This Week on Great Minds: People & Culture
Ren Akinci is joined by Professor Joseph Fuller, a leading expert on workforce strategy from Harvard Business School. Together, they dive into why so many companies still treat talent like a spot-market transaction, how employers can reframe community colleges as strategic partners, and what it will take to move from degree-based to skills-based hiring. It’s a timely conversation for any leader rethinking how to build a more resilient and future-ready workforce.
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Hi, everybody. Welcome to season two of Great Minds People and Culture podcast. I’m your host, Ren Akinci, Chief People Officer of Advertising Week and Emerald. Today’s guest is Joseph Fuller. He’s a professor of management practice at Harvard Business School, where he leads its flagship research initiative on the future of work. His work spans a wide range of critical topics, including the impact of artificial intelligence on employment, the rise of the gig economy, economic mobility, the care economy, and the persistent skills gap. Joe is the co-host of Managing the Future of Work, a podcast that has garnered nearly three million downloads and is widely recognized as a leading platform on the subject. His research and insights have been featured in major global media outlets across print, television, and radio. Before joining the Harvard faculty, Professor Fuller was a founder, the first employee, and a long-serving CEO of the global consultancy Monitor Group, now Monitor Deloitte.
Hi, Joe. So nice to have you here.
Ren, I’m delighted to join you and your audience. Thank you so much. I want to jump right into some of your research, The Partnership Imperative Community Colleges Employers and America’s Chronic Skills Gap, where you highlight a major disconnect between community colleges and employers. What are the biggest leadership failures on both sides that have contributed to the skills gap?
Well, for business, it’s that they treat community colleges like one of their talent suppliers, but very few of them actually are prepared to go beyond just ensuring that whatever job postings they’ve got are accessible to local community college students and career placement people. They don’t invest in helping the community college understand whether or not their curriculum is state-of-the-art. They don’t give any feedback to the community college. They certainly don’t provide, with rare exceptions, compensated work-based learning or internship programs for students. It’s very much, they just treat them as a source of talent and they don’t try to cultivate a relationship in the way that a really good buyer of any important input works with its suppliers to be a better supplier and to get more value from that supplier.
So if a caterpillar has a troubled problem with an engine in one of its trucks, it doesn’t not call up Cummins Engine Company and say, we’ve got this problem, we need to work together to solve it. Or if they’re going to launch a new product line, they don’t forget to advise their key suppliers and get their input on the designs and then show up and say, oops, we forgot to mention that we need all this engineering from you that you haven’t done.
On the school side, there are some excellent schools, but exceptions prove rules. And on the whole, educators and the community college leadership too often is not really that connected to business. They want to be connected to business, but they view that connection as business should hire more of our graduates. And by the way, it’d be great if you became a donor and bought a table at our annual fundraising dinner, as opposed to really saying our job here is to get our graduates in good positions that have a future. And we’re really going to listen to employers, seek them out, try to convince them to give us more feedback, try to get an understanding of our economics a little bit better. So maybe they’ll see where they can help us.
So it’s really baked into the title, Ren. What we really need between the two parties is active partnership. And that just doesn’t exist except outside ofmaybe 50 to 80 large community colleges in the US. And what’s the impact of loss on, like, what is the opportunity loss in your research and your opinion on not cultivating this relationship and not tapping into these graduates that go through the community college curriculum?
Well, there are three big pools:
The first is one to the country. When a business can’t find the employees it needs to execute a strategy, it doesn’t say, oh, shoot, I guess we won’t do that. It finds an alternative. And if that alternative is in Mexico or that alternative is in China or that alternative is in Vietnam, they’ll make the product there or they’ll source the software there. So there really is a societal loss when you’ve got a skills gap.
The second is for the employer. They do end up paying more for the talent they can find, and they often end up having to do something like invest in more capital equipment or more advanced technologies because they can’t find the right talent. Employers make a consistent mistake, and we’re seeing it in the economy right now, which is they always try to hire at the last minute. They never want to have more payroll than they can avoid. So they play it like you play a spot market. I actually call it the spot market for labor. They suddenly dive into the market, having not created a supply chain of talent by having things like a good relationship with community colleges. And then they’re surprised they can’t find anybody. Often they’re hiring at the exact same time as everyone else and looking for the same skills. Cyber would be a good example of that.
The final party, which is heard, are, of course, the lures and the aspiring workers, the community college graduates or students. And for them, it’s particularly dangerous because in the labor market over time, you kind of are what you eat. And by that, I mean, once you’ve done two or three versions of a job and you’ve aged from, let’s say, 20 or 21 or 22, and now you’re 27, 28, and you’ve had three pretty low paying, not very hard to do jobs, it’s not just you haven’t made much money. And by the way, in that period, a lot of life can happen. You can have a child. Maybe you’ve got a parent that now is relying on you for some income or something like that. But the way artificial intelligence, which has been embedded in recruiting systems for years, I’m not talking about brand new gendered AI, but the way it evaluates candidates really looks at your job history and you start getting excluded from consideration for anything that doesn’t look like what you’ve already done. So if you’ve had three jobs in a quick service restaurant, the AI, and you’re applying for an entry level marketing analyst job, the AI looks at you and says, too bad we don’t have any fast food jobs because that’s what you’re good at. But I’m not going to consider you for this because you haven’t done any marketing.
Bizarrely, in a bunch of companies, the entry level positions would say two to four years of experience. It’s interesting that you brought up AI and the fact that it’s been around for much longer than generative AI, which we’re all talking about. What are some limitations of AI as it’s used for applicant tracking systems? Does it not look for certain words? Because for me, someone who’s worked in a quick restaurant or in a server role or even a retail job is actually perfect entry level person because they’ve already done the customer service, the problem solving, the independent thought process. Those are actually really valuable skills that they learn. Why doesn’t AI pick up on that?
Well, AI doesn’t think. It does what it was trained to do. And in applicant tracking systems, as you may know, when you set up your applicant tracking system or when you’re posting a new job, you’re given a lot of opportunities to filter things. And usually there are two choices,one which is include, exclude. So if you have, let’s say, a job, you’ve posted a job for an armored car driver that’s going to go around to banks and stores and pick up cash. They will have a felony conviction field, and you can say, just exclude anybody with a felony conviction. I presume that armored car companies exclude people with felony convictions from becoming armored car guards. They also have rank.
So, well, let’s say I’m hiring for a quick service restaurant worker, a worker at a McDonald’s. I can rank, say, well, if someone has a felony conviction, rank them lower for that. So the AI just does what it’s told.
And in terms of the filtering, very often people are a little bit like an eight-year-old in the run-up to the holidays. They’re looking for, they want a real live stegosaurus and they want a real tank and they want to ride on SpaceX and five other things. People really describe an idealized candidate, not realizing that they may be pruning or pushing down below the threshold they’re ever going to look, someone who really looks great on, let’s say, eight of the 10 characteristics you really count.
The second way that AI is abused in the process is that people either don’t update their job descriptions very often. That’s true for lower-wage jobs. Or they don’t, even when they update it regularly, they don’t take out old stuff. And they don’t want to be choiceful. They don’t say, here are the five things I’ve got to have. If you give me those five, you know, I’m just going to give up, you know, I’ll be happy if I don’t get six, seven, eight.
So the job descriptions are often too long, don’t have the right emphasis, have archaic language. Well, the AI doesn’t know which paragraph you didn’t really mean. So it uses natural language processing and it’s just looking for keyword matches. And so if you’ve got 20 attributes that are in that job characteristic, job description that you don’t care about, it’s reading the people that it’s surveying on things that are extraneous to you.
So the problem with AI is people overly dignified and don’t understand that you have to do the thinking for it. And then it’ll do a great job executing your thinking. But if you haven’t put in the upfront effort, don’t count on it to bail you out.
I love that distinction. Do you think there is room for generative AI to help with these job descriptions if you’re prompting in a way to say, make sure it’s not excluding people, make sure it’s not overqualified for a job that’s entry level? Like how can we best use generative AI to actually help do the work to curb what you’ve just described as being disadvantaged to people who are looking for jobs and who have skills that are very transferable?
Well, Rena, your illustration is really good ones. And I think actually generative AI is going to be a big, big boost to the labor market in helping us avoid what I’m going to call mismatches where either people apply for jobs they’re never going to get or people get hired into jobs that they’re not going to be good at or won’t like or companies hire people that aren’t going to succeed or are going to leave soon.
Companies regularly underestimate just how expensive turnover is. And so if you attract somebody to apply for a job that’s going to hate it, you’re actually inflicting a cost on yourself. Similarly, if you hire somebody that’s more obvious to people that isn’t any good at the job, and then you end up firing them, you have the economic loss of having a not very well-performing employee for a while, and then you have the cost of firing them and the cost of replacing them.
A couple of examples of what generative AI is going to do: You raised the question, how would I know, find me a good candidate going beyond just these simple filters I’ve been relying on. In the not-too-distantIn the future, I’m sure companies that are in the human asset software space will create tools to do things like the following. I’m looking for a new marketing analyst. What are the attributes? I’m asking the AI, what are the attributes of this? Rather than going into the public domain, it will go in automatically into your personnel performance management files.
It will look at the highest rated marketing analysts you’ve ever had while it’s looking at those that were promoted quickly. It’ll limit itself to people who stayed more than some interval of time. So not someone who’s great but left after eight months, but someone who came within the job for two years now is two levels above that, still a high performer. It’ll look for that data.
It will go and look for equivalent data on something like LinkedIn and say, well, in our arch rival, gee, this is what their marketing analysts look like. We’ve seen someone who’s been promoted three times in the same company, started in marketing analysts for deducing what we’re looking at their self description. We’re looking at the job descriptions they’ve been promoted into. We’re inferring what across all those data sets.
It may go into open source large language models. It may go to industry journals or trade magazines or current job postings on live websites. It’ll do all that in about eight seconds, but it’ll be hugely better than relying on the hiring managers, which we call someone who’s going to be the supervisor of being hired or some recruiters judgment, no offense to those people, but a recruiter is not going to spend a week going through the corporate archive to look at hundreds of interviewees.
Now we’re getting some companies, entrepreneurial companies. You know, Adept ID would be an example. You know, a company like Bright Hire. They’re getting pretty sophisticated at not only that type of analysis, but also tying it to how interviewing is done, tying it to social media support for advertising job opportunities, the language you use on your website. If you’ve got one of those things on your website where you click, we’re hiring, click here to contact us, things like that. So it’s already beginning to be visible, but still a long way to go.
I love how you’ve outlined that. And I specifically want to index on the fact that you said if we have it set up correctly, it’ll actually remove the bias more so than a recruiter or a hiring manager, which is true because we’re all humans and we have our faults, unconscious bias being one of them.
When they get to the stage where they go beyond the screening, how should business leaders rethink their hiring and training approaches to help support workers that are maybe coming from either community colleges or from backgrounds that are not strictly corporate developed?
I wrote a paper with some colleagues called Hidden Workers Untapped Talent. And it kind of walks through this cycle of how the AI crowds out a lot of people and those people in no way have any idea why they got excluded. So in it, we raised a number of points about what companies can do:
Recognize this cycle we just discussed and ask themselves, are there pools of talent that have attributes that should match well with what we’re looking for here, but we think we probably have been inadvertently excluding?
I’ll give you an example, which is caregivers. In about half the jobs in the United States, there’s a filter called the continuity of employment filter. And it says if either exclude or rank lower, someone that has a gap on their resume of six months or more.
Now, there are reasons a company might be concerned aboutthat. Maybe that person doesn’t have a lot of get up and go. Maybe it certainly seems that people who’ve worked with them. Oh, maybe it certainly seems that people who have worked with him previously weren’t standing in line to hire him as soon as they heard they were available or anything like that. But I know someone who left to work for us for six months, my wife with our first pregnancy because she was having twins and her doctor wanted her on bed rest. Now, she’s a Phi Beta Kappa from Brown University and an honor graduate of the Harvard Business School. But in 50% of the jobs in the United States, she couldn’t have gotten an interview for an entry-level job at lots of companies just based on that gap.
In fact, I tell people, never leave a gap in your resume. If you’re taking care of a dying parent or a child with an illness or you quit your job, fell off your bike and rehab for six months, literally put in “rehabilitating from bike accident” and the AI isn’t looking for the word rehabilitation, but it doesn’t ding you for the gap on your resume.
So it’s identifying these populations, finding ways to how you’re going to adjust the algorithms in terms of the way you’re searching, create some programs for them. In this survey, it was very interesting, we identified a bunch of hidden worker populations and companies that had programs for one or more hidden worker populations reported the employees in those programs were more productive, more engaged, had a lower turnover and higher promotion rates.
So you have to rethink your processes if you want a different outcome. And if you want an outcome that gives you a broader pool of talent, you have to not say just “I want a broader pool of talent.” You have to say “I’m going to broaden my aperture on what I’m looking for and I’m going to adjust other processes.” A very important one is onboarding, so that this population that’s coming new into my workplace has a reasonable potential to thrive.
I love that you said still put it on your resume because I actually did a podcast that specifically says putting “mother” on a resume because I wholeheartedly believe and I’ve seen this happen with my own friends, even if they’ve taken more than six months, you know, a few years, they start self-doubting themselves about coming into the workplace and they need a little encouragement. And some of the skills that they have developed in managing their household and managing their kids is so transferable as middle manager and even leadership skills.
Absolutely. And I know you’re a big proponent of hiring for skills-based approach. Where do you think we are as a workforce in the US on skills-based hiring? Are there hesitations? And if so, why are there hesitations in putting skills first ahead of degrees?
The vast majority of large employers have psychologically passed that threshold and say we want to be, we want to hire for skills. That’s what we’re actually paying for. And therefore, we don’t want to exclude people with skills merely because they don’t have a degree. And I don’t doubt that the companies that have removed their degree requirements did it with sincerity and all the best intentions. But that’s not nearly enough.
What we see in my research with a frequent co-author of mine, Matt Sigelman, the founder of the Burning Glass Institute, what we found in some research is a very small percentage of the jobs that have been made available by companies removing a degree requirement have actually gone to somebody other than degree holders. It’s a very small percentage, like three and a half.
Why is that? Well, when you remove a degree requirement at corporate level, of course, there’s still plenty of jobs that would require a degree. All that’s been removed is an absolute rule. You can’t hire anybody here unless they have a college degree. So that’spart of it. But a big part of it is a different version of what we’ve been talking about so far, Wren, that if you don’t say, oh, I’m trying to get a different outcome here, I’ve got to revisit my processes and ask what are the associated changes I need to make. Yeah, maybe it is something in the filters at the front end of the applicant tracking system.
But let’s just do a little imaginary exercise here. I’m a supervisor. I need to hire somebody. I’m the hiring manager. The job I had before this was the job I’m now hiring for. I have a college degree. Everybody today hired into that position had a college degree. My boss has a college degree. My peers at the same level of manager as I do all have college degrees. Now the company has removed the degree requirement.
Okay. And we make a really sustained effort to get some non-college degree candidates in the pool. Maybe I, in fact, instructed the AI to find me at least two non-college degree holders. Now I’ve got four or five candidates that I’m talking to. Only one of them doesn’t have a college degree. What am I going to talk to them about in the interview? How do I evaluate a skill when I’m not looking at a transcript or looking at the name of a well-known local university that I know is selective because maybe I hope my kid will go there someday?
How am I going to get comfortable that I know enough about a skill? Are there even any rules? In fact, there are that I have to be scared about legally, that I can ask questions or ask people to demonstrate competencies in a way that ultimately the EOC can object to? What am I going to tell my boss if I hire the non-college degree candidate and they fail? They’re a disaster. And what if that disaster is not just they’re no good and we had to fire them? It’s visible. We have a major problem, a customer service problem, an engineering problem, a financial problem. And I’m not talking about malfeasance, just they accidentally sent a deposit to the wrong account and now we’re having someone didn’t get paid, whatever else.
So when my boss said to me, well, what happened with that person you hired? Well, it turns out they didn’t work out. Well, tell me more about them because we need to learn from this mistake. Well, they didn’t have a college degree and I wasn’t really comfortable. I’m not quite sure they really got how we do things around here. My supervisor is going to be likely to say to me, well, I guess you learned your lesson. I mean, we didn’t change the rule to say you have to hire non-college degree. Everyone who’s ever had this job has had a college degree. The next person just hire someone with a degree. Will you? Because I don’t want to live through this again.
So it’s risk aversion. It’s lack of preparation. It’s lack of understanding the system’s effects. And in probability, a company that hasn’t made some adjustments of those types probably hasn’t also made the adjustments in the way the ATS works and whatnot. So they may just say, gee, I’d be happy to, but I never get any candidates that don’t have one.
So I’m not trying to save the world here. I’m trying to get a job for someone to work for me who will be productive so I can make my objectives. I mean, I’m not, you know, this isn’t a, if this is someone who’s in my budget, I want to hire the person who’s going to do the best job. And if that happens to be someone without a degree or veteran or someone who’s been on a career break or someone with a criminal record, fine. But I’m not going to turn down someone who I’m really confident in to hire someone I’m less confident in, irrespective of whether it’s because of one of those reasons.
Absolutely. And let’s be honest, there have been many candidates who haven’t worked who have had college degrees, including elite schools and MBAs, et cetera. So from what you’re saying and from what I take away from that is people tend to just use that as a reason instead of questioning their own hiring and maybe interview process and maybe the waythat they’re assessing skills, they’re reverting to saying they didn’t have a college degree and that must have been it versus really looking to see did I set this person up for success during the onboarding? Did I give them the right tools? Did I assess them in the right way during the interview process?
It’s company and the people, companies and the people in them try to do something, everything as efficiently as they know how. We’ve all gone to a gym and had a trainer show us how to do something the right way, an exercise or stretch, and then you’re doing it a week later and you know, gee, this has really gotten easier. Then you realize, of course, you’re not doing it in any way the way they taught you to do it. Your body has said, well, that hurts, so that’s hard, so do it differently. And it’s the exact same thing in hiring. It’s the exact same thing in most activities in business. People want to do things efficiently and effectively.
So if they say, look, we’re going to interview five people for this, but the first candidate is a graduate of a school where the company has not only a great record of hiring talent, but really kind of understands the transcripts. When I was a CEO, we very much limited where we were hiring because we knew the faculty, we knew that this course was a gut and that course is hard, and we knew how the activities were like, things like that. And they’re terrific in the interview, and they’ve got a previous experience that is relevant to what I need or a gap in my team, I’m not going to probably interview the other four people. I’m just going to hire this person right now. I saved myself four hours of not having to interview people. I get the person sooner rather than later.
But you did say something I want to come back to a second ago because I think it’s very important that people understand that AI has the potential to be much less biased than the current system, much less. And I constantly being asked, isn’t it biased, isn’t it biased? Compared to what? And in AI, what I can do is I can use AI to make it less biased. I can create synthetic data and see does it systematically turn down people from certain zip codes or with certain phonetics in their first name or people that took multiple years to create, extra years to create a degree or whatever it is. So I can not only train it to be less biased, I can demonstrate whether or not it’s biased. And I can never get inside between the ears of human beings. The vast majority of them are sitting around saying, oh, I’ll never hire a gay person or I’ll never hire a black person or I really don’t like Chinese Americans. That may be implicit. It may be they’re more inclined, but we know from lots of research that people behave tribally and are more likely to relate to people who share lots of things in common with them.
But in any case, people need to get over this platitude that there’s some deep danger thing in AI that’s called bias. It’s there. It’s because to the degree it’s there because people with biases created the data. But unlike a person with a bias, even you’ve logged them to reduce and eliminate the bias, which is pretty handy in areas like selecting candidates.
As you were talking about bias and all the different biases that we have as humans, one that came into mind and that’s the proximity bias. And I wanted to ask you what your opinion is on the shift to going back into an office and if you feel like companies are making the wrong decision in calling people back or if you feel like hybrid is the best approach. What are your thoughts on that? I know you mentioned in your research with the caregivers, giving flexibility to their schedule is really important in retaining them and these are a workforce that we haven’t really tapped into that provide a lot of loyalty, promotion opportunities, et cetera, for thecompany. What are your thoughts on what we’ve been seeing as a change from post-COVID to now with work happening in the office. The first thing that I want to emphasize is this is happening on a pretty broad basis in big companies. And a number of the companies that have led on this are very well-run companies and very data-driven companies. Let’s take JPMorgan Chase, for example. It’s been easily the most successful of those banks for a long time. It’s got a CEO that will, at some point, if there ever is a big company CEO Hall of Fame, Jamie Dimon will be in the inaugural class. Not only is it those things, but it has a consistent, excellent record on things like diversity in hiring, sophisticated personnel practices. And they’re making this decision.
So the kind of angry white guys who are theory X managers, or this is the revenge of the power-hungry elite. I’m sorry, that doesn’t wash. If they didn’t have numbers that suggest productivity is suffering, turnover is a problem, process efficiency is a problem, they wouldn’t be doing it. So let’s ask why that might be the case.
Managers in COVID, with a huge amount of an adrenaline rush, were able to pull off a miracle to keep the economy moving forward for about a year in shutdown conditions. But then all of a sudden, COVID, thank God, leaves us, or doesn’t leave us, but we understand it better, we can treat it. And now we’re beginning to move into this weird intermediate period where some people are still remote, other people have moved and been doing their work remotely from their summer house or from someplace they always wanted to live. And I’m trying to figure out how to run the process that I need to run in my department if I’m a manager.
Once again, no one’s said, you know what, we better figure out what’s going to be different about that so the managers will be effective managing a hybrid workforce. We didn’t say to the workers either, you know, what we were doing in COVID was created by a crisis and we’re going to have to figure out how this works. And don’t be coming, you know, you should have no expectation that this is the new normal. That was hugely abnormal. Now we’re going to try some things so we can learn what works and what doesn’t. And do not plan your life around the assumption that you can be hybrid three days a week. We’re going to try it and we hope it works. And we hope that works for you, but, you know, no tats. I’m not tattooing it anywhere. And so don’t tattoo it on yourself.
And so I think it’s really the big driver in moving back is that managers had not been understood and not invested in how do I manage this process on an ongoing basis. And here there’s some research I want to draw on, which I think has analogy value. I did a large paper about white collar gig workers, like technical people. There’s a good company here in Boston called Catalyst that is basically a marketplace for consultants. What we found, we asked companies about their experience using white collar workers. And one of the principal drivers of which companies were getting good value out of these workers and which weren’t, in which companies gave the whole concept a significant endorsement, which didn’t, was to what extent was there training and development for managers is how do you run a team where one or more of the people doesn’t work for you, you don’t have hiringand firing ability over them, they’re probably making significantly more per hour than the other members of the team. They don’t know anything specific about your company. They don’t know about the history of the Walmart account or the GM account, etc., etc. And so when you have a fundamental change in the process for creating work, whether it’s where people are, what their employment status is, or what their previous experience is, that has to be accounted for managerially.
And the managers running these teams with gig workers didn’t know how to change their style, their planning, the communications to do that. And then the gig workers were a disappointment. And the manager or maybe the manager or supervisor is saying that gig idea wasn’t a good one. Well, how would you know? You didn’t give it a fair chance.
And I think it’s the same thing with a lot of these. This isn’t working the way we want. We’re just going to wrench everyone back here. And I think that is an error. And just like a bunch of companies that started off by saying, oh, we’re just going to be all remote forever, and then watch them walk it back when they started figuring out.
One final thing is that I think there’s a spurious argument that comes up within white-collar companies that, well, we have to have equity for everybody when it comes to hybrid work. The ability for hybrid to be productive is very different based on what your job is. And I’m not talking about UPF drivers and police officers.
And that just because we’re both white-collar workers in a company, you might be in product development, and that really doesn’t lend itself to being off-site a lot because a lot of that work goes on in teams. And I’m working in internal audit, and all I do all day is use AI to look for anomalies and look for budget issues and to check on people honoring our policies and procedures. My job really lends itself to being remote, not just hybrid. Your job doesn’t. That’s just life.
And the fact that we make the same, we have the same pay band in the company, and we went to the same university, even though you did better than I did in college, as John Kennedy said, sometimes life isn’t fair. And so the notion of the standard is that, well, it’s all or nothing, everybody or not. Even people who are essential workers and had to go into work during COVID, somehow there should be some adjustment for them because they’re not, they don’t get the opportunity to be a hybrid. Sorry, you know, we got better things to worry about.
You know, your points highlight a very important question and one that I always think about. It’s around like, how do we measure success? If we could rethink how we measure manager effectiveness and productivity in the workforce development, what key metrics should organizations prioritize to ensure managers are driving both employee growth and as well as, you know, business success in a more sustainable way?
Right, I think metrics like that are actually indigenous to well-managed companies already. I think that, for example, a good company keeps track of who, what supervisors oversaw the initial time working for our company of workers that really have proven to be great. I ask companies whether they track that regularly, a lot of them don’t. When they start tracking it, they really learn good things. They’ll regularly find that something like 20% of your supervisors for entry-level workers account for like 80% of your high flyers in your company. There’s just something about the way they bring them into the company, acculturate them, show them the ropes, give them self-confidence that is magic and you want to bottle it.
We cannot constantly hold people to period performance, sales, profitability, whatnot, and then attach a whole bunch of other variables that we don’t care about if you’re not meeting your other numbers, but only care about if you’re meeting your numbers. Most people have far too many objectives. And when you’ve got 20 objectives, no human being is going to go 20 for 20.
And so when I’m sitting getting evaluated by you, and you’re saying, well, you didn’t do this very well, what about that? I’m saying, Ren, give me a break. I mean, the three that really count are:
Did I make my financial budget?
Did we land that key new account we wanted to develop?
Did I run the implementation of that new technology in the division well?
And now you want to talk about, I was late filing my personnel evaluations. You know how hard I was working. Something had to give. And you’re nodding, and yes, that’s right, but okay. But I could be having a similar dialogue about something that’s important.
So having my balance scorecard with 17 things on it, I’m sorry. Balance scorecard was developed by a colleague of mine here. It’s a very useful tool, but most companies have just, it’s like a Christmas tree with five households worth of ornaments on it. It’s just too much.
Having the cultivation of people’s skills and things like it be something that’s discussed regularly, not part of just, it’s a regular part of the routine, putting the issue on the table and being very comfortable.
There’s a little bit like our biased, unbiased discussion. Employees and companies constantly are trying to get to some state that does not exist, which is that, quote, every evaluation is objective. What? First of all, evaluators are biased, but there’s a huge amount of subjectivity in someone’s evaluation. It always will be.
And there’s no reasonable standard for an employee to say, it’s unfair for my supervisor to have subjective opinions of me, nor is it sensible for a company to say, we only make such decisions on objective data. The art of management is intuition, instinct. The really good managers are, what they’re really good at is it doesn’t matter if it’s a personnel or a customer or investment, they make exceptions to rules because their heuristics, their experience, their knowledge, their values cause them to be comfortable doing that.
Well, thank you so much for all of your insights today, Joe. My takeaway from our conversation that I hope our audience can also walk away with are:
Building strong relationships with community colleges.
Using AI to your advantage to remove biases from the hiring process.
Not overlooking caregivers with gaps in their resume.
Ensuring that as leaders, your measurement for success are fair and clearly communicated and discussed regularly as part of the routine.
All I ask of anybody that reads my research, Ren, is not to assume that I’m right about everything, but just ask yourself a few questions and satisfy yourself that the way you’re doing things now is the best thing for your organization. Thank you so much.
And where can our audience read your research? So if you would Google Joseph Fuller, Harvard Business School, and there are a couple of large projects here that I co-lead. One is called Managing the Future of Work. We also have a podcast by the same name, which is happily very well reviewed. And also the project on workforce at Harvard. So if you mention Harvard, workforce, project, Fuller, you’ll find us fast enough. Thank you so much, Joe. Thank you.
