The importance of forgetting to creativity and innovation

Science fiction author Spider Robinson won the 1983 Hugo Award for Best Short Story with Melancholy Elephants. It’s a prescient take on an essential tension between creativity and commerce. Still worth reading. More worth contemplating.

Robinson explores where the boundaries of creativity might lie and what those boundaries might imply. There are tradeoffs to be made between the needs of artists and the interests of art as a whole. Those tradeoffs have artistic and economic consequences and striking the balance is by no means as self-evident as they might appear. Here’s the nub of his argument in his own words:

“I think it comes down to a kind of innate failure of mathematical intuition, common to most humans.   We tend to confuse any sufficiently high number with infinity.”  


For millions of years we looked at the ocean and said, ‘That is infinite.   It will accept our garbage and waste forever.’   We looked at the sky and said, ‘That is infinite: it will hold an infinite amount of smoke.’   We like the idea of infinity.   A problem with infinity in it is easily solved.   How long can you pollute a planet infinitely large?   Easy: forever.   Stop thinking.  

”Then one day there are so many of us that the planet no longer seems infinitely large.  


The ultimate bottleneck is this: that we have only five senses with which to apprehend art, and that is a finite number.


“Artists have been deluding themselves for centuries with the notion that they create.   In fact they do nothing of the sort.   They discover.   Inherent in the nature of reality are a number of combinations of musical tones that will be perceived as pleasing by a human central nervous system.   For millennia we have been discovering them, implicit in the universe–and telling ourselves that we ‘created’ them.   To create implies infinite possibility, to discover implies finite possibility.   As a species I think we will react poorly to having our noses rubbed in the fact that we are discoverers and not creators.”  

Go read the whole thing. It won’t take you long, But it will leave you thinking.

Problem-findng on the Path from Invention to Adoption

The intersection of two key dimensions of how we think offers an interesting insight into the path from new idea to successful innovation. Alan Kay discusses them in a talk he gave last year at Demo 2014 called “The Future Doesn’t Have to Be Incremental.” It’s an excellent use of your time, if you’re prepared to think about what Alan is saying. Alan can be a deep and a dense thinker; he’s the kind of teacher where it might take days or weeks before the argument he is making hits you with its full force. This is our problem as the student; not Alan’s as teacher. Consider yourself warned as well as encouraged. The payoff is worth the effort.

If you want to skip to the part of the video I want to examine today, go to the 18-minute mark. The first dimension he addresses is how we respond to new ideas or tools when they appear. Most of us (95% per Alan) respond to a new idea or tool in an instrumental way; we evaluate the idea in terms of how it might advance our current agenda. Our default response is WIIFM—what’s in it for me? One in twenty of us, however, asks a more generative question—should I revise my agenda based on this new idea? This difference in attitude is essential to invention.

Another way to characterize this is whether someone reacts to a new idea in a closed or an open way. A closed response to a new idea treats the idea in terms of how it advances an existing agenda or goal, while an open response maps to Kay’s notion of reacting to a new idea in terms of how it might modify, reshape, or obsolete a current agenda. While WIIFM may be the question in either case, the shift in stance is important.

The second dimension Alan explores is that of extraversion/introversion. I find it more helpful to think of this dimension as your compass; is it social or personal? Do you look to the group for your primary source of direction or do you look inwardly. Again, more than 80% of us take our cues from the group. We are, after all, social animals.

Taken together, we get the following diagram, which I’ve scaled to reflect the general 80/20 proportions at work:

NSC-AlanKayInventionInnovationGrid-2015-02-10

These dimensions aren’t completely orthogonal, but they do set up an interesting set of questions about invention and innovation. Work gets done by the grand majority of people who are tuned into the social matrix and see new ideas in terms of how they can advance existing agendas. At the opposite end of the diagonal, new ideas are generated by the few percent who don’t pay much attention to the social matrix and are on the prowl for truly new ideas.

The challenge is that you need both groups to collaborate to generate big innovations. This collaboration is hard because the mindsets are so different from one another. The greater burden, I suspect, lies with the inventors (broadly writ). They are the ones who must walk their thinking back from what might be to what can be done now and set a path forward that avoids the temptations to settle for the incremental.

This is a leadership task. And not simply a visionary exercise in painting the future in an attractive and compelling way. It depends on some ability to anticipate key forks in the path and to recognize the risks of alluring junctions that lead to the incremental rather than the transformative. Essentially the leadership task here is one of problem-finding and problem-framing; it is about directing the problem-solving capacities of the organization toward a future that is not simply a straight line projection of the present.

Using Moore’s Law in Reverse: Alan Kay on Invention vs. Innovation

I’m an unapologetic fanboy of Alan Kay. This can be problematic given that the average person has no idea who Alan is even though they benefit from his work on a daily basis.

Earlier this year, Alan presented at the Demo 2014 conference, offering his reflections and insights on the relationship between invention and innovation. It’s about 45 minutes in total and well worth the investment of time and attention.

Although Alan doesn’t say so explicitly, he suggests that we have become so enamored of innovation that we are systematically neglecting invention. If you spend time reflecting on Alan’s observations you get real insight into the difference between strategic and tactical thinking.

Alan Kay on innovation and risk

Here’s a pointer to an excellent interview with Alan Kay. As always, Alan shares some deep insights about technology innovation and the willingness to take on risk (he’s not confident in the ability of most organizations to tolerate risk no matter how small the level of funding involved).

Anyone with an interest in the continuing role and development of Smalltalk has had lots to chew on over the past few days.

As part of a series of investigations into the most widely-used programming languages, Computerworld Australia has published a conversation with Alan Kay about his role in the development of the foundation of much of modern programming today: Smalltalk-80 , Object-Oriented Programming, and modern software development.

The Weekly Squeak: Smalltalk: the past, the present, and the future?
Michael Davies
Thu, 15 Jul 2010 10:00:45 GMT

Here’s a sample of Alan’s thinking :

What are the hurdles to those leaps in personal computing technology and concepts? Are companies attempting to redefine existing concepts or are they simply innovating too slowly?

It s largely about the enormous difference between News and New to human minds. Marketing people really want News (= a little difference to perk up attention, but on something completely understandable and incremental). This allows News to be told in a minute or two, yet is interesting to humans. New means invisible not immediately comprehensible , etc.

So New is often rejected outright, or is accepted only by denaturing it into News . For example, the big deal about computers is their programmability, and the big deal about that is meta .

For the public, the News made out of the first is to simply simulate old media they are already familiar with and make it a little more convenient on some dimensions and often making it less convenient in ones they don t care about (such as the poorer readability of text on a screen, especially for good readers).

For most computer people, the News that has been made out of New eliminates most meta from the way they go about designing and programming.

One way to look at this is that we are genetically much better set up to cope than to learn. So familiar-plus-pain is acceptable to most people.

[ComputerWorld Australia]

Alan can occasionally be a bit cryptic, but that’s because he assumes that you will do your share of the thinking when you listen to what he has to say.

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Can you design business models? A review of "Seizing the White Space."

[cross posted at FASTforward blog]

Seizing the White Space: Business Model Innovation for Growth and Renewal, Johnson, Mark W.

What is a "business model" and can you create a new one in a systematic and disciplined way? That’s the question that Mark Johnson, chairman of the consulting firm Innosight, sets for himself in Seizing the White Space.

The term entered the popular business lexicon during the dotcom boom in the late 1990s. There wasn’t any particular definition behind the term at the outset. Effectively, it was shorthand for the answer to question zero about any business – "How are we planning to make money?" Before the dotcom boom, nine times out of ten, the answer was "we’ll copy what Company X is doing and execute better than they do." During the boom, the answer seemed to be "we have absolutely no idea, but it’s going to be great." Now we recognize that both of those answers are weak and that we need some theory to design answers that are likely to be successful.

Over the last decade and a half, there’s been a steady stream of excellent thought and research focuses on building that theory. One of the major tributaries in that stream has been the work of Clay Christensen on disruptive innovation. Christensen and his colleagues, including Johnson, have been engaged in a multi-year action research program working out the details and practical implications of the theory of disruptive innovation. Seizing the White Space is the latest installment in this effort and is best understood if you’ve already invested in understanding what has come before.

Johnson starts with a definition of white space as

the range of potential activities not defined or addressed by the company’s current business model, that is, the opportunities outside its core and beyond its adjacencies that require a different business model to exploit

p.7

Why do organizations need to worry about white space? Even with success at exploiting their current business model and serving existing customers, organizations reach a point where they can’t meet their growth goals. Many an ill-considered acquisition has been pursued to plug this growth gap. Haphazard efforts at innovations to create new products or services or enter new markets get their share of the action.

Johnson combines an examination of white space and business models in an effort to bring some more order and discipline to the challenge of filling those growth gaps. One implication of this approach is that the primary audience for his advice is existing organizations with existing successful business models. He is less interested in how disruptive innovation processes apply in start up situations.

Johnson’s model of business models is deceptively simple. He illustrates it with the following diagram:

Johnson-WhiteSpace-Four-BoxBusinessModel

Johnson expands the next level of detail for each of these elements. Most of that is straightforward. More importantly, this model places its emphasis on the importance of balancing each of these elements against the others.

In the middle third of the book, Johnson takes a deeper look at white space, dividing it into white space within, beyond, and between which correspond to transforming existing markets, creating new markets, and dealing with industry discontinuity. It’s a bit clever for my tastes, but it does provide Johnson with the opportunity to examine a series of illuminating cases including Dow Corning’s Xiameter, Hilti’s tool management and leasing program, Hindustan Unilever’s Shakti Initiative, and Better Place’s attempt to reconceptualize electric vehicles. While the organization of the stories is a bit too clever, it does serve a useful purpose. It takes a potentially skeptical reader from the familiar to the unfamiliar as they wrap their heads around Johnson’s ideas.

With a basic model and a collection of concrete examples in hand, the last third of the book lays out an approach to making business model innovation a repeatable process. This process starts from what has evolved into a core element of Christensen’s theories – the notion of "jobs to be done." This is an update on Ted Levitt’s old marketing saw that a customer isn’t in the store to buy a drill but to make a hole. The problem is that most established marketers forget Levitt’s point shortly after they leave business school and get wrapped up instead in pushing the products and services that already exist. "Jobs to be done" is an effort to persuade organizations to go back to the necessary open-ended research about customer behavior and needs that leads to deep insight about potential new products and services.

With insight into potential jobs to be done, Johnson’s four-box model provides the structure to design a business model to accomplish the job to be done. In his exposition, he works his way through each of the four boxes, offering up suggestions and examples at each point. With a potentially viable design in hand, he shifts to considerations of implementation and, here, emphasizes that the early stages of implementation need to focus on testing, tuning, and revising the assumptions built into the prospective business model.

Johnson clearly understands that creating a new business model is a design effort not an execution effort. Seizing the White Space puts shape and structure underneath this design process. All books represent compromises. The compromise that Johnson has made is to make this design process appear more linear and structured than it can ever be in practice. He knows that it isn’t in his emphasis on the need to balance the elements of a business model and  to learn during the early stages of implementation. There’s a reason that the arrows in his four-box model flow both ways. I’m not sure every reader will pick up on that nuance.

He also clearly points out the role of learning from failures as well as successes during implementation. But the demands of fitting the story into a finite space again undercut this central lesson. The models here will go a long way toward making business model design more manageable, but they can’t make it neat and orderly.

This review is part of a "blogger book tour" that Renee Hopkins, editor of Strategy and Innovation and Innoblog, arranged.

Previous stops on the tour:

Upcoming stops

If you’re interested in digging deeper into the work of Clay Christensen and his posse, here are some previous posts where I’ve pulled together some reviews and pointers. I hope you find them helpful.

Innovating innovation: An Interview with Scott Anthony of Innosight

[cross posted at FASTforward blog]

Scott Anthony of Innosight Back in late May I got an email from Renee Callahan who edits Strategy and Innovation asking if I wanted to be part of a "blogger’s virtual book tour" for Scott Anthony’s soon to be released book, The Silver Lining: An Innovation Playbook for Uncertain Times. Who could resist? Especially for a book I was planning on reading anyway. I’m one of five bloggers speaking with Scott about his first solo book, The Silver Lining. The first three interviews can be found at

 

and Boris Pluskowski will wrap it up tomorrow at The Complete Innovator. One excellent fringe benefit of this effort is discovering four new bloggers worth following.

Scott is the President of Innosight, a boutique consulting firm founded by Clay Christensen of the Harvard Business School. I caught up with Scott two weeks ago just after his return from trips to England, Switzerland, and Singapore. Clearly Scott was going to benefit greatly from the virtual aspects of this book tour. You can find my review of The Silver Lining at Constraints and innovation – is there a silver lining? What follows is an edited transcript of our conversation. I’ve also added links to supporting ideas and materials that we referenced during our conversation.

Chunking innovation processes

The Silver Lining advocates breaking the innovation process down into smaller chunks so that you’re not betting on a single roll of the dice. What lessons do you think you’re learning about managing the innovation process?

Scott: If you break things down into enough component pieces, you increase the odds that luck will turn in your favor. And that too goes to the whole notion of having a portfolio. If any one thing doesn’t work out that’s OK because you’ve got something else right behind it.

Now, you can take that to an extreme. You couldn’t take the notion of "let a thousand flowers bloom" inside a company because they can’t manage that kind of complexity but there is something to be said for having eggs in more than one basket.

That’s an interesting observation about the organizational capacity to manage complexity and dealing with the tension between the level of granularity you might like to have vs. the level you’re capable of managing. What about the rhetoric pushing for more market like processes within organizations?

Scott: Even the poster child of the full market approach, Google, is saying ""Hey, something isn’t quite working here. We need to instill a bit more rigor and discipline in these innovation processes. Because while we appear to be great at inventing, we aren’t great at actually innovating and creating an income statement that has more than 3% of our income in something other than search based advertising."

Innovation factories and their limits

How has Innosight’s mix of work shifted from finding and designing individual innovation ideas to putting more structure and discipline around the innovation process?

Scott: Not surprisingly, the mix has shifted toward the latter, although the two are inextricably linked. Five years ago, 80-90% of our work was "I’ve got this ideas, what do I do with it?" or "I don’t have any ideas, can you help me come up with some?" Today,50- 60% of our mix is "I need to build capabilities so this isn’t a one shot deal. How can I create an ‘Innovation Factory’ so I can churn out businesses."

I’m always a bit suspicious of factory analogies around knowledge intensive processes. How have you managed to create disciplined innovation processes without killing real innovation?

Scott: It’s a really delicate balance, There has been academic research that shows that the better organizations get at six sigma kinds of processes, the better they get at incremental innovation and the worse they get at disruptive innovation.

The notion that there is discipline in innovation is absolutely critical. The notion that disruptive innovation can be managed and can be mastered is absolutely critical. But you have to also recognize that it’s an intensely human effort so you cannot treat it the same way as an assembly line. I use those metaphors with some caution inside companies, because I know someone will ask me for the forms to be filled out.

P&G is one of the companies I’ve drawn examples from in the book. I know them and they’ve been very generous in sharing their experiences.That’s one of the sources of tension inside the company. They are a very process focused organization and have great stage-gate capabilities. What we’re telling them is that for some of these things you’ve got to trust the gut and intuition of a human being. If you don’t do that, you’re going to make the wrong decision. Some people are comfortable with that and some people are getting there.

Lessons learned about innovation processes

Have you found methods or practices in the way you deliver your intellectual capital or ways to structure the process and its metrics that have proven particularly effective?

Scott:If you go back to The Innovator’s Guide to Growth, which we published last year, versions of the qualitative measures we talked about in Chapter 6 are proving helpful. These qualitative and light quantitative measures help

The other thing we’ve come to believe is that it’s hard to do disruptive innovation in particular democratically; to be something that works at a grassroots level. Senior leaders either need to create a situation where there’s a great deal of organizational autonomy and people don’t have to go through standard operating procedures, or they’ve got to get personally involved. Otherwise, the efforts just stall out at some point.That was always in the literature, but from the field experience we believe it even more strongly.

Interesting…in other areas, such as the Enterprise 2.0 space that Andrew McAfee describes and the organizational changes triggered by new forms of collaboration technology, you see an argument that the grassroots is the place to start. Is it the particular characteristics of disruptive innovation  that means you’re going to need a level of organizational air cover to succeed?

Scott: I’m absolutely sure that is the case. There’s a classification scheme out there which would make it clear how to handle a particular innovation. It could be fit with the business model, or degree of certainty you have, it could be degree of fit with your current capabilities. It’s certainly clear that there are things that not only can be done at the grassroots, but have to be done at the grassroots to work. But there are other things where if you don’t have the ”grasstops" leading in the right way, it just will not work. You need to have that supportive environment or the grassroots just wither and die.

Isn’t there a third level where you have to have a level of senior leadership engagement beyond the level of simply providing a supportive environment?

Scott:I’ve seen two benefits from this. One, a senior leader can do things that other can’t. A senior leader can route around existing processes in ways that a line manager can’t.

There’s a second thing a senior leader is able to do. Typically senior leaders haven’t got where they are by accident. They got a lot of informed judgment and intuition about industry space. Now, for some people that can lead to them having blinders on, but for others it gives them a tremendously good feel for a market space. That makes them hugely value-added team members, if you can get them to act in that kind of role. They know a lot from their accumulated experience and that allows them to say "that might work, but you need to do it this way" or "we tried this in 1973 and it didn’t work. If we made this change it might work today."

Value of shared frameworks about disruptive innovation 

Isn’t the challenge there to equip senior leaders with a better feel for the underlying intellectual capital? To make sure they’re equipped with the right vocabularies and distinctions so that they don’t short circuit the process with "we tried that in 1973 and it’s not going to work."

Scott: There’s a huge role in all of this in having a common language in order to support the necessary culture change. It’s important to have those common frameworks, those common guides to discussion. The other thing that I really strongly urge senior leaders to do is to make sure they are bringing in different voices to these types of discussions.

It’s very easy to fall into the 73 trap of "we tried that and it’s not going to work." An outside person can say "yes, but it’s now 2009 and these are the three things that are different." You just don’t understand the unstated assumptions you are making until someone states them.

Jobs to be done

I’m struck by how the notion of "jobs to be done" appears to be a centerpiece of your work. It feels a lot like Ted Levitt’s old observation that people don’t buy drills because they like drills but because they need to make a hole somewhere. I’m curious as to what you see as the strengths of that element of your intellectual capital and where you see the limits and edges of that particular idea.

Scott:  "Jobs to be done" isn’t a new notion at all. You can reference Levitt and you can go back to Drucker’s observation that your customer is rarely buying what you think you’re selling. In the world of innovation Dick Foster had pointed out many of the same phenomena in his work in the early 1980s. The hard part in these things and what Christensen did was to get the causal mechanisms and language right. He gave people a language to talk about it and tools to do something with it in a useful way.

That to me is the hard part about the ‘jobs to be done’ notion. The concept is easy. The hard part is what do I actually do with these intuitively appealing stories as a line manager?  Providing that next level down to break this apart into a fundamental problem of a job to be done, some performance metrics to measure how well its being done, the barriers customers face, and some potential new solutions for them is the challenge. I think we’re maybe in the second or third inning of at least nine to go in terms of developing the tools and approaches that can really help people crack the nut on this one.

To be honest, I’ve been surprised about this. I remember back in 2002 when I was working with Clay and he was working on The Innovator’s Solution. In a very early draft of the book, Clay thought that the biggest idea in the book was the notion of jobs to be done. He wanted to call the book "Getting the Innovation Job Done." I told him he was crazy. The idea was too simple and I had to believe that people had already solved this problem.

As I’ve since learned, Clay’s intuitions were right. It’s an elegantly simple idea and not a new one at all. What Clay did was provide a language system and tools to work with the idea in a useful way.
I have to keep reminding myself of what Bob Sutton and Jeff Pfeffer pointed out in The Knowing-Doing Gap. Having the right tool or framework only solves about 5% of the problem. It’s why we exist as an organization. If people could just read books and have the answers to everything, there would be no need for them to hire Innosite, McKinsey, Bain, or any other consulting firm. The knowledge is all out there, but actually doing it inside a large, complicated organization is very challenging.

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Constraints and innovation – is there a silver lining?

The Silver Lining: An Innovation Playbook for Uncertain Times, Anthony, Scott D.

The Silver Lining is positioned as a case for the strategic value of innovation in economic downturns. It evolves into a reflection on the role of constraints in innovation and on the possibility of successful innovation within large, complex, organizations. Scott Anthony, the author, is a former student and current colleague of Clay Christensen and is President of the boutique consulting firm Innosight. The book was conceived in October of 2008 and the manuscript delivered to HBS Press in January and offers itself as a good example of the value of tight constraints. (Here is the obligatory book website)

The Silver Lining presents a succinct, focused, argument for how to do effective disruptive innovation within existing organizations. This runs contrary to the research conclusions in Christensen’s The Innovator’s Dilemma that linked successful disruptive innovation with new entrants not industry incumbents. The management practices of successful market leaders emphasize the prudent deployment of resources to address clearly understood problems and clearly meaningful opportunities. Those practices are about coloring inside the lines. Disruptive innovation goes beyond just coloring outside the lines to redrawing the lines and creating entirely new pictures.

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A reader’s guide to Clay Christensen and disruptive innovation

[cross posted at FASTforward blog]

A dozen years ago, at the height of the dotcom boom, Harvard Business School professor Clay Christensen published The Innovator’s Dilemma. It started from a simple observation that transformative innovations that reshaped competitive landscapes and created new industries almost invariable came from new organizations. Conventional wisdom held that this was a reflection of poor management and decision making on the part of incumbents. Christensen started with a more interesting, and ultimately more productive, question. What if it was sound management practice on the part of incumbents that prevented them from investing in those innovations that went on to create new industries? This question and Christensen’s research led to his distinguishing disruptive vs. sustaining forms of innovation. I originally reviewed the book in the Spring 1998 issue of Context Magazine. It became the bible of consulting firms working in the dotcom space. Every proposed idea was labeled as disruptive. Who knows, some of those consultant’s might even have read the book.

Meanwhile, Christensen and his colleagues and collaborators continued to work out the ideas and implications of his emerging theoretical framework. The Innovator’s Dilemma was followed by

  • The Innovator’s Solution: Creating and Sustaining Successful Growth.

    In this book, Christensen begins to lay out how you can take the notions of disruptive innovation and use them to design a reasonable course of action in the absence of the kind of analytical data strategy consultants desire. Disruptive innovations attack either the lower ends of existing markets where there are customers willing to settle for less performance at less cost, or new markets where a new packaging and design of available technologies creates an alternative to non-consumption. The example I found easiest to understand here was Sony’s invention of the portable transistor radio. Compared to vacuum tube radios the first transistor radios were crappy, but good enough for teenagers and others on the go whose alternative was no music at all.

  •  Seeing What’s Next: Using Theories of Innovation to Predict Industry Change.

    In this third effort to work out the implications of distinguishing between sustaining and disruptive innovation, Christensen and his collaborators shift their attention from individual competitors to industry level analysis. They take their theoretical structures and apply them across several industry settings and ask how those particular industries (education, aviation, health care, semiconductors, and telecommunications) are more or less vulnerable to disruptive innovation strategies. What Christensen and colleagues are doing here is to begin integrating their innovation theories and Porter’s theories of competitive strategy. This is not so much a case of seeing whether their new theoretical hammer can pound strategy nails as it is of whether they are making progress in creating a new and robust toolkit for strategy problems.

  • The Innovator’s Guide to Growth: Putting Disruptive Innovation to Work, Anthony, Scott D.

    This volume is written by Scott Anthony and several other collaborators of Christensen who are putting his ideas to work at the consulting firm Innosight. They develop the next level of operational detail to transform strategic insights into execution details. If you re an organization seeking to develop its own disruptive strategy, the authors here have worked out the next level questions and identified the supporting analyses and design steps you would need to answer and complete. This volume is not a teaser; it s complete and coherent. You could pretty much take the book as a recipe and use it to develop your project plans. On the other hand, the plans by themselves won t guarantee that you can assemble a team with the necessary qualifications to execute the plan successfully. The other thing that this book does quite nicely is identify the kinds of organizational support structures and processes that you would want to put in place to institutionalize systematic disruptive innovation.

This core of books would equip you with a robust set of insights and practical techniques to begin thinking about when and where you might attempt to develop and deploy new products, services, and business models in disruptively innovative ways. The one area that is underdeveloped in this framework is that of design. There is an implicit bias in the material that tends to keep design in the "perform magic" category. I believe this is part and parcel of the general execution bias of business literature in general. Design is flaky, creative, stuff and real managers distinguish themselves on execution. But that is a topic for another post. These books belong on your shelf and the ideas belong in your toolkit.

More on management and messiness – video interview from FASTforward’09

Joshua-Mich le Ross did an excellent set of interviews at last week’s FASTforward’09 conference. We talked some more about the challenges of managing innovation. Here’s the video for those of you who might be interested.

FASTforward 09: Jim McGee, Managing Director of New Shoreham Consulting

by Joshua-Mich le Ross

February 11, 2009 at 11:15 am Filed under FASTforward’09, FFC09 Interviews

Jim s comments focused on two basic themes. On the plus side is the notion that the heavy lifting of search is being hidden from end users who can t/won t learn to do sophisticated search queries on their own. On the mildly troubling side is something that he posted to the blog about this afternoon. As Jim explained, that post addresses the following notion: one of the management challenges being glossed over in the marketing focus of the conference is that managing search implementations and enterprise 2.0 implementations runs counter to the sense of order that makes most managers comfortable.

To manage these changes requires managers to become much more comfortable dealing with a messy environment. More importantly, perhaps, they need be careful lest they cripple innovation and experimentation by imposing an inappropriate level of management overhead and structure on these efforts. Technology management has become gunshy in too many organizations about technology project failure. They need to be careful to not take those lessons over into Enterprise 2.0 or they will kill the necessary degree of innovation we need to see.

BIO: Jim McGee: For over 30 years, I ve helped executives and organizations become more effective by making better use of information and communications technology. I ve attacked these problems as an entrepreneur, senior executive, professor, author, blogger, speaker, systems developer, designer, and consultant. Today, I work with senior executives in organizations to formulate, structure, and solve problems in the effective use of information technology in complex knowledge work settings. I am adept at working with organizations to recognize patterns and make sense of complex situations. My clients and I then collaborate to design and build new business patterns and practices to take advantage of these situations and opportunities.

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Business models for health care: Andy Kessler’s take on the future of medicine

The End of Medicine: How Silicon Valley (and Naked Mice) Will Reboot Your Doctor, Kessler, Andy

 

Andy Kessler is a former Wall Street investment analyst turned author. He learned his trade following Silicon Valley and its successful, long-term, obsession with Moore’s Law. In that world, as technology scales, costs fall predictably, and new markets emerge. In The End of Medicine, Kessler takes to the world of health care and medicine to discover how and where that underlying investment model might apply. It’s an interesting premise and, despite some annoying stylistic quirks, Kessler delivers some real value. It doesn’t get to anything remotely like an answer, but it collects and organizes a lot of useful information that might help us get closer to one.

Kessler opts for a highly anecdotal style; presumably to put a more human face on a large, complex, subject. For me, he overshoots the mark and loses the big picture. The color commentary overwhelms the underlying story line, which was my primary interest. But there is a good story line that is worth finding and holding on to.

Medicine’s roots are in making the sick and injured better. Triage is baked into the system at all levels. Observe symptoms, diagnose problem, apply treatment, repeat. Over time we’ve increased our capacity to observe symptoms and have gotten more sophisticated in the treatments we can apply, but the underlying logic is based on pathology. Also over time, a collection of industries have evolved around this core logic and these industries have grown in particularly organic and unsystematic ways.

Kessler runs into these roots and this logic throughout his journey. However, coming from the semiconductor and computer industries, as he does, he doesn’t fully pick up on their relevance. As industries, computers and semiconductors are infants compared to medicine and health care. Not only do Kessler’s industries operate according to Moore’s Law, but they are structurally designed around it. His analysis of health care identifies a number of crucial pieces, but he stops short of assembling a picture of the puzzle.

Kessler focuses much of his attention on developments in imaging and diagnostics. Both areas have seen tremendous advances and hold out promises of continued technological development similar to what we’ve seen in semiconductors.

Imaging is a computationally intensive area that benefits fully as an application of computing technologies. What is far less clear is whether the current structure of the health care industry will be able to absorb advances in imaging technologies at the pace that will let Moore’s Law play out in full force.

There is a second problem with imaging technologies that applies equally to other diagnostic improvement efforts. As we get better and better at capturing detail, we run into the problem of correctly distinguishing normal from pathological. While we may know what a tumor looks like on a mammogram what we really want to know is whether that fuzzy patch is an early warning sign of a future tumor or something we can safely ignore. The better we get at detecting and resolving the details of smaller and smaller fuzzy patches, the more we run into the problem of false positives; finding indicators of what might be a tumor that turn out on closer inspection to be false alarms. Our health care system is organized around pathologies; we fix things that are broken. Because of that, the data samples we work with are skewed; we have a much fuzzier picture of what normal looks like than what broken looks like.

This is the underlying conceptual problem that efforts to improve diagnostics and early detection have to tackle. Kessler devotes much of his later stories to this problem. He profiles the work of Don Listwin, successful Silicon Valley entrepreneur, and his Canary Fund efforts. Here’s the conundrum. If you detect cancers early, treatment is generally straightforward and highly successful. If you catch them later, treatment is difficult and success is problematic. Figuring out how to reliably detect cancer early has a huge potential payoff.

The kicker is the word “reliably” and the problem of false positives, especially as you begin screening larger and larger populations. If you have a test that is 99% accurate, then for every 100 people you screen you will get the answer wrong for one person. The test will either report a false positive – that you have cancer when, in fact, you don’t – or a false negative – that you are cancer-free when you aren’t. As you pursue early detection, the false positive problem becomes the bigger problem. Screen a million people and you will have 10,000 mistakes to deal with, the vast majority of which will be false positives. That represents a lot of worry and a lot of unnecessary expense to get to the right answer.

Kessler brings us to this point but doesn’t push through to a satisfactory analysis of the implications. Implicitly, he leaves it as an exercise for the reader. His suggestion is that this transition will present an opportunity for the scaling laws he is familiar with to operate. I think that shows an insufficient appreciation for the complexities of industry structure in health care. Nonetheless, Kessler’s book is worth your time in spite of its flaws.

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