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Linda A. Hill reflects on different approaches by companies and leaders to extracting the best performance from employees.

Harvard leadership expert on why you need ‘nuisances' in decision-making process

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Uh Thank you all again, so much for coming and joining us tonight. And we're so honored and so fortunate to have you here, Linda from, from Harvard Business School. Um And uh I wanted to kind of jump right into things. Um You know, one of the big themes of this evening is digital transformation. Pretty much everybody in this room has kind of a punch list of things that they need to execute on, on some kind of uh digital transformation journey. Um But just to set the table a little bit for, for you, you know, you have put a lot of time and into researching and studying what kind of corporate culture and structure it takes to kind of make a transformation possible. Um Can you talk a little bit about what are some of the key elements uh of that culture? What what does a company need to foster to make its way for, for any kind of change, but digital change in particular. So as we were talking about, it's really a pleasure to be here with all of you. And one thing I did learn at Harvard Business School is you shouldn't speak too much because other people are much more interesting. So I'm, I'm torn here. But what I really have tried to understand and the reason I became interested in digital transformation is I actually look at the connection between leadership and innovation and how do you build organizations that can routinely innovate. And so about nine years ago or so I began to understand even better that digital tools and data are quite important to that. So what we know from our research and what we ended up writing about, and I will tell you, I always research with an executive, first, worked with the Chief Technology Officer of Pixar and right now with the man who did stra strategic partnerships with sales force and also someone who's in her twenties or he can be in his twenties, someone who's young is gonna be a nuisance so that these are my co authors all the time and what we found in our research when we looked at this connection between leadership and innovation and then digital is a piece of it. So forgive me for starting there is that basically leading innovation is different from leading change. And I'm actually a protege of John Cotter who taught us that, you know, leadership was about having a vision, et cetera. When you're dealing with innovation, you actually don't really have a vision, you know, your purpose, you know your question, why you're doing the work, but you don't really have a vision. As many of the people told me instead, what you need to do is create an environment in which people are willing and able to innovate. And we know a lot about that. So these tools, one of the things that surprised me in some ways is just because you have the tools, just because you have data, you all told me people don't always use them and they don't use them to help them innovate. So that's why culture matters. And so we did look at what makes people willing is if they, there's a particular culture, I'm gonna be real quick, but I wanna jump to the capabilities. What makes people able to do? It are really three capabilities. The first is creative abrasion. Do people know how to generate a marketplace of ideas through debate and discourse? Because you rarely get innovation without collaboration of people have diversity of thought. So then you have this can't be a top down kind of leader with the vision my way or the highway. It's really gotta be collective, it has to be collective. So the man who built out the infrastructure for Google said to me, I stopped reading books on leadership because it tells me I'm supposed to have a vision. Now, the man's brilliant, he was considered to be the best leader, you know, digital, anything at Bell Labs. And he said, Linda, I only took the job at Google because I've never scaled anything at the pace that they want to scale it. It's only because I don't have the answer that I'm doing this. So what I need to do is figure out how to get, you know, my 1000 a few engineers to be able to really do the hard work of innovation because it's really intellectually emotionally hard. So you got to get him to really debate and, and that's how you get this marketplace of ideas. Secondly, you have to, and you all know this, you've got to get them to be willing to experiment and learn to take those risks. Now, that's really hard in small companies, but also incumbents to really experiment and learn if you're in a regulated business, that's hard. And, and then the final one is how you make decisions because as you're doing all that you're doing, you have to make sure that people know how to make decisions in the first place with data or without, and most organizations really have trouble being clear about decision making, right? And they have also um you need to have a more patient and inclusive way of hearing the voices going back to the, generating the ideas. But then you've got to make sure as Steve Jobs would say, don't let the experts dominate and don't let the bosses dominate. So how do you do decision making that way? And the data help? But just because you have the data and you have the tools if you don't actually have a good process to do decision making. If you can't deal with, you know, those those realities of the conflict, then you're not going to use the data in a way that will help you do something differentiated for your customers. So that's why we talk about how the culture, the way you do the work impacts whether these, the investments you're making in all of this, these tools and data really pay off. So it sounds like there's a little bit of silo busting happening where you're where if obviously, if you have very strict divisions between departments or very strict hierarchies of, I love the phrase decision making rights, which I think you introduce me to. Um if, if, if those hiar well, that may say more about me than no. Yeah. Well, those companies aren't clear about decision making rights actually. Right. Yes. And that's a great point. So you, it sounds like, you know, so you need a sort of a flatter hierarchy in the, in some sense, but also maybe a willingness you mentioned earlier needing uh to have a young person on your writing team who can be a nuisance. It sounds like if you've got a company that's multi generational, which we all do, right? Uh You've gotta be listening to your nuisances. Yeah. Well, they are helpful. So, um so we're writing an article now about how do you embrace digital natives and make sure that helps you keep a pace of what you wanna do in your organization. But I think that the issue of hearing the different voices and I don't know that it's flatter hierarchy does. There's a purpose for hierarchy just to be clear that the, the dilemma is it's silo busting is difficult across functions across geographies, but it's really difficult across levels. And so one of the things we've been doing, we've had a survey that just came in of 4000 executives and asking them about how they're, how they're doing their digital transformations. And so one of the the challenges you have, it's not that you're removing. Um as I said, Steve Jobs worried about the experts and the bosses because the experts are experts about the status quo, right? So what you want to do is figure out how do you include as many voices as possible and do it in a fairly efficient way when you first start to do this, I mean, the data and having a single source of truth can help. It's very hard to get to that. But when you first start to do this kind of work, um people are really pretty clumsy and it takes longer and it's harder and more complicated to deal with the conflict over time. You get better at it actually, but it does require practice. So I want, I don't want to just say I, I guess I'm that it's not flatter. Yes, maybe it's flatter but organizations have whatever structures they have. The question is, can you actively advocate um for a point of view and not just actively listen. So there's a lot of talk about actively listening and you know, making you need to because we all could listen more, but you also need to know how to advocate for your point of view and you want everybody to have that capacity. So one organization we worked with, they taught people about critical thinking and advocacy and they had 25 year olds coming up with $15 million ideas for their customers. But you have to know how to communicate to, you know, people who are more senior to you who have different expertise, different points of view. So what's that storytelling, that narrative that lets you make the argument so that people will buy it, sort of a two part question flowing out of that. Can you cite some examples of companies that you've seen that have, have made that change, that have figured out how to like how to inculcate the advocacy when it maybe wasn't there before and relatedly what other, what other leaders have in common, what the leaders have in common is. Well, I'm gonna go back, Pixar is not what we all are. So I'm actually uh well, when you think about it. So at Pixar and the reason why we wrote a book called Collective Genius right now, I'm looking at scaling as I'm very interested in scaling of innovation. But what they say at Pixar is that everybody has a slice of genius, everyone has talents, everyone has passions, none of us can afford to leave those talents and passions. They're not equal, not all slices are equal, but again, everyone has them. And so what you see about these leaders, and I think the thing that can make you not be able to do this if you don't actually see potential in people. So at Cleveland Clinic, Abu Dhabi, which I've been studying for about six years, one of the, one of the most advanced in terms of digital transformation hospitals I've ever seen. They very, very uh one of the things that the CEO who was a surgeon, robotics, leading surgeon in a robotic cardiac surgery when he was putting together the team for COVID. And I don't know whether you know this, but they Abu Dhabi didn't have, they really managed their COVID. He found out in December that COVID was happening because someone in the kitchen. So I need to tell the CEO that something's going on in my hometown of Wuhan, December 2019. So in January, they were testing for the different variants of COVID. And imagine if the person in the kitchen understood I can get to the CEO who is a Rhodes scholar and a pioneer in robotic surgery to tell him there's something happening in my hometown that that literally is what happened. And he said there's a freight train coming. And so then they began to collect data. And what he did is he put someone on the team who had never seen and a pandemic, an epidemic are before of any sort because he said we've seen Ebola, we've seen everything, I mean, but we need someone who's never seen it so that she will, this is a she, she will ask us those questions that get first at first assumption. Of course, just because you put her on the team, the task force doesn't mean people are going to hear her. He had to throw his weight. So what he did imagine the surgeon. My husband is a professor at Harvard Medical School. So I'm picking on him. Um He said, he said, I am scared on this one. I'm scared but I trust all of you. I, I I'm really scared but I know we're gonna do this. And so when she spoke because he had put it and he said this is a sacred space. We're having a sacred conversation. It is about life and he talked this way and he's a pretty serious fella, very capable and he wanted people to know he had no idea. So he said, I'm leading through a fog and what does it mean to lead when you have no vision? And you can't see, we do have the digit, we have tools and we have data and we're going to use as much as we can, but we're going to have to make decisions and we're gonna make decisions in the last piece of it that this is the way the leadership played out. He said, we're not gonna know if that decision was right until we get the feedback. And again, we're going to use our digital tools and the data to get the feedback on whether that decision is going in the right direction. And if it's not going in the right direction, we're gonna have to pivot and if it is, we'll continue. But all of the digital, the data and everything were really serious parts of the puzzle. But it was the framing of the problem. Everything is a working hypothesis. We're collecting data. I'm scared. I don't know that allowed that team to operate that way. And because he led that way, someone in the kitchen said you gotta tell him something's happening in Wuhan, right? Time flies very fast when you're talking. I mean that in the best way because our time but in but framing what you were just talking about. When we spoke earlier, you talked about the distinction between a data driven decision and a data informed decision. And you know, thinking about the Dubai uh Cleveland Clinic through that lens. To me that there's not really enough data at that Abu Dhabi, they'll kill me. Abu Dhabi. I apologize. OK. Even though it's the UAE Abu Dhabi Dubai to different place I removed from my post I know but, but seriously, I mean, in the distinction between data driven and data informed uh in this case, it feels like am am I right in seeing this as data informed? Yeah, so the the way that came up is that one of the things as you all know, information is power. So data is power. So when you have data, you have power and we're talking about the power dynamics of organizations and we all know they're complicated. So when you say data, data driven, first off, everybody's thinking, excuse me, do you think those little crazy people over there know more than I do with all my experience and all my expertise, you immediately they put up a wall because why is the data more relevant? But what these organizations do is they have three rules of engagement about how we think together. The first one is you always have to tell people your evidence. So you can say, I believe this and my evidence are data, right? Whatever or you can say, I believe this is my gut tells me this is what's right and your gut is your experience. But then the second rule of engagement is everyone can question you and say is your experience or are the data really relevant to what we're talking about right now? So people can question and then the third one is people can say relevant et cetera. But are we thinking holistically, my function can't do what we're coming up with. So can we have the conversation a little longer to say how my function can deliver on what I agree is the right answer. Gotten out. We've gone through that. So those three rules of engagement, which are actually rather difficult to put in place because people often say, I believe X or the CEO or whomever and everyone's going to say like, why does he believe that? No, you, you know, that's too hard a question to ask as opposed to. And this is my evidence. And then people can say, oh, let's look at the evidence and it's less personal, it's about the evidence. So those are the rules. So data informed. And the last thing I'd say about A I, I really believe deeply and I, I've started an A I company which I was telling you about which so I can learn about it. But the thing about A I is you want people to use their judgment so you don't want them to think it's data driven. You actually have a set of questions you want everyone to ask when they're using the results of A I or generative A I. There's so, so it is not just the data, it's the data in combination with judgment. So it's very important that nowadays people get because, you know, it's just because we can do it. Should we do it? Could we do it et cetera? So I think it's really important for that reason. That data informed is what you're really asking for because there's nothing I, I, the good thing about living in Cambridge is I'm invited to the salons that the doctoral students, they have pizza night, the A I doctoral students at MIT. That is fun. You all would have, you would have a blast. So they just, they meet every six weeks and have pizza and then they invite old people. Ok. It is wild. Ok, to see what they're working on and what they're thinking about. But in that context, which is why you do want to be with them, they show me and you know, I have to, there's a whole set of questions you want executives to think about when you're using what they're creating. So please say data informed and not data driven and please come up with one of those questions. I think that's the direction where that, this is all being steered. Um, Linda, we're so grateful for your time and this is the end of our one on one. We're gonna serve the main course, but I hope that if this conversation is generated questions from you too, Linda don't be shy about asking them uh, at the dinner table over, well, the fish or the steak, whichever you had. But Linda, thank you. So, thank you. And I apologize. I'm an anthropologist. So I'm a storyteller. I know all good. That's right. Anyway, thank you.

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