These are turbulent times for business, as companies struggle to adjust to the globalization of markets and competition, the expansion of the service-based economy, the impact of deregulation and privatization, and the explosion of the knowledge revolution. All of these forces are driving firms to fundamentally rethink their business models and radically transform their capabilities – but an equally important (though less obvious) business transformation is taking place with respect to design.

As we leave behind one economic age and enter another, many of our philosophical assumptions about what constituted competitive success grew out of a different world. Value creation in the 20^th century was largely defined by the conversion of heuristics to algorithms. It was about taking a fundamental understanding of a ‘mystery’ -- a heuristic -- and driving it to a formula, an algorithm – so that it could be driven to huge scale and scope. As a result, many 20^th century organizations succeeded by instituting fairly linear improvements, such as reengineering, supply chain management, enhanced customer responsiveness, and cost controls. These ideas were consistent with the traditional Taylorist view of the company as a centrally-driven entity that creates wealth by getting better and better at doing the same thing.

Competition is no longer in global scale-intensive industries; rather, it's in non-traditional, imagination-intensive industries. Today’s businesses are sensing an increased demand for speed in product development, design cycles, inventory turns, and competitive response, and there are major implications for the individuals within those organizations. I would argue that in the 21^st century, value creation will be defined more by the conversion of mysteries to heuristics – and that as a result, we are on the cusp of a design revolution in business.

The Progression from Mysteries to Binary Code
Over the course of time, phenomena enter our collective consciousness as mysteries – things that we observe, but don’t really understand. For instance, the mystery of gravity once confounded our forefathers: when they looked around the world, they saw that many things, like rocks, seemed to fall to the ground almost immediately; but others didn’t -- like birds, and some seemed to take forever, like leaves. In art, there was the long battle to understand how to represent on a two-dimensional page what we saw in front of us in three dimensions. Music continues to be a mystery that confounds: what patterns of notes and sounds are enjoyable and make listeners feel happy and contented?

We start out with these mysteries, and at some point, we put enough thought into them to produce a first-level understanding of the question at hand. We develop heuristics -- ways of understanding the general principles of heretofore mysteries. Heuristics are rules of thumb or sets of guidelines for solving a mystery by organized exploration of the possibilities.

So why do things fall down? We develop a notion of a universal force called ‘gravity’ that tends to pull things down. In art, we develop a notion called ‘perspective’ that guides our efforts to create renderings that appear to the eye to have three-dimensions rather than two. What kind of music do people like to listen to? We learn about chords, and then create song types like ballads, or folk songs, or the blues. If one follows a set of guidelines, one will likely create something that people enjoy listening to.

Heuristics don’t guarantee success – they simply increase the probability of getting to a successful outcome. They represent an incomplete understanding of a heretofore mystery. In any given field, some people barely understand heuristics, while others master them. The difference between them is the difference between one-hit-wonder Don McLean, author of "American Pie", and Bruce Springsteen, author of scores of hit songs. For McLean, the mystery remained just that: he came up with a single inspiration that created one random event – one of the biggest pop song hits of all time. Yet he failed to produce another hit of any consequence in his entire musical career. In contrast, Springsteen developed a heuristic – a way of understanding the world and the people in it – that enables him to write songs that have great meaning to people and are immensely popular. His mastery of heuristics has allowed him to generate a steady stream of hit albums/CDs over a 30-year period.

In due course, increasing understanding can (though in many cases it never does) produce an algorithm: a logical, arithmetic or computational procedure that, if correctly applied, ensures the solution of the problem. With gravity, great scientists like Sir Isaac Newton studied and experimented long and hard enough to create precise rules for determining how fast an object will fall under any circumstance. In the late 1970s, musical innovators like British techno-music guru Brian Eno experimented with the human heartbeat and determined that songs with a synthesized heartbeat as their rhythm track are instinctively enjoyed by listeners, no matter what you added on top of them. The end result of such algorithms is not always positive, of course – this discovery led to electro-pop and eventually to sham bands like Milli Vanilli, who lip-synched recorded music onstage until caught in the act by an unsuspecting audience. And in art, we eventually got paint by numbers.

In the modern era, a fourth important step has been added to the sequence of mystery to heuristic to algorithm. Eventually, some algorithms now get coded into software. This means reducing the algorithm -- the strict set of rules -- into a series of 0’s and 1’s – binary code – that enables a computer to produce a result. For example, with gravity, the fact that we had an algorithm for how things fall meant that we could program aircraft with autopilot, enabling a plane to ‘fall’ from the sky in the organized fashion that we want it to, so that it lands in exactly the right spot. At the coding level, there is no longer any judgment involved: the plane lands on the basis computer instructions that are nothing but a series of 1’s and 0’s, because our understanding of gravity has moved from a mystery to a heuristic to an algorithm to binary code.

Implications for the Design of Business
The progression of the ‘march of understanding’ described here has important practical implications for today’s business people. Broadly speaking, value creation in the 20^th century was about taking a fundamental understanding of a mystery -- a heuristic -- and reducing it to a formula, an algorithm – so that it could be driven to huge scale and scope.

Take McDonalds, for instance. In 1955, the McDonald brothers took a mystery – ‘how and what do Californians want to eat’? And they created a format for answering that – a heuristic – which was the quick-service restaurant. Is this heuristic what created enormous value? No, because there were many restaurants in California doing similar things at the time, and all of them were discovering that Californians wanted faster, more convenient food. What made McDonalds different is that Ray Kroc came along and saw that he could drive the McDonald brothers’ heuristic to an algorithm. He bought the store and figured out exactly how to cook a hamburger, exactly how to hire people, exactly how to set up stores, exactly how to manage stores, and exactly how to franchise stores. Under Kroc, nothing was left to chance in the McDonald’s kitchen: every hamburger came out of a stamping machine weighing exactly 1.6 ounces, its thickness measured to the thousandth of an inch, and the cooking process stopped automatically after 38 seconds, when the burgers reached an internal temperature of exactly 155 degrees. By creating an algorithm out of a heuristic, Kroc was able to drive McDonalds to huge size and scope, and to its place today as a global icon.

This move from heuristic to algorithm was repeated over and over throughout the 20^th century. Early in the century, Ford developed the algorithm for assembling cars – the assembly line -- and with it grew to immense size. Late in the 20^th century, Electronic Data Services (EDS) developed algorithms for routinizing systems integration and training COBOL programmers, and with it grew to previously unimagined size in the systems integration business. In between, Procter & Gamble created the algorithm for brand managing, Anheuser Busch for making and selling beer, Frito Lay for making and distributing snack chips, on so on. For these companies, as well as Dell and Wal-Mart, success depended not so much on a superior product, but on a superior process, and each is an example of the relentless ‘algorithm-ization’ that paved the way for massive value creation in the 20^th century.

This dynamic accelerated in the latter part of the 20^th century (1985-2000), when many algorithms were driven to code. Like most things in life, this final step of reducing something to binary code has good and not-so-good aspects to it. While coding enables an incredible increase in efficiency, it is also true that with coding comes the end of judgment: patterns of 0’s and 1’s have no judgment or artistry – they just automatically apply an algorithm. In many respects, the extreme achievement of the 20^th century is soulless numbers. Neither all bad or all good, this is simply the result of the combination of the relentless march of understanding (from mystery to heuristic to algorithm) with the relentless march of Moore’s Law (Intel co-founder Gordon Moore’s prediction that data density would double approximately every 18 months, and the resultant diminishing costs of information technology) – all of which lead to binary code.

So where do we go from here? Will there be more relentless algorithm-ization? I don’t think so. I believe that we will look back on the 20^th century as a tour de force of producing ‘stuff’ -- lots of it, as efficiently as possible. I believe we are transitioning into a 21^st century world in which value creation is moving back to the world of taking mysteries and turning them into heuristics. I see the beginnings of a fundamental backlash against algorithm-ization and the codification of the world around us – a realization that reaching to grab the benefits of economies of scale often involves accepting standardization and soullessness in exchange.

I believe the 21^st century will go down in history as the century of producing elegant, refined products and services – products and services that delight users with the gracefulness of their utility and output; ‘goods’ that are produced elegantly -- for example, that have the most minimal environmental footprint possible, or that produce the fewest worker injuries, whether it be broken limbs or repetitive stress syndrome.

The 21^st century presents us with an opportunity to delve into mysteries and come up with new heuristics. As a society we are faced with major mysteries like, ‘how can big cities actually work’? There are more of them than ever before, and while Toronto works pretty well, many cities around the world don’t, and fixing that is a major mystery. Another big mystery involves how to make health care work, when there’s an infinite demand and a constrained supply. These are the kind of modern mysteries that are being presented to us, and there is no algorithm for them, no coding to magically solve the problems they engender.

But unlike in the 20^th century, this time the goal won’t be to develop mass formulas or algorithms. Firms today are desperately trying to find out what each individual customer wants. Kellogg’s cereal and Hershey's chocolate bars have 1-800 phone numbers printed on them encouraging consumers to call them with feedback. Pepsi has its Web site printed on each can. Information is being gathered and used to cater to and customize solutions to your every need.

I would argue that to be successful in the future, businesspeople will have to become more like designers – more ‘masters of heuristics’ than ‘managers of algorithms’. For much of the 20^th century, they moved ahead by demonstrating the latter capability. This shift creates a huge challenge, as it will require entirely new kinds of education and training, since until now, design skills have not been explicitly valued in business. The truth is, highly-skilled designers are currently leading many of the world’s top organizations --they just don’t know they are designers, because they were never trained as such.

The second implication is that we need a new kind of business enterprise. This new world into which we are delving will require us to tackle mysteries and develop heuristics – and that will require a substantial change in some of the fundamental ways we work. Traditional firms will have to start looking much more like design shops on a number of important dimensions.

Whereas traditional firms organize around ongoing tasks and permanent assignments, in design shops, work flows around projects with defined terms. The source of status in traditional firms is ‘managing big budgets and large staffs’, but in design shops, it derives from building a track record of finding solutions to ‘wicked problems’ – solving tough mysteries with elegant solutions. Whereas the style of work in traditional firms involves defined roles and waiting for the perfect answer, design firms feature extensive collaboration, ‘charettes’ (focused brainstorming sessions), and constant dialogue with clients.

When it comes to innovation, businesses have much to learn from designers. The philosophy in design shops is, ‘let’s try it, prototype it, and improve it’. Designers learn by doing. The style of thinking in traditional firms is largely inductive – proving that something actually operates – and deductive – proving that something must be. Design shops add abductive reasoning to the fray – which involves suggesting that something may be, and reaching out to it. Designers may not be able to prove that something is or must be, but they nevertheless reason that it may be, and this style of thinking is critical to the creative process. Whereas the dominant attitude in traditional firms is to see constraints as the enemy and budgets as the drivers of decisions, in design firms, the mindset is ‘nothing can’t be done for sure," and constraints only increase the excitement level.

The third implication is that we must change the focus of our thinking on design and business. The trends discussed here have generated increased interest in design by the business world, but it is largely focused on ‘the business of design’: the traditional business world is trying to figure out what designers do, how they do it, and how best to manage them. This misses the point fundamentally, and it won’t save the traditional firm. The focus should actually be placed on ‘the design of business’: We need to think much more about designing our businesses to provide elegant products and services in the most graceful manner possible.

Conclusion
Business people don’t need to understand designers better: they need to be designers. They need to think and work like designers, have attitudes like designers, and learn to evaluate each other as designers do. Most companies' top managers will tell you that they have spent the bulk of their time over the last decade on improvement. Now it's no longer enough to get better; you have to ‘get different’.