 Yeah, it's been doing agile stuff for quite a few years, and I'm very pleased and happy to be here today With you to share some of my ideas and to hear some of yours So I'm really looking forward to this discussion now and perhaps other discussions as we go forward so One of the things that we talk we hear a lot about these days is agile portfolio management I Wanted to you know, we also hear about scaling as with the enterprise it was to hear more and more about the cultural issues that are associated with adoption of agile stuff and But we hear about that when you're doing agile on a team we're doing on a program But as you get into broader engagement you often run into What do I call cultural issues or hard ways to develop alignment? But really the problem is the real big payout for agile investment is the broader skill adoption is the agile the ability to use those agile techniques to run the The portfolio so but we still have to overcome these cultural barriers somehow so The traditional business approaches and the agile value approaches need to somehow be reconciled So one thing that I'm hoping to do today is provide maybe some ways to make that bridge between the two walls And then also For this side, it's a particular it's very clear that agile has been extremely successful in software development And there's a lot of talk about including that talk right before this one about how those same ideas and principles could be applied to other areas and If that were the case then it isn't so much that Agile's works well because software is so peculiar But because there's something that about software development that is holding come with maybe lots of other things And in particular if what that is or a lot of what that has to do with is Managing through uncertainty it could very well be the case any time in any other domain where we have to manage through uncertainty We could draw upon the value of agile principles. That's what I want to explore today Nothing I want to do is just talk a little bit is in from my perspective And I imagine a lot of you share this with me as we think about where did agile come from? There's really two big traditions One of them is lean and one of them is complexity theory And it's really kind of almost a mash-up of a lot of these ideas that have given us the agile stuff that we use today And there's so much discussion and about agile today and scaling up today that it's lean lean lean lean I sometimes get concerned that there's actually not just lean There's actually other things that are fundamentally extremely important to consider especially I think when it comes to managing uncertainty I really do believe it's not so much that scaling agile means just go lean everything that's seen agile could be in lean But I think they complement each other quite a bit And especially when you look at lean from a waste reduction perspective as uncertainty Wises the danger for great great ways to increase it So there's a very good partnership between those two concepts and I think that is one of the reasons that the agile approach has been so powerful But today what I want to focus is less on the lean side more on the complexity side the other thing too is When we talk about Where does business culture come from word management principles come from they really come from? Some basis of a world view and then from that basis a world view management principles come up and they then Produce practices and governance ideas and finally we do the work So what I want to do now is kind of talk about it from a traditional business Ideas and principles. Where has that tradition come from? I want to start talking about a guy named Frank Knight And who was the first person who really made a big point about making a difference between risk and uncertainty? And when he talked about risk what he talked about was the idea that you may not know for sure what's going to happen But you have a pretty good idea what the probability of the different events are going to be like the perfect example of that Is for and dice is you don't know for sure if you're going to get two sixes or three and a two But you know the probability of what you're going to get And when people talk about risk, that's really what they're talking about They're talking about of the ability to make a projection into the future But that's based on probability distribution Information that is applicable and that kind of way of thinking which also is very closely related to the idea of maximizing utility and Expected value computations to figure out. What is the potentially greatest value that are risk? Managed if you will is very much a foundational block for how we approach business investment It's it's really where classic risk management techniques come from on the idea of the threat matrix What's the probability of the threat? What is the cost of the outage multiplying that out? That's when we think about risk management It's very hard to separate this idea of probability distribution and computation of value from an expected value perspective It's also how we think it when we think about rash decision-making This is what we're talking about and it's the approach traditionally that's taken in building business cases for business investments Now on the side of uncertainty What that's that's really in terms of what a knight said he says that's something else That's essentially when you don't know what's going to happen And you don't know the probability of something happening either And so it doesn't hit that threshold of being able to play any kind of rational decision-making is simply uncertain And he said at that point that you know when no one spent explored that very much We're not really sure this is back in the 20s, you know what we should do with this, but Most of the approach that people take is when they see uncertainty when they don't know enough They simply avoid that and do something else And in fact the idea of embracing uncertainty is considered irrational almost the definition of an irrational so what I want to do now is just kind of Talk a little bit about where some of these this risk analytical world view Where does that come from? What's that? What's we're looking at that for a broader perspective? And we were just talking about right night risk uncertainty and profit Now I'm going to go back a little bit in time to 1776 for Adam Smith in wealth nations And I'm sure many of you heard of that before and it's referred to all the time in a sense It's kind of the birth of capitalism in a sense so a way of a model to think about how people operate in the marketplace and It's very much predicated on this idea of people Washley making decisions to do what is in their best self interest We're going to talk a little bit more about that in a second There's also the principles of scientific management sometimes called Taylorism and this is this idea that often comes up in agile occurrences, etc. This whole notion of work Which is essentially? Mechanized and that what people are our skylight labor units and you try to optimize How much value can get out of them by extracting that labor by applying optimal mechanistic kind of algorithms to them doing work? But it's very consistent to with this kind of mechanized idea of what people do and how people operate and Then the Harvard Business Review, which everybody knows about was founded in the 20s and probably more than anything else is kind of the symbol of Taking the idea of business and applying analytical techniques to run businesses That's pretty much the culture the NBA culture apply analysis make good Calculated decisions go forward and then there's a theory of game and behavior This is by Von Neumann the same Von Neumann of computer science did a lot of different things and in this particular case He was one of the kind of co-inventors you might say a game theory And this is this idea of setting up simulations where if you will rational agents work things out and again the assumption is is that they're pursuing their individual interests so all of these ideas and Finally in 1971 B. F. Skinner, you know a psychologist if most people have heard about Who really focus the attention of Psychology not on the mind, but on what could be observed and That the whole idea there was is that the same reductive Principles that people use in physics and chemistry should be applied to the observation of human and animals And if you do anything else, it's nonsense So so it's not that people act rationally But you can't learn anything about people if you don't just observe them as you would be observing atoms for example Put all this stuff together. It's kind of this is where this Risk analytical world view has come from which started, you know Two or three hundred years ago perhaps even earlier it really matured and came into the maximum in that early part of the 20th century So let's look at what uncertainty then is how would you define that from a risk analytical perspective? And to a large degree what we could do is say that risk is simply the absence of knowledge The the risk analytical perspective takes kind of an enlightenment perspective about knowledge Which is essentially that you can learn things and as you learn things it just goes away To a certain to a large degree what uncertainty is is simply that you haven't learned yet Well, you will learn that then the uncertainty will go away and there's automatic progression as knowledge accumulates in society Progress is made and things work out When you don't have enough knowledge to make a rational Compute the risk if you will then that's what uncertainty is Knowledge in the risk analytical world is very much the kind of this idea of scientific facts These are enduring facts that you can fit into forms to develop causal relationships And and this is really how you estimate the risks and you make your predictions One of the key components of this whole idea is taking a logical analytical perspective of analysis of The environment and facts is that there's one only one right answer that is a best answer by definition There is a best answer and it can be discovered through analysis The other idea is that the same same people will come to the same conclusion because it's all objective It's all analytic and essentially just the way the world is wired people too Are pretty much the same in the sense that the rational self-interested Utility optimizing machines This is it's almost like you can imagine little doctor Spock's from Star Trek That's what people are and that's like the ideal form of a person. I'll try to pursue their individual interests And now yes, there are things like individual differences emotions Impulses, but that's considered Variants that isn't really considered how you characterize what people do what characters what people do is optimizing Utility in a rational way the stuff is kind of noise or it's waste or its weakness Now we take it from a social perspective And we're going to go back to Adam Smith who had the famous idea of how he talked about unintended consequences And what he said is is that everybody in the society the baker the candlestick maker whoever they are They pursue their individual interests and by doing that Automatically the maximum amount of wealth will be generated for the society And he said so they and hit that's how he defined unintended consequences that They didn't want to do that But a side effect of doing that it's the greater good for everybody and this is this this idea of the invisible hand That's guiding society as very much becomes the you know almost an article of belief these days and Capitalistic and democratic societies that is based on this idea that The world should be a level playing field the government or anything else should interfere let people work it out in the free marketplace Lose if your capitalism and the best outcome will happen. That's the pure theory. This is where it began Now the idea work in from this perspective is is very much comes out of the manufacturing tradition is very Production-focused and the value that people contribute is their labor and this labor is something that's essentially Commodity or fungible when I say fungible. I like to use this idea of the fungible work machine It's basically what that is like a function you put certain things in the input and you get a consistent output on the other side And the thing about the fungible work machine is that if you switch the person in and out It won't have any impact on the results So essentially people are fungible units. They do the work and that's really considered good. That's considered Optimizing getting real clarity in terms of what you're trying to obtain from our efficiency perspective So together this stuff makes up the risk analytical world and this really Riscalical world then is the foundation will view that the Management principles that are tradition management principles come from so I'm going to talk a little bit about what those principles are One of them identify the best solution because we said in principle you can't be discovered so You should achieve it. You should get it up fun And you should centralize information rather than distribute it in centralized management decisions because you're going to go all the same Conclusion anyway, there's no value in distributing things out since analysis will yield to the same conclusion Centralize get it done figure out what the best solution and then go forward He should do things right the first time by in principle because after all since you know what you're trying to do You could go with the optimal plan if you can do that then you should proceed That's that's the logical way to do it and you can apply external constraints down the road That means that once you know what the plan is in the objective You really can just set up constraints to make sure that whoever does what they do will be will do so and not go off plan And you should be able to leverage economies of scale because you can optimize the value We're trying to do you can say well How can I get the biggest bang for the buck as I do this and of course avoid uncertainty? So the risk analytical business philosophy is you centralized evaluation centralized planning and then production You come up with the best solution You do it right the first time with the optimal plan and In your leverage economies of scale the objective is to optimize your overall production and the styles algorithmic No, I say algorithmic what I mean is is that it's a very prescriptive Sequential step process first you do the evaluation in a stepwise manner Then you do the planning then you do the production and it's a sequence So the risk algorithm There's the zone of last one query where you do business And there's a that which is outside that zone So those are management principles From a business initiative perspective you start in the position of manageable risk The path to the values clear through the plan You manage variance and you get your um um and you do What you wanted to do So we just to look take a real quick way through this is our standard approach is You do the analysis You set a charter you get a comprehensive specification you implement the plan There's a little bit of variance But essentially you get the outcome that you expected because you're able to do the analysis up front set up the external constraints And it worked now from a risk analytical governance perspective You have the project charter which constrains the work to what the business case said You then have detailed plan of specification which constrains the production to the specification And then you take the big bang release to try to get the maximum utility out of the out of the release Risk is to manage an uncertainty is to avoid so the special work machine really is Is is set that is is provided a way to live in this world of risk analytical business culture From this perspective competition will gradually eliminate the low risk opportunities prudence this dictates that you don't Go into the uncertain zone So really you exploit business opportunities in this risk-manageable area an objective inquiry will generate opportunities What's excuse me But what if that doesn't happen today? We are a lot of our business uncertainty Over the last last year I know if it's still the case but us the large US corporations are sitting on more cash Than they ever have in history So they have more cash in history even though the economy is down and the reason is because they haven't been investing and Out of this this kind of world view that we're looking at that's what prudent dictates It's too uncertain to invest so you don't invest But it still doesn't really play with what we should expect because we feel as as progress continues We learn more and we certainly should we'd be reduced not increased So is this just an anomaly or something else going on is the question? So we can talk about what's driving business uncertainty. So let's take a little bit look at the history of technology very very briefly We start the stonage and invention of the wheel and ancient Greece finally came up with the principles for rational inquiry that Became the foundation for technology and science in the future and at this time Technology is evolving and it is increasing, but it's doing us such a slow rate It doesn't seem like it the change of technology is so slow that the things that are technical things in that's in your society Don't move. It's just like the watching the hour hand that doesn't change when you're looking at it the real sense we have our pre-class we get to the steam engine and then in the 20th century the that wages shoots up and So go wow What's going on here? If this were if if like a thousand years ago the rate of technology was so slow was almost like evolution Is there's animals out there and they don't change in any noticeable way so does the Now the technology changes so quickly would almost be like you will you go to sleep at night and wake up the next day And the the animal has changed into something else so if we look at in this graph right here what we see is is is how many years for subsequent kinds of technology has taken For 25% of US households to adopt that technology what we see is is that Radiation of new technology is is moving forward very very quickly We all know good old laws law which sets that foundation for a broader and broader Cheaper more comprehensive memory and computing power which drives this technology change And this rate of technology change goes up It puts pressure on product life cycles It's just a case we look at my space here and two or three years up into the tens of millions of users Then you see Facebook popping up is something I remember at the time of Facebook. Yes, like it's like my face It's like my space, but some university students use it. That's about I know and then before you know it Boom, it's it's taken off So when you look at it from this perspective From a traditional approach you make an investment you expect to return time that you're going to get that investment But if the product cycles are shrinking and the investment stays the same Then there's a danger of you're losing that investment and at certain point you may even Need to reduce the investment to get to some unacceptable return. So there's a lot of pressure there Okay, so technology is changing Very rapidly, but okay, so why is that a problem? I mean, what is that? What's that got to do with this after all progress is supposed to get better Maybe the full playing field is simply better and so people can have higher performance Just like tennis rackets today make tennis players much better than they were in the past But still then why do things seem to be more uncertain? Why isn't it just that things are speeding up and staying more and becoming more certain? They're not they're speeding up and becoming less certain So let's go to New Zealand like in the middle of the 1800s somebody introduced the rabbit and Before you know it the rabbit plagues that developed this was an unintended consequence Now the unintended consequence that we talked about before Was that the person that was the candlestick maker of the baker didn't intend to generate wealth for the whole community? This is a different kind of unintended consequence. This is an unintended consequence where it's unexpected So by definition it can't be predicted So what causes these? Well, there's the idea of the platform effect and this is something If we in evolution One of the big problems that I'm sure many people have heard about is if evolution makes these ground for changes And how could the eye ever exist and where did it come from? And sometimes people come up with the idea of intelligent design as an explanation for that Well, so there might have been some there had been some plan that foresaw that's what it was trying to do But there's an alternative solution or there's many other explanations But one of us by Stuart Kaufman is this idea of the platform effect and that is is that when there's an incremental change just because there's a slight change in the the organism because of a change in the DNA that creates a little bit of a change in the platform Which opens up a new kind of opportunity for that organism that didn't exist before So and then as time goes on literally the eye emerges for that kind of random random walk In working with the environment and we can think about the technology change in the same way is that when there's a new Technology platform it opens up new opportunities Immediately that nobody could have guessed beforehand. We see this happening to you all the time We see how cell phones lead to texting etc etc etc And when we think about the technology platform the large Technology platform the internet really everything together that base just allows things to go quicker and quicker and quicker because it can be leveraged up But the same time It is It introduces options that no one had anticipated Now the other thing too is is that in the last 15 20 years The idea of like how people water has changed quite a bit So there's a book a judgment under absurdity heuristics and biases and What they did is they did a lot of experiments to see how rational people really are so here's one example You receive a thousand dollars everyone gets a thousand bucks You get to choose between this to now think about this You can have a 50% chance of winning a thousand dollars or nothing or five hundred bucks for sure make your choice Okay, now I'm going to give a different situation You receive two thousand dollars Now choose between the following a 50% chance to lose one thousand dollars or lose five hundred dollars for sure So this first case most people choose a The second case most people choose B You form a maximum utility perspective They're exactly the same thing if you logically look at it It's the same outcome by how they're playing in the one case is framed as you're going to get something the other case You're going to lose something and that's enough to really change the behavior of people People hate to lose more than they hate to win. It's in our hard wiring And there's a host of examples of other things There's they've done studies where they looked at the length of sentences that judges give and as they get hungrier The sentences go up. So if you people are like really making the kind of they make rational decisions an important circumstances You wouldn't expect that to happen and it goes on and there's many many different examples That really defy logic David Cohn and one of the co-authors of this book Receive the the first psychologist to receive a Nobel Prize in economics Which really announced us to show where this early 20th century idea of economic marketplace rational agent It was the same is now we've got these quirky people out there and who knows exactly when these quirky people Won against this rapidly changing economy. What's going to come out of that? So the extent rate of technology change really increases the rate of unexpected consequences And they have a bigger and bigger because of the platform effect There's more and more unexpected things that can happen and the nature of these unexpected consequences Disturbs what might be just the natural wrapper progression towards something and moves it off into some other direction So this kind of messes up this idea of That the world is more or less rationally wired And they're going to converge on optimal that to me that there's a lot of wild cards Things are changing all the time and as a technology changes rapidly then Uncertainty is going to increase because of unexpected consequences So this means this few and fewer good bets But if you don't do anything that's a problem because those are changed so much What was a secure investment in the past is always is not necessarily going to last tomorrow So you have to continue other things So we have no choice but to start to begin to invest now In where maybe 30 years ago from a from a Harvard MBA Perspective would have been an improved and we'd invest money. So Uncertainty is inescapable Um The we can't avoid it like we could with the risk of electrical approach And this is a different kind of uncertainty. It can't be avoided. There's a lot of it, and it can't be predicted And this technology accelerates on unintended consequences start to breed like rabbits and we disrupt this rational analytical ecology So what do we do? now We've kind of talked about how it doesn't seem to fit But I think the natural inclination is that we just try to fine-tune and work out better Those practices that it worked us in the in the past Calculating rest of his work. Let's apply the same techniques. Let's do it with more with broader more sensitive confidence intervals Let's do it in a more sophisticated way and thereby reduce This is so we're going to just kind of whip through this scenario that we saw before But now was before we would have had more information. We decided to proceed anyway because We if we don't do anything, it's also a risk So a shaky that means we don't have the spec and we all know this story We have the flood implementation plan and the progress There's no way to change to learn as you go and the outcome is to spend the money But it's not it's not a good deal, so here we have a situation Where the tool? Maybe is not the best tool for the nature of the problem that we have in front of us So the question is maybe we need different tools What we're seeing here is that the work is an outcome isn't working And we saw there is that the very government structure that worked in the traditional approach no impeded success in This later approach so the practices and governance don't work either Which means then the management principles may be suspect and even the approach that we've been taking from a world view so If that's not right Then what should be so here we're going to go and we'll now talk about another set of ideas We're going to start here at the Heisenberg uncertain principle here in the sense was kind of like the limit of Reductive science was at this point you finally discovered that there is a limit of being able to discover through science direct causal relations and That wasn't expected And now we're going to do this is the kind of beginning of the chaos Theory with the whole idea that we've heard so many times about is that the butterfly Happening here could create the hurricane down the road And I'm going to be literally true But what it means is is that there's also phenomena at the macro level at the larger level that defies causal analysis So there's found in the world that just the way science has been dept in the world it where we've done in the past It's aren't going to help us as we go forward We've got the structure scientific revolutions was this idea of the pair word paradigm was almost invented by this guy is the idea that that people first of all Scientific breakthroughs don't happen in a rational linear way that happened and people when a new idea hits the scene People resisted tremendously until finally breaks through but when it does that new paradigm can be a completely different way to look at phenomena that's seen before And then of course we have fractals fact is the idea that It has been applied more and more in complexity theory that very very simple rules can would be responsible for incredibly complex phenomena And we talked about this Alan Greenspan was chairman of that Federal Reserve Board in the United States was in 1996 Talked about a rational exuberance right before the dot a combust He was actually a student of night and that was that kind of thinking people aren't acting rationally But boom this phenomenon is happening anyway And then we've got Steve Johnson He also wrote a book called emergence that talked about simple rules and swarm behavior in just I think a couple years ago But this book we're good ideas come from and look back at the history of technology and and points out that even though we think of Big inventions and technical breakthroughs has been attributed to a single person that in fact it almost always is the product of Collaboration with many people over a long period of time So when we started here We're now here and this is this summer when the Harvard Business Review on the front cover says embracing complexity So in a sense, we're starting to see even though complexity is something that in the agile world has been talked a lot about It's it's really starting to bleed over into mainstream thinking David's known a few years before that in the Harvard Business Review I had this quote in where he introduces in the Harvard Business Review the connection framework where he said the time is brought to broad and traditional approach to leadership and From a new perspective based on complexity science. So what might that be? so like the risk analytical world we can look at the different the Complex world and other kinds of worlds we'll talk about here in a second as how we range from a certain to uncertain but they also different represent different ontologies what I mean by that is that Water is water When it's frozen as liquid when it's gas it has a really different state and therefore the tools that you use when it was ice Are not going to work so well if when it's liquid or steam if you were able to walk on ice and you hit Water you couldn't you'd have to go around you'd have to avoid it and we can think of them that then as Okay, so as we go from one mode From the and go to the other we cross over and now the nature of things has changed such that the tools that made sense before No longer apply and we need new tools So very briefly we could take you know a simple thing is cause relations are self-evident as an example Ask fault distributor put it on the streets. It's very straightforward And we take as an example of what's complicated is this is very much Exactly what we're talking about from that risk analytical perspective where you take knowledge you do analysis make predictions and Explore and kind of make bets and and see what you can do Now these together really very much Compunt with what we were talking about before but now we're going to go to this idea of complexity and here now The solution is an emergent which means that it was not predictable beforehand and you have to learn as you go You can't know up front and the plan is going to evolve with the emerging solution and Certainly can't really escape And green energy I'll use that as an example to make it you know and where there's all this interest and all this money In figuring out how to enter the green energy market But we're no one knows how it's going to come out No one knows what the standards are going to be no one's with the plant platforms are who's going to win Our things going to be done centrally distributed. It's it's emerging It's happening but it's unsettled And then the chaotic is really such a dead area where there's so much turmoil that just no coherence There's nothing you can do I'm so to speak to get some business value from that so If we look at it, you know today We're the business opportunities the simple business opportunities are long gone or as soon as a good one pops up Competitive forces will push it away Caddox is the opposite really leaves this complex adaptive and the risk of analytical places. These are the two different old views and So let's look now we talked about the risk analytical world and let's now look at the complex adaptive world How might that be the same or might be different than what we talked about and as we discussed When we just look at uncertainty the root cause of absurdity is not just simply be the lack of information In fact, emergent phenomena cannot be have don't have no outcomes yet. They're part of the landscape No amount of research under those conditions are going to yield the best solution So if we think about Knowledge in the complex adaptive world There's few hard facts that we can count on things that are happening in real time So there's a huge dependence on tacit knowledge as opposed to hard factual knowledge this tacit knowledge is the knowledge It's in our brains. It's not somewhere in a book that you can read it needs interpretation The value of information is changing and tentative and different perspectives need to try realize if you will The stuff that we're seeing to make sense of it And that's good how we do with collaboration and we're We have this different idea of a person is we're not just a robot that's maximized utility much less the same way Um We actually have multiple perspectives and those multiple perspectives are really important through collaboration to actually understand What's happening with emergent phenomena? And that's in fact how emerging new ideas take place so instead of having all these new agents with the the We'll put this together and take Steve Johnson's idea of collaboration as being the way that new ideas emerge It's it's really people sharing ideas thinking about those ideas going back and forth Which is where value comes from in this complex adaptive world And the nature of work is is different too whereas before here we the operating Paradigm for work isn't so much production But it's more like knowledge work. It's more designed than manufacturing here the the as I mentioned the tacit knowledge helps us Reveal what's going on through collaboration And it's also important here too that whereas before we could take a person out and put another person in and the outcome would be Same now when people do design work under these circumstances you change the person the outcome is going to change too So all of a sudden the importance of people as individuals all of a sudden is extremely important whereas before it was almost variance And we can put these two side by side and we can see that they're very qualitatively different from each other So the risk analytical business culture doubts that were always before Maybe resolved by a study to replace him with a complex of active world view And now here we've got the would now be the complex of death of adaptive management principles now For this audience This is kind of the usual suspects and what we're seeing here. What I've done here is try to take some Some basic principles out of agile approaches and show them as as kind of management Principles that we could look look at that we can compare to the management principles of before And they encapsulate a lot of what we expect to see in an agile type environment And I would go through In tremendous detail in this right now I want to Just kind of highlight a couple of things here first of all this notion of sharing information Is really important whereas before we talked about centralizing information and the reason was was because The analysis that one does on information is going to yield the same results So there's really no value in distributing it out But in a situation where ideas emerge through collaboration with people in different perspectives You need to push Information out so you can get multiple perspectives to really understand what's going on and in fact You don't even know you don't even know what information to share You don't know what might come of that. So just the basic principle of information sharing Is is a key notion and shows how different the same concept could be done seems so differently from a two different perspectives Just to kind of lay these two side-by-side and note some of the differences Whereas before in principle, we could identify the best solution here from a complex adaptive perspective You have to make iterative progress because conditions are changing Whereas before we could do it right the first time in this case We really to address feedback and change course and according to that We're applying external constraints in an algorithmic way or just to make sure that people didn't deviate from the course The plan made sense in the traditional approach Really facilitating self-organization and collaboration is what needs to be done in this world Because you don't have that information and you don't have the knowledge to do that It has to be discovered by the people that are closest to the problem People are production units so much as their ink their idea incubators And this is a really different perspective and they have different needs and different, you know situations so this was a risk analytical business philosophy and Well, we've done is we take those that evaluate Production which were step one step two step three in the algorithmic approach and we kind of do a mash-up with those And we iterate through those things applying these principles using the feedback Through the iterative progress and the frequent delivery to get more feedback and continue in a systemic way To get results and involve the solution over time and of course that solution is just like that emerging technology We're talking about is that there's possibilities that come in the complex adaptive world But that one can't really replace the other we actually have both there's a need of both the world of course has both There is ice and liquid and steam. We cannot not see the other We just have to all know of you to have both perspectives So as we looked at before we had this idea that we started a place to the management risk We get our plan and the value Is what was predicted Now in a situation where we might say that if we if the world was covered with ice And there was a few lakes which is maybe how it was in the early 20th century And we could safely walked on ice But then we hit water and then you just go around it or avoid it But with global warming all of a sudden there's huge lakes all over the place There's not as and you can't you you actually get stuck where you have to somehow traverse that water You have to navigate it somehow so really then that's what the situation is today Is we have to start much earlier than we normally would like to and the nature of the world in that place is Liquid as opposed to frozen is that's why we need the new pool that a new way to we need a boat We need to learn how to swim and then come that you get isn't the one that you knew you're gonna get us the one that emerges over time so How do we reconcile these two worlds? The most of the 20th century The risk analytic carried more weight and in fact as we saw the tradition this whole risk analytical tradition started You know 200 years before the 20th century Well, we also saw that in the latter part of the 20th century these other ideas started to pop up what I didn't I didn't mention before was The tipping point that most people have heard about and the tipping point is a popularization of how complexity works in society in the world the idea that that progression sometimes Have incremented the steps and then boom something transformational happens. That's how complex systems behave And if if I you know 500 years ago technology was so slow It wasn't it didn't change any more maybe even less than the tree outside your house and today it's changing weekly You need a different kind of approach to think about how to live in that world which is filled with the emerging technology That's rapidly changing So that's starting to carry more weight and as that happens, you know Perhaps we are reaching a tipping point where it's not that the risk analytical world doesn't exist But the filter that we want to look at things is more from a complex adaptive perspective Less from that rational analytical perspective if you look at the risk analytical perspective Complexity is that a certain thing? It's kind of annoying on getting out of the way But if you look at it, but risk analysis, that's Chris extremely key We don't want to that's that's important. We can't be successful without it But if we look at it from a complex adaptive perspective, our world view is more kind of naturally innovative We're focused first on innovation optimization second So now we've got these new management principles That we've been talking about And we can kind of go back to that problem case that we had a moment before where the traditional governance Given the current situations of higher uncertainty were a bad fit And we can do is start to talk about a different kind of governance that we can now apply to substitute the traditional business case project charter comprehensive specification and first of all do is is explore this idea of real options Real options is a concept that's talked a lot about in the agile community often in conjunction with lean and And we're often familiar with it the idea of like deferring the decision to the last responsible moment Which if you think about it as a very practical perspective in a very uncertain emergent set of circumstances Here I want to kind of focus on a different aspect of real options Which is that if there's if you look at a business case that's uncertain When we look at that is that there's a bunch of open variables that That need to be constrained before it could get to a point that you could get to a threshold to say yes So real options then becomes a way to explore those ideas and those options and you can kind of go one assumption at a time Validate Disprover or prove that it's legitimate and then move to the next step and as you do that process I mean they also come across new assumptions new ideas and so in a very Immersion sort of way you can either discard the idea or move on to another one This is also an exploratory activity that could be done at a very small cost compared to doing you know committing the capital to do a whole project with just a little bit of information and So if we think about that comparing the approach that of the traditional approach of start with expectation of idea solution and then manage the variance To you get to your goal Here with the real options approach in this uncertain environment you start with a lot of possibilities and Over time you explore new options and you've actually refined these ideas and at that point Then you get to a point where business cases start to make so we take that idea That small best can help determine direction And then if your business case emerges Proceed but keep it open we'll talk a little bit more about that in a second and then of course we'll apply as a project management Which we're all familiar with and when we do these things together we work together as a system And this is kind of a different than to because like the algorithmic approach is first you do this thing and then this You know and then you're done and then you move on to the next then you do this thing And then this artifact goes with that etc. This is a different scenario Where we're essentially Intererating on this whole process is that we we start with the real options It leads to emerging business cases We mix in investment we get feedback We decide to increase that investment or decrease that investment it may lead to a new idea goes back into the real options We do only frequent delivery to get market feedback So the idea is to keep the cycle going keep the cycle going and Having a collaborative framework to exchange this information This is going to be one of the key things is is that in the IT community these days where Agile's works well There's a set can be information radiation as it's through collaboration But even when it confronts the business with a different set of communication structures and policies There is no basis to do this kind of collaboration and one of the things we're talking about here Is that when the traditional part of the business is anchored in a traditional risk analytical world perspective? They see no reason to change on the other hand if they did Then there would be a way to have these common business principles could be applied across both areas And now they have something in common and of course we need to collaborate of course We need to share information and so this is a heuristic and adaptive process as opposed to a algorithmic process focused on optimization Excuse me. I do a time check here How much time do I have? 30 30. Thank you So now I'm gonna do is take that idea what I just showed you is something that could be applied To a program or a project But we're gonna do sense. Let's take this idea just try to move it up You know to this whole idea of like the enterprise and see what might happen So if you take the idea of business strategy and is is that The people that are making investments the ones that are sitting on the cash in the US corporations They're aware of the situation. They're looking for their concern about these risks They have motivation to come up with a different way to make changes And if you think about it what that time cycle and technology change where if in the last 20 years that rates changing it's not going to slow down What that means is is that there is the world landscape can change within a budget year can happen very easily So if you're stuck to an annual cycle to make those types of decisions from a strategy perspective even a longer cycle Then how you gonna adjust? Okay, I'm trying to say that there isn't coherence in a long-term perspective You know and there's an abstraction of business strategy that should be persistent and and important to persist But I think a lot of what people have called business strategy in the past and thought about something can do very rarely Really is going to need to adapt more frequently and the income of the year which 30 years ago might send quickly enough To look at it again decide if we change may not be quick enough today And the way that's going to happen is through feedback is through information sharing and collaboration and Integrating that knowledge throughout the organization to feed on what the strategy should be Capital budgeting to them very closely related is the annual plan for capital budgeting Also, there's we still in the annual process That's the expectation that we have in the marketplace, etc But but the kinds of decisions sometimes that have been made at the animal basis and they're not they don't look at it Again for a year those things perhaps there should be subject to a more frequent change One idea is to Allocate capital to different kinds of sectors. So for example, if you had to use our own example stuff in the green energy area and Something else that was like your traditional platform, which is kind of a cash cow The the policies that you do for business cases in one perhaps shouldn't be the same for the other Perhaps that would be in the green energy area the place to put down a fair amount of money in the real options kinds of Exploration maybe either feed several emergent business cases to use language that I talked about before with the expectation that maybe 75% of them will fail, but that has to be compared against the danger of sitting on the silence and If you if you've got a technology or service that is likely to be transformed through what emerges on the green marketplace You can't afford to do that. So this provides a way to play Now finally here it is is this is kind of like, you know, the shiny Castle on the hill. This is the big deal right as a portfolio management That's what people are looking for us. What they're talking about. Although. I think for the most part It's a very big fuzzball that means many different things to many different people But in this context, let's say what this is what it means first thing is as a portfolio management is active portfolio management and if you think about it, if you think about it just on a personal finance perspective is that a Portfolio management strategy is one where you put down a bunch of stocks and bonds that are diversified and Then no matter what happens you do nothing Because if you do something you're actually going to probably do more damage than good is the idea Okay, so so even though there's both things in the marketplace You ignore that because the idea is over time that some of these things will head you out and you'll end up maybe a little bit Better than average That's a portfolio management strategy. It's predicated on doing very little Now an active portfolio management strategy is what we're actually want to respond to what you're learning Okay, so you have to be you have to be able to do that and one thing I haven't focused on I want to stress at this point is That this possibility of agile portfolio management did could not exist until the the whole IT organization was agile Because if only a part of the IT our organization was agile It would allow enough it wouldn't able to look at the whole portfolio The idea is that you have to see all those resources that could potentially be Reallocated to grow other projects or downsize to grow another one and have to work in this type of environment Understand how operate in this environment. So so it's natural that we haven't heard a whole lot about agile portfolio management until a recent Time because there hasn't even been any possibility of doing it until now now What I want to say is is that if you're a single product technology company actually you can't there You know, it's a different case right because the technology product company and the business Are pretty much doing one thing we're getting the product out the door They're very much in alignment in that regard Especially when it's a one product company or things are organized by product divisions where you're pretty much doing your own thing There's a natural alignment in that case But we take but what we're seeing today is actually the majority of people who are doing agile today You are not in the software product area simply because I don't enough people in the software product area to account for all the people Speaking software development More of them vast majority of them and this will continue as time goes on are in tech in Companies that aren't first and foremost to technology companies. They're in retail. They're in banking. They're in finance But they're heavy users of technology Their portfolio management is a much more difficult situation because you have all these different vested interests They're trying to leverage the same cost center so the resistance to change and the size of getting people to agree and the What's really going to keep you the agile from expand to the next level is we're trying to figure out how can we communicate? effectively with that typical corporate perspective You know where You know to get to this next level, so I also want to do to say that The idea here is is rather than you kick off a project from the PMO And it's an 18 month project and all you just check in to see if the money's being spent and then hope for that You know, that's all going to work. No, there's actually more rigorous quality review concept where there were certain assumptions that were made There's new information needs to be evaluated And then you recompute the business case on the basis of that and the size is still a valid business case And by the way those real options things they popped up some new ideas in the middle of the year Now this whole business case has to compete against this. This is a different perspective than the entrenched interest All I'm going to do is get my project funded then I'm clear, you know It could be the worst project in the world doesn't make any difference that decisions You know the trains left the station so to speak this idea is a different idea that that idea the business case It's open tentatively but has to be proven and proven and proven and proven this works If there's a way to communicate in the Robert continuous way on these things in this case poorly is continuous Also, we have what we talked about risk adjustment, but we also need to start talking about uncertainty adjustment and This is something that we're talking about a solutions IQ and I don't know that I have a complete handle on that But I would say this is that that model of risk that we talked about before which is kind of an expected value model Is not what I'm talking about here risk is important and at some point risk computation needs to be part of the calculation I'll tell you more about like a volatility measure like an analogy where if you say look at the stock market or the prices of Commodity there's times where it's very very volatile and other times that it's not So we can think of uncertainty more as a volatility measure in terms of an emerging marketplace And that then becomes it needs to be a way that we discount our return expectations And if that's the case then it becomes immediately evident that instead of putting a whole lot of money in two or three investments We distribute this out, you know to in quite a few other and immediately the opportunity and likelihood of us being able to make progress Or had successes there. I sometimes think about that too is that Well, I better not go to that right now Persistent teams all of a sudden now seem just more and much more justifiable We like in the edge of rule to say there's value persistent teams and we want we we want those teams We know that's true and we have a lot of intuitive arguments for that is But now I have a even kind of a management principle based argument The idea is is that these persistent teams as idea incubators Have invested in each other And lovers to retain as developed as collaborative power and and the ability to do this tacit knowledge integration Okay, so that if you disassemble that you have to rebuild it again Okay, and that's the lost value because it was from a management perspective what you needed you need to create this Environment that allows these ideas to be formed nurtured and bought it brought to marketplace So we put this all together And we have our innovative enterprise We're the center of this is is this concept of the active portfolio management Which is really kind of the the where the ceiling management and the people working on the teams This is the idea exchange We're on that poorly heartbeat Decisions are made does this still make sense? Do we double down? Do we drop it? Etc. There was not a prejudice towards something simply a some cost We have tried to escape that some cost mentality that what we've invested in this much far We need to do it anyway ruthlessly not look at things like in those terms And this is the way that the organization anyway the organization can become adaptive can be more look at the world in a more collaborative way then in a risk analytical optimization kind of a way so Now what we do is with these new governance techniques We have a fitting governance for the type of work that we're addressing That fits a lot better than we had before And finally and so this idea incubator this this focus on knowledge Manage knowledge work as opposed to production work or I should say Physical production work is got the right framework for it to be successful Time please how much yeah, how much time do I have? Okay, good Questions