The Flood: An Account

I was nearly killed during the drafting of this post.  I hope that some of you out there in Blogland will benefit from my experience.

Part I:  Organic Intelligence

West Greenwich Village, New York City—Monday October 29, 2012 4:00pm ET.  As I draft this, I’m in the middle of readying our downtown, Hudson River-fronting New York apartment for Hurricane Sandy, which by most accounts could be the biggest storm here in, well, recorded history.  Big enough that it could bring over ten feet of storm surge onto our street—and into our duplex apartment, the lower floor of which is partly below ground.

What goes through my mind?  I have to prepare to:  (1) make sure I physically survive (my wife is safely out of town, and my kids are both grown men living in safer places), (2) make sure our cats survive, and (3) make sure our most-prized possessions are out of harm’s way to the extent possible. This is the value hierarchy that guides my actions, sometimes coming down to would I rather save this (camera equipment) or that (books).

How fast do I need to prepare?  That depends on many factors—how fast the storm is moving, when and where it will hit land, how it coincides with tides and the moon cycles, its barometric pressure (which is historically low, lower pressure tending to create a semi-vacuum that essentially sucks the water upwards)…lots of factor all changing at once, and all interacting with each other rapidly and unpredictably.

Kind of like real life in the business world.  While I could be chastised for remaking everything into a metaphor for organizational intelligence, in fact that’s the way I most often view the world.

My intelligence stew

I take in lots of information—ranging from satellite photos being streamed on the Internet, to hallway conversations with building neighbors, and everything in between.  My ‘life partner’ Ellen, though back in Atlanta taking care of her mother, is emailing and calling our neighbors to see what they have heard and what they are doing about it.  It’s all a very kinetic, intuitive, non-deliberate process.  I’m ‘playing by sense of smell’.

I weave it all into a story, a real-time dynamic picture of my situation going forward.  Its choices and payoff tables are very organic, given the ‘value proposition’ I mentioned above.  While not (yet) life-and-death, it’s maybe one rung down on that ladder.

It’s more than a picture, it’s a model of how the various causal factors could interact—many of which I can only monitor and react to, but over which I have little control.  For example, it is rumored that Con Edison has decided to preemptively turn off the power—which so far has not happened, but I’m keeping my batteries charged just in case.

I consider all factors within my sphere of awareness. The most obvious of these, direct observation, is too often overlooked.  I just got in from visiting the river across the street, and am encouraged that now (just after low tide), the river is significantly lower, and not nearly as angry-looking, as it was at high tide this morning.  The wind is picking up, though, and it’s raining moderately.

High tide tonight at 9pm will be the real test, when the full moon will magnify the tide, and the storm is predicted to hit land (though farther south of here.)

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Value for Dummeze

There’s so much talk around here about value that I’ve been accused of being obsessed by it.  I plead no contest.

Bang buck CROPParticularly in these stressed economic times in which we seem mired for the foreseeable future, the quest for value is a search that most of us pursue, in both our personal and professional lives, almost continually.

But what is value?  Most of us realize it’s not the same as cost or price.  It’s what you get for that cost — the ‘bang for the buck’.  Economists would say it’s the benefit/cost ratio.

My two bucks not to Chuck

I like wine.  One of my hobbies is discovering really good wines that sell for less than $10 — but taste like they’re worth several times that.  To me, it wouldn’t be nearly as much fun discovering a great bottle for $100 — too easy — besides which my Scottish heritage would never stand for it.

I’ll never forget our trip to Languedoc-Roussillon in the south of France, where we got delicious local wines in the supermarket — for $2 a bottle. That cured me forever of wine price snobbery — but made me forever a wine value snob.

“Value” implies getting more (of something) for a given amount of money.  A value investor is one who likes to buy low, then sell high.  A value stock is one that seems underpriced relative to its fundamentals and earnings potential.

Thinking like an MBA

Value creation is the fundamental keystone of our competitive economy — and one of the genuine Mysteries of the Universe.  For me one of the best things about business school was the opportunity to think and talk about value for two intense years — both in an abstract theoretical sense, and in an applied sense as it relates to producing value in live enterprise situations.

As an MBA, you learn not only not to take value for granted, but even to have a certain reverence for it — that value is transient, not to be treated carelessly — it can come and go.  Much like other living organisms, products, business models, companies, even whole industries have life cycles — they are born, they grow, they thrive, they ebb, they die.  The value life-cycle is an entirely natural process — even predictable, once you understand it.

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What’s a Record Store, Grandpa?

When I first moved to New York in the mid-70s, I was working downtown for New York State’s Emergency Financial Control Board.  Yes, Virginia, we’ve had financial crises before, and that was a pretty bad one.  My job was conducting ‘financial intelligence’ about the city subway system.

A guy I worked with shared my interest in music, and told me about this great new record store just down the street — J&R.  It was for years my first stop when I wanted to find something unusual.  As many of you know, in the interim they expanded from that one store to now occupy many of the storefronts opposite City Hall.  They now carry cameras, computers, TV and other electronics, small appliances, and on and on.J&R

‘This could be the last time’

These days, whenever I’m downtown, I’ve taken to stopping in — because I’m always afraid it will be the last time.  Tower Records, Virgin, Sam Goody’s, and HMV, formerly the other biggies in town, have long since left the market for vinyl records and CDs — because obviously the markets for these products are increasingly niche-based, and the major (legal) markets for recorded music are for MP3 downloads and streaming à la Pandora and Spotify.  I still buy CDs to get the best quality sound, but do it almost exclusively now from Amazon.

Even while they were around, records changed a lot.  My first memories of buying music are of going to the record store with my dad and having the clerk take out the record you were interested in so you could listen to it in a listening booth before committing to it.

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Health Care Spending III: Alice in Health Care Land

AliceWhen Alice tumbled down the rabbit hole, she entered a world (“Wonderland”) reminiscent of her own—but in which everything seemed upside-down, and nothing worked as expected.

After spending over a year researching the economics of the health care industry, I’ve concluded that health care is its own economic Wonderland.  If you were given the hypothetical task of designing an economic system in which the laws of ‘economic physics’ had been miraculously suspended, you could not do a better job than the current US healthcare system.

As a result, health care costs continue to escalate considerably faster than most other household expenses.  Our $2.6 trillion in 2010 health care spending represented nearly 18% of GDP, a proportion that has doubled during the past 30 years.

Economic fundamentals

Most of my knowledge of economics comes, not from academics, but from working as a researcher and adviser to businesses over a period of 40 years.   As a result, I always err on the side of empiricism (i.e., what is) and pragmatism (i.e., how to improve it).

For reference I always come back to capital fundamentalism—the basics of supply, demand, and market exchange.  A ‘pure’ economic exchange works something like this:  you own a product or service that I want to acquire.  You name your price (or we negotiate and agree on a price), I decide whether it’s ‘worth it’ or not, then I decide whether I want to buy, and (if appropriate) in what quantity.  In the purest form, I am also the consumer or user of the product or service, so I can make this value choice first-hand.

Then we ‘do the deal’. I pay you and acquire the product or service, and everyone’s immediate economic needs and goals are presumably satisfied.  We all live happily ever after.  Or if not, and I’m not happy with the result you provided relative to the price I paid you, I buy from another provider next time.

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Making Intelligence Relevant

I recently found a whitepaper the name of which startled me:  “Fixing Intel:  A Blueprint for Making Intelligence Relevant in Afghanistan”.  Startling in the frankness of its analysis, startling in the clarity of the remedies it calls for, and most of all startling in its applicability to my own field of business research and analytics.

Impressive credentials aside, its authors speak from deep hands-on knowledge.   General Michael T. Flynn served in Afghanistan for three decades as an intelligence officer, Captain Matt Pottinger served under Flynn in Afghanistan, and Paul Batchelor works at the Defense Intelligence Agency.  They have all walked the walk.

An alarming assessment

Flynn report shadow“Eight years into the war in Afghanistan,” begins the candid January 2010 assessment, “the U.S. intelligence community is only marginally relevant to the overall strategy.”  The authors go on to quote General Stanley McChrystal, then head of NATO and US forces in Afghanistan: “Our senior leaders—the Chairman of the Joints Chiefs of Staff, the Secretary of Defense, Congress, the President of the United States—are not getting the right information to make decisions with.”

If you are (as I am) a ‘value-oriented taxpayer’—aware that the US currently spends over $80 billion in intelligence each year, one-third of that military intelligence—you’d justifiably find this alarming.  It helps explain why, now ten years into that conflict, we are facing a less-than-optimal conclusion.

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Truth is Not Enough

When I first got to Yale, I was struck that our motto LUX ET VERITAS was an extension of Harvard’s Veritas.  I used to kid people that Yale was obviously twice as good—you got all the same Veritas, with the 100% added bonus of the Lux.  Whatever that was.

Product differentiation

Yale 2Later I came to see this as a marketing strategy on Yale’s part—pure product differentiation.  Harvard was the first colonial university in 1636, and claimed the all-time killer motto, Latin for “truth”.  Coming along in 1701, Yale had to differentiate its ‘brand’ somehow.  It did that by anchoring with the “et Veritas” part, and adding the “Lux” (light) up front — kind of a new improved ingredient for the upstart rival.

It wasn’t until years later that I gave much thought to what the words mean.  I still believe that Yale has the better motto—but for much different reasons than I did then.

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Health Care Spending II: Where Does It Come From?

Last time we looked at where our health care funds in the US are spent.  At more than one-sixth of our GDP, it’s undeniably a huge factor in our financial lives.  Who pays for all this?  Ultimately, of course, we all do—but the mechanisms by which this happens may surprise you.

Since non-personal spending ($407 billion) is accounted for somewhat differently at the federal level, our focus here is just on the $2.2 trillion in Personal Health Care (PHC) spending in 2010.  A similar pie chart as in the previous post, but this time broken out by funding source, looks like this (figures in millions):

Health care by source

About one-third of PHC spending ($746 billion) is by private health insurance companies—Aetna, ‘the Blues’, Cigna, Humana, United, Wellpoint, and smaller companies.  Medicare, federal health insurance for the elderly, accounts for nearly a quarter of spending ($494 billion).  Medicaid, a joint federal-state program for the poor and disabled, pays for $372 billion.  Of that, about two-thirds is federal, one-third from state and local sources.

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Health Care Spending I: Where Does It Go?

Everyone knows health care is expensive, and is a significant part of our individual and collective budgets.  How expensive, exactly?  And how is that money spent?

In 2010 we in the US spent $2.6 trillion on health care. That’s 2.6 with twelve zeros behind it, or 2.6 million millions if (like me) you get lost in the zeros.  That comes to about $8,500 for each US resident, and more than $11,000 for each adult over age 18.

World GDP b

GDP Data (IMF as reported by Wikipedia)

This is nearly 18% of our $14.5 trillion Gross Domestic Product as a country.  For perspective, it’s larger than the entire US durable goods manufacturing sector ($2.3 trillion), which includes, among others, the computer industry ($377 billion) and the auto/truck industry ($360 billion).  If US health care were its own country, it would stand at number five in the world, behind Germany and just ahead of France.

Where does it go?  The following chart summarizes our outlays of funds (in millions):

Total Health NS

Five of every six health care dollars are spent on Personal Health Care (PHC) — the professional direct care we actually ‘consume’ when we visit the doctor or take our medicine.  The other categories, together about one-sixth of health spending, represent much of the ‘overhead’ of health care.  Administration ($176 billion) includes state and local government program admistration expenditures, as well as the portion of private health insurance that does not directly pay for care.  Public Health activities like vaccinations and disease prevention make up another $82 billion.

Structures & Equipment ($100 billion) includes new building construction and capital equipment.  Research ($49 billion) represents non-profit and government activities like grants for medical research.

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Using Roots and Derivatives

In the interest of full disclosure, this post is not about algebra or calculus, nor is it about financial instruments.  It’s about various kinds of business research ‘raw materials’ and how to discern their quality if you are a producer or user of such research.

Whether you are navigating the waters off Tuscany in a cruise ship, or analyzing a new business opportunity, the quality of the data you use is integral to the outcome you will deliver.  While the availability and use of high-quality data does not guarantee a desired outcome, the absence of it renders the desired outcome more a result of chance than of strategic intention.

Manufacturing re-thought quality

When I originally developed the KVC model, it was partly a test to see how well best practices in manufacturing could be applied to organizational intelligence.  In so doing I borrowed heavily from earlier work I had done in TQM (Total Quality Management).  One of TQM’s most basic principles is that in any manufacturing process, it is no longer acceptable to just get to the end of the process — the finished goods — and weed out the ones that do not meet quality standards.  Instead, it is much more efficient to build quality checks into each stage of the process, reducing the number of adverse quality-related surprises at the end of the process.

Intelligence can, too

So it is with intelligence — the ‘manufacture’ of a knowledge-based product.  One of the implications is that each step up the value chain tends to replicate (and in my experience, amplify) any quality shortfalls embedded in earlier stages.  ‘Garbage in, garbage out’, as the expression goes — though we prefer its converse, ‘Quality in, quality out.’

tree_with_rootsAnother implication is that wherever possible, in developing your source data, you go to the lowest possible level on the chain at which it’s available.  If information and intelligence are the branches and leaves of the ‘knowledge tree’, then data points are the roots.  You want to get to the ‘root-most’ level in order to start your analysis.

To the extent you accept at face value someone else’s processing or analysis of the data, you may save yourself some analytic time and effort — but also you leave yourself open to inheriting and building on their errors.

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