Innovation: The Paradox of Constraints

If you've worked in a group on a creative task, you may have noticed how constraints can spark innovation.

This article from the WSJ (Chains That Set Us Free) discusses some of the experimental evidence.

And, this article on groupthink from The New Yorker is a nice summary of the history of the technique of brainstorming (thanks for John Ganter for bringing it to my attention), along with a refreshing discussion of why the lack of constraints in brainstorming seem to make it a relatively ineffective approach to innovation.

There seems to be a bit of a paradox here: many formal innovation activities that focus on the removal of boundaries to get folks "outside of their box" result only in shallow thinking.

This is consistent with my experience where such exercises usually result in bland lowest-common-denominator ideas with little new value.  What seems to help is the creation of new "boxes" that help highlight and break existing (often unseen) boxes.  Here's a few boundaries I've seen that helped unearth creative ideas:

• Identify key resource constraints in the domain under discourse and play with scenarios where they become either 10x more constrained or 10x less constrained.  This highlights the constraint structure of the problem/solution landscape in a way that can help identify radically different solutions.  IT-intensive domains are especially susceptible to this approach; even though we understand Moore's Law at a cognitive level, it's usually very unclear how that affects a solution space.
• Keep the group size to five or less.  If you don't, the more assertive members will tend to define and structure a discourse landscape that's largely inside the boxes they know.  If you keep the group small with diverse subject matter experts (see the next bullet), "ritual dissent" tends to emerge organically.
• Ensure that group members are subject matter experts in a different, but related, areas ... the goal is to force discussions about non-obvious, but key, underlying assumptions.  The tendency toward lowest-common-denominator solutions means that each member should be at or above the level of innovation you're trying to achieve.
• Don't use a formal innovation process ... recipes generally produce minor variations of existing ideas instead of something new.  Using Complicated approaches in a largely Complex domain is a common mistake.
• Incorporate multiple cycles of focused discussions, unfocused discussions, focused thinking alone, unfocused thinking alone.  Ideally, scatter these over a period of weeks to months.  Ideas need time to percolate. 

Hope that's not too much of a recipe ... :-)   Dave Snowden's "management of the emergence of coherence within attractors within boundaries" remains for me the best succinct description of any type of exploratory activity in a largely Complex context.

Social Media, Emergence, and Telos

MIT's Sloan Management Review recently published an interview with Anthony Bradley and Mark McDonald about their new book "The Social Organization: How to Use Social Media to Tap the Collective Genius of Your Customers and Employees."

I was encouraged to see them emphasize the need for Purpose in the creation of effective social media-based communities.  There's a lot of money being thrown at corporate social media with a "build it and they will come" / "emergence magic" mindset.

Social media with no coherence, boundaries, and attractors is Chaos.  Internet-scale chaos works for socialization purposes where individuals form their own informal communities.  But, even the largest companies will probably find the intersection of "bottom-up" communities and the company's key exploratory activities relatively small.

Within a company, purposefully working to "manage the emergence of beneficial coherence within boundaries, within attractors" would seem to be an essential partial constraint on social media.

Seems like we prefer mindless solutions: an algorithm at one extreme or "emergence magic" at the other.  Managing complexity (and complicatedness) requires intention and mindfulness ... drones need not apply.

Identity as a Learning Disability

Two recent articles on identity's effect on learning caught my eye.  Both seem to lean toward the possibility that Identity inhibits learning when it focuses more on what I am (we are) than on what I do (we do) ... ontology vs. action/telos.

• "Why Do Some People Learn Faster?" - Wired blog post discussing a new study showing that academic accomplishment is increased by praising effort and inhibited by praising ability.  My reaction: seems like more fallout from a century-old societal shift  from Christian skepticism about fallen humanity to secular optimism about human perfectability.  For more, see Freud , John Dewey, the birth of modern progressivism.  The therapeutic mindset, so strange barely a 100 years ago, is now so pervasive as to be invisible.
• "Can Everyone Be Smart At Everything?" - KQED covering much of the same ground.

This is one of those topics that quickly becomes a lightening rod for all kinds of noise. I suspect it's  not productive to allow culture war issues associated with identity to detract from the task at hand.  As someone who loves to create stories (and despite my antipathy towards pragmatism as a worldview), I liked this quote from a recent Peggy Noonan column:

"Here's the problem: There is no story.  At the end of the day, there is only reality.  Things work or they don't.  When they work, people notice, and say it."

Data Priori Computing

A year ago I discussed the possibility of an emerging frontier of computing ... "smart machine, smart human".  Instead of me sitting in/on a machine's hard-coded data processing loop, the machine uses a mesh of sensors and processors to look over my shoulder and anticipate what information I need to maker better decisions.

It's a "machine on my loop" instead of "me in/on a machine's loop".

Walt Mossberg's WSJ review of a new browser add-on called Digital Folio made me wonder whether smart computing will be more about data than function.  What makes Digital Folio compelling is that it's tightly focused on one type of data (price) within a specific context (shopping), and that the add-on has been designed to smartly and unobtrusively weave "just enough" additional data into the user's sensemaking work.

At a more general level, I'm beginning to wonder if the primary "smart machine" design challenge is to make it fun for the novice user to "play" with them.  And, to make it unobtrusively slip into the user's normal sensemaking flow.
If that's the case, then what makes a smart machine fun/playful?  Here's some snap reactions on a design approach:

• Identify the one/few data items that are the "pivot points" of a decision/sensemaking context.  For Digital Folio, these include the product and its price, along with the context of shopping for electronics equipment.
• Identify what makes these data item(s) most intriguing within the context ... specifically, determine how the core data item values/relationships shift between ambiguity and clarity.  For Digital Folio, price is the key data item.
• Finally, create a compelling "in-the-flow" user interface so that a novice user can "play with / probe" the data and its connections within a specific sensemaking context.

The design work order ....

• Identify key data within a specific sensemaking context
• Design a UI that  (a) makes key data/connections compelling, (b) allows the user to immediately see interesting possibilities in the data/connections, and (c) enables the user to easily explore the data/connections
• Define the required functionality

... reverses the typical machine design process:

• Define function(s) that automate one or more tasks
• Create a user interface for a specific user community-need
• Design the data schema

Since the user's key sensemaking/decision data precedes everything, I thought the term Data Priori Computing captured the overall concept which:

• focuses on sensemaking-centric data (traditional computing focuses on machine-function-centric data)
• leverages the user's contextual flow of sensemaking data to create a framework for the emergence of presentation and function, possibly guided by the user's interaction with the data
• is a context-centric bundle of data-presentation-function where the data is a tightly focused nexus around which all sensemaking and decision making revolves (it is not BI or data mining)

BTW, when I googled "Data Priori" the only place I saw this term used in a similar way was "The Global Data Palette: Massive Databases and the Reformation of Content Creation in Film/Video and Music/Sound Art Practice" ... data-priori movie-making.

Deloitte Report on Social SW in Business

Deloitte has released an interesting report on the ongoing effort to discover how social SW can create real value in an enterprise.

It's a helpful reminder that social SW in business requires much more than "build it and they will come", since a business's stakeholder community has neither the size nor the scope of the Internet.

And, it emphasizes the need to focus on outputs (eg, value-added) instead of inputs (eg, adoption rates).

There are several challenges discussed:

1. Employees must gain some basic familiarity with the tool. While some Internet-based knowledge will transfer, business-specific tools will have their own learning curve, even if they're based on common open source SW.

2. Employees must discover how the tool can help them do their job better. There's no recipe for this, and I suspect that existing roles & processes will have to remain largely intact during the initial adoption phase. One employee at Alcoa is quoted as saying "One day it just clicked for me. ... That's when I started seeing Traction help me do my job better."

3. There's a bit of an ontological mismatch between the formal teleological structures of a workplace (processes, roles, organizations, etc) and the unstructured (mostly) telos-free landscape of social SW. A "deer in the headlights" response is entirely appropriate. Add in employee workload and a relative low level of employee engagement, and you're looking at a daunting task to (a) find potential high-value, low-cost bridges between "as-is" and "to-be", and (b) build critical mass once promising bridges are identified. This mismatch seems to grow exponentially as the size & bureaucracy of the business grows.

None of this is Simple or Complicated; it's definitely "managing the emergence of beneficial coherence within attractors within boundaries" (Snowden).

Deloitte asserts that the need for these tools is becoming critical as work is increasingly characterized by activities with significant Complex (exploratory) aspects (page 7).

Figure 3 lists five "unique" capabilities of social SW:
1. Identify expertise
2. Facilitate cross-boundary communication & conversation
3. Preserve institutional memory
4. Harness distributed knowledge
5. Discover emerging opportunities

Unfortunately, there seems to be little, if any, awareness that these tools are unlikely to be used effectively for these purposes unless there's good social connectivity across the business. There's a "chicken-egg" problem here that folks like Dave Snowden have addressed with such activities as Social Network Stimulation. I'm not sure I see much awareness in this report of how critical this issue is.

The discussion of metrics (pp. 9-11) made me slightly uneasy (eg. "Recipe for Success"); an understanding that there's a risk that a metric will become a goal (thereby ceasing to be a metric) seems to be missing. A boundaries/attractors approach would seem to be more effective; maybe this was done for the OSIsoft example, but if so, it's not clear. It seems more of a "build it and they will come", though that may just be retrospective coherence.

Figure 10, a "Social software capability and tool heatmap", may be the most interesting part of the report. My initial reaction was that the ratings (eg, a Prediction Market is rated as Low for "Preserve institutional memory") might be a bit simplistic, but they're still interesting. I suppose you could try to envision scenarios where a rating is completely wrong if you find the table offensive.

Bottom line: the overall approach feels more Complicated than Complex; I kept thinking that a sensemaking approach (eg, construction of a Cynefin map) would be much more effective in identifying and exploring how to best use social SW in a business context. Although there are hints that the authors understand this (pp. 16-17), I would have thought that they (John Hagel and John Seely Brown) would have spent more time discussing Complex needs and approaches.

A Flat World is Noisy

Much (negative and positive) has been written about Thomas Friedman's 2005 discussion of globalization ("The World Is Flat"). A key enabler of globalization has been transportation, communications, and information technologies.

The current issue of the Sloan Management Review has an article discussing leadership in this context ("Flat World, Hard Boundaries - How To Lead Across Them", Ernst & Chrobot-Mason).

A few snap reactions (which are equally applicable to the use of social media inside an organization):

1. A flat world is noisy. Although the opportunity for amazing new "signal" emerges in a flat world, the risk of increased noise drowning it out is real. Brokers of various types used to manage this risk in the physical world. Increasingly connected and transparent individuals and organizations are almost bereft of tools to manage this risk in the virtual world.

2. Focus becomes much more important in a noisy world. At the same time, leaders are much more constrained in their ability to control & command focus. They are left with a largely complex task; in Dave Snowden's memorable phrase "managing the emergence of beneficial coherence within attractors within boundaries." At the same time, they are largely unprepared to either recognize or effectively engage complex contexts.

3. As a result, leaders must simultaneously address at two difficult and novel issues: increased noise, and managing complexity.

The six boundary-spanning practices the authors discuss are not inherently bad. I'd feel better, however, if they emphasized the need for these practices to be introduced in the context of very specific customer-driven tasks and goals. Without that focus and discipline I'm afraid the authors' advice could easily be warped into some sort of "happy-clappy" initiative where generic "do-good" activities do more to breed cynicism than success.

Misc. Sensemaking Items

• Figure 5 of this AF report has sensemaking woven all through it
• A human-intensive approach to defeating IED attacks shows promise
• Our understanding of how to weave the mindful and the mindless (i.e., unordered and ordered) is immature at best; see, for example, experiments in easing traffic-related "boundaries"
• "Self-evident computing"? ... something about "self-evident" grates, but the basic idea reflects the trend toward weaving technology and sensemaking
• Sensemaking always has a teleological aspect ... a good, if rambling reminder, from one social media commentator
• A key driver for sensemaking is the explosion of IT-based solution spaces and the associated need to constrain them enough for useful innovation to occur
• More evidence of just how utopian the dreams of singularity are ... and of the vast gulf between IT and neurological structures/processes
• As someone who has taught Statistics, I liked this discussion of the scientific method and statistical analysis. It highlights a basic fact: getting really good data is the hard part; the numbers are easy. And, despite a few exceptions, it shows that any statistical discussion of a complex system (and all biological systems are complex) is very vulnerable to mis-interpretation.
  

SW Development Archetypes

Forrester analyst Jeffrey Hammond has published a report on Software Development Archetypes. In it, he describes 3 archetypes: Solid Utility, Trusted Supplier, Partner Player. Based on his description, these seem to map to the Simple, Complicated, and Complex domains of Cynefin (using Cynefin as a taxonomy).

Since the report is behind a paywall, see slide 16 of this recent presentation by Hammond on open source software and lean development for a summary of the archetypes.

Smart Machine, Smart Human

At the risk of being simplistic, I'm starting to wonder whether the evolution of information tools might not be something like the following:

1. Dumb machine, dumb human - hammers, shovels, etc. (caveat: I'm not dissing the craftsmanship of a Michelangelo...I'm talking about information)

2. Smart machine, dumb human - monolithic systems (e.g., mainframes) with a priesthood of operators that tend to them. "human on the loop"

3. Dumb machine, smart human - distributed systems (e.g. networked PCs, pre-mobile Internet) with humans using the machine as a "speed of need" information tool in a fixed location. "human in the loop"

4. Smart machine, smart human - adaptive agent-like chunks of IT that we weave into our everyday sensemaking activities everywhere we go. "machine on the loop"

The last stage is just emerging...Apple's amazing market cap is evidence of the potential value of such a combination. However, it is a complete paradigm shift (in the strong Kuhnian sense of the word) from machine-centric to human-centric

It raises a fundamental issue: how do you enable humans to easily create, monitor, and manage automated micro-models/narratives? And, do all this within the daily flow of sensemaking?

I mentioned one possible approach a couple of years ago...it seems awfully crude in retrospect and it does not begin to address the create/monitor/manage challenge (which is the real "magic" in the ecosystems that Apple has created).

The only widely used general user IT *modeling* tool I can think of is a spreadsheet (Project is a specialist tool IMO). However, spreadsheet modeling is not done "on-the-fly", so it provides no insight into how to weave micro-modeling into sensemaking flow.

The challenge posed by a smart human, smart machine capability is daunting; the potential is incredible. The good news is that the necessary pre-conditions are largely in place, the needed tools are emerging, and we have some good frameworks for thinking about how to go about architecting this kind of IT (e.g., Klein's Data-Frame, Cynefin).

Meshing Exploration and Exploitation

Earlier this year I posted a couple of items discussing how information technology seems to cycle through complex-complicated-simple-chaotic as a new capability moves from (a) a one-of-a-kind monolithic structure to (b) a partially decoupled structure to (c) a commoditized fully decoupled structure which then (d) provides a chaotic swirl of standardized components that are then used to create a brand new capability with a monolithic structure (Techno-Apocalypse and Business Models, IT, Architecture, Cynefin). I also alluded to the possibility that the time it takes IT to traverse this cycle is rapidly dropping...which may be one reason the whole Explore-Exploit contrast is getting more attention.

Anyway, I just ran across an OSCON (July 2010) presentation by Simon Wardley entitled "Situation Normal, Everything Must Change") that covers much of the same ground...though in a far more entertaining fashion. Highly recommended (even though I'm not a big fan of the "flashing/slashing graphics" style of presentation).

Explore and Exploit - some background

Although it's been several years since this compare-contrast first hit me, I suppose I should make a note of a few of the resources that helped me see that this view/pattern is probably widespread.

1. This first came from my thinking about the Cynefin framework (as a taxonomy, in this case) in conjunction with business processes and innovation...I first saw this as Discovery and Execution. This morphed into Exploration and Execution.

When I went searching for literature with these terms, I came across a number of items, including the following:

2. John Hagel and John Seely Brown's disucussion of Push Programs and Pull Platforms.

3. "When Learning and Performance are at Odds: Confronting the Tension", Singer and Edmondson, Harvard Business School Working Paper. See especially Figure 3.

4. Various HBS working papers by Tushman, et. al. Two that I found useful were:
"Organizational Designs and Innovation Streams"
"Ambidexterity as a Dynamic Capability"

5. "Strategy and Your Stronger Hand" by Geoffrey Moore (Harvard Business Review, December 2005.

6. "Organizing for Innovation in the 21st Century" by Deborah Dougherty (Rutgers Business School September 2004) - this has a nice summary of various approaches to innovation

7. "Planning: Complex Endeavors" by Alberts and Hayes - one in a series of publications about complexity and NCW that was published by the DoD's CCRP. This publication is the follow-on to Alberts and Hayes' "Understanding Command and Control", also recommended. If you're completely unfamiliar with how complexity science relates to organizations, Czerwinski's "Coping with the Bounds" is not a bad intro.

I'm sure there are lots of other (and much earlier) writers who've discussed this...these just happen to be some of the folks that helped me see what seems to be a basic pattern. Now that I think about it, Klein's Data Frame model covers this space well (i.e., "elaborate" is Exploit, "question" and "reframe" are Explore).

"Simple" IT

One possible indication of the end of the Dark Age of IT will be that "complex" has a negative connotation and "simple" has a positive one when used in conjunction with IT products/services.

Seems like the labels we currently use to describe IT capabilities tend to be more ontological than epistemological....I suppose there are lots of potential reasons why...one might be that there's no end in sight to the ontological task of creating IT models of "the world."

NCW Update

Recently the Defense Business Board recommended that the Assistant SecDef's Networking and Information Integration (NII) office be eliminated. With that recommendation has come a new round of "death of NCW" commentaries (e.g., Lexington Institute, Wired).

I hesitate to comment on these since I've done so before...but, I feel obliged to make two observations:

• These critiques continue to either misunderstand or mischaracterize the nature of NCW. They create a techno-centric strawman, one that makes war deterministic and neat. This is wrong...NCW is more about cognitive and social factors than technology. The core of NCW is improving sensemaking and decision making, with technology only a tool. Large technology-rich armies and small technology-poor groups of insurgents can both operate in a net-centric fashion. See, as previously mentioned, "The Implementation of Network Centric Warfare", especially Figures 5 and 11.
• The US has a bias towards technology and formal processes. So, it's not surprising that the US implementation of NCW theory has largely ignored its social and cognitive aspects. And, it's not surprising that, as net-centric technologies and concepts became pervasive, a central office (NII) for their promulgation became largely irrelevant.

Leaders Aren't Hoop-Jumpers

The American Scholar has published a speech that William Deresiewicz gave last year at West Point. Entitled "Solitude and Leadership", it has some observations about leadership that are similar to those made by the Hopper brothers in "The Puritan Gift."

I especially liked the following:

• An observation about kids at Yale...seems like this is the implicit goal of all large Western organizations these days...the creation of "excellent sheep."
  
  So what I saw around me were great kids who had been trained to be world-class hoop jumpers. Any goal you set them, they could achieve. Any test you gave them, they could pass with flying colors. They were, as one of them put it herself, “excellent sheep.”
• A comparison of Marlow's description of the Central Station manager in Conrad's "Heart of Darkness" with the stereotypical hoop-jumping bureaucrat:
  About the 10th time I read that passage, I realized it was a perfect description of the kind of person who tends to prosper in the bureaucratic environment. ..... it was a perfect description of the head of the bureaucracy that I was part of, the chairman of my academic department—who had that exact same smile, like a shark, and that exact same ability to make you uneasy, like you were doing something wrong, only she wasn’t ever going to tell you what. Like the manager ...... the head of my department had no genius for organizing or initiative or even order, no particular learning or intelligence, no distinguishing characteristics at all. Just the ability to keep the routine going ...
• On leadership:
  ...... for too long we have been training leaders who only know how to keep the routine going. Who can answer questions, but don’t know how to ask them. Who can fulfill goals, but don’t know how to set them. Who think about how to get things done, but not whether they’re worth doing in the first place. What we have now are the greatest technocrats the world has ever seen, people who have been trained to be incredibly good at one specific thing, but who have no interest in anything beyond their area of exper­tise. What we don’t have are leaders. What we don’t have, in other words, are thinkers. People who can think for themselves. People who can formulate a new direction: for the country, for a corporation or a college, for the Army—a new way of doing things, a new way of looking at things. People, in other words, with vision.
• On multitasking:
  Multitasking, in short, is not only not thinking, it impairs your ability to think. Thinking means concentrating on one thing long enough to develop an idea about it. Not learning other people’s ideas, or memorizing a body of information, however much those may sometimes be useful. Developing your own ideas. In short, thinking for yourself. You simply cannot do that in bursts of 20 seconds at a time, constantly interrupted by Facebook messages or Twitter tweets, or fiddling with your iPod, or watching something on YouTube.

I'm a little uneasy about some of the fuzziness in the author's description of solitude...nothing in, nothing out. But, I completely agree that we need time for things to soak in and we need to periodically take some serious time out to consider ideas that have been percolating.

Bill Gates' annual retreat is a bit too structured for me, but anyone who's serious about ideas has to occasionally spend a significant amount of time slowly chewing on core aspects of fundamentals (e.g., assumptions, constraints, coupling, connections, etc) of what matters most.

Nick Carr's upcoming book "The Shallows" looks to be an interesting look at how IT is "making us dumber."

Web OS Speculations

A couple of "must read" takes on the companies, architectures, and business models that will dominate the next wave of IT:

• Charlie Stross on "Why Steve Jobs Hates Flash". I thoroughly enjoyed Stross's "Halting State", so I'm always intrigued by his take on IT
• Tim O'Reilly on the "State of the Internet Operating System" (Part 1, Part 2) - O'Reilly's always worth reading, but these two (long) posts are "must read".

I haven't seen stuff this intriguing since the early Web 2.0 days....

"Thinking Traps" Trap

A couple of recent posts on "Thinking Traps" (Part 1, Part 2) are typical examples of discussions of how cognitive limitations can result in poor decision making.

While an awareness of this sort of thing is good, these discussions almost always focus on (a) specific biases, or (b) processes/heuristics that help compensate for or avoid these biases.

Those of us who design IT-intensive capabilities for expert use need something more substantive: models of how experts make decisions in the real world. Which is why I'm a big fan of Gary Klein's writing (e.g., Data-Frame, Sources of Power).

Techno-Apocalypse

Clay Shirky sparked a fair amount of dialogue about the dangers of what he called "Complex Business Models" in a recent post. This is an important topic that is not discussed enough, so I was happy to see him take a shot at it.

My snap reaction was that he was describing a dynamic that is (a) becoming commonplace, and (b) accelerating. This dynamic consists of the following:

• A concept/technology emerges.
• An almost "one-of-a-kind" capability is built (e.g., IBM's Stretch computer). This capability is tightly coupled internally, and certain aspects of it are not well understood.
• If the capability becomes more available (e.g., cheaper), fault lines in the internally coupling begin to emerge (e.g., plug-compatible peripherals). At this point, variations of the capability are created and adapted to different specific needs/uses (e.g., IBM 360).
• If the capability moves toward a mass market, key coupling fault lines will be institutionalized via de facto or de jure standards, and the capability will be built of interoperable components (e.g., IBM PC).
• Finally, these interoperable components and standards will provide much of the raw material for the creation of a new concept/technology (e.g., what has become the Web), starting the process all over.

The risk Clay discusses is real during the tightly-coupled phase of this dynamic. And, his concerns are becoming increasingly valid as (a) these loops are being traversed faster and faster for IT-intensive capabilities, (b) the interoperable components/standards ecosystem grows at an exponential rate, and (c) the transparency of a capability's structure (which allows critical dependencies to be seen clearly) decreases exponentially, at least during the tightly-coupled phase.

Complicating the Complex

Almost every week I see confusion caused by the lack of a vocabulary that distinguishes between Cynefin's Complicated domain and its Complex domain.

The latest incident was an article entitled "We Have Met the Enemy and He Is PowerPoint" in the 27 April New York Times. I was walking through the airport that Tuesday morning and was amused to see a familiar diagram above the fold on Page 1.

The article was the latest in a long line of critiques of the use and abuse of PowerPoint, including a dash of McLuhanesque "media is the message" thrown in for good measure. There's not much to add here...though I do find it slightly puzzling that the focus is almost totally on how the tool can/is abused, versus how the tool can/should be used to be effective.

Regardless, the graphic shown is the real story...it's a classic Systems Dynamics concept map that provides a good example of the limitations of trying to create a Complicated map of a Complex context. In defense of those who created it, I suspect that the conversations that went into creating it were valuable. And, as a focal point for an ongoing series of conversations about the social/cultural landscape, it probably has some use.

However, this diagram has inevitably left out key entities and linkages that are (a) rarely active, and (b) extremely important....i.e., it left out linkages that may provide the most leverage in achieving a specific contextually activated goal. If you're familiar with the Cognitive Edge tools and methods, you understand that there's a more effective way to address this kind of need. Unfortunately, most folks still lack the vocabulary to distinguish between the Complicated from the Complex and fail to realize that this "unknown unknown" would significantly increase their ability to effectively characterize a Complex context.

Cultural Perceptions

I ran across an interesting monograph by Christine MacNulty that discusses (among other things) how culture influences perception. A few snap reactions:

• p. 11 - a nice table contrasting how Eastern and Western thinking differs. Dave Snowden often points this out in his talks.
• p. 22 - alludes to a move "away from authoritarian epistemology of medieval religious doctrine"....while this monograph only touches on the emergence of modern science, this seems slightly simplistic. See, for example, Frances Yates' "Giordano Bruno and the Hermetic Tradition", Carl Becker's "The Heavenly City of the Eighteenth-Century Philosophyers", or Pierre Duhem's "The System of the World."
• p. 26 - places epistemology on a spectrum from authority-based to empirical - seems like a triad with the emotive at a third corner might be a bit more realistic (inspired by Cognitive Edge's patent-pending triadic scale)....I understand the reason for the over-simplification, but it still makes me cringe slightly... :-)

Anyway, it's an intriguing take on cultural analysis. Check it out if you have an interest in this sort of thing.

Business Models, IT, Architecture, Cynefin

Dave Snowden continues to hone his description of business life cycles in a recent presentation and podcast from the Henley KM Forum Conference.

His discussion coheres with thoughts I've be considering recently...how People, Processes, Organizations, and Technology intersect with Cynefin. Here's a few observations:

• It seems that IT-intensive businesses move roughly from Complex to Complicated to Simple in the following sense: an amorphous vision emerges in Complex space where existing knowledge and interoperable resources are "mashed-up" in unexpected ways to explore potential new capabilities. A one-of-a-kind capability is created, which, if it is valuable enough, creates a rough pattern for creating new versions of the capability in Complicated space. If the new capability can find a relatively large market, then a vertically integrated architecture will emerge where the capability begins to segment into interoperable layers. Finally, if the interfaces among the layers become standardized, the overall capability may move into Simple space where each of the layers becomes a submarket with vendors competing to provide components, assembly line integrators allowing end users to "build their own" capability, and the few vendors with critical intellectual property controlling the ecosystem of the new mass market version of the capability.
• An example from the area of computers: IBM's Stretch (Complex, moving into Complicated), IBM System/360 family (Complicated, moving into Simple), and the IBM PC (built from interchangeable parts; quickly became dominated by Intel and Microsoft, and a volatile, competitive, low margin market for almost everything else, including integration of the parts).
• Such a cycle might be seen in physically-intensive industries (e.g., automobiles, guns), but the lack of malleability of a product that is mostly physical (vs. a product that is dominated by information) constrains the evolutionary potential.
• Businesses in Complex space tend toward small high-margin consultancies, innovation groups, and startups. They are exploratory groups that focus on vision, probing, and prototyping.
• Businesses in Complicated space tend toward large medium-margin analytically-oriented organizations that work to bridge the gap between a new capability and the existing ecosystems of People, Processes, Organizations, and Technology. They are exploitative groups that focus on architecting and systems engineering to provide the new capability to users who can afford it. As the vertically integrated capability finds a larger market, it begins to segment horizontally, and the businesses tend to shift toward processes that are less "skunk works" and more "Six Sigma."
• Businesses in Simple space tend to be large low-margin rules-oriented organizations that work to provide a generic capability at the cheapest price possible. They are exploitative groups that focus on predictable process execution. As the capability moves into a mass market, standard interfaces result in submarkets of interoperable components.
• The interoperable components and associated standards eventually float into a Chaotic space where they can be recombined to start a new cycle of Complex-Complicated-Simple.
• The cycle time through C-C-S decreases dramatically wherever a wide range of interoperable components and associated standards appears. At some point, the cycle may be largely Complex-Simple, with little, if any, movement through Complicated.

As I was putting these thoughts together, I reviewed a HBS Working Paper ("The Architecture of Platforms") by Carliss Baldwin and Jason Woodard I had read a year or so ago. My notes in the paper prompted me to look for other presentations by Baldwin. She has a number of them that discuss IT architecture's shift from vertically integrated capabilities to horizontal layers of modules...her "Design Theory and Methods" presentation at L'Ecole de Mines (Oct 2007) has a series of slides on the computer industry from 1979 to 2005 that nicely illustrates the point.

And, Clayton Christensen's latest book, "The Innovator's Prescription", covers similar ground. See this presentation from the Health Information Technology (HIT) Symposium. The voice track helps but is not free (unless your company subscribes to a service which provides this sort of thing).

Finally, it's not just the good guys who understand this dynamic...the agility and adaptability of the bad guys in asymmetric warfare indicates the importance of being able to quickly cycle through Complex to Complicated to Simple...or maybe just cycle quickly between Complex and Simple as communications, command and control, processing, and sensor capabilities are increasingly interoperable, cheap, and pervasive.