Designing The Architecture Of Change: How Organizations Transform

Hi everybody this is the point where if we were in a room I would ask you to answer a question: how many of you are in a digital transformation at the moment? And I would count the hands. And I would see that pretty much everybody is in a digital transformation. And what I would say is to those who have not raised their hands don't worry you'll get there soon. So let me talk to you about how we can think about how we change large organizations from the inside by talking to you about a fairly old digital transformation story. Those of you who are my age or thereabouts will recognize these immediately. For those of you who don't know what these are on the screen are their film canisters. And there was a point in time when this was the gold standard for photography. There was no Instagram, there were no camera phones and there were certainly no TikTok. And you would pop one of these in your camera. And then when you were done shooting and you didn't know what you were shooting you would take it to a lab and it would get developed. And Kodak was the undisputed ruler of the photography world. In 1970 1970s however, there was an engineer who worked at Kodak who started thinking about how we can disrupt. How can we change the world of photography? How can we do things in a different way because the first digital technologies were starting to emerge? He in fact developed the first digital camera in 1975. And when he showed it to his bosses at Kodak they said Well you know it is cute but it is filmless photography so just don't talk to anybody about it. The reality is that soon, as well as the r & d and development and marketing development leader at Kodak, had commissioned studies and they discovered that digital photography was an upcoming trend and that the film business so the canister business was probably being threatened by these new friends that were in our region.
They produced a report again to upper management saying we've got bad news and we've got good news. The bad news is that the market is telling us that digital photography will be a thing that stays and we all know that. But the good news is that the technology is still so primitive that we have about a 10-year window of opportunity to develop the digital camera that can go to market. Again the day we're told that's cute don't worry our business is making the film. We'll get there. But eventually, they succumb to the pressure. And in fact, Kodak was the first company to come out with a digital camera. And it looked a little bit like this. In fact, it was this. Now if you were to look closely though you would notice that it is a digital camera in that you have a digital screen where you can preview the shot that you're taking but it's still technology based on the film on the screen. You should see that right in the middle there is a canister so effectively the digital technology was applied after the film technology was employed. History shows us that Kodak is no longer a massive player in that space. In fact, you know it is pretty much focused on professional services and digital photography is everything we do. What is interesting though is understanding Why this set of events took place. And it's not that they only happened at Kodak they happened in a number of other organizations. But the Kodak example is particularly visible shall we say. So we can use a mathematical concept to explain what happened. If you're not familiar with advanced math or mathematical theory I'm not but you know I looked into this the reality is a concept called the concept of the local optimum. So in computer sciences and applied mathematics, the local optimum of an optimization problem is a solution that is optimal within a neighbouring set of candidate solutions. So the problem is digital photography. We are a film business. A neighbouring solution is a film camera with a digital post-view display. The opposite of a local optimum which is what we call thinking outside of the box is called the global optimum which is the optimal solution among all possible solutions. Now clearly we could go into announcer nouns. We don't know what is optimal among all possible solutions but if you look outside you know the neighbouring concepts. So what was corrected was optimizing if you Will and which is what a lot of the organizations we work in do at the same time they focus on improving the current situation. But that often or almost always does not lead to the best solution. And these local optima problems affect most of our transformation initiatives. Because they are, you know, primarily focused on optimization activity. I've heard lots of colleagues in current past jobs in our industry saying we're not really doing a digital transformation or we are digitizing the same old processes that we have. But the bottom line is that if you set a goal based on starting where you are today and heading in a direction that will improve your current situation you're always going to stay in the vicinity. So you will remain in your local optimum but possibly unlikely it will not be the true optimal strategy because some competitor will end up getting you up to the top of that metaphorical mountain. And it may be announcing that we've not even seen kind of as happened with Kodak. And the reason we do that is that we can transform you know in optimization we can transform processes that we know. And the process brings seductively strong near-term outcomes. This is not me you know this is not I saying this is Reed Hastings; he's the CEO and founder of Netflix. So we use the label digital transformation. And that is not inaccurate because we are using digital technologies to change our business. But we are still missing a huge part of the transformation picture and that part that's missing is disruption. Unfortunately, our traditional management and leadership techniques fail us. They don't only fail us in this kind of circumstance, they tend to make things much worse. There are studies everywhere. But you know one of the recent ones shows that less than 30% have established companies that begin to somehow falter ever rebound. And that translates into a 70% rate for the most successful companies when they are not staying on top of the market and focusing on you know the neighbouring solutions. And the reason for this is that the models that this kind of company generally employ when or when they find themselves do too. situations often do not work. You know if we want to go back to Kodak it's not that they didn't care about their users. It's not that they didn't care about photography, it was quite the opposite. The organization was so large and as an organization gets larger they become super entrenched in its communities and they become more risk averse.
And they are much more vested in maintaining the status quo. You have stakeholders, you have shareholders that you're responsible to end taking big risks. It is terrifying. So we become so risk averse that we create an environment where failure is not an option. We value consistency and predictability. And while you know these things in the short term can bring outcomes that are positive. The reality is that they make us much more vulnerable to disruptions and you know black swan events think about the pandemic. For those organizations that only rely on known processes. It's been a completely game-changing event. So the reality is that you know I talked a little bit about how old management techniques are not our friends. And what I've noticed is that we tend to follow three main archetypes when we look at transformation and establishing the organization. The first one is the prince charming archetype. Let me bring in a fearless leader that's going to solve all of our issues and it's going to change everything for us. Yeah, we know how that one's right. He knew nothing about the political domain. You know generally, these leaders are taken from other industries that are high profiles they come in and they want to apply their proven methods to an organization or a situation that they don't necessarily know. And then the results are not what you know what was promised. The other approach is the skunkworks model, the experimentation at all costs of the Google axes of this world. Let's take the most brilliant minds and chuck them in a corner with money and all the toys that they want. It's generally called an innovation department. And let's hope that they will come up with a splendid idea that's going to turn things around. The reality is that sometimes good ideas come up, right? But because it's so detached from the reality of the organization it's a little bit like Milli Vanilli one hit wonder never to be repeated. So it's not a recipe for sustainability. And then the third archetype is around consultants. What are management consultancies and external partners? So these people are incredibly smart. They conduct tons of nog Rafi testing validating they have all the strategies they explore potential business models then they give you a report and you're supposed to implement it. Again this is often a recipe for disaster because all the domain knowledge that they have acquired then leads the experts to the understanding that customer empathy is never transferred to those who have to implement it. And I've seen the cycles repeat themselves over and over and for me, the interesting question is why does that happen? Why do we keep making the same mistakes? And the best explanation about why this happens is I've heard from a colleague and so I'm going to try and paraphrase how we explained it to me. So the book you see on the slide is Thinking Fast and slow the book by Daniel Kahneman
is the book that every designer said they've read but that also has the potential to put an insomniac to sleep because it's very dense. It's very interesting. And I love it in small doses. So Kahneman talks about our way to process information and decision making as system one and systems system two system one is the fast unconscious automatic way in which we make a decision we rely on you know experience information that we know. And we kind of just go on autopilot. It's like when you get in the car you don't think about all the steps after you've been driving for a while just sit down sometimes you don't even know how you get from A to Z if it's something that you do. This is system one system two which is you know it's an area of cognitive strain is how we think we are when we make decisions. It's slow conscious, it takes effort and it's applied to complex decisions. The reality is that if while I'm talking to you I were to start thinking about oh my god does my hair look okay now I'm going to move my hand this way. Now I'm going to break. If I were on a stage I would think about how I walk. I'm getting anxious and hyperventilating already. We tend to be in system one much more than we are in system two. So we tend to make a decision in a much more impulsive and automatic way. This is in fact how we make decisions. This is called the ladder of inference by an organizational psychologist called Krista gyrus the reality is that we take from the bottom reality and facts that we see and we select the ones that completely automatically clearly the ones that we think are relevant to interpret them we make assumptions we jump to conclusions we develop beliefs and that's how we act. And that is interestingly very it is aligned to you know Maslow's hierarchy of needs where you know the decision making is part of the self-actualization. So we want to get to that state where we are you know we belong we have steam and we realize but we tend to do so by using our you know automatic system we want to be in cognitive is. This makes things even more interesting because if you think about processes if you think about you know the three archetypes if we think about the fact that we are focused on outcomes being knowledge workers our outcomes are often incredibly intangible. If you're not familiar with the term knowledge worker it's a term that was coined by Peter Drucker who used it to describe people who use and create knowledge to create value in their work we are differentiated by the fact that we do a high degree of non-routine work in a non-deterministic environment. And that means that process is really hard to apply because it's non-routine work and in a non-deterministic environment. And I will touch on that means that di D we start with an idea but we're not really sure of the outcome that is going to emerge. In the end, we do know the end state of a process from the process at the beginning of that, and because of the complexity that's inherent with nondeterministic work the level of collaboration and communication is infinitely higher. This is compounded also by the fact that we work in complex adaptive systems. So there we work in an organization that is self-organizing we have our own internal rules and exhibit emergent properties. What does that mean emergent properties determine are those properties that literally emerge when something in the system changes let me use the example of a team the team is a self-organizing system. And the dynamic in that team will change.
When the elements of the thing that is the people ask the workers that are in it change. So it's not just the work that we do that is non-deterministic. It's also the organization that we work in that is not non-deterministic. Things change all the time. They have the word changes we call those favourites and teams change organization changes all the time. So at this point, I would show you a video and we will embed it so that you can click on it and just jump out of this presentation and refer to it. And this is a video by one of my favourite systems thinkers. That lends a really important message. The system is not more than the sum of its parts. It's an invisible hole and it loses its essential properties when it's taken apart. This is Dr. Aiko. And so makes me I would like you to think about this as we go and talk and touch for a little bit on systems of people. So we work as they said in teams and organizations that are non-deterministic. Yet when we talk about people this is the language that we use we say people are our most important assets that can be part of a process. It all begins with talent. The definition of talent is something that baffles me. We need to win the war for talent and leadership matter more. And we apply this kind of thinking to our organizations that look a little bit like this in every org chart I've ever seen. The reality however is that the org chart is a little more like this there are all these emergent properties of the systems that you cannot see when they're represented. You got secret resentments from someone who's hidden but really makes all the decisions. Someone who sells drugs there's you know Brodeur's football Team allegiances. And it's an environment that's messy and as complex as humans are. However, we reduce everything to matrices. We talked about potential and we talked about performance. And we tend to invest accordingly to drive these organizations that are struggling. So of course an organization will invest in high potential high performance. I'd like to know what the sciences are between the termination of that. And the people that are in the lower corner are left out. The reality is that if you think about a sports team which is the analogy that I think is closest to our world of work we found displayers that don't always score without those players that are not that maybe are smaller in a scrum. The biggest players would not be able to score and so I argue that we need a bit of both. This is why we should focus, I think, on transforming all of our organizations into learning organizations, meaning organizations that are non-deterministic and yes that complex. But organizations attempt to arrange themselves so that they can foster learning both in individuals and in the organization as a whole. And this is where I think systems thinking comes into play. Systems thinking is about encouraging people to learn to see their world work as part of the larger system so not just this thing that I'm making but as part of this organization that needs to change. And personal mastery is about you know commitment to personal learning and to learning of the organization. So as a part of the organization, it facilitates the retention of domain knowledge and expertise that otherwise is lost. So going back to organizations they are all based on the intention on the foundation it's about you know everybody it's not that organization crop up they are based on an idea whether it's Nike I want to make the best sneaker for running or Vodafone the organization where I am you know we want to enable people to communicate if we take all these elements that we've talked about the magic spot is where the organizational goal or the intent the group goal so the team objectives and the team learning intersect the individual goals. And if we can find that spot in the middle we will find an area where people get better, the team gets better and the people near them get better. It is a very intentional pursuit. It's a difficult one. But it's one that will yield the biggest results.
Now. To conclude there's much more than I could talk about. But to conclude, when people don't understand how they send in an organization they will back themselves into a corner and they will not participate in the improvements that are required to really transform from the inside. And if there are a few things that I would like you to take away I would like you to remember that everything is connected. And that when you're part of the transformation or not you need to consider the system in order to make a real and sustainable change that you need to innovate in the context of the organization. Don't just go and do something in the corner and then hope that it will fit. That diversity of talent is absolutely fundamental to creating an organization that can respond to different pressures and to black swan events that you need to foster continuous learning organizationally and personally and that humans are the key to everything. Thank you