Corporate America is obsessed with numbers.
Analyst meetings focus on earnings expectations, revenue growth and margins rather than business fundamentals. PowerPoint presentations look naked if they lack charts and graphs to buttress their message. Lofty corporate mission statements are often trumped by pressure to “hit the targets.” Job applicants are advised to stress tangible achievements, and above all, to quantify them. And the ultimate sign of a trend past its sell-by date: a January 2006 Business Week cover story, “Math Will Rock Your World”.
This love affair with figures increasingly looks like an addiction. Numbers serve to analyze, justify, and communicate. But numbers are abstractions. When they begin to assume a reality of their own, independent of the reality they are meant to represent, it is time to take warning, as some are. When McKinsey surveyed over 1000 directors of public companies in 2005, the majority made it clear they wanted to hear less about financial results and more about things not so readily quantified, like strategy, risks, leadership development, organizational issues, and markets.
We believe it is time for business managers to recognize the limitations of metrics. Mind you, we are not saying that metrics and measurement are bad things. A well structured performance measurement system is essential to the well being of large enterprises.
Nevertheless, quantitative measures can be and frequently are used naively. It is all too easy to abdicate judgment to the output of a model or scorecard. And even when measurements are recognized to be incomplete, the reflex is often to make the model more elaborate, when other approaches would yield more insight.
Metrics presuppose that situations are orderly, predictable, and rational. When that tenet collides with realities that are chaotic, non-linear, and subject to the force of personalities, that faith – the belief in the sanctity of numbers –often trumps seemingly irrefutable facts.
In an ideal world, we’d be able to offer a roadmap for the proper use of metrics –what should be measured and when, what are the best ways to measure, how should they be interpreted? But it isn’t simply space constraints that get in the way of this objective. Whether quantitative measures are beneficial or not depends less on the measurement themselves and more on how they are integrated into decision processes. Quick and dirty calculations can be helpful if users understand their limitations, and very precise models can be dangerous if given undue credence.
We’d like to give a broad overview of the problem, with the hope of making you better able to recognize when your metrics might be giving an incomplete or misleading picture, and offer some remedies.
Why We Love Numbers
Math-based techniques have led to important advances in business. Indeed, modern commerce would be impossible without them. But history demonstrates that a good thing can be taken to excess.
Frederick Taylor, whose 1911 “Principles of Scientific Management” inaugurated time and motion studies and job descriptions, accelerated the development of large scale manufacturing enterprises. Henry Ford not only created process engineering, and with it, the assembly line out of his search for efficiency, but his drive to achieve mass production and economies of scale in turn fostered administrative innovations like logistics planning, standard operating procedures, and functional administration design.
But Taylorism also unwittingly devalued workers, in effect treating them as machines. Some scholars believe that this dehumanization of the workplace strengthened and radicalized the union movement, a development that plagued industry for the next fifty years. Similarly, some companies took the Fordist pursuit of scale economies to the point where they lost strategic flexibility. Coca Cola, for example, built up a sizeable inventory of its distinctive 6 oz bottles in the 1930s, and was unable to respond when a struggling, twice bankrupt Pepsi was able to sell a 12 oz drink for a nickel by using recycled beer bottles.
Other techniques we simply applied too broadly. For example, during the heyday of econometrics in the 1970s, most large companies had an in-house econometrist and had a penchant for modeling problems, when simple back of the envelope calculations would often suffice.
We have a cultural bias in favor of science and mathematics. We see numbers as “hard” outputs: objective, reliable, repeatable, verifiable. But most management data are not as firm as, say, your company’s stock price at the close of trading. Even if we understand those limitations intellectually, we somehow lose that perspective when we wrestle with figures.
In fact, we have not only a romanticized view of management information but also of science itself. We attribute to science a rigor and degree of accuracy that would give scientists pause, and this cognitive bias has been repeatedly discusses in scientific literature. For example, in 1961, Michael Scriven called “inaccuracy” the key attribute of physical laws because, “its almost universal presence is a kind of unadmitted shocking fact like the Emperor’s nakedness and needs to be pointed out if we are to get a true picture of the role of laws.” Mind you, this article refers to fields we regard as scientifically mature, such as Newtonian physics. His arguments have been taken further in Professor Nancy Cartwright’s “How the Laws of Physics Lie”.
Matters that laymen would think are well settled, like what constitutes the nature of proof, are open questions. In addition, statistical inferences, which are the type of analysis commonly used in business, are not conclusive. First, even under the best of circumstances, measurements are not perfectly accurate. Second, the sample chosen for study may not truly represent the population as a whole. Third, correlation is not causation: there may be other factors at work, and the ones we have focused on may be secondary or even incidental (recall how ulcers were once believed to be caused by diet and stress?)
Since scientific findings are less solid than many of us would like to believe, it is prudent to regard management “findings” with a healthy dose of skepticism.
Common Mistakes
Since metrics provide a window for viewing our world, how can we recognize when the glass is clouded?
While this list is illustrative rather than exhaustive, watch for:
Focusing on numbers rather than behaviors. In the management information game, “how much” is easy to capture, when “how” can be more illuminating. Too often, companies unwittingly mimic the drunk looking for his lost keys under the streetlight, because that is where he can see well, rather than where he lost them.
Take R&D spending. It is an article of faith that companies should increase their R&D budgets if they want more new products. Yet a 2006 survey by Booz Allen of the top 1000 corporations, measured by their R&D spending, found “no discernible statistical relationship between R&D spending levels and nearly all measures of business success, including sales growth, gross profit, operating margin, enterprise profit, market capitalization, or total shareholder return.” Michael Schrage, a researcher at MIT and an expert on innovation and modeling, argues in a recent Financial Times article that R&D spending is similarly unrelated to innovation. He cites examples such as Reckitt Benckiser, the Anglo-Dutch cleaning products company, and Illinois Tool Works, both of which spend only 1% of sales on R&D (versus a US average of 4.5% and a European figure of 3.3%) when each is considered a highly innovative organization. Schrage also cites Apple Computer, whose R&D spending of 5.9% of revenues, considerably lags the industry norm of 7.6%. Conversely, GM has spend more on R&D over the last 25 years than any company on the earth, and its flirtation with bankruptcy shows how little this outlay has produced.
Framing the problem incorrectly. Sometimes mistakes are glaringly obvious, once they are pointed out. A financial services company regularly surveyed its network partners on their customer satisfaction, measured by ratings on various attributes of the service, and then would try to improve the low scores. However, no one had bothered to ascertain which aspects of service were important to these partners. As a result, considerable effort had been spent improving low ratings that didn’t bother the partners.
Or, since businessmen often compare competitive struggles to combat, consider a military example, the Vietnam War. Two key measures used to measure progress were the “body count”, meaning enemy deaths, and “hamlets under GVN (government of Viet Nam) control”.
The US saw the problem in conventional warfare terms, of gaining territory and thinning the enemy’s ranks. But this viewpoint turned out to be woefully misguided.
First, the body count totals were often exaggerated, sometimes by a considerable margin. Second, we didn’t know who we were killing. Were they really VC, or local sympathizers, or just civilians caught in the crossfire? The more we killed non-combatants, the more we alienated the population and facilitated VC recruitment. Third, and probably most important, we entirely misunderstood the nature of the war. The North Vietnamese saw it as a war of liberation, to eject yet another colonial power. The Vietnamese will had been hugely underestimated, and indicators of it were ignored. For instance, Rand experts who dealt with prisoner interrogation material from World War II, Korea, and Eastern Europe, had never seen interviews like the ones of VC, and concluded that unlike other opponents, they could not be coerced.
Thus, the body counts were relevant only to measure the progress towards exterminating the entire population.
If possible, the “hamlets under control” stats were even more dubious, These figures were reported by the GVN, which obviously wanted to maintain US sponsorship. Yet the US government took these reports at face value, ignoring objections of experienced US operatives.
These measures allowed the command structure to assert that the North Vietnamese effort was on the verge of collapse, until the Tet Offensive of 1968 dramatically demonstrated otherwise, shattering the belief that the US could win the war.
Overlooking perverse incentives and feedback loops. In 1975, Steven Kerr, former president of the Academy of Management, and most recently the Chief Learning Officer of Goldman Sachs, wrote the classic, “On the Folly of Rewarding A, While Hoping for B”. The article describes a range of “fouled up” incentive systems in athletics, academia, medicine, the military, and business.
Kerr lists the causes of these misguided incentives, two of which are particularly germane. The first is “fascination with an ‘objective’ criterion”. While managers like simple, quantifiable standards, they tend to work only in areas where the activities are highly predictable, and break down elsewhere. Second is “overemphasis on highly visible behaviors”, which tends to encourage individual action at the expense of activities like creativity and team building, which are hard to observe.
For instance, there has been a great deal of tooth-gnashing about the corporate fixation with quarterly earnings targets, which are objective, to the detriment of long-term competitiveness, which is harder to assess.
A 2005 McKinsey article, “Building the Healthy Corporation”, describes how some companies have responded by developing scorecards for “performance and health”. It recommends general measures in five areas, with particular emphasis on metrics.
Although the article sets forth a coherent, wide ranging program, it nevertheless runs the risk of being inadequate to the task. In simple terms, a problem that may have started with metrics is not necessarily solvable through metrics, or even metrics plus exhortation.
The article gives CEOs the hope that if they retool their systems and encourage siloized managers to play together, they can redirect their managers’ actions. And normally, that would be a good assumption. But in this case, the “health” program has two major hurdles to overcome. First, most of the health measures will be seen as soft, even if they are quantified (what does it mean to raise customer satisfaction from 3.2 to 3.5? What is that worth?), and as we discussed earlier, “soft” measures are generally taken less seriously than “hard” ones, like costs. Second, placating Wall Street has become an overarching objective in corporate America, reinforced daily in the business press. Even thought the article advocates educating analysts to the payoff to be gained by paying attention to these metrics, that sort of persuasion is an uphill battle. Similarly, the McKinsey piece also recommends cultivating new investors, ones more long-term oriented. Short of going private, it is hard to see how to put that into effect.
No middle level manager is going to do things differently unless he gets an unambiguous signal from the top, like Costco’s rejection of analyst calls to extract more short-term profit. Until top management demonstrates that it will not slavishly bow to the dictates of the financial community, its efforts to persuade the ranks otherwise are likely to fail.
Another danger is feedback loops. Measurement systems are often self-referential, and participants can, sometimes innocently, game the system. The seeming unending rise of CEO pay shows how this process operates.
You know the drill: a compensation survey determines what “comparable” CEOs earn, and then the CEO’s package is set in reference to this universe. But several perverse factors are at work. First, just as the children at Lake Woebegone are all above average, so too are boards reluctant to have their CEO paid in the bottom quartile or half. So there is a mechanism in place, that has clearly been operating quite effectively, to keep moving the averages upward, despite the fact that the evidence is weak to non-existent of any correlation between CEO pay and performance.
Why does this persist? One culprit is the social dynamic among the directors and the compensation consultants. But a contributing factor is that CEO pay is “market” pay, and “market” data is seen as objective, even virtuous. But this notion quickly breaks down. In a real market, such a price rise would fuel a search for substitutes, which in this case would be dark horse candidates, like business unit managers that might have delivered great performance but be wanting in polish (Liz Claiborne’s CEO Paul Charron, who had neither CEO nor apparel experience before he took the helm is the exception that proves the rule) . Similarly, few boards are willing to consider whether their CEO could really get a similar package anywhere else.
Misreading the data. Even when you have the right metrics, you may not interpret them correctly. And since this happens to the best and the brightest, it can certainly happen to you.
You may recall that LTCM debacle in 1998: a high-flying bond trading firm with the best analytical talent in the industry, including two Nobel laureates, had to be bailed out by a consortium of banks to prevent wide-scale disruption of the financial markets. Although there are different views of why the firm collapsed (the big reason is that it began to trade in markets in which it had limited experience), some argue that it was a “perfect storm” that perhaps no one could have anticipated. A more jaundiced and persuasive view is that their models assumed a normal distribution of events (a bell curve), when in fact markets often exhibit both an asymmetrical distribution and “fat tails” (meaning events “far” from the mean in a statistical sense have a greater likelihood of happening than assumed by a normal distribution). Given the huge bets they were taking in unfamiliar waters, it would have seemed a reasonable precaution to have stress tested their models using other distributions of events.
A 2006 article by Malcolm Gladwell discusses how various organizational and social issues have remained unsolved because the remedies assumed a normal distribution, when in fact the problem had a “power law” distribution (think of it as 80/20 on steroids). For example, the LAPD studied complaints of the use of excessive force. They had expected to see the complaints broadly distributed across the entire force, which would suggest that more training and better procedures were the answer. Much to its surprise, it found instead that the complaints were concentrated among a very few officers. The solution was to fire them, or at the very least, get them off the street.
Another factor is cognitive bias. The field of behavioral finance has analyzed the many ways that people fail to deal rationally with numbers. One phenomenon is anchoring. Individuals’ estimates are influenced by random suggestion. In one famous experiment, a roulette wheel generated an illustrative, and clearly arbitrary, value when participants were asked to estimate the percentage of countries in the United Nations that are in Africa. High numbers on the wheel elicited considerably higher guesses.
Or consider a more relevant illustration: acquisitions. Inevitably, the discussion of the pending deal revolves around the projections. The financial model assumes a reality of its own. Anything that isn’t incorporated in the model is implicitly assumed away.
Buyers continue to use this approach despite evidence that it produces bad outcomes. Depending on which study you choose, every analysis of mergers says that most fail (typical estimates are in the 60 to 75% range), and the buyer overpaying is the most frequent cause. Yet the “anchor” of the forecasts is powerful, and woefully difficult to dislodge.
Some Suggestions
The most important change a senior executive can make is a shift in mindset, to regard figures as a useful input rather than gospel. It helps to recognize when these quantitative measures are most valid (e.g., when applied to discrete processes that can be measured objectively, such as transaction processing) and when they are more tenuous. To reinforce a healthy skepticism:
Perform retrospective reviews. While post mortems are standard practice in sport and in medicine, they are virtually non-existent in business. A noteworthy exception: a major financial institution is analyzing the results of its bonus and promotion process to see if they in fact reward the behaviors that senor management believes they are rewarding.
Most companies would learn a great deal if, for instance, they looked at all their capital investment decisions from, say, 1999 to 2002 (both the projects approved and the ones turned down) to see which decisions were good, which were not so astute, and what if anything could have been done to improve the decision process.
Question the logic. Too often, managers are reluctant to ask how certain analyses were derived for fear of appearing ignorant. Yet it is important to inquire, particularly for one-off studies, what analytic methods were used, and what assumptions were implicit in the use of that methodology. For example, a regression analysis assumes a linear relationship between the variables. What if the relationship is actually a step function? Trying to fit a regression to the data would produce misleading results. Similarly, “real options” have become popular as a way of valuing investment opportunities. But option valuation is a tricky business. According to Black-Scholes, some variables, such as the length of the option and the implied volatility, have a significant impact on the option price. It is critical to understand the rationale for the use of the chosen values and run sensitivity analyses around those assumptions.
If you don’t’ have the appetite for this line of inquiry, engage someone with strong advanced math skills, such as a doctoral candidate in applied mathematics, to serve as a house skeptic.
Probe the data. As noted before, all data are not created equal. Generally speaking, the most reliable are ones of physical activity. Financial and accounting data are less solid, and metrics on consumer behavior are even more tricky. It is notoriously difficult to ascertain whether and why consumers will buy a product, since their responses are very much influenced by the test environment. Anyone who has done survey research, for example, will confirm that results can be skewed significantly by how the question is phrased. Similarly, researchers have found that when consumers are given a taste test and asked to rate, say, which salsa they like best, their answers are completely different if they are asked to rate the various attributes (spiciness, texture, etc.) and then say which they prefer. In a bizarre analogy to the Heisenberg uncertainty principle, the act of making the consumer explain why he likes a product shifts his choice.
And probably the most slippery data of all is personnel assessments, where most large companies force subjective, and despite their efforts, not very comparable information into tidy grids and rankings. (Doubters should read Patrick D. Larkey’s, and Jonathan P. Caulkiins’ 1992 paper, “All Above Average, and Other Unintended Consequences of Performance Appraisal Systems”, a provocative and well documented indictment).
The remedy, particularly for important decisions, is to understand the factual underpinnings and be willing to invest in additional research. For example, New Coke was considered a shoe in because it scored so well on sip tests compared to other colas. But consumers don’t buy soda in sips, they buy entire cans, and sip tests favor sweeter drinks. New Coke bombed because many target customers found it to be cloying. Had Coca Cola used multiple approaches to vet New Coke’s consumer appeal, they may well have surfaced its shortcomings.
Be alert to new information. A persistent mistake is attachment to an old perception of a situation (another manifestation of anchoring). Although it is fashionable to blame lumbering corporate reporting systems that filter out bad news, this tendency to dismiss new data is a well documented individual behavior. Recall Thomas Kuhn’s The Structure of Scientific Revolutions: scientists who grew up with an old paradigm simply could not accept a new model. A whole generation had to die out before a new theory, no matter how well proven, became widely accepted.
How can you overcome this cognitive inertia? By demonstrating keen interest in new developments, and fostering that attitude in others. The tried and true approach of talking directly to customers is invaluable. It also helps to ask front line staff often about trends and developments they see, and encourage them to pass them along. You will get a lot of noise along with some choice nuggets, but in this case, the discipline of cultivating awareness and mental flexibility is as important as any bits of intelligence you glean.
Consult your gut. A recent study published in the journal Science found that for complex decisions (defined in this study as involving 12 variables, versus 4 for the “simple” decision) unconscious decision processes yielded much better results than trying to reason it out. Our rational mind can comprehend a limited amount of data, while our unconscious processes, honed over thousands of years of evolution, are better at dealing with complicated situations. In these cases, studying the data and sleeping on it produces demonstrable better choices.
* * *
An overreliance on metrics can lead to “knowing the price of everything and the value of nothing.” Take heed: that is how Oscar Wilde defined a cynic, and cynicism is not viewed favorably in most organizations.
Yet American corporations have for some time been engaged in what can well be described as cynical behavior: taking aggressive accounting measures, engaging in short-term expediencies to improve results, too often displaying little concern for the impact of their actions on employees and communities. Now it is no doubt a stretch to blame these actions on the use of numbers. But the two do seem to go hand in hand.
Management is the art of making decisions in the face of uncertainty. Statistics and analysis can help us understand the nature of that uncertainty and dimension the risks we are taking. But they can also provide false comfort and engender undue confidence. Perhaps the biggest obstacle to giving up the metrics habit is that it will require executives to acknowledge their limitations.
April 21st, 2007
Back in 1999, Peter Drucker wrote about “The Real Meaning of the Merger Boom.” In a punchy essay for the Conference Board’s Annual Report, the guru for all gurus proclaimed, “there is no merger boom today.” End of story.
In fact, he made clear that “in total dollar volume,” it was a zero sum game. De-mergers, unnoticed, were equal to the mergers. Moreover, “the majority of today’s mergers are defensive, the majority of yesterday’s were offensive.” If anything, this has simply become more the case in 2006 and 2007. For example, the major auto companies, so enamored of mergers for a while, have now taken to joint ventures. Many, many mergers today are consolidation plays, tactical efforts to hang on in dying businesses, pulling together wounded enterprises that think they can afford heart surgery when they are large enough to pay the bill.
Drucker could have gone on to point out that history is littered with mergers that subtracted value for shareholders and society. Even the wave of industry consolidations that have taken place from 2000-2007 may in the end prove strategically short-sighted –investments in dying industries without regard to tomorrow.
“The truly important developments in corporate and economic structure today are not the mergers and de-mergers. They are, largely unnoticed or at least unreported, new and different ways of corporate structure, corporate growth, and corporate strategy….the real boom has been in alliances of all kinds, such as partnerships, a big business buying a minority stake in a small one, cooperative agreements in research or marketing, joint ventures, and, often, ‘handshake agreements’ with few formal and legally binding controls behind them.”
Drucker spotted the real boom – alliances. But an utter fascination with the doings of Wall Street, even in our highest political councils, has distracted all of us, riveting us on merger headlines and concealing from us this deep enduring trend of our time.
The most adroit of a new breed of global chief executive gets it. Such is Carlos Ghosn who turned around Japan’s Nissan Auto, peeling away layers of fat instead of adding extraneous divisions. He went from massive losses to $7 billion in profits and wiped out $23 billion of debt. Nissan’s 11% operating profit margin has made it the most profitable of the world’s big automakers (See Economist, February 26, 2005, p. 66). Now to head Renault as well, Ghosn has said that the power of the alliance between them lies “in its respect for the identities of the two companies, and on the other, in the necessity of developing synergies.” If Nissan had been fused with Renault, failure would have followed.
We ourselves are very aware of the negatives that crop up with mergers. It was only a short time after Allegheny Airlines absorbed PSA and Piedmont Airlines (both better companies than it incidentally) that the combined market value of the three added up to less than the value of each of the components prior to their homogenization. This unhappy trinity, once known as Agony Airlines to wags in the Northeast, has since become the teetering bankrupt U.S. Airways, affectionately called UseLess Airways by its passengers. After many false re-starts, it is hoped that America West’s management, which took over U.S. Air, can run the new combined airline to better effect.
As well, one can not overestimate the size of the merger friction costs imposed by investment bankers, lawyers, and accountants who created and distorted this and other stillborn combinations. Reduced friction costs for continuing operations have traditionally been the excuse for bloated business combinations and expensive asset bases, but this does not at all account for the absolutely horrendous sunk costs imposed by middlemen in the merger/de-merger process. In fact, the mechanics of mergering themselves often distort the shape of the resulting enterprise, creating a lumbering creature nobody envisioned. But the financial and strategic costs that lard the merger process are well obscured by the middlemen and their sales people who make such a good living off of such transactions.
There are broad conceptual reasons as well why a collaborative model free of hierarchy and legalistic strictures is productive of much more economic value. With increasing amounts of the work to be done by corporations in advanced economies consisting of knowledge and professional services chores involving far different workflows, the fuel for business activity consists of pockets of intelligence that are broadly distributed throughout the world, often outside the corporation. One cannot accumulate the human resources one needs to play on a global scale within one’s walls. Organizations need to tap into a multitude of other organizations. And they need to avail themselves of workers strewn about the globe—some in outsourcing companies and others entirely on their own.
Charles Handy finds that “many organizations have more people working outside them than they have inside them.” Furthermore, “only about half the working population is working inside an organization.” The successful company, with perhaps only 20% of its workforce on its own payrolls, has to learn to virtually coordinate companies and independent workers who are bound to it by no more than a handshake. Handy chats about this brave new world in “The Future of Work in a Changing World” in an interview with Aurora Online.
For the past 10 years the goal of our own staff has been to divine the rules of the road for the still emerging collaborative enterprise. In every way, they fly in the face of all the dogmas we laid out for the corporation in the 20th century. For this reason, the postulates of collaboration are usually counter-intuitive. Consider here just two examples:
Rule 1: At best the chief executive should be a fish out of water. Take a look at Nissan. Carlos Ghosn was born in Brazil in a Lebanese immigrant family, then had a French education first in Lebanon and later at the Ecole Polytechnique where he studied engineering. For openers he turned around Michelin, the tire company, in Brazil to begin with, then in America. He went on to become a cost-cutter at Renault. Louis Schweitzer, the very original business mind who headed up Renault, posted him to Nissan with little in-France business experience and not even a smidgeon of Japanese grounding in his system. But he was effective because he could bring a pan-global outsider’s objectivity to Nissan. He succeeded in part because he was an alien from outer space. He was the stranger who could see what makes the natives tick and who had no sentimental ties to sever as he cleaned house.
Rule 2: The best alliances are very, very unlikely. For instance, Kirin Beer, once the IBM of the Japanese beer business, came to George Rathmann of Amgen as he was getting ready to ramp up production of Epogen. It contributed its fermentation production techniques to the biotech company, as well as a slug of capital. Rathmann has since acknowledged that its role was central to the growth of Amgen into a multi-billion dollar company. Most likely, a start up will find that the process knowledge it really needs lies 10,000 miles away in a dramatically different industry and in a vastly different culture. But, of course, the Japanese bring special skills and excellence to manufacturing which is why, as we used to say, that the American dream got interrupted by the Japanese clock radio.
Alliances are best, then, if they overcome all the inbreeding tendencies of conventional businessmen. The dynamics of mergerdom tend to preclude such unlikely alliances.
What’s at issue here is how to devise an organizational model that encourages rapid, insistent global learning by an organization. As we have said elsewhere in “Better Learning Networks,” (see item #187) researchers at the Santa Fe Institute have come to understand that there is an optimal coupling within an organization that encourages learning. It is simply too hard for knowledge to interpenetrate an organization where the bonds are made of steel rather than nervous tissue.
Those who think about software systems have come up with the same insight in respect to information systems. Ubiquity interviewed us about collaboration a while back. There we reference an article by John Seely Brown and John Hagel called “The Joy of Flex” in which they said, “”Loose coupling makes it easier to improvise without worrying about disruptions elsewhere in the system.” While hardwired systems afford short-term cost advantages, they are costly in the end, since they cannot accommodate the disruptions imposed by global realities. Likewise, we would contend, merged companies achieve a rigidity that is antagonistic to agile behavior.
If alliances are the fluid organizational form that should dominate our business activity, many head-in-the-sand executives don’t know it. Squabblers debate about the value of strategic alliances and how to make them work. This is all rather academic. Alliances are very much a fact of life in our lean business society, and so the only option for the business generalissimo is to saddle up the horse and see if he can ride this new kind of stallion.
Well, the future is always a bit uncomfortable until it is past.
January 29th, 2007
Carlos is the CEO of a successful food company. He is brilliant, hard-working, and an expert in his field. He started out on the factory floor and rose through sales and marketing to the top spot. There is nothing in his business that he hasn’t seen firsthand. Like many creative people, he is also hyperactive, with the metabolism and attention span of a hummingbird. He loves to buzz around his company’s facilities, dropping in on employees to see what they’re working on and shoot the breeze. Carlos loves people and he loves to talk. All in all, Carlos presents a very charming package, except when his mouth runs ahead of his brain.
One month ago his design team presented him with their ideas for the packaging of a new line of snacks. Carlos was delighted with the designs. He only had one suggestion.
“What do you think about changing the color to baby blue?” he said. “Blue says expensive and upmarket.”
Today the designers are back with the finished packaging. Carlos is pleased with the results. But he muses aloud, “I think it might be better in red.”
The design team in unison roll their eyes. They are confused. A month ago their CEO said he preferred blue. They’ve busted their humps to deliver a finished product to his liking, and now he’s changed his mind. They leave the meeting dispirited and less than enthralled with Carlos.
Carlos is a very confident CEO. But he has a bad habit of verbalizing any and every internal monologue in his head. And he doesn’t fully appreciate that this habit becomes a make-or-break issue as people ascend the chain of command, A lowly clerk expressing an opinion doesn’t get people’s notice at a company. But when the CEO expresses that opinion, everyone jumps to attention. The higher up you go, the more your suggestions become orders.
Carlos thinks he’s merely tossing an idea against the wall to see if it sticks. His employees think he’s giving them a direct command.
Carlos thinks he’s running a democracy, with everyone allowed to voice their opinion. His employees think it’s a monarchy, with Carlos as king.
Carlos thinks he’s giving people the benefit of his years of experience. His employees see it as micromanaging and excessive meddling.
Carlos has no idea how he’s coming across to his employees.
He is guilty of Habit #2: Adding too much value.
It’s not that people like Carlos don’t know who they are or where they’re going or what they want to achieve. Nor is it that they don’t have an adequate sense of self-worth. In fact, they tend to be very successful (and their self-esteem can often be excessive). What’s wrong is that they have no idea how their behavior is coming across to the people who matter—their bosses, colleagues, subordinates, customers, and clients. (And that’s not just true at work; the same goes for their home life.)
They think they have all the answers, but others see it as arrogance.
They think they’re contributing to a situation with helpful comments, but others see it as butting in.
They think they’re delegating effectively, but others see it as shirking responsibilities.
They think they’re holding their tongue, but others see it as unresponsiveness.
They think they’re letting people think for themselves, but others see it as ignoring them.
Over time these “minor” workplace foibles begin to chip away at the goodwill we’ve all accumulated in life and that other people normally extend to colleagues and friends. That’s when the minor irritation blows up into a major crisis.
Why does this happen? More often than not, it’s because people’s inner compass of correct behavior has gone out of whack—and they become clueless about their position among their coworkers.
You can learn more about this phenomenon in my new book- What Got You Here Won’t Get You There: The Twenty Habits That Are Holding You Back from the Top — and How to Stop Them.
December 15th, 2006
New products, new processes and new business models require a steady flow of good ideas, knowledge, resources, and the ability to execute.
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Our founding “thought-leaders” include:
Douglas K. Smith
Doug Smith is one of the world’s leading management thinkers and consultants. While at McKinsey & Company, he co-led the Firm’s worldwide organization practice and launched the “horizontal organization,” a part of the reengineering revolution that Fortune called “the model for the next fifty years.” Most recently, he authored On Value and Values — a sweeping vision to revitalize our values for our new world of markets, networks, organizations, friends and families. He is the co-author (with Jon Katzenbach) of The Wisdom of Teams and The Discipline of Teams, books used by millions of people in organizations the world over. Smith also authored Make Success Measurable and Taking Charge of Change — praised for using performance to drive real change in a dynamic world. His book Fumbling The Future changed forever how Fortune 500 companies manage innovation. He has contributed to performance, innovation, strategy and change in scores of organizations across more than forty industries in all three sectors: private, government and non-profit. He is the architect of Achieving Excellence in Community Development, a performance-driven organizational investment program that has revolutionized executive and leadership education. Cited in High Impact Consulting for having the number one impact of all consultants mentioned, his philosophy and practices routinely generate better than 100:1 returns.
John Hagel III
John Hagel is an independent management consultant and author who works with senior management to shape global business strategies and improve business performance. His experience includes senior management positions in technology businesses and sixteen years as a consultant with McKinsey & Co. John has written numerous books, including The Only Sustainable Edge with co-author John Seely Brown; they have created a joint web site – www.edgeperspectives.com – where their continuing research on “edge-strategy” can be accessed. Hagel is also the author of Out of the Box, Net Worth and Net Gain, all published by Harvard Business School Press. He has also written frequently for major business publications including Harvard Business Review, Wall Street Journal, Financial Times and McKinsey Quarterly.
John Seely Brown
JSB is currently a visiting scholar at USC and prior to that he was the Chief Scientist of Xerox Corporation and the director of its Palo Alto Research Center (PARC)-a position he held for nearly two decades. While head of PARC, Brown expanded the role of corporate research to include such topics as organizational learning, knowledge management, complex adaptive systems, ethnographic studies of the workscape and nano technology. He was a cofounder of the Institute for Research on Learning (IRL). His personal research interests include the impact of globalization on business, the management of radical innovation, digital culture, ubiquitous computing and organizational and individual learning.
Tom Davenport
Thomas H. Davenport is the President’s Distinguished Professor of Information Technology and Management at Babson College in Babson Park, Massachusetts, the director of research at Babson Executive Education, and a fellow at Accenture. He is the author of Thinking for a Living (Harvard Business School Press, 2005). Davenport directed research centers at Ernst & Young, McKinsey & Company, and CSC Index, and most recently, what used to be called the Accenture Institute of Strategic Change. He has written, co-authored or edited ten books, including the first books on business process reengineering, knowledge management, and the business use of enterprise systems.
Marshall Goldsmith
Marshall Goldsmith is a coach to top executives in many of the world’s leading companies, a prominent speaker and educator, and the well-known author of many books and articles on leadership. He is one of the foremost authorities on how to help leaders achieve positive, measurable changes in their own behavior and in the behavior of their people and teams. In his coaching career, Dr. Goldsmith has worked with over 70 CEOs and their management teams. He continues to conduct workshops for executives, high-potential leaders and HR professionals. Recently, the American Management Association named Dr. Goldsmith as one of the 50 greatest thinkers and business leaders who have most influenced the field of management. Forbes named him as one of the five most-respected executive coaches. Dr. Goldsmith’s work has received recognition from the Academy of Management, the Institute for Management Studies, the American Society for Training and Developing, the Center for Creative Leadership, the Conference Board and the Human Resource Planning Society. He serves on the faculty of the executive education programs at Dartmouth and the University of Michigan. He has authored 18 books, including the best-selling The Leader of the Future. For 10 years, Dr. Goldsmith served as a Board Member at the Peter Drucker Foundation. He also donates a substantial amount of time to non-profit organizations. He has been selected as an American Red Cross “National Volunteer of the Year.” Dr. Goldsmith holds a B.S. degree from Rose-Hulman Institute of Technology, an MBA from Indiana University and a PhD. from U.C.L.A.
Vijay Govindarajan
Vijay Govindarajan, known as VG, is the Earl C. Daum 1924 Professor of International Business at the Tuck School and founding director of Tuck’s Center for Global Leadership. He is also the faculty co-director for Global Leadership 2020, Tuck’s executive education program that focuses on global management and is taught on three continents.VG’s area of expertise is strategy, with particular emphasis on strategic innovation, industry transformation, and global strategy and organization. Professional credits include: Outstanding Faculty, named by Business Week in its Guide to Best B-Schools; Top Ten Business School Professor in Corporate Executive Education, named by Business Week; Top Five Most Respected Executive Coach on Strategy, rated by Forbes; Top Ten Thought Leader in Strategy Coaching, named in Profiles in Coaching; Outstanding Teacher of the Year, voted by MBA students; and Top 50 Non-Resident Indians of the Year, named by NRI World. Prior to joining the faculty at Tuck, VG was on the faculties of The Ohio State University and the Indian Institute of Management (Ahmedabad, India). He has also served as a visiting professor at Harvard Business School, INSEAD (Fontainebleau, France), the International University of Japan (Urasa, Japan), and Helsinki School of Economics (Helsinki, Finland). VG has published seven books, including Ten Rules for Strategic Innovators — from Idea to Execution, co-authored with Chris Trimble.
Laurence Haughton
Laurence Haughton is a management consultant with over 20 years of front-line experience in manufacturing, retail, media and service industries. He is the author of It’s Not What You Say… It’s What You Do – How Following Through at Every Level Can Make or Break Your Company and co-author of It’s not the big that eat the small… It’s the FAST that eat the slow. An expert on execution and follow-through, Haughton has helped thousands of entrepreneurs and executives achieve higher revenues and profits by sharing new strategies for finding, keeping and growing customers and revolutionary tactics that make leaders faster and more effective. Haughton has co-hosted televised conferences, keynoted end-user meetings and keynoted presentations for trade groups, entrepreneurs and Fortune 50 companies like Kodak and AOL Time-Warner.
David Maister
David Maister is widely acknowledged as one of the world’s leading authorities on the management of professional service firms. In 2002, he was identified as one of the top 40 business thinkers in the world (BUSINESS MINDS, Financial Times/Prentice Hall.) His first book on the professions, Managing the Professional Service Firm, published in 1993, collected many of his best articles. It was followed in 1997 by True Professionalism, and in 2000 by The Trusted Advisor, written with Charles H. Green and Robert M. Galford. In 2001 he published Practice What You Preach and in 2002, First Among Equals, co-authored with Patrick McKenna. A native of Great Britain, Maister holds degrees from the University of Birmingham, the London School of Economics and a doctorate in Business Administration from the Harvard Business School. He began his teaching career at the University of British Columbia, Canada, and then joined the Harvard faculty, where he taught courses in managing service businesses and managing production operations from 1979-85. During that period he published seven books on academic business topics such as managing trucking and airline companies, factory operations, and architectural firms. Maister lives in Boston with his wife and coach, Kathy. He is an avid collector of popular music, and owns more than 15,000 CD’s and a rapidly growing number of DVDs. In March of 2005, he finally took his own advice, gave up smoking and lost 30 pounds.
Laurence Prusak
Larry Prusak is a researcher and consultant and was the founder and Executive Director of the Institute for Knowledge Management (IKM). This was a global consortium of member organizations engaged in advancing the practice of knowledge management through action research. Larry has had extensive experience, within the U.S. and internationally, in helping organizations work with their information and knowledge resources. He has also consulted with many U.S. and overseas government agencies and international organizations (NGO’s). He currently co-directs “Working Knowledge,” a knowledge research program at Babson College, where he is a Distinguished Scholar in Residence.
December 11th, 2006