The Pharmaceutical Innovation Crisis

I used to read a lot of management books.  Or rather, buy a lot of them, then take a quick look — and promise myself to get around to reading them someday.  When (and if) I finally did, I’d often find the information dated and the advice stale.

Not so with most of Peter Drucker’s work.  In Drucker I find things that sound timely — sometime prophetic — even today.

The productivity of knowledge

Drucker spoke of the productivity of knowledge, and how firms, industries, and even countries who managed to excel at it would over time come to dominate their respective sectors.

When I first heard him use that term, it sounded abstract — and not immediately relevant to my work in business strategy. That changed recently when I conducted a study of the innovation crisis in the US pharmaceutical industry (which represents 80%  of the industry’s R&D worldwide.)  This is widely known in the press as the patent cliff that affects most major pharma manufacturers to some extent.

How pharma creates value

pillsIn a nutshell, a significant portion of the industry’s revenues and profits depends on branded drugs — the more successful of which you see advertised on TV.  Most of these are discovered by rapidly scanning lots of molecules, or computer models of the molecules, for potentially beneficial properties.  The most promising of these are first matched with diseases for which they might be useful, then registered under patents.  Then they are developed by being rigorously tested, first on animals, then on humans in a range of clinical trials.

The data from all these tests are presented to the Food and Drug Administration (FDA) for approval.  Drugs that are approved, and that are added to the ‘formularies’ of insurance companies and government payers who will reimburse patients for their use, can becomes wildly successful.  Lipitor, the statin used to control cholesterol in the blood, is the most successful drug to date, with total sales over $125 billion.

These blockbuster drugs (generally defined as those with annual sales over $1 billion) command prices in the marketplace much higher than their cost to manufacture.  Their gross margins can be as high as 75-80 percent.

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The Moneyball Lessons

I love numbers.

I first realized this around the age of ten, when I started collecting baseball cards pretty seriously.  On the back of each card was a bunch of numbers, each player’s ‘stats’, important metrics of how well he played.  Hits, batting average, runs batted in (RBIs), runs scored, and so on.Elston Howard

It later developed that much of what we took as gospel was wrong.  Not wrong, really — it’s just that there was a more productive way of looking at the game.  I’m speaking of sabermetrics, ‘the empirical analysis of baseball’ popularized in the book and movie Moneyball.

The main implication of sabermetrics was that the numbers that everybody knew and had been following were not always the best for predicting the ultimate value goal:  winning games.  Winning is the means by which professional ball teams (which are businesses) fill stadiums and make money.  By correlating each player’s performance with how that player contributed to that value goal, a much better set of metrics was developed.

The team that first operationalized these insights (the early-2000s Oakland Athletics) was able to put together a winning team on a player budget representing a fraction of  that of, say, the NY Yankees.  Once their story was written, other teams  started using the same system, and the comparative competitive advantage eroded.

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Metrics That Matter

I had the great pleasure recently to address the students in Guy St. Clair’s class (K4301) at Columbia University’s Information and Knowledge Strategies (IKNS) program.  These are tomorrow’s leaders in developing and managing knowledge-based strategies.

My most challenging question

Of course I told them about the Knowledge Value Chain, and was gratified by their positive reactions.  I also got my most-received question — one that over time has also become one of my most challenging.

That question is, “What is your favorite metric for knowledge?

It’s a logical question, and one that it would be useful to know the answer to — if it could be answered definitively.  But there is no single correct answer.  And it’s challenging, in that it may signify that I have fallen short in my efforts to communicate my core message:  integrating knowledge tightly with business processes.

Inputs, outputs, outcomes

In the KVC Handbook 4.0 (upcoming) I identify three classes of metric that can be applied to knowledge processes and assets:  inputs, outputs, and outcomes.

Metrics arrows

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75 Things About a Candle

Each year when back-to-school bells ring, I recall some of the key lessons I learned there.  Some of the best had little to do with course content—and a lot to do with the process of gaining knowledge.  My first day of high school chemistry, for example, had little to do with chemistry — but provided a lesson I have used ever since.

One whacky task

xmas-2006bOur teacher (Mr. Keath of Nether Providence High School in suburban Philadelphia) gave us a whacky homework assignment:  light a household candle, then write down a list of observations about it.  No right or wrong answers; no time limit; and no quota, either low or high, for the number of things observed.

Easy—borderline stupid.  That evening I went into our kitchen, turned off the lights, lit a candle, sat there with a paper and pencil, and started my list.  The flame is yellowish-white…and gets reddish as you go toward the top…but has a blue base…It gives off heat…The solid wax of the candle melts and pools around the base of the flame…The wick turns from white to black as it burns.

And so on, you get the idea.  My observations started quickly, I could barely get them down fast enough.  After a while they came more slowly, then finally gave out.  I had a list of around 75 things about a candle.

I kind of got lost in the exercise, and don’t remember how much time had gone by.  It might have been 45 minutes, even an hour.

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Knowledge is Power — NOT!

Knowledge is power. All of us know this slogan.  Those of us in the knowledge professions use it when needed as a banner of professional pride and aspiration.

It sounds reassuring, and probably had major validity when Francis Bacon coined it nearly 400 years ago during the Enlightenment.

The problem is — it simply is not true.  In terms of the politics of the modern organization, KNOWLEDGE IS NOT POWER.  Or, in mathematical terms:

knowledge power intel a

Please read on to find how I reached this conclusion, and what its implications are.

Production and use

I created the Knowledge Value Chain® framework in 1996 to address what I had seen as a persistent and critical gap throughout my career — that the production of knowledge on the one hand, and its use or application on the other, were largely treated and managed as separate and distinct functions.  I came to believe this shortcoming was key to many knowledge/ intelligence malfunctions, and starting giving talks about knowledge-value chains being broken.

The KVC model has two halves — the PRODUCTION half (Data-Information-Knowledge), and the USE half (Decisions-Actions-Value).  In an ideal situation, the two halves work together as a seamless ‘engine’ of organizational awareness.

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Competition: the Wonder Drug for Health Care

Bubble chartOne broad goal for US health care that most of us can agree on is the need to rationalize and reduce overall costs. As a society, we can meet this goal — but only if we ensure that the health care industry remains competitive in each of its component sectors.

Competition update

Unfortunately, in key sectors this goal remains distant — one that in some cases we are even moving away from. Here’s some of what’s happening in three of the largest sectors:

Pharmaceuticals. Most of the profits here are made in branded drugs, where prices are significantly higher than in the corresponding generics.  Some of these drugs generate revenues in the tens of billions of dollars each year.  When a period of patent protection expires, these revenues typically fall drastically (the ‘patent cliff’).

Certain pharma companies have begun to pay generics manufacturers not to produce a generic version, which presumably would erode the branded version’s profitability.  Such ‘pay for delay’ seems on the face of it to be designed to discourage competition, and has the net effect of keeping drug prices relatively high.  The US Supreme Court has apparently reached the same conclusion, and on June 17 ruled that these agreements could be pursued by the Federal Trade Commission as anti-competitive. Whether or not FTC enforcement will follow through remains to be seen, but it’s a step in the right direction.

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Competitive Dynamics: Understanding the ‘Even-Newer Normal’

I’m a lucky guy.  Nearly every day I walk between home and office along the Hudson River, just north of where it widens out into New York Harbor.  As an amateur photographer, I have begun to pay closer attention to — and often photograph — the scene (as below).

Each day the sky as the sun sets over New Jersey is different.  Sometime clear, sometimes cloudy, often mixed — with many variations in cloud types, formations, heights, and so on.  Each day the river water is different — sometimes calm and almost glassy, sometimes choppy and almost ocean-like, with thousands of variations in between.

The tides create a 4-5 foot variation in river height on a typical day, as well as variation in the direction and interactions of the channel flow and the surface texture.  Sometimes the air is still, sometimes pleasantly breezy, sometimes downright windy.  Each day of the year, the sun sets in a slightly different place.

Harbor 3In the five years I’ve been doing this, I do not recall seeing the identical sky-water combination more than once.  There are simply too many factors that change over too wide a range, and that interact in complex ways to see much repetition.  The building and piers are the only relative constants — and sometimes those change too.

New York Harbor is an open, dynamic, complex system, with an innumerable number of factors interacting continually.

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The Myth of Second-Mover Advantage

Back in the 20th century, it became fashionable in business strategy circles to speak of ‘first mover advantage’.  This idea — that if you got there first and staked out a market, it would forever remain yours to dominate — was used to justify funding business plans that would have otherwise seemed, at best, sketchy.

First-movers fall short

Then people began to notice that this is not always how the world really works.  In technology, we could see this evolution in fast-motion.  The ‘first movers’ in online user-to-user communications were MCI Mail and CompuServe.  They were eclipsed (and the latter was bought out) by AOL, which in turn became the vehicle to buy the largest media conglomerate in the world (Time Inc.) — but whose more modest recent successes have come by reinventing itself as a ‘brand company’ (whatever that is).  Google and Microsoft now dominate those categories, which have in effect become loss leaders for their other businesses.

Visicalc was the first dominant electronic spreadsheet — until Lotus 123 arrived, which in turn was hugely successful — until Microsoft Excel came along.  Palm was the early leader in what we now call ‘smart phones’ — and now struggles as a division of HP.  Ashton-Tate was the king of database software — a category that has since effectively disappeared entirely.  Similar happened to just about every early tech mover.

Then, somewhere along the line, true innovation started to develop a bad reputation.

Fast followers follow

Soon the idea of intentionally being a ‘fast follower‘ began to gain adherents — then began to move toward canonization as a smart, modern business strategy.  Articles started being written on it.  ‘Everyone knew’ that Microsoft, poster child for the concept, became what it was largely by copying others and by buying existing innovations that others had created — Windows largely copied the Apple Macintosh, and they bought Word and even the original DOS from others.  Microsoft’s subsequent successes helped legitimize ‘fast follow’ as a strategy to be seriously considered.

The canon goes, “Let them make the investments in R&D. Let them create the markets.  Let them make the mistakes.  Then we’ll just adopt what they do.”  In poker logic, this goes, “We’ll see you and (maybe) raise you one — then we’ll reap most of the return without making much investment.”  Put that way, it seems to make sense.

However, I submit (though few dare say it) that it’s also because it’s easier than determining what the market wants and will want in the future.  It becomes an ‘E-Z Strategy Finder’.  There is even a whole management discipline (competitive intelligence), aspects of which tacitly encourage and thrive on this (often hidden) assumption/myth.

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Avoid the Biggest Mistake in Market Intelligence

The late Ted Levitt, professor at Harvard Business School, used to tell this apocryphal story:  The CEO of a tool manufacturer gathers his executives into a meeting and says, “People, I have bad news.  I’ve discovered our customers don’t want quarter-inch drill bits — they want quarter-inch holes.”

What we sell vs. what they buy

In my view, that would count that as good news — since the executive has figured out that there is an important distinction between what our customer buys and what we make.  Your company makes and sells a product or service; your customer buys value – a benefit as he defines it.  They may be the same thing — your product may completely (or at least sufficiently) satisfy the customer’s need.  But when they diverge, you’re in trouble if you don’t realize it and adjust quickly.  Some companies never catch up when such a value shift occurs.

To play out Levitt’s example:  You make and sell a ¼” drill. What your customer needs and buys is ¼” hole.  Hypothetically there are other ways to get that ¼” hole:

  • hire a handyman who has a drill;
  • buy a pre-drilled piece of lumber; or
  • buy something that can be assembled with clamps instead of holes, thereby doing away with the need for holes altogether.

The point is that, on a value basis, these are also your competition (in addition, of course, to the other drill makers.)  You should keep them on your radar, and maybe even borrow from what they do to compete with yourself — and thereby pre-empt them from doing so.

A current example:  the PC industry

Companies and whole industries make this mistake over and over.  A textbook example is currently playing out in the personal computer industry.  Personal computers as we know them became common business tools in the 1980s.  The growth figures roared along, and with them star companies like Dell and Hewlett-Packard.  Both of these companies now seem to have lost their bearings, and could now be seen as fallen angels — largely due to the shifts in technology that went on around them.

Screen Shot 2013-04-10 at 8.31.19 PM Read the rest of this entry »

Value Starts at the Top

My colleague Robert Reiss studies CEOs — especially their successes and failures — in order that others might benefit from them.  His Internet show The CEO Show produces interviews from these CEOs on leadership, and how they make their organizations ‘tick’.  His book (with Jeffrey J. Fox) The Transformative CEO (McGraw-Hill, 2012) gathers some of their stories, principles, and accomplishments.CEO Show

Robert characterizes the CEO’s primary job as getting the organization from here to there.  Whatever resources are required to do that, it’s his or her job to make sure they’re in place — fully resourced, focused, and firing on all cylinders.

Robert sensed intuitively that the CEOs he interviewed on his show were adding substantial value to their organizations.   But was what seemed subjectively true also objectively verifiable?  When Robert wanted an independent test of his hypothesis, he turned to The Knowledge Agency®.

The TKA test

TKA devised a test using a widely-accepted benchmark — the change in the stock price during their respective tenures as CEO.  But market conditions were very different over the differing time frames we tested — even staying flat in a down market like that of 2008-09 would be judged superior. To adjust for such variations, we gauged the results against the return from the overall market, as measured by the return on the S&P 500.

So our benchmark metric was stock price return in excess of the return from the S&P 500.  We tested the eleven of Robert’s ‘transformative’ public companies having market capitalizations over $1 billion.

The envelope, please

The results were astonishing.   As shown in the table, the median gain was 44 percent over the benchmark, with the range from a slight loss against the benchmark to an excess gain of more than 5400 percentage points.  These results were for periods of time ranging from 5-23 years.

CEO chart shadows

Only one company (Xerox) did not beat the market over the CEO’s tenure — and on further examination we found that in fact it did for most of that CEO’s tenure, until the sharp recession of 2008-09.

Click here to download a short article from The CEO Forum magazine based on TKA’s Transformative CEO study.

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    COMPETING IN THE KNOWLEDGE ECONOMY is written by Timothy Powell, an independent researcher and consultant in knowledge strategy. Tim is president of The Knowledge Agency® (TKA) and serves on the faculty of Columbia University's Information and Knowledge Strategy (IKNS) graduate program.

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