Businesses thrive on stability and repeatability. Stable and repeatable processes justify large-scale capital expenses; they justify large-scale employee training; and they reduce cognitive overhead because processes and decisions do not change and hence their rationale does not have to be explained repeatedly.

By contrast, an analytically based enterprise of the future will have to be designed around volatility rather than repeatability. Volatility—or rapidly changing decisions that are context- and time-sensitive—will be a big challenge for enterprises. Decisions are no longer easily explainable; capital investments cannot be based on mass repeatability but must cater to endemic volatility

There are three very distinct ways that organizations can fall into the analysis-paralysis trap. One is a managerial tendency to “over-fit the curve”—a statistical term that refers to the diminishing value of additional data once a pattern (or curve, in the graphic sense) has been found. Data collection has a price, inaction has a price and an analytically literate organization will clearly understand the cost of over-fitting.

The second cause of analysis-paralysis is waiting for data that simply does not exist, which reflects an inability to design experiments to generate the needed data. As mentioned above, experimentation has a price and inaction has a price, so an analytically literate organization will be characterized by a clear understanding of data gaps and the value of experimentation to break the logjam.

The third cause of analysis-paralysis is the fact that most companies do not know or articulate their risk tolerance clearly and are much more likely to penalize failed action than inaction. As a result, many managers do not act unless there is enough data to assure them of successful outcomes. An analytically literate organization will have a firm grasp of its risk tolerance. With guidelines and models for action under uncertainty, it will restore the symmetry between how it treats failed action and inaction.

We have to rely both on analysis and synthesis. Analysis—taking complex things and studying and understanding them—is very useful for knowing how well something is going to work and how you might improve it or make it more efficient. It’s not very good for coming up with major new ideas. There we have to be able to synthesize many competing ideas or competing insights—even if those things are in tension—into something that is somehow a whole. What designers and design thinkers are always searching for is the alternative that’s better than the initial starting points.

Over the years, I have found that most executives are smart and hardworking, and want to do the right thing. But they are terrible at critical thinking and analytical rigor — usually because they confuse the factors that lead to high performance with attributions based on that performance. They confuse drivers and results. We see this in everything from corporate culture to leadership to employee satisfaction to customer orientation.

Cost-benefit analysis can be an effective tool to analyze simple, one-dimensional problems, such as whether to install dividers on dangerous stretches of highway, where relatively unambiguous data is in abundant supply and there is little controversy. It also is a good way to elucidate the trade-offs for a given policy or regulation, or to produce a summary statistic about its economic efficiency.

But the cost-benefit method loses its authority when it’s used to assess more complex decisions. It is inadequate for evaluations of interventions that will affect many different dimensions, such as markets, economies, health, the environment, and endangered species. Cost-benefit analysis is also inappropriate for products or processes over which there are disagreements about benefits or about which outcomes are important. And it should never be used as the basis for regulation in the presence of scientific uncertainty or value conflicts, or in an area where there are no authorities one can trust to know all the answers. Decisions like these require a more expansive methodology — one that isn’t dependent on the affectation of translating all value into economic terms, that is more transparent and responsive to outside criticism, and that pragmatically represents the interests of everyone involved: industry, government, and the public.

If you can explain one thing and its opposite using the same data you don't have an explanation. It takes a lot of courage to keep silent.

The Plural of Anecdote is Not Data.

When this [Web 2.0] model allows many new ideas, then the cost of solving problems and of generating content will go down. It also means the cost and the need for filtering will go up. You will need to filter not only for what's good versus what's bad but also for what fits your strategy. Not every idea will work given your asset base, your strengths, and your differentiation. The challenge will not be to find the smart people or ideas but to find a way to teach your whole company to filter on the same set of ideas.

We are creating a society of just two classes. The first and larger class will spend incredible amounts of time to save money. The second will spend incredible amounts of money to save time.

The shift toward tacit (complex) interactions upends everything we know about organizations. Since the days of Alfred Sloan, corporations have resembled pyramids, with a limited number of tacit employees (managers) on top coordinating a broad span of workers engaged in production and transactional labor. Hierarchical structures and strict performance metrics that tabulate inputs and outputs therefore lie at the heart of most organizations today.

But the rise of the tacit workforce and the decline of the transformational and transactional ones demand new thinking about the organizational structures that could help companies make the best use of this shifting blend of talent

So much of what we hear and what we're taught turns out to be false on closer scrutiny. Whether it is expert advice, what you read in the paper, or what your mother told you, if it is important, take the time to figure out for yourself whether it is really true.

Collaboration will be the critical business competency of the Internet Age. It won't be the ability to fiercely compete, but the ability to lovingly cooperate that will determine success. Rather than focusing on stomping the competition into the ground, true leaders of the Internet Age will focus on creating value for their customers, intelligence and skill in their talent, and wealth for their investors and shareholders. In a more complex, wired world, the winning strategies will always be based upon a "we" not "I" philosophy.

The new currency won't be intellectual capital. It will be social capital-the collective value of whom we know and what we'll do for each other. When social connections are strong and numerous, there is more trust, reciprocity, information flow, collective action, happiness, and, by the way, greater wealth.

Most people overestimate what is going to happen in the next 2 or 3 years and underestimate what is going to happen in the next decade.

In our economy, more and more of the output is in quality, variety, customer service, timeliness, and components of output other than the number of units produced at a given cost. As a result, the nature of our GDP is changing; the nature of our competition is changing on the output side.

The same thing is happening on the input side, where more and more of the important inputs to production aren't just labor, capital, energy, and materials, but organizational capital and other intangible assets. Real research and management agendas for the coming decade are to understand better these intangible outputs and inputs because you can't manage what you don't measure.

Because...markets are moving so fast, data is not worthless, but it almost is. Everything is based on pattern recognition. Metaphors are organizing principles that explain a pattern. Metaphors also present a set of relationships that you can test against reality. When you find great metaphors they explain the universe. It's not in any sense trivial. It is playful.

Strategy gurus often assert that winning comes from "thinking out of the box" or "reframing the problem." They are wrong. Across the 55 industries we studied, only four common ideas accounted for 80 percent of successful breakouts: power retailing (Home Depot, Circuit City); bypassing one or more steps in the value chain (Frito-Lay, Dell Computer); focusing, simplifying and standardizing (McDonald's, Nucor); and megabranding (Disney).

The big winners weren't even the originators of the ideas; they were the first to make an existing concept work on a large scale in a new industry.

A few decades ago, our lives were centered in places. We had the most in common with our village or city neighbors, with the people geographically closest to us. Place formed our connections to the social groups that mattered most: our tribes, churches, jobs, and schools. The defining politics -- and so, defining values -- were those rooted in physical communities.

Today, place has lost relevance for most of us in a connected, global world. We reside in places, of course, but that's basically a lifestyle choice. Rather, Doug Smith writes, "it is in markets, organizations, and networks, and among family and friends that you spend your time, pursue your most pressing purposes, and find meaning in your life." So "Where do you live?" is an interesting question, but "What do you do?" is more telling.

Smith sees the shift in community from place to "purpose," as he says, as profound. For while place-based communities historically understood how to make the values-based decisions that shaped society, organizations -- especially corporations -- are flailing. They have the power to change the future for better or worse, but not the ethical will or know-how.

The truly successful managers and leaders of the next century will. . . be characterized not by how they can access information, but by how they can access the most relevant information and differentiate it from the exponentially multiplying masses of non-relevant information.

Three simultaneous revolutions-new technologies, globalization, and the end of communism-are destroying the fixed reference points for business. As they do, would-be business leaders have to think of themselves as economic explorers. Leaders are people who know they're at point B and need to go to point A. Their problem is to find a route from B to A and persuade the troops to follow. Explorers are people who don't know where they are, don't know where they want to go, don't know how they'll get there, but do know they want to get rich. Explorers are essentially strategic thinkers without a road map.

Ultimately, the only purpose of the buffers and caches we rely upon today, such as diskettes and compact discs and DVDs, is to overcome real or perceived supply inefficiency. As our networks become hyperefficient we will rely upon storage less and less. In other words, if you believe in a future of ubiquitous connectivity, where we can get all the digits we want wherever we are and whenever we want them, we'll have little or no need to store them or carry them around.

One important characteristic of the next big thing is that it must have the power to surprise at the time it starts to become big, but surprise only a little bit.It's not whether you can see it coming; it's whether your neighbour doesn't, but only by a little bit. Your neighbour must also share the perception that the next big thing has the power to disrupt the current order. The next big thing is about perception more than reality.

Marketers are in a slow, denial-laden shift from buying content-attached audiences, like those of TV shows, to buying intent-attached audiences, like those of search engines and personal video recorders.

If you were to ask what the two main challenges are that we face, technology is not going to help you with either.

One is to increase the dismal productivity of the new labor force-knowledge workers and service workers. In blue-collar work, the question is how the job is done. But in knowledge work, the question is what should be done. Managements haven't asked that question yet. For this challenge, technology isn't helping very much.

The other challenge is to figure out what's going on outside the company. Inside the company, there are only costsÂ…But we know nothing about the outside. The biggest change that technology could bring would not be a faster computer. It would be concepts for getting information about the outside. These concepts are very, very slow in coming.

The greatest mistake I made in a long life, and I made lots of them, was to invent the phrase "profit center." There ain't no profit centers inside a business; there are only cost centers. The only profit center is a customer whose check hasn't bounced.

Fundamentally, prediction is never valued as much as explanation in academia.

When a great question is first started, there are very few, even of the greatest minds, which suddenly and intuitively comprehend it in all of its consequences.