I have always believed that there is a natural, organic rate at which a business should grow, and that if we expanded too fast, the wheels would come flying off.  Then I came across a quote from Geoffrey Moore, who is best known for his best-selling book Crossing the Chasm, which is about how businesses cross over from their initial niche markets to dominate larger markets. In another book, called Inside the Tornado, Moore writes about the great battle between Oracle and Ingres in the early 1980s. The winner of that battle is well known: Oracle now has a market cap of more than $100 billion, and I’ll bet you’ve never heard of Ingres.  Moore explains that “for pragmatist customers, the first freedom in a rapidly shifting market is order and security. That can only come from rallying around a clear market leader. Once the apparent leader-to-be emerges, pragmatists will support that company, virtually regardless of how arrogant, unresponsive, or overpriced it is.”

The reasons why breakneck growth may be preferable to steady, conservative growth can be summed up in two bullet points:

1. As noted above. network effects that attach to the market leader
2. Generation of revenue and capital that can be reinvested in the firm to improve systems, products, as well as increase advertising spend and bolster sales efforts

To be sure, these are logical arguments.  However, I think to what extent the logic holds is dependent on a few factors, such as product and/or industry.  Additionally, whether a high-growth strategy will be successful depends in large part on whether their is a plan at the outset that includes provisions for how to effectively manage the growth.

First, network effects do not obtain in every industry or for every product. In some cases, like software, social networking websites, etc, a product’s worth is highly dependent on how many people use it. Issues of compatibility, integration, and utility will push customers to select the service with the highest volume of users. This in turn makes the service more attractive to additional users, etc, etc. When you look at business models like Twitter or Facebook, they’ve absolutely pushed to expand membership (basically, their customer base) at a pace that at times has outpaced their infrastructure and ability to delivery crisp service. However, they’ve built up such a lead in terms of users and customers that the barrier to entry for additional social networking or micro-blogging sites is extremely high. But this isn’t necessarily the case for all other products or industries. Take breakfast cereal. Is there some advantage customers gain by purchasing the highest-selling cereal in the market as opposed to the cereal that meets their taste and nutritional requirements? To be sure, branding can provide customers with a shortcut for their buying decision, but if quality deteriorates their are no shortage of competing products for customers to flock to.

A better example might be strategy consulting. McKinsey is often mentioned as the Cadillac of strategy consulting. To be sure, they are a market leader and employ tens of thousands of consultants. However, what makes them so dominant is not simply that their client base encompass most of the Fortune 500 or that they have thousands of consultants–it’s the quality of their work. McKinsey didn’t become a market leader because they grew rapidly. They became a market leader because the quality of their work was unmatched. McKinsey has relied less on a network-effect than on a halo-effect–the perception that their work is far superior to their competitors and, as a result, other firms feel compelled to leverage their expertise as a result. (If anything, the latter may have caused the former.) In other words, working with McKinsey is a best-practice. As the saying goes, no one ever got fired for hiring McKinsey.

Hypothetical Returns from Growth

Second, given the advantages listed above a business should certainly push the envelope but only to the extent that it can manage its rapid growth. Think of the relationship between growth rate and the return from that growth as a parabolic function. Like the Laffer Curve, the idea is that while increase growth theoretically bestows all sorts of advantages on a firm there comes a point where the growth will actually bring negative returns. As Spolsky notes, rapid growth can strain a firm’s ability to delivery quality to its customers. However, I would argue the difference between the wheels falling off altogether and reaping the full rewards of the growth is whether the business built itself as a platform for growth. What I mean by this is that firms that will be successful pursuing a high-growth strategy will have likely been engineered to deal effectively with that growth.  Here are just a few provisions/topics I think would need to be addressed at the outset:

• developing a strategy for recruiting and retaining top talent during growth phase, as competitors will likely try to siphon off employees in an attempt to catch up (this would include pay, recognition, promotion requirements, etc).
• identifying tasks that will need to be automated sooner rather than later as volume crosses various thresholds
• building systems that are scalable and amenable to rapid expansion and integration with customer and partner systems
• identifying alternative ways of meeting manufacturing requirements, either through acquisition, partnership, or outsourcing

Admittedly this is easier said than done.  However, the choice isn’t all or nothing.  Companies that consciously pursue a breakneck growth strategy out of the gate should do what they can to support that growth with a forward-looking strategy, not one that only focuses on how to grow, but also with what to do once you grow.  As they progress, the strategy will obviously need to be revisited and revised, but I would think trying to think through the implications of growth ahead of time will make a big difference.

1. Piracy as a Signal of Value? [Updated]: Think-piece on whether the pirating of content is a reliable signal of its worth
2. Split-screen Browsing for Firefox: Still an add-on that I could not live without, personally or professionally
3. Evaluating Human Capital Investments Through the Prism of Baseball: Think-piece on how measuring employee performance suffers from the same issues that inspired a revolution in player evaluation in baseball
4. Crowdsourcing Resources: A collection of websites, books, articles, and references related to the practice and business of crowdsourcing
5. Visualizing my Social Network: First-run at analyzing my LinkedIn connections using Many Eyes
6. Lightsabers: Coming to a battlefield near you: Some very cool technology
7. More on a Data-driven World: Links & Commentary: Reference post with lots of links
8. You don’t always know what you want: How to avoid sameness and create conditions for innovation
9. The Role of Polymaths in Innovation: The advantages of of intellectual ADD
10. Organizing for Innovation: A conversation with Ana Andjelic: Part I of a discussion between me and Ana on the optimal way to organize a group/organization for innovation and creativity
11. An Innovator’s Dilemma: Amazon and Apple: My first substantive piece after the site launched in August.
12. Theory vs. Practice: Umair Haque’s 10 Rules for 5G Warfare: My critique of Haque’s application of 5G to current politics
13. Brand Power in a Recession: How resilient is brand power when the economy tanks?
14. Extended rant: Mark Helprin is not a crowdsourcing/social tech fan: Self explanatory
15. The ‘Soft Sciences’ to get their Day: A confluence of events is increasing the demand for individuals with a training in the social sciences
16. Machiavelli on Barriers to Innovation: Great quote
17. We are all creatives now (or, at least, will be by 2013): The growth of creatives and some implications
18. Post hoc ergo propter hoc: A critique of a Charles Blow op/ed
19. The Firm, Transaction Costs, and Organizing for Innovation: Part II of my discussion with Ana
20. Signaling and Communication: The inherent difficulties that lie in getting others to believe what you say

The Network

Part I: The Man Who Wired Silicon Valley (How Rajaratnam built his empire)

Part II: Fund Chief Snared by Taps, Turncoats (How the feds closed in)

Interactive Graphic: Galleon’s Web

If you are looking for a last minute gift, or just something to read over the holidays, you could do much worse.

Happy Holidays!

The first study, “Rethinking Brand Contamination” (link to PDF), examined to what extent consumers can spot counterfeit or knock-off versions of luxury goods.  The data suggested that when knock-off goods were displayed by the owner without additional cues or context, observers were less likely to differentiate between authentic and knock-off luxury goods:

To determine the impact of counterfeits on how consumers value the real brand, Gosline constructed experiments where she showed consumers pictures of products against neutral backgrounds and asked if they could distinguish between the counterfeits and the legitimate items and if they would be willing to buy the products. Under those circumstances, consumers’ confidence in determining the “real” products decreased as did their willingness to purchase them. However, when she showed pictures of people actually using the products, consumers’ confidence in their ability to identify the real versus the fake increased as did their willingness to pay for the real brands.

In an earlier post I hypothesized that the ability to differentiate between a premium and low-cost brand was key to the premium brand’s ability to extract a higher price in the market.  The relationship should be the same for premium brands and knock-off products.  This study would seem to confirm that idea–if consumers can’t tell the difference between the real and knock-off products, why pay the premium for the real product when you can seemingly send the same signal for for less money?

The second study was equally insightful. Gosline looked at the extent to which counterfeit goods depress sales of luxury goods or serve as a kind of ‘gateway’ purchase. What did she find?

Many purchasers of knock-off bags move on to buy real ones within a few years, Gosline found in a separate study of 100 consumers.

“The counterfeit actually served as a placebo for brand attachment,” she said. “People were becoming increasingly attached to the real brand even though they never possessed it at all.”

Forty-six percent of the counterfeit-bag owners bought the authentic products within two and a half years, she said.

One question I have is to what extent the 46% of counterfeit-owners who went on to buy the real products perceived that their fake could easily be differentiated from the authentic product.  One could imagine that if their attempt to signal their status through the counterfeit good was hampered by the ability for others to easily distinguish between the two it could prompt them to purchase the real thing.  However, if they did not feel there was a significant distinction I wonder what compelled them to eventually buy the real thing. I could not find a link to the second study, so if anyone has it please pass it along.

By delaying payment Dubai has not only created serious doubts about its dedication and ability to repay its loans, but also the credit worthiness and risk-level for other sovereigns.  The price to insure against debt-default by Dubai more than doubled (from $300M to $675M).  Additionally, the price of default insurance rose in general for many sovereigns, including Bulgaria, Abu Dhabi, Hungary, the U.K. and the U.S. (see graphic below).

Graphic Credit: The Wall Street Journal

It’s unclear at this point to what extent concerns for default (or an actual default) by Dubai would act as a contagion, setting off another global financial crisis.  On Friday, global markets took a significant hit based largely on investor reaction to the payment delay.  U.S. and Asian markets took the biggest hits, with European markets managing to close higher on the on the day.

At first glance, the sell-off for firms linked to Dubai World was contained on Friday. Additionally, the amount of risk at stake in this case is minuscule compared to the financial crises of a year ago. The Financial Times notes:

Credit Suisse, for example, assumes that European banks account for half of Dubai’s debt, estimated at about $80bn. If they lost 50 per cent on their exposure, bad loan provisions would rise by 5 per cent next year, equivalent to a €5bn after-tax hit. Compared with the $1,700bn of toxic assets European and US banks have wiped out in the credit crisis, that is a drop in the Burj Al Arab swimming pool.

It would appear at first blush that, financial speaking, there isn’t a great threat of a Dubai default leading to a global financial meltdown (however, I have not seen data on the holders of credit default swaps [cds] and to what extent they’ve assumed too much risk, as AIG did last year). However, I do wonder about the other major variable in financial crises–the psychological risk. Financial crises are the result of both economic and psychological variables interacting in dangerous ways (namely, a positive feedback loop where negative economic conditions feed into negative views on the market which leads to actions that increase negative economics conditions which feed into negative views on the market, etc, etc). As Mark Gongloff notes:

Every episode of sovereign worry raises market fears of contagion, “reminders that pockets of post-credit-excesses are intact and destabilizing,” Gluskin Sheff chief economist David Rosenberg told clients on Friday.

To me, that is the real risk. With states’ balance sheets in total disarray around the globe, investors will not long for worrisome indicators and troublesome cases to analyze (think of the conditions that facilitate brush fires).

We’ll see to what extent this scenario plays out in the coming days. Would love to hear feedback from sovereign debt specialists and global finance experts.

When Robert Menschel, a senior director at Goldman Sachs Group Inc., was considering deals involving large consumer companies such as Procter & Gamble, he would pick the brain of fellow club member Ed Meyer, the former chief executive of Grey Advertising.

“We were all young kids starting out, and it is easy when you are so involved in building your career to lose touch with other people who are outside your field,” says Mr. Menschel, who has been at Goldman Sachs for 55 years. “It helped me to understand why other people do what they do—which is important in life and in business. You don’t learn anything from talking to sameness.”

The Wednesday 10 comprised, at various points, more than 20 men; the goal was a number small enough to maintain intimacy yet large enough to ensure that at least 10 members would show up for each of the monthly Wednesday-night meetings. No more than two representatives of any one industry were permitted. The idea was to combat insularity, to keep the men connected to people and events outside their own professions.

The engineering of the group is particularly interesting: keep the group small enough so members could develop some sense of intimacy, but large enough to ensure decent and consistent attendance; and ensure that no single industry was overrepresented.  By ensuring diverse membership the group could benefit from an exposure to ideas and viewpoints from outside their day-to-day professional circles.  Additionally, the members would invite guest speakers for each session, further benefiting from a diverse membership that could tap into various experts from all sorts of fields.

There are, of course, questions to what extent the group succeeded in maximizing diversity and guarding against sameness.  However, the fact that these individuals in late 1950 were cognizant of these issues and tried to guard against them by organizing the group in a specific way is quite impressive and instructional for folks living in the age of social media.

To get my feet wet I decided to create a visualization of my network using data from LinkedIn.  I currently have ~350 connections and decided to visualize the frequency with which particular companies and organizations were observed among those connections.  So here is what the first cut looks like:

Clicking on the visualization will allow you to interact with it, selecting companies to see what percentage of the data they account for.

Looking at the data a few patterns quickly emerge:

• My current employer (Gerson Lehrman Group) accounts for the highest share of contacts (20%)
• My current and previous employer (Kroll) together account for 33% of my contacts. This is not surprising, as it seems intuitive that a) you tend to connect with people that you have either met in person or have conducted some kind of business with (even if only by phone), and your most frequent touch points during the course of a day will be with people you work with.
• My network is very much long tail. Over 54% of the companies in my network have less than 3 people I know working for them; over 40% include only 1 connection (see graph below).  Again, I would suspect this is similar for most networks.

• The other thing to note is that this is only a sample of my actual contacts.  This only represents those people I have connected with on LinkedIn–it doesn’t include Facebook, Twitter, or for that matter anyone I know professional/personally who is not on a social networking site.  Now, there is some overlap with Facebook (and a much smaller amount with Twitter), but I would say I am only connected to ~50% of my Facebook friends on LinkedIn.

What I don’t have–and what I’d like to see–is an industry breakdown (LinkedIn doesn’t provide that data on their exports).  Now, you can see the top 4 of 5 through your account on LinkedIn, but I’d rather have the full data to play with.  I would also like to see the date I added someone as a contact.  I think some interesting patterns would emerge in terms of firm, industry, and date of connection.  Additionally, I would be interested in how tightly connected my network is–meaning, how many of my connections are directly connected.  I would imagine the two employers would naturally be tightly bundled, but it would be interesting to see how many other connections share a link.  Again, this is data that LinkedIn doesn’t export.