By Christopher Rollyson Last night I attended TiE Chicago’s “The Great Chicago Tech Debate,” which turned out to be a rousing panel discussion (no, that’s not necessarily an oxymoron 😉 replete with insights. As it was my first TiE (The Indus Entrepreneur) event, I enjoyed taking an informal survey of members afterwards, and everyone I spoke with found it extremely valuable (not awfully surprising, but still..). TiE, which was founded in The Valley and has chapters globally, is a network to support entrepreneurs. As its name suggests, many of its leaders originally hail from India, and many have founded, led or helped to launch successful start-ups that have leveraged offshore partners in India.
Although the setting of this tale is Chicago, its lessons will apply to many other cities, provinces or countries that find themselves in a global knowledge economy, with the need to form a vision to galvanize their citizens to make changes in order to succeed in the new environment. Two of the main challenges are: making the shift from the industrial economy to the knowledge economy and the need to differentiate to compete. “Technology” plays a supporting role, which we’ll discuss more in a minute. After some observations on the debate, I will offer what I think we have to do differently and how Chicago, and other industrial economy regions, will blossom again.
By Christopher Rollyson Sidebar: Industrial Economy DNA
Chicago, in being one of the foremost industrial regions, has industrial economy DNA. This DNA isn’t well suited to the first phase of the knowledge economy, which turns many industrial economy assumptions on their heads. For example, even more remarkable than tech companies’ ability to create wealth quickly is their lack of constraints from raw material inputs: these companies can be located anywhere, irrespective of natural resources. Their main physical requirements are power and fiber, which can be built or brought almost anywhere. In contrast, putting together an industrial enterprise involves accommodating materials with physical constraints at every turn: the sources of raw material inputs are often limited and scarce. Moving the material or parts from one area of the enterprise to another often requires special machines and specialized equipment. Dangerous chemicals are often involved in transforming raw materials. Disposing of waste is not trivial. Often, machinery to transform the raw materials must be custom built, and the machinery imposes its own constraints. Consequently, Chicagoans are accustomed to changes being incremental; we are accustomed to things taking time. This economy is bits, not bytes.
Chicago is renowned as a distribution hub, which began with its proximity to water. Since it was already a distribution hub when rail and air transport were born, this infrastructure was hard-wired into Chicago; a similar dynamic made it a fiber infrastructure hub. Transporting pigs is quite a different proposition from lumber, iron ore or hydrochloric acid. The process of meat packing is subject to spoilage, the type of animal, the markets and locations of customers. Dealing with these things is in Chicagoans’ DNA. Mastering their foibles is what made Chicagoans excel, and it’s hard to give up.
As discussed in The 3.x Economies, the agrarian economy preceded the industrial economy, and it was even more imbued with physical constraints. The point here is that we humans have hardwired into our brains the imprint of these economies’ lessons and impulses. Many of these do not apply in a knowledge economy, and that stymies us. The impulses are often so profound, we are not aware of them. People don’t change unless they have to. The fact that we are alive is testament to the fact that we made the right decisions in the past. This is a profound truth and difficult to deal with. It often makes us stick with something longer than we should.
Transformation is so difficult because it challenges us to selectively unlearn part of what we knew before. We have to figure out what parts of what made us successful in the past will help us in the future, and we have to modify the rest or throw them away.
To illustrate what I mean, here are some of the lessons that have made us successful in the past and which are altered drastically in the knowledge economy. Be warned, they contain myriad generalizations, and exceptions abound. Since we’re talking about deep beliefs of Chicagoans as a group of people (i.e. critical mass), I think they are relevant:
| Industrial Economy Lessons |
Knowledge Economy Lessons |
| Barriers to entry are immense because they are based on topography and history; Chicago is the heart of the U.S. when it comes to distributing agricultural and industrial products to the U.S. and beyond. No city will replace Chicago as a distribution hub for physical products. This fact can lead to a certain smugness and imperviousness to change. |
Barriers to entry are often fleeting; a new alliance of hardware or network vendors could roust our software from its dominant position; this leads to legendary (and healthy) paranoia. |
| Zero sum: if I get that parcel of land by the river for my new plant, you can’t have it. If I make that tree into a chair, you can’t use it. If I win, you lose. Even more important: if you win, I lose. |
Not zero sum: if the input is digital, we can both use the same input. Digital assets are infinitely scalable, almost instantly, too. |
| Alliance relationships, because they have often been about raw materials in the past or distribution agreements, have often had a zero sum flavor. |
Alliance relationships are often fleeting as they are based on exploiting temporary conditions in the market. |
| Collaboration usually denotes sharing thoughts with a distinct, independent party on a project that will be jointly accredited; it is done sporadically and guardedly. Industry features a command/control structure, not a collaborative structure. You have production lines because process is often linear. |
Collaboration is the lifeblood of innovation because combining various points of view is crucial in creating transformative products. |
| Innovation is incremental, not transformative. It’s not efficient to rip up an entire factory to drastically change the flow of production based on a radical new idea. Machines are heavy. The long iron pipe inputs couldn’t be brought in that door if the milling machines were put there. Moving the milling machines would mean displacing the grinders and… you get the idea. |
Innovation is often transformative to a fault. Making changes to software can be labor intensive due to complexity, but they need not be. They are much less risky than tearing up a shop floor. |
| Transformation in thought and action is fanciful; efficiency is wisdom, not thinking up discontinuous change ideas. |
Transformation is a key part of the value proposition. It is often a technology start-up’s middle name. |
| Product life cycles are long; we amortize our investments in R&D, packaging, deals with our distribution partners, who have a certain kind of trucks (say, refrigeration at a certain temperature) that couldn’t safely transport a frozen version of the product. Therefore, we operate within physical constraints and invent new flavors instead. |
Product life cycles are short by definition because making significant changes is relatively easy for everyone. |
| Outlook: I am a powerful financier/industrialist/professor/x: the world comes to me to get done what I do. |
I am a technology entrepreneur. The world isn’t here. We have to create a prototype, (get funding) and get customers. We have to go to the world. |
| Information: is scarce, and conditions change slowly which gives information a longer shelf life. Therefore, it is a better strategy to hoard information and share it guardedly. This makes collaboration more difficult. |
Conditions change rapidly, and information rapidly becomes outdated. Therefore, it’s a better strategy to share information. |
In the knowledge economy, inputs are mainly information and knowledge. Hence, the importance of universities and the leverage of repeat technology entrepreneurs and tech-savvy financiers, attorneys and marketers. Moving product means FTP or email. Waste? Empty the trash with no environmentalist consequences. Workers can be anywhere. Plug these differences into Ronald Coase’s economic theory around transaction costs, and you will see a gigantic difference between industrial transactions and knowledge transactions. That is why knowledge economy companies and products develop so fast; they warp our industrial economy perspective.
Transformation means profound change by definition, and people don’t like change. They need powerful, galvanizing and persistent motivation. In being more successful than Massachusetts, Silicon Valley, Austin or North Carolina during the industrial economy, Chicago is challenged to forget many of the lessons that it learned during the industrial economy. We are still too successful today to be universally motivated. Jerry Mitchell pointed out to me that the Route 128 phenomenon was born of the fact that area textiles and other manufacturing were devastated, and there was simply no alternative to taking the risks necessary to build something new. In Chicago, we have not and will never reach that point, which is a curse in the short term and a blessing in the long term. We have a diverse economy, and the industrial economy will continue to be important, although its value will continue to slip relative to the knowledge economy.
By Christopher Rollyson The End of Corporate Imperialism, by C.K. Prahalad and Kenneth Lieberthal, encapsulates the obvious elegantly and factually, and its thesis is far more true today than in 1998, when it was written: “Too often, companies try to impose Western models of commerce on developing countries. They’d do better—and learn more—if they tailored their operations to the unique conditions of emerging markets.” Western MNCs (multinational corporations) perceive the primitive state of consumption in emerging markets, and they too often develop a strategy in which they: 1) focus on the extreme minority of wealthy consumers and/or 2) address the order of magnitude larger middle tier of the market by offering their past-mature products with minor cosmetic changes.
This is another symptom of MNCs’ being stuck between industrial and knowledge economies. As I stated in my Transourcing Point of View, “Enterprises are ambivalent about innovation and product creation because they represent an inherent conflict: the drive to amortize past investments (including process-oriented constraints of marketing, distribution, service, etc.) conflicts with companies’ need to satisfy customers’ wishes for novelty. In practice, this too often leads to vapid product extensions.” The industrial-era enterprise derived its competitiveness largely through production and distribution efficiency, and it marketed to customers in a (relative to today) era of scarcity in which they were grateful for what they could get. Mastering efficiency in transforming heavy, constraint-laden raw materials into products imprinted on executives the impulse to develop products to satisfy their needs to extend past investments while satisfying customer wants as well. This impulse is dangerously out of synch in the knowledge economy, where leaders are differentiated through innovation and marketing excellence. MNCs must focus on innovation that puts customer wants first while retaining their competences in efficiency.
Value-added goods of all types are loaded with assumptions that simply do not hold true in emerging markets. Two common examples are mobile phones and laptops. Cellular infrastructure and usage patterns are different in China and India, so companies cannot address these markets my making current models more cheaply; they must design for the environment. In India, for example, most customers are accustomed to inconsistent infrastructure, and people take it in stride if they have to place three calls to complete a mobile phone conversation. This would be intolerable for a U.S. customer, and this has been built into phones and infrastructure, adding to the cost of the phone and putting it out of reach of many potential customers in India.
If you had asked any computer manufacturer five years ago whether it was possible to make a $100 laptop, s/he would have smiled kindly at your ignorance. Even today’s most advanced designs and supply chains can produce a price four to five times that amount. Yet 2006/2007 will probably see it done (see The $100 Laptop Moves Closer to Reality, The Wall Street Journal, 14 November 2005). To make it happen, however, designers had to go back to the drawing board and discard past assumptions. They had to design for the customer first.
This is the big lesson for emerging markets, which have “usage scenarios” vastly different from those of western countries. Admittedly, there is risk involved in investing in R&D for a market that differs significantly from traditional markets. There are two responses: 1) companies have lived in an era of long product life cycles, and innovation was a core competence for few. Therefore, few are good at it; they are inefficient and success rates are low. Approaching emerging markets through innovation will enable leaders to get better at innovation in general, which will benefit them many times over.
Secondly, the rapidly developing human capital market is waiting to be tapped. By partnering with design and engineering talent within the markets, MNCs will develop a competence that will serve them well: to design products specifically for these markets at a lower cost than they would pay at home. They can take the design lessons they learn and apply them to developed markets as well.
Innovation and tapping the global human capital market are ends in themselves. They are the core competencies of the knowledge economy. Put another way, those that don’t develop these competencies will become less relevant and fade into obscurity.
By Christopher Rollyson In the entry on innovation, I mentioned that an excessive focus on the numbers produced irrational behavior, and I found a perfect example of it this morning. Coca-Cola spends millions of dollars on developing new flavors of Coke, most of which have proven to be well publicized, expensive flops, at least compared to projected goals. According to The Wall Street Journal (“U.S. Thirst for Mexican Cola Poses Sticky Problem for Coke“), the growing Hispanic community in the U.S., a large portion of which is from Mexico, thirsts for its home-grown version of Coke, which Coca-Cola refuses to import due to its agreements with U.S. bottlers. Some enterprising distributors manage to quasi-circumvent the system to import just under $120 million of soda into the U.S. each year. Coke threatens retailers and distributors with legal niceties when bottlers cry foul but otherwise looks the other way.
Let me get this right. Coke spends millions on developing product extensions that flop, yet it has a $120 million nascent market for a product that already exists, which it is resisting.. all because of its relationship with its distribution channel. This is a perfect example of industrial economy thinking: restrict and control while putting customers second to the needs of its organization.
Customers around the world will develop their tastes independent of companies, and this trend will accelerate in the foreseeable future. Companies that learn to become more flexible and responsive will thrive in the global knowledge economy while others that get caught up in command and control will lose ground. The good news is that it’s a choice that every one is free to make. Carpe diem.
By Christopher Rollyson At the MIT Enterprise Forum’s Innovation and Technology Forecast in Chicago Tuesday, there was significant discussion about China’s growth and what that would mean for innovation in Illinois. Many speakers also made references to the importance of catering to knowledge workers. Chunka Mui, Dan Ratner, Geoffrey Kasselman and Jerry Mitchell were panelists, and Jerry spends significant time in China. His admiration for what is happening in China was contagious and triggered the train of thought here.
Continue reading Global Inflection Points
By Christopher Rollyson Innovation
I had the privilege of hearing Larry Keeley, Co-founder of Doblin, the innovation strategy firm, at the GCB Innovation Round Table last night. He painted a vivid picture of the white water global economy in which we find ourselves as a context for his talk on innovation. In brief, the degree of uncertainty and change has created a “nervous time” for corporate executives. The pace of change is probably unprecedented in the experience of the human race (my take on this below). He implied that the anxiety around terrorism is amplifying this underlying general nervousness:
- We face a high degree of ambiguity on political, economic and societal levels. People hate ambiguity.
- Complexity has two meanings: things are difficult to understand and we cannot know the outcome of our actions (because there are too many inter-related concepts, dependencies and data for us to comprehend). People find this overwhelming.
- Volatility of markets; Wall Street (fill in the blank for other markets) punishes executives for vagaries in the numbers, which has led to a legendary “make the numbers at any cost” attitude. People find this mystifying and unsettling because it constantly produces nonsensical behavior.
If we define innovation as measured risk-taking and using new thinking to create an advantage, that usually involves taking people out of their comfort zone. Since the environment does not permit executives to be in a comfort zone in the first place ;-), it is very difficult for companies to find the moxie to innovate. Keeley strongly implied, though, that innovation is a way to thrive in this environment because it’s the new way to create value. However, the way that “innovation is done” by corporations is vapid and off-base. Doblin’s numbers say that it fails 95.5% of the time.
Innovation Framework
After that, Keeley laid out a very compelling framework for innovation that identified several types of innovation and gave substantial examples of firms that used them. Moreover, he believes that innovation is a practicable science as soon as we understand the patterns and learn to apply them appropriately. There are four categories (which contain sub-categories): Finance (Business Model; Network), Process (Enabling Process; Core Process), Offering (Product Performance; Product System; Service) and Delivery (Channel; Brand; Customer Experience). Here it is exploded:
| Doblin’s 10 Types of Innovation* |
| Finance |
| Business Model |
How the enterprise makes money |
Dell |
| Networking |
The enterprise’s structure/value chain |
Wal-Mart |
| Process |
| Enabling Process |
Assembled capabilities (think package solutions) |
Siebel |
| Core Process |
Proprietary processes that add value |
GE Capital Aviation Services |
| Offering |
| Product Performance |
Basic features, performance and functionality |
Intel Pentium 4 |
| Product System |
Extended system that surrounds an offering |
Microsoft Office |
| Service |
How the enterprise services its customers |
FedEx |
| Delivery |
| Channel |
How the enterprise connects its offerings to its customers |
Niketown |
| Brand |
How the enterprise expresses its offering’s benefit to customers |
Virgin |
| Customer Experience |
How the enterprise creates an overall experience for customers |
Lexus |
| *For more detail, see Doblin’s website |
Innovation and Operational Excellence
Of course, even the most on-point innovation will not produce results if it’s the wrong kind. Doblin has done extensive research into patterns for various industries and even countries to measure how they stack up according to each type of innovation. This framework is a key tool that they use to help companies learn to do the right kind of innovation: software companies, for example, compete brutally in Product Performance and Product System because engineers are product junkies. But look at how salesforce.com is trying to change the rules by distributing software differently.
Innovation’s time is coming, according to Keeley, because operational excellence is becoming so widespread that it doesn’t offer a sustainable advantage any longer. Therefore, companies that unlearn what they think is true about innovation (which produces a whopping 4.5% success rate) will emerge as leaders.
Interaction and Change
As I’ve written elsewhere, I firmly believe that our macro-concept of business itself contains many assumptions from the imprint of the industrial economy from which we are just now emerging. Industry entails manipulating and transforming heavy raw materials or parts that constrain most areas of a business and make companies difficult to change. Because the economy was more stable during the industrial economy, innovation was practiced rarely, and few companies ever developed a true competence. Today, they try to practice innovation with a corporate mindset, using industrial processes of elimination to sort ideas. The very concept of a corporation stems from the industrial economy, and its cornerstone was economies of scale. The competence was production, efficiency and power, not new ideas. New ideas were needed, but infrequently, because product life cycles were long.
Larry’s depiction of the “nervous time” reflected what I predicted during the height of e-business: interaction among suppliers and customers drives product (service) life cycles. The more interaction, the shorter the life cycle. Ubiquitous digital networks enable us to communicate information in ever-increasing ways. If a product’s performance, or a vendor’s promise, is lacking, we can let millions of people know about it instantaneously.. as individuals! Companies don’t control information about products the way they did before digital networks.
In addition, consumers’ collective perception of value is constantly changing based on new information. This *requires* innovation in order to not only survive but thrive in the knowledge economy, where information about the underlying product is often more important than the product itself, at least in the product’s perceived value and differentiation. Today’s hot product has a very short lifespan because the supplier market analyzes its success, applies new technology or (using Doblin’s chart) a new business model or service or experience to change the collective perception of value.
In short, innovation has traditionally had the role of placekicker on the corporate team, and now it’s the quarterback.
By Christopher Rollyson Rare Legal and Business Insight into Offshore Countries and Regions describes Baker & McKenzie’s excellent webcasts focused on offshore business.
Depending on your business strategy, it may make sense to explore offshoring to several regions of the world to mitigate the risk that your partner might be affected by natural disasters or political upheaval. In fact, many offshore experts recommend a portfolio strategy for risk mitigation or operational effectiveness (follow the sun operations can reduce time to market) while meeting cost objectives.
Continue reading Rare Legal and Business Insight into Offshore Countries and Regions
By Christopher Rollyson The current revolution in enterprise software is only a preview of a much larger, more pervasive shift that will transform the global economy within the next decade. Service-oriented architecture and Web services are two of the more well-known elements of the maturation of distributed computing, which is changing the rules of the vaunted software development life cycle.
In short, we are on the way to becoming a real-time market for global human capital whose ascendancy will increase with the growth of the knowledge economy and global standards for work processes. If we classify economic value according to knowledge/information, manufacturing and agricultural products and services, the knowledge portion has been steadily increasing its share of the value chain, and this trend is accelerating. Of course, information technology facilitates the creation, distribution and sharing of knowledge.
What does this mean for outsourcing and offshoring? By understanding how standards-based technologies have combined to transform enterprise software, we can learn how the coming standardization of work processes will drive explosive demand for an always-on market for knowledge workers and real-time value chains.
Read a longer version of the article published in the Technology Executives Club Journal. Forthcoming next month, my point of view will explain in more detail how we can apply learnings from e-business adoption and software transformation to pervasive outsourcing. This article is an hors d’oeuvre.
By Christopher Rollyson China: The New Economy summarizes that, by any measure, China is a juggernaut in the early stages of flowering on the global stage: As a consumer market, it has the potential to be the largest in the world as the country is the most populous. As a hub of human capital in a knowledge economy, it will become an epicenter of service-based knowledge workers. As an ambassador of Southeast Asia, it will influence what will arguably be the deepest talent pool in the world. This will cause a reconfiguration of the world’s knowledge network.
Continue reading China: The New Economy
By Christopher Rollyson The adoption of object-oriented, distributed systems grew throughout the 1990s, and the systems are becoming the norm for global enterprises as of this writing. Distributed systems, in conjunction with the rapid growth of the Internet, signify a profound change in how software is built, managed, maintained and consumed, and this development facilitates outsourcing in several ways:
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