Slow-fermented Genius

That genius Kathy Sierra gives hope to all of us *mumble*somethings who haven't yet taken the world by storm with a post entitled It's Not Too Late To Be A Genius! She references an article by Dan Pink in the July issue of Wired Magazine entitled What Kind of Genius Are You? The article chronicles the work of economist David Galenson, who - through exhaustive study of the value of various artists' paintings - discovered that geniuses fell into one of two camps: Conceptual and Experimental.

"What he has found is that genius – whether in art or architecture or even business – is not the sole province of 17-year-old Picassos and 22-year-old Andreessens. Instead, it comes in two very different forms, embodied by two very different types of people. “Conceptual innovators,” as Galenson calls them, make bold, dramatic leaps in their disciplines. They do their breakthrough work when they are young. Think Edvard Munch, Herman Melville, and Orson Welles. They make the rest of us feel like also-rans. Then there’s a second character type, someone who’s just as significant but trudging by comparison. Galenson calls this group “experimental innovators.” Geniuses like Auguste Rodin, Mark Twain, and Alfred Hitchcock proceed by a lifetime of trial and error and thus do their important work much later in their careers. Galenson maintains that this duality – conceptualists are from Mars, experimentalists are from Venus – is the core of the creative process. And it applies to virtually every field of intellectual endeavor, from painters and poets to economists."

The tale of how Galenson sleuthed his way to this insight is an archetypal tale of experimental innovation, and a ripping yarn to boot!

“Since the Renaissance, genius has been associated with virtuosos who are young. The idea is that you’re born that way – it’s innate and it manifests itself very young,” Galenson says. But that leaves the vocabulary of human possibility incomplete. “Who’s to say that Virginia Woolf or Cézanne didn’t have an innate quality that simply had to be nourished for 40 or 50 years before it bloomed?” The world exalts the young turks – the Larrys and the Sergeys, the Picassos and the Samuelsons. And it should. We need those brash, certain, paradigm-busting youthful conceptualists. We should give them free rein to do bold work and avoid saddling them with rules and bureaucracy.

But we should also leave room for those of us who have, er, avoided peaking too early, whose most innovative days may lie ahead. Nobody would have heard of Jackson Pollock had he died at 31. But the same would be true had Pollock given up at 31. He didn’t. He kept at it. We need to look at that more halting, less certain fellow and perhaps not write him off too early, give him a chance to ride the upward curve of middle age.

As the old malapropism says: I resemble that remark! Or can harbor the fantasy that I do...

UPDATE: The Agonist discusses the distinction between liquid and crystal intelligence; the former being the analog of Galenson's conceptual genius, and the latter being analogous to experimental genius. Except that crystal intelligence involves garnering a critical mass of understanding of an area of knowledge (crystalizing), not necessarily experimenting itself. A very keen insight!

How to Make Important Decisions

[Note: Republishing with significant changes from previous version]

Lovaglia's Law: The more important the outcome of a decision, the more people will resist using evidence to make it.

Why is it so difficult to rationally make big decisions?

We agonize over the decision; we debate ourselves; we finally decide; and then we immediately begin to second-guess our choice!



It doesn't have to be that way.

David Maister points to an interesting post by Bob Sutton on how "the more consequential the outcome, the more power, greed, stress and irrationality come into play in influencing how people react and how individual and collective decisions are made" (quoting David).

In our research for Moonshots and Tsunamis, Mark and I looked at the brain science behind these kinds of issues, and came across some startling (but upon review intuitively obvious) findings.

The key to understanding the problem and devising a solution is understanding our triune brains:



You can also represent the three parts of the brain this way:


This is Ogg. He represents the r-Complex brain, in which a perfect day consists of sitting in the sun on a warm rock, occasionally gobbling up small prey that wanders by, listening for snapping twigs and other signs that we might be imminent prey, and occasionally scratching our procreative itch. The r-Complex is reflexive and automatic, not contemplative.



Let's call the next guy Thag. He represents the right brain, the seat of creativity and pattern matching and experience. Thag's job is to interpret complex, often conflicting input about weather and terrain to decide where to hunt or where to plant. He lives is a social environment where wisdom is embodied in stories passed from one generation to the next, and skill is obtained through apprenticeship, with mastery of one's craft taking years or even decades of practice.



Finally we have Oleg, who represents the fully developed left brain. He's the master of logic and rational thought. Oleg's reasoning ability has given rise to great cities, miracle drugs, and return-of-premium life insurance.


Oleg looks to be leading the pack, but guess again! Neuroscience shows that Ogg and Thag have veto power over his rational thought. And in that order! The picture should really look like this:


Ogg and Thag are kind enough to let Oleg make all the small decisions, but they both have specific triggers for when they exercise veto power. Ogg has two: Fear and Love. Ogg is focused on preservation of self and species. Most of the time he doesn't see the need to do more than monitor the environment, but when his interest is piqued, Thag and Oleg better get out of the way before they get hurt!

Thag has many triggers, some hard-wired, but also many created by his culture and personal experience. His part of the brain is constantly pattern-matching observations against that store of triggers.

Admit it, for much of the day you operate in Thag-mode. You're observing and orienting and acting in response to external stimuli without a lot of conscious decision-making. [I've seen you driving down the road, talking on your cell phone!]

Not convinced on the whole Ogg-Thag-Veto concept? Okay, let's try a little thought experiment. Have you ever had a habit that you wanted to get rid of? Maybe you sucked your thumb as a child. Maybe you took up smoking or drinking or internet surfing or watching reality TV. They made perfect sense at the time you started, but eventually you realized that they weren't in your best interest. So the Oleg in you decided to make a change for all the logical reasons. You convinced yourself that there was absolutely no reason to keep that old habit. And so you quit cold turkey on the spot and never reverted to the old behavior. Right? No??

What happened?

Yep. We've all been there. Aside from any physical addiction, Thag's pattern-response mechanisms made it awfully hard to break that habit, didn't they?

But this post isn't about changing habits. We'll go into that in the book. Today we're focused on making important decisions. And there's one more important concept to discuss before we can propose a solution to the Ogg-Thag-Veto problem.


Categories of Problems

Problems (and Opportunities) come in three varieties:

• Simple
• Complicated
• Complex

Let's define each of these:

• Simple - Ogg can figure out a solution


• Complicated - not simple, but the solution is deterministically knowable. A Thag-era complicated problem was napping a nice, sharp flint tip for a spear. An Oleg-era complicated problem is designing a modern jumbo-jet.
  
• Complex - not simple, and the solution cannot be known in advance. A Thag-era complex problem was bringing down a wooly mammoth in coordination with 8 twitchy, fur-slippered cohorts. An Oleg-era complex problem is predicting what will happen when you fill that jumbo-jet with 400 people (and maybe a few snakes) and fly it from L.A. to N.Y.
  
  

Oleg is the master of the complicated problem, using his skills in mathematics, science, and engineering. But when things get complex, Thag takes over. And despite what we would like to think, our world is a lot more complex than complicated. The main source of complexity in the world:


Isn't that the truth? People are moody and suspicious and predictably unpredictable. You can't know what's going on in their heads from one minute to the next. Only through interaction and observation can we get start to form opinions on the subject. Our Thag-brains are great at generating patterns and hypotheses about the future. With respect to decision making, our experiences with the people involved and their likely actions in the future often allow us to synthesize these scenarios and make an informed decision.


But if Thag can't make sense of a situation, guess who makes the call?


And there ain't no Abundance Mentality in "Fight or Flight"!


So much for the problem; what about the solution?

The solution begins with the acknowledgement that Ogg and Thag have done a pretty good job of advancing human civilization, and that they're both acting in what they perceive to be our own best interest based on the information available (genetic, cultural, and experiential). They may in actuality be dead wrong, but they're trying to do the right thing.

So how can our inner Oleg "manage up" within the brain hierarchy to make better decisions?

Bob Sutton's suggestion is to turn a big decision into a series of small ones that don't register on Ogg or Thag's radar. How might we do that?

The key would be to define a series of complicated problems that Ogg and Thag would delegate to Oleg. So we must ask:

Is there a set of necessary and sufficient facts that will allow us to logically determine the right course of action?

If the answer is yes, we can make a rational decision!



Thanks, Fred, but you know that we live in a complex world. If we can't define the problem as complicated, what next?

Back to brain research.



Or not.

Experimental data has shown that the human brain evaluates down-side risk and up-side risk disproportionately. Ogg focuses on the down side WAY more than the upside, and influences Thag in the process. There are two ways to counteract this influence: 1) Thag recalls or constructs superior models of the current situation, or 2) Thag and Oleg create options that allow exploration of multiple paths to the goal, thus eliminating the single "do or die" decision.

The first alternative: creating a superior model of the current and future situation, can be done in a number of ways. Our pattern-matching Thag-brains work largely on existing knowledge and experience. If I am making a decision for the first time, how do gain experience without actually making and living with the decision?



One surprisingly effective method is to create a simulator of the interaction between the key assumptions, inputs, and outputs of a system. Simulators are used in all kinds of applications, but seem to me to be sorely underutilized in business decision-making. Most businesses aspire to evaluate their investment decisions based on some Return on Investment formula. When someone proposes a new investment, they often create a model for that return and present a single set of assumptions, inputs, and outputs as the rationale for the investment. A common alternative is to provide an Optimistic, Pessimistic, and Middle-of-the-Road-Kind-of-Expected-Results scenario. These scenarios may be perfectly valid, but they don't give Thag the experiential needed to override Ogg's natural wariness. Ogg thinks: "These business case calculations are always gamed to the presenter's advantage!"

The simple solution to this problem is to create a simple simulator that easily allows users to modify the assumptions and inputs and to view the algorithms involved in creating the outputs. This gives the users' Thag-brains a chance to play with those numbers and to gain a feel for the dynamics of the system. By trying different sets of numbers on their own, users' Thag-brains can create that superior model of the full range of options - especially the upside that Ogg and Thag couldn't see at the start of the process. My experience is that in every single case where I allowed a customer to play with the model of return instead of just presenting three scenarios, they settled on a more optimistic return than I had suggested.


If you are unable to effectively model the dynamics of the decision and its consequences, a second alternative for avoiding Ogg-mode decision making is the option approach. In the financial world, options allow investors to purchase the ability to take a specified position in the future without obligating them to take that position. For instance, you might be holding 100 shares of a stock selling at $10 per share, and buy options that allow you to sell for $9 per share, thus locking in the value of your investment. If the price rises to $11, you won't exercise your option, but you eliminate the Ogg-based fear that the bottom could drop out of the stock and you'd lose everything!

Things work the same way in the real world. Instead of making a single one-shot decision, is there a way to economically pursue multiple paths simultaneously? Or to at least give us the option of quickly switching paths if our favorite turns out not to be the best? This is akin to, but not the same as, Bob Sutton's suggestion to break one decision into a series of smaller decisions. In the small decision case, making a wrong decision requires backtracking, which could involve great cost. In our investment analogy, instead of taking out options, we sold at $7 per share and invested in something else. An agrarian Thag-oriented example of the option strategy is to plant multiple crops, some of which are bound not to fetch top price, rather than plant only one, which might fail or drop in price because everyone else planted the same thing.


In summary, the questions to ask yourself when faced with an important decision are:

1. Can I define a necessary and sufficient set of facts to make this decision a complicated one?
2. Can I simulate the dynamics of the decision sufficiently to create an adequate model of the situation?
3. Can I devise and buy options that defer the ultimate decision until I have a better understanding?

This simple checklist will insure that you won't unwittingly fall victim to Lovaglia's Law.

Gratzon Takes Control of Arizona Diamondbacks

Fred Gratzon, former ice cream magnate and author of The Lazy Way to Success has apparently taken control of the Arizona Diamondbacks front office. That's the only possible explanation I can find for the headline at the top of page C-5 in today's Arizona Republic:

Final Roster Spot Filled by Hammock

These types of bold moves are probably easier once you've been mathematically elminated from playoff contention, but it should elevate clubhouse morale after the team announced they were parting ways with fan favorite Luis Gonzales.

Attaboy, Fred!

Nick Carr on Categories of Innovation

When Nick Carr speaks, Spooky Action listens.

The Business Pundit alerts us to an interview in StartupJournal with Mr. Carr regarding innovation. You'll never guess what he says! Actually, you probably can already figure out what he'll say. My first post here at Spooky Action lauded his "I.T. Doesn't Matter" article. We're both skeptical of management fads.

Carr's take on innovation is that a fetish of innovation, in which all areas of a business must be innovate, is a bad thing.

"One good example is if you look in the personal-computer industry at Dell and Apple. Dell's having some problems now, but it's still the most profitable PC maker and has been for some time. Apple is doing very well with a different strategy.

You look at those two companies and you see that Dell has been very aggressive as an innovator in its basic processes, and particularly [in] finding ways to reduce costs as low as possible. But it hasn't been an innovator in the product itself. It's in fact very much gone the commodity route, which up until now was a very powerful strategy for it.

Apple is almost the mirror image of Dell in that it has been very good at copying the process side [by] looking at what companies like Dell have been doing, and then being a very aggressive innovator on the product side, trying to get distinctive products out there. Both have been successful by being very focused in the way they innovate.

A company like Gateway tried to do both. It tried to innovate in its products and get differentiated products, and it also tried to innovate in its processes. It even tried to innovate in its retailing strategy and tried to roll out a bunch of services as well. By innovating so broadly it didn't actually create any competitive advantage and ultimately struggled enormously and fell behind those more disciplined innovators."

Here, here!

Carr highlights that there are different types of innovation; the two most common being product and process. As with the strategic value of I.T., Carr points out that first-mover advantages are often elusive, citing the wild success of the iPod despite the fact that it was not the first product in the category.

I don't have much to offer with respect to product innovation. Others cover that much better than I can. On the process side, one key to success is picking the right processes to change. In the original post regarding Carr's ideas, I stated that there are two broad categories of processes: Asset processes and Liability processes.

"The objective of any organization is to provide something of value for which other parties (customers) will be willing to make an exchange (usually of money). Business processes that create and deliver customer value are called core, or asset, processes. Improvements to these asset processes generally improve top and bottom line performance, but not always.

An organization also has a set of processes that do not create and deliver customer value, but are necessary for the care and feeding of the asset processes. These would include hiring new employees, the annual budget process, governmental compliance reporting, and IT infrastructure management, to name a few. These processes are known as context, or liability, processes. They are called liability processes because that is what they are to an organization, because they. only get noticed when they break down. The only way a company’s payroll process can affect customer satisfaction is if foul-ups create disgruntled employees who degrade the quality of the asset processes. Nobody’s going to be walking around with extra spring in their step because their direct deposit hit at exactly 12:00:00 a.m., for the exact correct amount!

Improvements in liability processes can translate into improved bottom line performance, but not in strategic advantage. The management strategy for these processes thus becomes to run them at the ‘rest practices’ standard of performance, while continually improving the cost efficiency of the process. Where have we heard that before?

So I.T. can be used for strategic advantage:

1. IF it improves an asset process
2. AND IF an organization has the right management team that will subordinate their own personal interests to the benefit of the entire organization
3. AND IF the organization has hired employees with the capability to adapt to the process changes successfully and invested in the change management activities necessary to facilitate those changes."

Substitute the word "innovation" for "I.T.", and I think the advice applies equally. Do go read the whole interview!

Pavlina Posits Panglossian Paradigm of Perfection

Sometimes the headline (and its link) say it all.

Candide, penetrated with so much goodness, threw himself at his feet, crying, "Now I am convinced that my Master Pangloss told me truth when he said that everything was for the best in this world; for I am infinitely more affected with your extraordinary generosity than with the inhumanity of that gentleman in the black cloak and his wife."