Full transcript
Intro from Debbie West:
Welcome to a first in a new mini-series of the c-suite podcast, Reflect Outcomes, recorded in partnership with World Bank Group.
I’m Debbie West and regular listeners to the show will know that a couple of episodes ago, I had the pleasure of chatting with Lisandro Martin who is director for outcomes at the World Bank Group, alongside Sir Michael Barber a world leading expert on delivery, government efficiency and system wide public service reform where we explored in detail what we mean by intelligent outcomes.
Following on from that conversation, we’re now excited to be hosting this new series, alongside Lisandro, where we continue to explore what it means to build a culture of outcomes which can help to inspire organisations and governments to think and act differently.
In this first discussion, Lisandro Martin is joined by Professor Dennis Campbell of Harvard Business School. Together they explore the shift from process to outcomes, the role of imagination and accountability, and how AI is redefining measurement and organisational agility. I hope you enjoy this conversation about leading with intention in a rapidly changing world.
Lisandro: Hi! Today I am here with Professor Dennis Campbell from the Harvard Business School to discuss how we build a culture of outcomes in organisations and governments. Hello, Dennis. Nice to see you.
Dennis: Hello. I’m very happy to be here and learn about the great efforts that you have in this area here.
Lisandro: So let me start with a question to you then, is what do you think it entails to create a culture of outcomes in organisations?
Dennis: Oh, that’s really interesting. You know, we actually studied this a lot and have a number of case studies on many private sector organisations typically. But I think this idea of culture of outcomes has several elements. You know first it’s your the name implies right. It’s actually focussed on outcomes that matter for the organisation. Right. What does it actually mean to win to achieve your objectives for example. And that’s very different than a focus on say process or inputs which are also important. But I think a focus on outcomes can feel a little more uncomfortable to people sometimes. Right. Because it is there are many things that can influence outcomes. You know, you think of a firm’s profitability or market value, right? That’s affected by many things other than even the CEO’s efforts, their team, and certainly people below them. I think of you guys, you have a much broader outcomes than like a private sector organisation, and you’re trying to impact really big issues in the world, right? You think about things around prosperity, around the health of the planet and so on. These are huge issues. These are huge sort of impacts that you’re trying to have. So I think that on the one hand that could feel uncomfortable, but it could also feel inspiring to people, right, that it is about the outcomes. It’s not just about process.
Dennis: Right. It’s that we’re really we individually actually can really have a much bigger impact. So I think it can be uncomfortable. But also inspiring is one thing. The other is that I think typically when we see a culture of outcomes, it tends to attract and sort of motivate people that want to be a little more entrepreneurial because it’s not just about, you know, doing things a checklist, right. It’s really about kind of outcomes and outcomes that you have to sort of be really creative about going after. You may have to, you know, you may not be able to control the outcome yourself, but you need to influence others, right? You need to mobilise support. And people have to kind of think and act like entrepreneurs to do that. And I think one of the things we often see with that is it does come along with broader accountability systems as well, right? Because if we want people to think like entrepreneurs, we need to broaden the scope of the metrics that they’re held accountable for as well. We need to get them to think in longer time horizons, for example. So I think a number of things come along with this culture and focus on outcomes. That’s very different than a focus on inputs or process in many, in many organisations.
Lisandro: Now, many of the words that you’re using actually resonate very well with the experience that we are having. Imagination, accountability, inspiration. I think these are words that go alongside precision when, you know, people normally think about outcomes as being precise about what we measure. But I think it goes beyond that, and it’s really using the imagination differently to deliver on those outcomes. One of the things that I’m seeing on my trips and conversations with clients is that in the context in which we are, which is a divided world with plenty of conflict, with many crisis outcomes, is becoming like a culture of cooperation, like a culture of really conversation across the world. And it brings everybody to the table around the same direction. And that’s what I like to emphasise when we talk about a culture of outcomes, is a culture of being clear about the direction that we all want to deliver on. Perhaps one of the things that I wanted to ask you about, Dennis, is AI and the world in which we live today. And how do you think AI is affecting this, this, this efforts towards a culture of outcomes?
Dennis: I would love to talk about that, but if you wouldn’t mind, I would like to maybe comment very briefly on what you mentioned around bringing people together. I think this focus on outcomes is really interesting as a way to force more collaboration. Right? And in fact, it necessitates it. Right. When you think about the kind of outcomes even a traditional private sector company would be trying to achieve. You know, typically those can’t be driven by any one business unit, right? Actually, when you sort of move to a focus on broader collective outcomes, it forces people to start to think more collectively, right? And to start to think about how we can influence people in other units. Right. Mobilise other people and collaborate across units to meet shared goals. And again, I think this idea of kind of you need to change many aspects of the culture and the systems to make that work, right. You need people to be aspiring to shared goals, which means you have to be measuring shared goals. People have to feel accountable to that beyond their individual goals. You have to create pathways for that interaction to happen, right? So many companies that might look like a matrix organisation where you’re literally forcing people to pay attention to other units and others, it might be cross-functional teams.
Dennis: Sometimes it might be internal kind of processes that bring people together regularly from across units. But I think you have to create both those pathways, but also the common shared kind of aspirations and goals. I think it is really important. It’s a natural that that collaboration happen. The other, I think in your case, especially when you think about the kind of things you are measuring on your scorecard in terms of outcomes, again, these are huge societal, global kind of goals. And I think, you know, here you’re talking about cooperation internally at the world Bank Group, but you’re also talking about cooperation with your clients. Right. The cooperation in their societies. For example, I think that this kind of focus on outcomes, it does push you to really be thinking about these kinds of much more collaborative kind of efforts. I think that’s one of the great things about this.
Lisandro: You are describing this complexity of delivering outcomes at the world Bank Group. And then one idea comes to mind on something that we talk regularly about that is moving away these conceptions of outcomes as being the end of what we do to bringing outcomes to every decision throughout the value chain of what we produce. And I call this developing an outcome reflex, like being able to very quickly, almost like a train habit, to make decisions with a real eye towards the effect on the overall outcomes. There are plenty of things that we can decide along the way that determine whether an outcome will be delivered or not. We know outcomes are correlated with the time that it takes to implement a project, are correlated with budget allocations, are correlated with the quality of measurement, and very often we don’t think about outcomes when we make those decisions. So if we develop this habit, this this trained way of responding, I think the likelihood of delivered outcomes is even greater. But we have that tendency of thinking that outcomes will come later and then they never come, because it’s a decision that you make on a on a regular basis. What’s your view on how AI is, you know, making this game a little bit more complicated or simpler perhaps.
Dennis: Oh, really interesting. Well, first of all, I think it just in there’s two angles to this, right. One is we do think that every organisation of any kind these days has to really be thinking about a strategy for AI and how you’re going to incorporate it. We know that this is a technology that is moving at a great pace in terms of the capabilities it’s developing. But we also know that most organisations are, you know, pretty linear in the way they’re adopting it. Right. And so, in one sense, the sort of pace at which capabilities are developing in AI looks exponential, organisational adoption looks linear. And you can imagine what that means over time is there’s a large and growing gap between the capabilities of these models and organisations sort of use and adoption of those capabilities. We believe it’s much harder to adapt to that later than to adapt now. So we think it’s important to be thinking about this now. I think the interesting thing about your focus on outcomes is that you’re building a muscle to create more collaboration across the organisation, and one of the things that we see in organisations struggling to adopt AI in a coherent way is it is putting new pressure on, on kind of collaboration and thinking more across boundaries, right? Because this is a technology that can affect so many different work processes in so many different ways, that you really do need that collaborative muscle to actually adopt this. So I think that one angle is just kind of how do you build the capacity to adopt this very fast moving technology? The other though is I think in your case, it’s pretty interesting is what role I could play in all of this focus on outcomes actually, and measurement and so on.
Dennis: And I think there’s a number of really interesting things there. And I think you’ve set the foundation for them already. Right. I think of one of these is you are measuring incredibly difficult to measure dimensions of performance and impact. I think AI is something that could help you do that actually. Right. So to think about you know, especially things like attribution, what part of these big impacts that you want to have are really due to your own efforts, right? And so I think that this idea of using AI as a way to extract patterns, understand causality, for example, I think there’s a lot of scope to be able to do that going forward, especially as you create the data infrastructure on the scorecard. The other thing I think is interesting is you already have kind of some efforts in place, I think, to think about causality in a structured way, but it’s with unstructured data. I think those results narratives that you have, I think is a really interesting innovation and really kind of using that as a way to capture the parts of the your impact that are more difficult to measure and building some narratives around that. I think over time that becomes unstructured data that’s going to be really interesting to analyse via things like generative AI. So I see I see a lot of scope here in the future as you build this infrastructure around outcomes measurement, to be using AI to make this kind of measurement and communication and learning from the scorecard a lot more effective.
Lisandro: No, I fully agree. I think that a lot of the concepts and practices of results measurement are really being changed upside down by AI. You mentioned attribution and contribution, perhaps no longer a dichotomy. The two of them can actually be pursued with AI tools. I think even the definitions of outcomes and outputs themselves will need to be rethought. Well, before we used to think that outcomes came after the outputs and significantly later. Right now, AI can work on the two at the same time and predict one in relation to the other, but also expose an ex-ante measurement, you know, quantitative and qualitative data. Both of them are now possible thanks to AI. A lot of things are changing, but I wanted to also say that one of the positive aspects that we are seeing on this is that it brings with it a different way of thinking as well. I have in my team a group of data scientists that have been trained and are very fluent in these technologies, and they really bring a different perspective to everything that we do. I tend to say that they don’t think in concepts anymore, they think in prompts, and they are able to really give you bite sized solutions to the problems that we have in bureaucracies, and without taking perhaps the overall complexity and trying to solve everything. At the same time. We just divide the problems into bites that AI can solve. But I think the other thing that I somehow find interesting is that we I learned from my colleagues this concept of working on perpetual beta, which is we continuously improve these tools over time, and we don’t have to wait two years until we have the perfect solution for the problems, because if we do so, those solutions are already obsolete. And I think beyond AI, that’s a concept that is affecting a lot of what we do at the bank to make sure that we are faster, more efficient, and then bring solutions and then learn over time how to improve those solutions.
Dennis: Well, and I think this goes back to what I was saying around the collaboration muscle, building this muscle to be able to do that fast iteration. I think that’s really important when we think about AI adoption, because again, this is a very fast-moving technology. It’s changing a lot. Right? And so building that muscle where people are continuously experimenting and updating how they’re using it is really important. I also think it would be interesting for you to think about the with the data scientists. Right. They have these capabilities. And how do you expand those capabilities to a broader set of people in the organisation? Right. Because I think as you create this infrastructure with the scorecard, where there’s so much ability to disaggregate the data and look at things in a much finer level and drive decisions, the more that people kind of throughout the bank group have access to AI and understand that prompting and those skills and how to use it. I think there’s going to really enhance the effectiveness of this data infrastructure that you’re building.
Lisandro: Fantastic. Really, as you say, to identify trends that were hidden somehow before the AI era. And then if we identify them, we can really find solutions. And I think this is the quest in which we are all together, really in the bank, trying to see whether this outcome orientation permeates through the structure and really affects what we do in the front lines at the business unit level, more than at the corporate level. Perhaps to finish I’d like to ask you, what would you say are the biggest obstacles that we have in this journey? You’ve seen many organisations working towards that. What are the things that we need to watch for?
Dennis: Well, the good news is I think that you’re addressing a lot of them, which is really interesting. Right? I mean, for example, one is that you know, don’t let the perfect be the enemy of the good, right? This idea that some things that are difficult to measure. And so we may just kind of ignore those. Right. And I think you guys have really pushed this idea of measuring everything you can but even using these results narratives to kind of really plug the gap. And maybe you can see some iteration over time with things we can’t measure now, we can measure later. So I think this idea of really pushing forward, even in areas that are difficult to measure. We often see even traditional private sector organisations kind of you lose steam as you go from the financial perspective, which is easy for most organisations to measure down to the customer, to the what we call learning and growth, where you’re measuring human capital and things right, you start to see the quality of measurement really drop off. So I think really keeping the focus on quality of measurement, even on dimensions that are difficult to measure. I think really critical, and I see you guys doing that.
Dennis: I think the other is to and I see you recognising this, right, that this isn’t just about measurement. This is a much broader culture change, actually. And so I think that this needs to be a whole organisation approach. And this means when we think about culture change, we have to also be thinking about changes in accountability systems that match that culture. For example, we have to be thinking maybe in the future about the kinds of people we’re hiring to match the culture, for example. So I think this requires a full rethink of all organisational systems. Right? This is a much bigger culture change. So I think that’s another. And the final is the kind of you’re recognising this need for collaboration that people can’t be thinking in isolated kind of units anymore. And again, I think that this shift to a focus on outcomes, shift to broader shared goals, I think that that’s kind of that that is a big evolution for any organisation. And I think you guys are on your way on that. But I think that recognising that is a much bigger shift, right? It’s about the culture. It’s not just about the tool.
Lisandro: Excellent. I think everything you say, it’s about intention. And really a culture of outcomes doesn’t happen on its own. It happens with intention and direction. One of the things that we observe, I tend to call this the tyranny of the now. People are so busy thinking about the urgencies, answering their emails, paying attention to the processes that we don’t spend enough time thinking bigger and thinking beyond the today. And I think with intention that can be achieved. And I think with the help of AI tools, a lot of the things that used to take longer, you know, the data that used to take longer to produce or the insights or the trends can now be put at the fingertips of people so that in the little time that they have, they can still develop that reflex towards decisions that affect the outcomes. Thank you so much. It’s been great having this chat and I look forward to chatting more offline.
Dennis: Thank you. And I look forward to learning more about what you’re doing here at the World Bank as well. Thank you.
Outro from Debbie West
My sincere thanks to Lisandro Martin and Professor Dennis Campbell for sharing their insights with us.
And thank you for listening to this first in our mini-series, Reflex Outcomes produced in partnership with World Bank Group.
I look forward to sharing more insights with you soon and in the meantime, we’d love to hear from you. Please feel welcome to add your thoughts to the conversation by leaving us a review on your podcast app or on our LinkedIn or YouTube posts.
Don’t forget to follow the c-suite podcast so you can keep up to date with all our other episodes.
You can also get in touch with the show and share your feedback with us via our website, that’s csuitepodcast.com or you can find me on LinkedIn, I’m Debbie West.
Thanks so much and goodbye for now.
