Mapping Strategy

Forecasting Their Way to Durable Profits

From the front page of today's Wall Street Journal [emphasis added]:

...a little-known tool of the insurance world: Computerized catastrophe modeling. Crafted by several independent firms and used by most insurers, so-called cat models rely on complex data to estimate probable losses from hurricanes.

But regulators and other critics contend that the latest cat models -- which include assumptions about various climate changes -- are triggering higher insurance rates.

Starting in the early 1990s, cat models began to replace the industry's older tools. Previously, insurers based their rates and underwriting policies largely on historical records of past claims.

Never mind if the forecasts are accurate or not. They work. To increase profits. That's not a pejorative statement as far as the insurance companies are concerned. It's their fiduciary responsibility to maximize return for their shareholders by any legal means available. It does however, set up an interesting, albeit very long-term test of the credulity and patience of their customers. I.e., should the forecasts prove inaccurate. More from the WSJ piece [emphasis added]:

Underlying the newer cat models are scientific theories that rising sea temperatures will result in more intense, and possibly more frequent, hurricanes. The hypotheses suggest that catastrophic hurricanes like 2005's Rita, Wilma and Katrina weren't an aberration, but rather the shape of things to come.

Large reinsurance companies... were early converts to theories of global warming and cite warming of the earth's oceans when predicting massive damages from future storms.

Well of course they were! Think about it for a second.

You're the CEO of a big reinsurance company. Two scientists walk into your office. One says he's got a new computer model that predicts big future costs due to storms.

"Of course I may be wrong," says scientists number one, "After all, I'm a scientist. We deal in hypotheses. You're the executive. You need to make the call on what to do with this."

"So let me get this straight", says the CEO. "If your models are right, we get to raise our rates because our competitors, customers, regulators and the general public are all looking at the same stuff, convinced that your predictions are true? Is that what you're saying?"

Hmm, she thinks to herself (the CEO). This is pretty good. If this guy is wrong, we get to pocket the difference for decades. It would take that long for anyone to prove this guy wrong. Even better, it's not that hard a sell to the general public. We've got cover. If he's right, well... we'll keep him on retainer. Keep his firm in good shape. Drop them some plum projects to keep 'em happy... maybe even kick this over to mar-com to manage. Under that scenario, we've at least got a decent business until I retire -- no better or worse than before. All upside. No downside. Suhweet!

The CEO smiles. She turns to scientist number two. "And what do you have to say for yourself?" she asks.

"Um...", stammers scientist number two (a geologist by training), "...the fossil record over several million years, and agricultural evidence over several millennia would tend to suggest that storm activity actually decreases during warmer climatic periods. And we're just getting this new data in from deep ocean probes suggesting that 80-90% of the ocean volume is staying the same temperature or maybe getting colder. It would be a bit hasty, in my opinion, for you to raise your rates based on a set of theories and prospective models that claim precise predictability when what we're really dealing with here is massive uncertainty. If you just sign the proposal we put on your desk to study this a little further, we can refine the numbers..."

"Thanks for your advice", asks the CEO. "I'll look into it. Have a nice day."

That's a fantasy dialogue, obviously. Read the WSJ article and draw your own conclusions [emphasis added]:

Perhaps the most prominent critic to surface is Karen Clark, an economist who founded one of the first cat-modeling firms two decades ago. Today, she warns about the programs' misapplication...

Companies that rely too heavily on cat-model data "are subjecting their businesses and their customers to the volatility of computer models," says Ms. Clark, who now runs a Boston cat-model consulting business. "The models are being used as if they produce definitive answers rather than uncertain estimates." Ms. Clark says she advises clients to use them in conjunction with other factors, such as broad historical data.

To be sure, insurers themselves are facing higher rates from the reinsurance companies that backstop their claims. The reinsurers, and the financial ratings agencies that assess the health of carriers, are also using the controversial newer models.

I just love this last bit:

...some models now attempt to estimate future losses over a shorter period of time. In doing so, they may also use selective historical data. One model, for example, was reprogrammed to give greater weight to years in which ocean temperatures were particularly warm and hurricane rates were high, such as the period from 1930 to 1945 [prior to broad industrialization and CO2 increases]. That particular model resulted in higher loss estimates for the near-term.

...and therefore higher rates. The logic is circular.

Thinking Exotically

With air travel on my mind after a West Coast trip last weekend, the following strikes me as positive, (and not just because I'm a marathon runner who tends to pack light). Rather, it's the kind of thinking we do routinely when we help clients develop scenarios. E.g., what if industry 'A' adopted the business model of industry 'B'? Emphasis added:

Imagine two scales at the airline ticket counter, one for your bags and one for you. The price of a ticket depends upon the weight of both.

That may not be so far-fetched.

"You listen to the airline CEOs, and nothing is beyond their imagination," said David Castelveter, a spokesman for the Air Transport Association, a Washington, D.C.-based trade group. "They have already begun to think exotically..."

With fuel costs almost tripling since 2000, now accounting for as much as 40 percent of operating expenses at some carriers, according to the ATA, airlines are cutting costs and raising revenue in ways that once were unthinkable...

Singapore Airlines... is "trying to eliminate unnecessary quantities of extra water" to save weight, Chief Executive Officer Chew Choon Seng said in an interview...

Robert Mann, head of R.W. Mann & Co., an aviation consultant based in Port Washington, New York [said,] "If you look at the air-freight business, that's the way they've always done it... We're getting treated like air freight when we travel by airlines, anyway."

This signals that an industry long characterized by minimal innovation starting to think beyond convention (but... we've always done it that way!) The shock is external and pressing in this case (fuel costs). It needn't be so. Better to do this kind of thinking every day.

Best-practice use of scenarios involves doing this systematically, comprehensively and, over time, making it an ingrained habit of strategic thinking among management. (How could we change the rules to our advantage?) Having several contingent strategies already fully 'baked' when a crisis hits can move one ahead of more flat-footed competition who must do all that thinking while under existential, immediate pressure.

Next up: refunds for in-flight diuretics.    ;-)

How Much is a Brand Worth?

About ten years ago, I ran across a piece of analysis I haven't seen since and can't seem to lay hands (or search-engine bots) on at the moment. It ran in CFO Magazine and -- according to a set of accounting calculations I don't claim to fully understand -- listed hundreds of major brands whose brand value had ascended or descended the most in the preceding years. I recall such brand icons from the '70s as Peugeot and Nikon as being near the top of the latter category (i.e., the bottom of the list one would want to be on).

What was striking -- at least to this non-accountant -- was how rapidly brand values can change and by how much (many billions of dollars, in some cases).

From the standpoint of the kind of work I do helping clients to think about future strategic imperatives under a wide range of possible scenarios, the implication was clear: even if it hurt in the short term, the value of preserving (or failing to preserve) the brand could be enormous. Take that into a financing event and the advantages (and disadvantages) multiply even more, creating (or precluding) a whole range of strategic options, and so on, and so on. Brands are some of the slipperiest and yet most important assets any firm has. (The same could be said for individuals, but that's a different post.)

All of it can seem tremendously academic to companies that don't deal with consumers directly -- and tremendously obvious to companies that do... which doesn't mean that all of the latter do it well.

Thus it was that this piece in today's WSJ caught my eye:

It all started about two years ago, when a ship carrying 4,703 shiny new Mazdas nearly sank in the Pacific. The freighter, the Cougar Ace, spent weeks bobbing on the high seas, listing at a severe 60-degree angle, before finally being righted.

The mishap created a dilemma: What to do with the cars? They had remained safely strapped down throughout the ordeal -- but no one knew for sure what damage, if any, might be caused by dangling cars at such a steep angle for so long. Might corrosive fluids seep into chambers where they don't belong? Was the Cougar Ace now full of lemons?

The Japanese car maker, controlled by Ford Motor Corp., easily could have found takers for the vehicles. Hundreds of people called about buying cheap Mazdas. Schools wanted them for auto-shop courses. Hollywood asked about using them for stunts.

Mazda turned everyone away. It worried about getting sued someday if, say, an air-bag failed to fire properly due to overexposure to salty sea air.

It also worried that scammers might find a way to spirit the cars abroad to sell as new. That happened to thousands of so-called "Katrina cars" salvaged from New Orleans' flooding three years ago. Those cars -- their electronics gone haywire and sand in the engines -- were given a paint job and unloaded in Latin America on unsuspecting buyers, damaging auto makers' reputations.

Mazda saw no easy way to guard against these outcomes. So it decided to destroy approximately $100 million worth of factory-new automobiles. "We couldn't run the risk of damaging the brand name that Mazda worked so hard over the years to develop," says Jeremy Barnes, the company's corporate-affairs director for North America.

It could be argued that a) $100M is fairly cheap to preserve (and, arguably enhance) a major brand name like Mazda (paltry in comparison with some product recalls, or lack-of-recalls that should have happened but didn't), b) it isn't even that much because both the cars and the demolition operations that Mazda had to invent and undertake were largely overed by insurance and c) it's a tremendous waste, even if it does make sense from a business perspective.

From Risk to Uncertainty

I don't agree with everything in this piece by Thomas Homer-Dixon that appeared last week in the Toronto Globe and Mail, but this quote is an absolute gem (emphasis added):

Our global financial system has become so staggeringly complex and opaque that we’ve moved from a world of risk to a world of uncertainty. In a world of risk, we can judge dangers and opportunities by using the best evidence at hand to estimate the probability of a particular outcome. But in a world of uncertainty, we can’t estimate probabilities, because we don’t have any clear basis for making such a judgment. In fact, we might not even know what the possible outcomes are. Surprises keep coming out of the blue, because we’re fundamentally ignorant of our own ignorance. We’re surrounded by unknown unknowns.

It's something I've said for a long time:

It's tempting to think that all things are predictable given enough information, enough minds, enough time and enough computing power. It's just not true. (Which is not to say that some things are not predictable... and with incredible precision... a phenomenon that leads to overestimating the scope of problems and questions that lend themselves to such methods.)

Telling which is which is the trick...

I would go even further to say that really smart people who, by life experience know that some things are fundamentally unpredictable still draw an unvoiced sense of emotional comfort in their business life from the idea that some wise expert somewhere has been to the future (for all intents and purposes) and if we could just find him or her things would be OK... and/or that a really sophisticated computer model or prediction market (the 'collective mind') can provide crystal ball-level insights.

Sometimes yes. Often, no.

I liken Mr. Homer-Dixon's observations to those tragically massive car pile-ups that happen a few times of year in fog-prone areas like the Central Valley of California. Everyone is driving along at a reasonable speed, with reasonable spacing between vehicles. People are sipping coffee, tuning radios, maybe talking on cell phones. Slightly distracted, but mostly responsible. All is normal.

Then the first guy hits a fog bank and can't see squat. He taps his brakes. The second guy sees red lights and fog coming up fast and taps his brakes just a little bit harder, and so on. In just a few seconds, hundreds of cars end up in a tangled heap and people die. All because the guy in front was convinced by every one of his senses and not without justification based on experience that the visibility on the next 100 yards of road would be the same as on the last 100 yards of road.

'Black Swans' Necessitate Resilience-Centric Strategy

Great discussion over at mi2g about how the impossibly large range of inherently unpredictable 'black swan' events inevitably drives organizations to a resilient rather than an anticipatory strategic stance.

Prof Jean-Pierre Lehmann enumerates five different ways that can help companies to prepare for black swans - in our opinion all these lead to the critical notion of resilience. In our highly connected, nonlinear and volatile world where relatively small disturbances can combine to produce large discontinuities that result in severe disruption of business, resilience is the only possible response. Resilience has to do with the ability and capacity of the firm to withstand systemic discontinuities and adapt to new risk environments.

It's a lesson some took long ago.

Perils of Prediction: The Elusiveness of Certainty and the Value of 'Simulated Hindsight'

I'm ten days late in posting on a great short take in The Economist ("The Perils of Prediction"), reviewing Nassim Nicholas Taleb's book, "The Black Swan: The Impact of the Highly Improbable"

...almost all forecasters work within the parameters of the Gaussian bell curve, which ignores large deviations and thus fails to take account of “Black Swans”. Mr Taleb defines a Black Swan as an event that is unexpected, has an extreme impact and is made to seem predictable by explanations concocted afterwards.

Taleb is correct: people like to create (and gravitate to) ex post facto explanations. We usually think of those as being of very little use (unless we're in the business of publishing sensationalist books). By definition, such explanations don't help to anticipate or deal well with the next unprecedented thing--even though people would like to think that they will. Unprecedented means, well... unprecedented. There will never be another 9-11, even though there will probably be other big nasty surprises that kill lots of people that we analogize to 9-11.

That's all by way of background to explain why we use a simple trick in our scenario workshops called "simulated hindsight". Short take: tap people's natural hunger for ex post facto sense-making stories explaining unexpected developments... using hypothetical future 'facts'.

Disoriented yet?   :)

Here's the slightly longer take: Assume it's 2012. Put away this morning's newspaper, as well as all of your assumptions and prognostications about what might happen in July and August, and in 2008 and 2009, and so on. That's all part of 'history' now. It's your job to explain it.

Be in 2012. Assume that the world has already turned out in a certain way that I've spelled out in a tightly-crafted one-page document we call an 'endstate'. Put on your historian 'hat' (or your research analyst 'hat' or reporter/news-anchor 'hat'). Your job is to tell us how the world got to be the way it is now in 2012. What were the major turning points since 2007? What developments led to what other ones? What things didn't happen that some people thought were virtually certain? What were some of the pivotal surprises that drove things to turn out the way they did?

Using a set of 150 discrete, short descriptions of things that might or might not have happened between June, 2007 and "now" (2012)--we call them 'events'--construct a story of how we got "here". Several other teams will do the same with their own separate 'endstates'. Pay no attention to them. They'll get to tell their 'history' stories too and then we'll compare and contrast them and look for the key points of intersection and divergence.

That's simulated hindsight and I've seen it work powerfully to unlock the thinking of hundreds of executives (probably thousands by now, come to think of is), enabling them to contemplate how various kinds of surprises might change their business.

The Economist's review of Taleb's book offers other gems [emphasis and link added]:

...humans have an uncontrollable urge to be precise, for better or (all too often) worse. That is a fine quality in a watch-repair man or a brain surgeon, but counter-productive when dealing with uncertainty... Why, [Taleb] asks, do we take absence of proof to be proof of absence? ...Mr Taleb argues convincingly that the spectacular collapse in 1998 of Long-Term Capital Management was caused by the inability of the hedge fund's managers to see a world that lay outside their flawed models. And yet those models are still widely used today...

...corporate “scenario planners” are better than they used to be at thinking about Black Swan-type events... [Taleb] suggests concentrating on the consequences of Black Swans, which can be known, rather than on the probability that they will occur, which can't (think of earthquakes). But he never makes professional predictions because it is better to be “broadly right rather than precisely wrong”.

All of which helps to explain why--despite their unquestionable value in an organization--financial executives, engineers, and those with talent for managing the details of day-to-day operations tend to be much less comfortable confronting the broad implications of longer-term uncertainties or dealing with the imprecision inherent in potentially sudden, unprecedented change. I'm not that good at the other stuff. Driving across the Golden Gate bridge recently, I gave thanks that we've got our domains of complementary expertise.

UPDATE: One amusing side-effect of Googling "Perils of Prediction" (the title of the Economist article) was the number of other pieces that came up (934), including this general treatment:

Perhaps the most difficult pitfall to avoid is when the predictor fails to take into account a factor that may not even exist at the time of making the prediction.

This take on the special problems of forecasting technology evolution:

In 1967, the 100-year-old company Keuffel & Esser was commissioned to study the future. A major failure of its analysis was not seeing that its own flagship product would become obsolete in just a few years. K&E was the country's leading slide-rule manufacturer, and it was blindsided by the product it failed to see, the electronic calculator.

This insanely precise (and internally inconsistent) long-term economic forecast (commentary here):

George Mason University's Stephen Fuller called up a PowerPoint slide predicting that in 2057, the average annual household income for the region will be $1,307,000. Whoo hoo! That sounded great. Then he pointed out that in 50 years, the average Washington area house will cost a whopping $14,061,000.

This description of the "butterfly effect" in perhaps its most classic form:

A little discrepancy in the pattern of air flowing more than 4,000 miles away had made the difference between an accurate forecast and a bust. The change in the winds in Alaska had displaced storms in the southeast by several hundreds of miles-endangering people living near Orlando, not New Orleans.

This semi-prescient August, 1998 assessment of economic models designed to predict currency crashes (right on the cusp of LTCM's almost world-cataclysmic implosion):

Investment banks and academic economists are building complicated models to predict currency crashes. Don't expect them to work.

And finally, this amusing if cautionary catalogue of bad predictions by Cynthia Crossen in the WSJ last January 8th (subscribers only):

"The giant airplane of 300- to 400-passenger capacity, while technically possible," wrote a U.S. aviation official in 1944, "appears to offer little economic advantage and to involve a great sacrifice of convenience for the traveler, owing to the inevitable reduction in scheduling frequency which results from using such large units."
...
In 1937, Hadley Cantril, a psychology professor at Princeton University, studied the relative prophetic ability of various types of people. He sent a questionnaire asking for predictions about world affairs to several hundred people... The two groups who were most confident that their predictions were correct were the bankers and the Communists.

China's "Authoritarian Resilience"

I note an interesting, seemingly oxymoronic concept in this piece: authoritarian resilience.

Beijing has pressed on, doing what Washington believed was impossible: compartmentalizing economic gain from political challenges. This does not mean that the market forces and various liberal instruments trumpeted by the United States should be dismissed or abandoned, but it does mean that as Beijing strengthens the resilience of its authoritarianism, Washington should cease basking in its delusions for inevitable democratic change. [emphasis added]

One key factor in the government's resilience, the author goes on to explain, is the supression of what are called "coordination goods", including:

...political rights, such as free speech and the right to organize and protest; general human rights, such as freedom from arbitrary arrest; and press freedom... the availability of coordination goods affects democratization because they drastically influence the ability of political opponents to coordinate and mobilize but have little impact on the continued economic growth that is crucial for sustaining an authoritarian regime’s legitimacy. [emphasis added]

It's a strange combination, to be sure, and in fact 'robustness' rather than resilience may be a better term for the Chinese government. The former connotes sheer strength and durability; the latter is more characteristic of a system that's able to bounce back seamlessly (or nearly so) from a wide array of unanticipated shocks and challenges. It's a distinction many large organizations should take to heart--and many have.

One could get balled up in a long semantic debate about the two 'r' words, but the point is this: Resilience tends to be associated with exactly the kind of nimble, distributed coordination the Chinese government is working to suppress in politics and promote in economics. (The limits of central planning--in any arena--having been amply proven by historical experiment.)

Durable, top-down organizations may be confused with resilient ones for a time simply because they're strong--and unafraid to wield their accumulated power. Longer-term, I would assert however (and contrary comments are welcome!) that the true resilience of highly distributed systems tends to triumph due to: 1) greater adaptability (they can deform in extreme ways without disintegrating altogether) and 2) the speed with which they can route around 'failure' (to borrow a familiar axiom about the architecture of the Internet).

Exactly how long that battle between resilience and robustness will take to play out in the case of China is anyone's guess. (Long term can mean very long indeed: the co-option of Rome by Christianity took several centuries--easy to see in hindsight but much harder to predict in advance.) The ray of light here may be the philosophical impossibility--at the margins anyway--of differentiating between coordination that is essential to economic growth and that which fuels political/religious change. The Chinese government faces the unenviable and ultimately fruitless task of teasing out the content and intent of each and every expression and drawing a clear line between these natural and overlapping forms of social cooperation.

So long as the tools for coordination in general are the same in business as in politics (laptops, cell phones, networks, fax machines, conversations between individuals, etc.), some political 'stuff' will sneak through--never having been formally identified as such. And so long as the tools are inherently empowering of the individual, their force in changing obedient, collectivist minds into questioning, impatient ones will be inexorable. At least we can hope. Timing is everything.

Infrastructure Priorities in a Pandemic

Glad someone is thinking about this. Unfortunately, it might well fall under the category of "planning" that Hayek rightly criticized decades before it became acceptable to do so.

Submarine Cable Routes

Following up on communications resiliency in and around the PRC after the Taiwan earthquake (previous posts here and here) an individual from Telegeography (whose maps I'd linked to in those posts) contacted me with links to maps that more accurately portray what I'd been seeking: physical undersea cable routes (page soon to be updated, I'm told), as well as overland routes and services between Asia and Europe via Russia... all of which is only as useful as the knowledge, foresight and budgets of those charged with provisioning resilient capacity for offices in-region.

UPDATE: Speaking of network gridlock in China...

Pandemic Preparation

Former Health and Human Services Secretary Tommy Thompson (who consults on pandemic planning) makes a coldly harsh but thoroughly rational statement about bird flu in the January/February, 2007 issue of Corporate Board Member Magazine (quick, free registration required):

“I keep telling them this planning is good for the company. If we have a pandemic we’ll build market share, because our competitors aren’t doing the planning.”

What kind of market share, you may ask? Earlier in the article, another consultant provides examples of opportunity in the midst of hypothetical chaos after avian flu has hit:

A big hotel chain, figuring tourism would collapse, is studying how to rent its properties to governments as places to tend the sick. A hospital operator has contracted for refrigeration trucks [because] their in-house mortuaries are too small... A communications corporation has built a self-contained “clean facility” within its headquarters to house critical personnel and key operations.

Sounds like the kind of grim-but-true advice I'd expect to hear on Six Feet Under. Elsewhere in the article, Robert E. Mittelstaedt Jr., dean of Arizona State University’s W.P. Carey School of Business comments on scenario planning, noting (as I have before) that scenarios are often misused as a predictive tool and at a far too detailed level for business continuity planning (or much of anything else, for that matter):

...it’s difficult to engage in detailed scenario planning, because no one knows how, exactly, a pandemic would unfold—“but we want to make sure there’s a plan there, while not micromanaging it.”

Shortly after 9-11, a client showed us a massive spreadsheet of disaster possibilities, deeming them all 'scenarios'. They were not. Every conceivable thing was covered--from half a dozen megatonnages and locations for nuclear detonations to countless permutations of bridges and tunnels being taken out, anthrax being mailed, utilities and emergency services being cut and the simultaneity of all of the above.

Too much. Waaaaay too much. The 'scenarios' were also confined by definition to what the client could conceive of on its own, colored, it's now clear in hindsight, by the headlines of the day. We were brought in in part to help make sense of it all.

Another angle some now see, and for which real scenarios are well suited, is thinking through supply chain risk and contingency--something many have woken up to in the wake of the Taiwan earthquake (some of the resilience implications of which I blogged about last week: here, here and here). The article continues:

For manufacturers, supply-chain resilience is a chief concern. Some have been conducting due diligence on the readiness of suppliers, knowing that if critical components aren’t delivered it will render their own contingency plans useless. Others are establishing relationships with alternative suppliers, just in case... [though] some directors privately concede that little attention is being paid to the specific challenges posed by a pandemic. Having lived through Y2K, 9/11, and Hurricane Katrina, many outfits feel comfortable that their general risk-management and business-continuity plans will suffice during a pandemic. [emphasis added]

Key differences to note: 9-11 was local; Katrina was regional; Y2K was long-anticipated. Yes they all had global effects, but none were even in the same league as a 1918-style pandemic. In no case were people unable or unwilling on a wholesale basis to travel to work for more than a few days.

All of which leads me to the conclusion the esteemed Former Secretary has already reached: surviving bird flu as a business entity may require as much clever seizing of new opportunities as it does determination to keep the old business running. In some cases there is no rational continuity strategy, only one of strategic resilience (building the capability--structurally, culturally and otherwise) to flexibly adapt to radically changed and changing circumstances.