s a psychology professor at the University of Queensland and also a Fellow of the Academy of the Social Sciences in Australia.
On the flipside, if a person’s underworked, that can also be just as unsafe.
Professor Andrew: Underload has effects as well. If you’re working in a job where for prolonged periods of time, you’re sort of sitting there with nothing to do, nothing much in the way of external stimulation – for some of us that sounds like, bliss, but it’s not – people have difficulty maintaining vigilance and attention to the task.
In air traffic control, for example, we think of air traffic control as a high workload environment, but often there are long periods of low workload where there’s nothing going on. So, late at night, you’re sitting in an air traffic control centre and actually the incident rates are higher during underload periods than overload periods.
Ginger: I’m Ginger Gorman and on Seriously Social today, we’re looking at how to [03:00] run an organisation a little bit like Goldilocks and the Three Bears. So, not too little, not too much. When it comes to staffing, getting it just right is much harder than you might think.
Professor Andrew: I think actually most people have good intentions. They don’t deliberately set out to micromanage or overwork people. Most managers, actually, I think do value employee wellbeing. They don’t want to overwork their employees, but often, they’re under production pressures themselves. So, it’s really a balancing act.
There are really kind of two problems that people face in trying to make those judgments. So, one is the planning fallacy. We always underestimate how long it’s going to take to do things. I’m really bad at that [04:00]. And the other is unplanned events or unexpected problems.
Stuff crops up always. There’s always stuff that’s unexpected, unplanned that gets in the way and means that your stuff takes longer to do than you’d originally planned. So, that makes it really difficult to make an accurate assessment of the amount of work somebody can actually do within a timeframe.
Ginger: Andrew, I acted manager at an ABC station for a period of time and what actually shocked me was the amount of time that was also taken up with people’s personal problems. So, people having marriage problems, or people taking time off for pregnancy or other illness or caring responsibilities, and on and on it goes. And that obviously adds another layer on top of this as well. It’s not just predicting the workload and unexpected work events, but it was actually just masses and masses of unexpected personal baggage that was coming into the office every day.
Professor Andrew: Yeah. That’s really hard to plan. You know, if you’re trying to figure out how [05:00] we’re going to get all of this work done in the time available, it’s really hard to anticipate all of that kind of stuff.
Ginger: Do you think that managers actually have the tools that they need to be good bosses then?
Professor Andrew: In general, no. I don’t think so. In some industries, managers have planning tools that will help them do this kind of thing, so they can figure out how many people are needed for a job, but they don’t account for a person’s subjective perception of workload, their psychological reaction to workload. They feel like where you’re at your limit or working beyond your limit, that kind of stuff’s not taken into account in those sort of very engineering type tools.
In most industries, managers don’t have access to those types of tools anyway. So, they’re basically just doing that in their head and they’ve got to make a subjective judgment on the fly of how much work is reasonable to give to somebody. And to do that well, that’s a complex judgment [06:00] with a whole lot of things you need to be taking into account and some people will do a better job than others.
Joel: My rules for being a good boss.
Ginger: This is my mate, Joel, and these days, he runs a team of content producers. But much earlier in his career, he worked in a totally different field and he actually had one of these bosses we were talking about earlier, a dude who would bully, berate and belittle him. So, now that Joel’s a boss himself, he has this really long list of what not to do and he also has some pretty firm rules that he makes himself follow.
Joel: First of all, I’m organised. The rosters are clear and any special requirements are spelled out way in advance. I know what’s coming and so do my people. I want my staff to feel supported, so I do my best to fill their requests for things like equipment and training. It’s not always in the budget, but I try.
Your staff have to be able to trust your word. And you have to be able to give honest feedback, be it positive or negative. [07:00] So, when people are doing well, tell them. And when people aren’t performing, you do them no favours by pussyfooting around. You’ve got to be absolutely clear about where they’re falling short and what the consequences are. And if they can’t do the job despite your repeated warnings, let them go. The rest of your staff will be really glad you handled it.
Finally, I learned this last lesson from my dad, who was a great boss. I have a jar of chocolates on my desk. Anyone can come and have one. It gives people a reason to pop by and chat and when there’s a tough conversation to be had, there’s nothing like a fun-sized Mars Bar to help people through it.
Ginger: Joel makes it sound easy, right? And I’m sure he’d be the first to say that is not always the case, but going back to Andrew Neal, he’s being trying to address the issue of overload and underload by looking at an industry where we all very much want staff to be on the ball.
Professor Andrew: What we’re doing is trying [08:00] to develop mathematical models to predict workload. Where we’ve done this is in air traffic control. So, what we’ve been trying to do is to predict the amount of traffic that a controller can safely handle within a given period of time.
And the way we do that is by running experiments in which we manipulate, put controllers in a simulator, a fairly realistic simulator and manipulate traffic levels. So, we can ramp them up, ramp them down, etc., and then insert unexpected events, like an aircraft losing an engine or a weather event or something like that. So, everything goes to hell in a handbasket pretty quickly. So, it’s about building a model.
Ginger: It’s making me nervous as someone that’s travelled on a lot of planes in my life because of my dad’s job. It’s making me very nervous thinking about engines failing, but go on.
Professor Andrew: The good news is that air traffic controllers are really good at doing with that pressure. What we’re trying to do is using data to build models [09:00] that can predict how many aircraft the controller can handle under normal routine conditions and then how much of a buffer needs to be provided to allow for those unexpected events so that if everything does go to hell in a handbasket very quickly, if those non-routine events occur, there’s a safety buffer there.
Ginger: Have you actually manage to do that though because I’m just thinking about all these factors you’ve talked about, the stress, the unpredictability, personal lives, unforeseen weather incidents and so forth? So, how can you possibly build a model that could make way for all those things and still give you a usable outcome?
ProfessorAndrew: Yeah. That’s the million-dollar question because the model can only predict the stuff that’s predictable, by definition. So, in the experiments, what we do is we throw in kind of things that subject matter experts regarded as plausible scenarios. So, on a bad day [10:00] at the office, it’s going to look like this, and then see what happens.
Ginger: And so, have you actually then come up with something that you think is workable in air traffic control or in other high-stress work environments?
ProfessorAndrew: Yeah. So, these types of models I think can do a reasonable job at saying, “Okay, under routine situations with about the sort of the workflow that you would normally expect people to have, people’s subjective workload would fall somewhere in a band between X and Y.” And then we can try to quantify how much of a buffer would then need to be allowed for, for examples of the types of non‑routine things, the actual unexpected things that actually happen and weather.
So, what you’re trying to do is to make sure that you’re trying to keep workload in that optimal zone. You’re maximizing the chances of workload staying within a safe boundary.
Ginger: And in an ideal world, would these tools you’re developing then [11:00] be transferable to other workplaces and other kinds of high-stress work environments?
Professor Andrew: Yeah. The general approach I think is broadly applicable. In most industries, most jobs, there’s a certain amount of work people generally have to do and I think that that’s something that is potentially predictable.
Ginger: What does this mean then, Andrew, for bosses managing into the future?
Professor Andrew: If you’ve got models like this, if you’ve got a mathematical model that you could simulate and make predictions ahead of time, that’s got a whole stack of practical uses. You’d say, “How many people do we need to run an operation safely?” So, the staffing problem.
The moment they pluck the numbers out of the air, based on a seat‑of‑the‑pants kind of estimate of how many people do we think we’re going to need, given past experience at running an operation or something like that, you could use these types of models to actually simulate it and say under representative scenarios, “We’re actually understaffed [12:00].” You can at least put some science behind the numbers of how many people do you need to employ to run your operation safely.
And the other thing is you could also use these models potentially in real time. You can say, “Okay, is there a spike out there? Do we need to get more people on the floor or the shop face or whatever, in order to keep workload within reasonable, and safe and healthy bounds?”
Ginger: And I suppose safety is a really key factor isn’t it, because so many workplaces you’re actually putting people’s lives at risk if you don’t get the staffing right.
ProfessorAndrew: Yeah. And so, I think it’s safety for customers, the public, whatever, but it’s also the safety of the workers themselves.
Ginger: Andrew, we’ve talked a lot about managing and bosses, but actually, some of this does fall on workers, doesn’t it? Workers are having to select their priorities, they’re having to manage their cognitive resources, they’re having to regulate their [13:00] own performance. What role do workers play in managing workload as opposed to bosses?
Professor Andrew: Yeah, that’s a good question. The thing that was really striking about the studies we do with air traffic controllers was, I suppose firstly, in general, how good they are at managing workload. They’re trained very rigorously and very effectively to manage high levels of workload. And the second is also, even given that training, there are also quite noticeable differences between controllers in how they do it.
And so, in experiments we ran, we saw differences between what you call like a reactive and a proactive approach to managing workload. Some controllers basically, as traffic ramped up, their approach is to work harder and faster, to get the job done without inconveniencing people by putting aircraft in holding patterns and stuff like that.
Other controllers had a more proactive approach to managing their workload. They’d seek out and get help from controllers in adjacent sectors [14:00] or from their supervisors or something like that. And the controllers that used a more proactive approach to managing workload reported lower levels of workload, going into the future in those experiments, were lower.
Ginger: Isn’t that interesting? So, some of this actually comes down to your own personality despite all these other factors that you’re talking about.
Professor Andrew: So, yeah. I think there are different strategies that people can use. And these are strategies that can be learnt. So, they’re not like kind of innate traits that some people are generally good or bad at this. They’re something that all of us could learn.
Ginger: You’re obviously a professor, so in some way, you manage people under you. I wonder what you’ve learnt through your research that you now apply in your own management of other people.
Professor Andrew: That’s a great question. So, I suppose I’m acutely aware at just how bad I am at making judgments of how long it’s going to take me to do a job. And therefore, [15:00] anybody that’s working for me, I’m aware of, even worse, my judgments are of how long it’s going to take them to it. So, I know that I’m subject to the planning fallacy.
And so, it’s constantly seeking feedback. You’re setting goals for someone, what they might get done in the next week or the next month. And it’s really important to be constantly checking in and assessing how they’re going and being open to revising those goals. I think that listening to people is really important.
Ginger: Listening is important. And thank you for listening to Seriously Social. I’m Ginger Gorman. If you liked this, make sure you check out our website, seriouslysocial.org.au, and if you want more people to know about Seriously Social, give us a five-star review on apple podcasts.
Next time, the changing expectations of men and masculinity.
Catch you soon.
[End of recorded material 15:53]
Useful Links
- A new approach to mental workload measurement in air traffic control Hartel, C. E., Neal, A., Halford, G. S. and Hartel, G. F.
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