2. Segment even further ex. career development course for specific sectors

From www.forentrepreneurs.com

There is no question that success for the entrepreneur starts with a breakthrough (or at the very least great) product or service. Yet too often, entrepreneurs fall into the “field of dreams” mentality (in the words of Terence Mann, AKA James Earl Jones: “build it and they’ll come”). But the truth is that defining the product is just the beginning. Entrepreneurs must spend significant time thinking about the complexity of their sales process and the cost of customer acquisition, as these factors will strongly impact a company’s ability to make money and attract investors.

An obvious requirement for a successful startup is that they are able to make more money from a customer than they spend for a customer, i.e. Lifetime value (LTV) should be greater than cost of customer acquisition (CAC) (see my prior blog post, Startup Killer: the Cost of Customer Acquisition). In this post, we’ll focus on the complexity of the sales cycle for various different types of B2B software and hardware products, and looking at how that impacts the viablity of startup business models by increasing CAC. And I will introduce a “zone system” that entrepreneurs can use to help evaluate different start up sales models.(Note: This post is primarily about B2B technology companies. Some of the concepts may apply to B2C internet, or to other industries, but it was not written with them in mind.)

Understanding Sales Cycle Complexity

Let’s start by looking at the sales cycle spectrum. Some products/services are easy to sell, and buyers will feel comfortable buying them online the first time they visit a web site, while other products and services require complex sales cycles with multiple on-site visits, meeting with various decision-makers, a protracted proof-of-concept trial of the product, etc.

The following diagram attempts to portray the spectrum that exists from the simple to the complex:

(Note: The categories shown are not hard and fast ways to define sales complexity, but are designed to provide a framework for discussion. For simplicity, I have also left out channel sales at this stage.)

Freemium

In this model, some version of the product or service is given away, with the goal of up-selling or cross-selling over time. Think Open Source products like JBoss, MySQL, and Asterisk, and web services such as DropBox and SugarSync. (Note that only some portion of the free customers will likely convert into paying customers.)

No Touch Self-Service

Here you drive traffic to the web site using SEM/Pay per Click ads, SEO, Inbound Marketing, Freemium, etc. Visitors convert to paying customers without any need for salespeople. The product needs to be simple to understand, and have a compelling value proposition.

Light Touch Inside Sales

In this model, you might provide some light level of human touch such as email exchange to answer questions and provide customer support. A slightly higher level of touch might involve a phone call with an inside sales person.

High Touch Inside Sales

Here you still sell your product/service over the phone, but the amount of work in closing the deal requires several phone calls, sales engineers, and/or web-based demos.

Field Sales, and Field Sales with SE’s

Now you require an on-site visit using a field sales organization. You might also need multiple on-site visits, selling to several decision-makers, use of SE’s (sales engineers), and perhaps on-site proof-of-concept installations that take considerable SE time.

Impact of Sales Complexity on Customer Acquisition Costs (CAC)

If you are like me, you would expect the Cost of Customer Acquisition (CAC) to rise as sales complexity increases. So the first time I talked about this topic, I drew the following simple graph:

However, when I looked a little deeper into the costs, a very different picture emerged. The diagram below shows rough estimates of how CAC increases with the complexity of the sales process. (For a look at the spreadsheets that support these estimates, take a look at the embedded spreadsheets in Startup Killer: the Cost of Customer Acquisition.)

Now let’s create a more accurate graph with these estimated numbers:

What we see above is something quite surprising: using the rough numbers that I had estimated for these different categories, CAC appears to increase exponentially as Sales Complexity increases.

To help understand this phenomenon further, I looked at the estimated numbers against a logarithmic scale:

The above diagram illustrates the same phenomenon in different way: using my estimated numbers, the cost of customer acquisition (CAC) jumps by about 10x as you move between these different sales models.

A warning about the data and the graph

Readers should be aware that there can be substantial variation in CAC for different real world companies from my estimates. The key driver of variation is the conversion rates and time taken at various stages in the sales cycle. However, despite that, I believe the diagram is a good indicator of the correlation between Sales Complexity and CAC, indicating a major rise in CAC as additional human touch is added into the process.

Reducing CAC by reducing Sales Complexity

The numbers indicate that it is possible to reduce CAC by very significant amounts if you could change your sales model from:

• Inside Sales –> No Touch
• Direct Field Sales –> Inside Sales

This is obviously much easier said than done. But the impact is so powerful, that it bears serious thought and brainstorming.

What causes Sales Complexity?

To understand if we can reduce sales complexity, we need to understand its causes. Here is a quick list of things that will make a product or service have high sales complexity:

• Complex to understand and/or evaluate, install, configure
• Requires multiple people to get a purchasing decision (frequently caused by a high price)
• Mission critical
• Has high cost if it fails (e.g. data loss, significant financial impact), and the risks of failure are high
• Expensive – high cost to the purchaser, and/or takes a long time to get an ROI
• Affects many other IT systems, people or departments
• Requires significant change to the way people work
• Requires the purchase of other elements, or integration/development work to make a complete solution
• No customer references that have the same usage needs as the buyer
• Pricing complexity, where the buyer can’t easily figure out the right configuration, etc.
• Custom contracts need to be negotiated

The list is probably incomplete, so please add your own thoughts via comments.

There are two other factors relating to your buyer that can make it harder to sell a product:

• Where there is low customer pain
• Where there is no sense of urgency

If you are an entrepreneur looking at your next startup, the following sections will help you understand the impact on your business of a product or service that has the specific sales complexity properties.

Customer Monetization (LTV) must exceed CAC

As stated in the introduction, for a profitable business the money that you make from your customers must exceed the cost that it takes to acquire them. i.e. LTV must be > CAC.  (This topic is covered at length in Startup Killer: the Cost of Customer Acquisition.)

As Sales Complexity and CAC increase, this means that businesses need to find a way to charge their customers more money for their product/service to remain profitable.

To get a customer to pay for a much higher priced product in today’s tough economic environment, I believe there are three driving forces that need to be in place:

• Value: the customer needs to perceive that they are getting good value for the money they are paying
• Pain: the customer needs to be experiencing some significant pain that they need to see resolved
• Urgency: there needs to be a sense of urgency to get the problem resolved

The combination of these three factors could be said to equate to your ability to monetize the customer (Lifetime Value of the Customer, or LTV).

Lets look at what happens when we plot Value/Pain/Urgency with a logarithmic scale against Sales Complexity:

Startups that fall below the line are likely to be in the Unprofitable Zone where their buyers will not be willing to pay them enough money to cover just their sales and marketing costs. See diagram below:

A Zone System for evaluating Startup Sales Models

Using the above chart, it is now possible to group startups into a series of interesting zones based on the complexity of their sales process. Lets start with the Red Zone.

Red Zone 1 (Field Sales)

As you might imagine, the color red signifies danger. Startups in Red Zone 1 usually have high priced sales people selling direct to the customer. Given a typical number of deals that those people can work on at any time, this will drive a high CAC number. (For the spreadsheet showing how sales productivity in terms of deals closed per sales person affects CAC, see Startup Killer: the Cost of Customer Acquisition.)

The only way to cover the high CAC number is to close high priced deals. In a strange twist of fate, charging your customers more money has the unfortunate effect of increasing sales complexity (because it lowers the perceived value for money; involves more people in the decision making process; and potentially introduces budgeting issues).

There is also another fundamental problem: buyers see high risk in purchasing from startups as there is a perceived high risk that those startups may not be around in the long term. This is the so-called “Safe Choice” problem, which adds to the sales complexity, and makes an already tough problem considerably harder.

Other problems that are likely to affect companies using direct sales forces are:

• Lumpy deal flow that makes revenue forecasting difficult and unpredictable
• Deals tend to close at the end of the quarter, which can make life uncomfortable for executives and the salesforce

Despite how difficult it is to be successful with a direct sales force, it is possible to be very successful in this area provided your product/service gets a high score on the Value/Pain/Urgency axis, allowing you to charge enough money to cover the high cost of customer acquisition. If you are an entrepreneur thinking about an idea in this area, I would caution you to remove the rose colored glasses, and ask yourself some very hard questions about your value/pain/urgency score, to make sure you don’t end up in the failure zone, like so many other venture backed companies. Given my own experiences in this area, I have seen only a small percentage of these make it into Blue Zone 1.

Despite the difficulties, good companies can successfully make it to Blue Zone 1. Matrix Partners has done very well investing in this area, and will continue to seek out good ideas in this space. Examples of successes in the Portfolio include:

• Netezza (IPO-ed in 2007) with an average initial deal size of around $1m
• Starent (recently acquired by Cisco for $2.9Bn) that successfully sold wireless data infrastructure equipment to wireless carriers. Very high LTV per customer.
• Aruba (IPO-ed in 2007), sold wireless infrastructure to enterprises. High LTV per customer.
• Airvana (IPO-ed in 2007), sold infrastructure to wireless carriers for 3G data services. Very high LTV per customer.

Using Strategic Partners

There is one very good strategy that companies in Red Zone 1 can follow which will move them into Blue Zone 2, and that is to sign up strategic partners like IBM, HP, Oracle, etc. to resell their products for them. These companies have built successful direct sales organizations and have the credibility with customers to get around the “safe choice” problem. A couple of my porfolio companies that were very successful at doing this were AppIQ (acquired by HP) who leveraged relationships with HP, Sun and HDS; and Diligent (acquired by IBM) who leveraged a relationship with HDS. To play this game right, ideally the partner should sell a platform version of the product, leaving open the opportunity for the startup to go back to those customers and up-sell them additional modules, thereby establishing its own customer relationships. Companies that only sell through one or two OEM channels and have no direct customer control are valued far lower than those with a broad set of customer relationships.

Another option is to try to move to selling through a VAR channel, but this move needs to be done early in the company’s life to get the culture right, otherwise it can be very difficult to change later.

Red Zone 2 (Channel Sales)

Channel Sales is complex category that is not easy to represent on this chart. It could span a range of complexity/CAC values depending on whether the channel management program is human intensive or not.

For simplicity sake, I chose to show channel in a zone between inside sales and field sales. I also chose to place this in the Red Zone, as it can be very hard to get a channel started and working well.  Entrepreneurs and startups tend to underestimate just how hard this can be, and how long it will take. Success requires a deep commitment to channel partner recruitment, training, support, and sales & marketing assistance. It may also require field sales people working alongside the channel if there is no existing demand in the market, as channel partners are not good at creating new markets or evangelizing a major new concept.

In this model, it is often more about your ability to successfully build a network for partners than it is about the uniqueness or marketability of your product.

The Amber Zones

The Amber Zones are a less dangerous place to find yourself as a startup, as your cost of customer acquisition can be low enough, that your primary problem is solving how to provide enough value to your customer in an area where they have adequate pain and urgency.

Amber Zone 1 (Freemium): this zone is for companies that have used a free product to acquire non-paying customers, e.g. Open Source. The challenge for these companies is to figure out how to monetize their customer base without damaging the growth of the free product. A good example of this kind of company is one of my portfolio companies, Digium, which produces Asterisk, the Open Source telephony server (most frequently used as a PBX). Asterisk is downloaded approximately 4,000 times every day. Digium has several strategies for monetizing its market position, including offering support, and a premium version of the product, Switchvox, that turns Asterisk into an easy-to-use, and bulletproof, PBX.

Why Amber and not Red?

There are two reasons why I prefer to use Amber as a color to indicate less danger than Red for these zones:

1. CAC is low enough here, that the challenge of figuring out how to increase value to move to the Green Zone is not as hard as it is for companies with higher CAC numbers.
2. Companies in the Amber Zone are likely to have the ability to leverage the transformational effects of the Internet on sales and marketing. See later section entitled: Make full use of the Web for Sales and Marketing for more details.

The Green Zones

The Green Zones represent a great place to make money. These are areas where I am particularly focused on finding investments.

Green Zone 1 (Freemium) can work well where the free version of the product is highly attractive to customers and drives considerable numbers of people, and when the conversion rate to paying customers is high.

Usually there is some additional selling work to do to convert the non-paying customers into paying customers. (e.g. JBoss used an inside sales organization, and Digium uses both inside sales and a channel to convert its customers to paying). Hence the arrow in the diagram above.

Green Zone 2 (No Touch Self-Service): One of the most powerful B2B business models. These companies in this zone have found a way to create very clear value propositions for their products/services that can be easily understood just by visiting their web sites. Having a touchless conversion from website visitor to buying customer means that all your focus should be on maximizing visitor traffic to your web site, provided you can do that and keep CAC at a reasonable level below your LTV (the lifetime value of your customer).

Green Zone 3: (Inside Sales): An attractive business model provided that you are able to appropriately monetize the value that you are providing to your customers. If your business is in this zone, it makes sense to ask questions about how to further simplify your sales complexity, and even ask if it might be possible to move some set of customers into a touchless conversion. There is the possibility of a very significant reduction in CAC if you are able to do this.

Winning by reducing your Sales Complexity

Product / Service Design plays a crucial role in Sales Complexity

A big question that this whole blog post raises is whether it is possible to take a product/service that has the properties described above in the section called What Causes Sales Complexity, and change them so that can use a less complex sales model. It is my current belief that the primary way to do that is to redesign the product/service to eliminate the issues.

SaaS example

By moving from a an on-premise, enterprise software product to a SaaS model, a company changes the following elements that contribute to Sales Complexity:

• Eliminates the need to involve IT in the decision making process
• Makes it easy for the customer to try the product
• Eliminates the need for any on-site installation, or new equipment purchases
• Greatly reduces the initial size of the $’s that have to be allocated to purchase
• Moves the expenditure from CapEx to OpEx which is usually an easier decision
• Greatly reduces risk for buyers, as if it doesn’t work, they can cancel and stop paying

This has the following effect on the diagram:

Freemium

Freemium offerings can aim to reduce sales complexity by doing the following:

• Making it easy for the customer to try to the product
• Eliminating risk for buyers, as they don’t pay for other services or upgrades until they have seen some results from the free version

The best Freemium offerings are like DropBox. They provide the full functionality of the product for free, but find a measurement that the customer will likely exceed that draws them into paying. By the time the customer reaches this threshold, they are likely very happy with the product and inclined to pay without too much difficulty, and also hooked by its sticky features (i.e. they have a lot of files on the system that are being shared with others that would be hard to move elsewhere.)

Free Trials

In a similar way, free trials reduce sales complexity by:

• Providing a very powerful way for your customers to ensure that your product will solve their problem
• Greatly reduce the risk for the customer when purchasing.

These are both important steps to allowing your customers to sell themselves.

Open Source

Open Source software has a similar transformative effect on Sales Complexity. By making your software free and Open Source, you change the following:

• Make it easy for the customer to try the product
• Eliminate risk for the buyer, as they don’t pay for other services or upgrades until they have seen some results from the Open Source version
• Greatly reducing the $’s that have to be allocated to purchase versus Enterprise software
• Lower customer risk if the vendor fails as you have a community that can support you

Leverage the Transformative Power of the Web for Sales and Marketing

The wide new range of tools available including SEO, SEM, the Social Web, Inbound Marketing, viral techniques, etc. all combine to provide a savvy marketer with great ways to generate low cost web traffic. Then once you have those visitors, other web tools allow the use of rich interactive media, videos, free trials, etc. to answer buyers’ key questions, and handle their objections. Businesses that are expert in this area have a huge cost and business model edge over those stuck using human touch which is expensive and doesn’t scale easily.

Leverage Engineering to solve Sales and Marketing problems

There are a few ways that engineering resources can be used to help with sales cycle complexity. In particular Engineering needs to adopt the cultural mindset of designing and building the product so it is far easier to evaluate during the buying cycle.

Sometimes, doing this well might involve building a separate version of the product just for evaluation. A good example of the latter is CloudSwitch, which produced a free Express version of its product that has a greatly simplified user interface from the Enterprise edition.

Leverage Channel Partners to do more of the Human Touch

To the extent that your company is doing the human touching, it is very expensive from a CAC perspective.  When channels are engaged, CAC to some degree migrates to more of a variable cost model in that there is some ongoing expense associated with training and managing the channel, but once a channel is trained and productive, that burden lessens.   Subsequently,  “others” are spending their dollars on CAC, and the manufacturer pays for success on a variable basis through margin to the partner.

The Internet Divide

One of the more interesting developments in the software industry is the emergence of a new breed of companies that have leveraged the revolutionary effects of the Internet together with either a touchless sale or inside sales model. That combination has created a far lower cost of sale than was previously possible for selling complex software. Pioneers in this area include JBoss, SolarWinds, Acronis, and HubSpot. These companies have developed new techniques and scientific approaches to lead generation, marketing automation, and inside sales, and used those advances to sell software in high volumes at low prices. This is in stark contrast to the old way of selling enterprise software which is very human intensive, and expensive.

The divide between the two approaches is illustrated on the diagram below:

For want of a better name to describe this new approach, I refer to it as the Low Cost Sales Model.

Disrupting the Enterprise Software world

The Low Cost Sales Model has the power to disrupt the industry as companies using the Low Cost Sales Model can disrupt players using the older enterprise sales model. As an example, JBoss used the Low Cost Sales Model to disrupt BEA and IBM that were selling the same solution for dramatically higher prices. BEA and IBM could not respond as they were stuck with a business model that would not be profitable at the lower price point.

Selling to SMBs (Small and Medium sized Businesses)

Sales and marketing costs are now low enough that it is finally possible to profitably sell sophisticated software to the SMB market. Previously it was simply too expensive to try to reach this market for anything but the simplest software. Since most SMB’s don’t have IT staffs, Software as a Service (SaaS) provides the perfect delivery mechanism. HubSpot is a great example of a company using the Low Cost Sales Model to sell software as a service to SMBs very successfully.

Extreme Profitability

Companies like SolarWinds are leveraging the power of the Low Cost Sales model to deliver extraordinary levels of profitability. In 2009, it reported EBITDA profits of $52m on revenues of $116m. That means its operating profit margins were 52%, placing it in rarified territory.

Conclusions

The most fascinating new insight that I discovered while writing this post, was how CAC grew at a roughly exponential rate as sales complexity forced higher levels of human touch into the sales process.

Given this, I recommend that B2B Entrepreneurs gain a clear understanding of the sales complexity of their proposed new business, and carefully contrast this with the associated customer value / pain / urgency levels. This comparison should help them understand if they have what it takes to make a viable business model. (A viable business model requires that you are able to monetize your customers at a higher level than it costs you to acquire them – i.e. LTV>CAC.)

The data also shows that it is extremely important to consider ways to redesign your product/service and resultant go-to-market models to minimize the amount of human touch involved in the sales process. It is not enough to simply want to use a lower touch sales channel. The product/service has to be simple enough to evaluate and purchase for it to work in that channel.

If you have an existing business, my recommendation is that the CEO should be leading brainstorming sessions with his or her VPs of Products, Sales and Marketing to see if it is possible to move from one tier of sales complexity to a lower tier.

Key Takeaways

• Understand the sales complexity of your business. Figure out your LTV and CAC, and make sure that your LTV>CAC so that you have a viable business model.
• Look for ways to decrease your sales complexity, which might involve redesigning your product and leveraging engineering resources to eliminate issues in the sales process.
• Realize that reducing sales complexity is an achievable goal, and should be an ongoing process that merits a significant investment.

Brainstorming suggestions:

• Do you have a clear documented picture of the issues in your buyers’ mind in each step of the sales cycle that have to be resolved before they can make a purchasing decision? (This needs to be in hard copy form for the brainstorming group to be effective. It is rare that I find this step has been properly completed.) For more details, refer to Building a Sales and Marketing Machine.
• What attributes of your product/service are causing it to require a complex sales cycle? Can these be changed?
• What would be required to allow your company to use the next step down in sales model (e.g. to move from Field Sales to Inside Sales, or from Inside Sales to No Touch Self-Service)?
• Are you using all the latest techniques for leveraging the web including Inbound Marketing, lead scoring and lead nurturing, marketing automation, SEO, SEM, social media, web video, etc. Those interested in pursuing the Low Cost Sales Model would do well to study the techniques and behaviors pioneered by the leading companies like SolarWinds, Acronis, HubSpot, ConstantContact, etc.
• Does your Web site answer all the questions and issues that arise in your buyers’ minds during their purchasing process?
• Are you making it easy for the customer to sell themselves, including providing a free trial?
• Is your pricing causing you problems by increasing sales complexity? Could you reduce entry level pricing to the point where only a single individual is required to make a buying decision?
• Can you use a free product to help acquire customers that you can later up-sell or cross-sell?

Important Final Note

It would be wrong to read this article and conclude that any business with high sales complexity is a bad business. There is nothing wrong with having high sales complexity provided you are able to get large enough orders, in a reasonable time period, to cover your cost of sales. That is a very viable business model.

The opposite situation is also worth stating: any business that has low sales complexity but inadequate value provided to a customer is very unlikely to be successful.

Acknowledgements

I would like to thank the following people for their highly valued input to this article: Dharmesh Shah of HubSpot; Danny Windham and Steve Harvey of Digium; Tim Barrows, Antonio Rodriguez and Nick Beim of Matrix.

The last decade has seen considerable progress in the scientific appreciation of how networks are structured. There are two reasons for this; the increase in the availability of data and information about real world networks, and the increased attention paid to the field by the scientific and mathematical research communities.

Analysis was hitherto primarily the domain of sociologists and was hampered by their inability to undertake anything more than small scale, qualitatively based research, where in some cases the research process itself distorted the results.

At first blush, it is difficult to see how a series of number crunching exercises on a university’s mainframe computer can help any of us in the prosaic, street level business of getting our names and talents known in the right places. However some of the insights this research provides are revelatory, and the dispassionate outlines of academic findings resonate directly with real world experience.

The research helps us because a network is an organic, natural phenomenon, built on a string of huge numbers of relatively tiny exchanges, decisions and interactions. Although each decision making process in social networking is itself complex and unique, analysis of the sum of these decisions provides some relevant lessons.

DISPELLING A MYTH? – SIX DEGREES AND SMALL WORLDS

The popular belief that we are all connected by a short series of acquaintances – the Small World Theory – acquired substance in 1967 when the social psychologist Stanley Milgram began a celebrated series of experiments. These entailed asking subjects, who were chosen at random, to get a package to somebody they had never heard of and who lived in a different part of the United States. Participants had to pass the package by hand to somebody they knew, who they thought would be a step closer to the target, and who was asked to continue the chain in the same way.

A number of chains were completed, and those that did contained an average of six steps between sender and target. These results were published in a popular psychology magazine and caught the public imagination. Dinner party conversations would centre on the apparent fact that if you knew, say, fifty people quite well, and they knew fifty others, and so on, by the time you took these links six stages you would have a network greater than the world’s population (50 to the power of 6 is 15.6bn.)

Unfortunately this neat argument is flawed (even if it were not it would be useless in practice). Later research found shortcomings in Milgram’s research methods, and unpublished papers revealed that the ratio of completed to uncompleted chains was so low (5% in one case) that the conclusions were of dubious validity. The jury is still out; the Small World Project at Columbia University is running a much larger, e-mail based version of Milgram’s experiments. Preliminary results released in 2002 showed that of 60,000 chains started across 171 countries, aimed at 19 targets, only 380 were completed; these had an average length of 5 links, increasing to 7 when borders were crossed.

WHY DOESN’T IT WORK?

In a word, homophily – the natural human tendency to associate with people like ourselves. Homophily leads to clustering, which we can describe as the formation of tightly linked, highly interconnected sub networks with limited external links. Clustering is an important aspect of network behaviour to which we shall return; for now a brief summary of another follow up to Milgram’s work will demonstrate its power. In 1976 JM Guiot asked 52 French Canadians living in Montreal to contact a prominent member of that City’s Jewish community, using telephone chains of acquaintances. They achieved an 85% success rate – the point being that once you had penetrated the tightly knit (i.e. clustered) Jewish community you could very quickly get to anybody in it (although limiting it to one city was also a factor). I mentioned that even if the six degree theory were valid, it would not help us, and to explain why we need to visit the world of mathematicians and Erdõs numbers.

Paul Erdõs was a prominent, and brilliant, Hungarian mathematician, an itinerant individual who collaborated prolifically. Mathematicians make ideal subjects, because when they work together they publish papers, making it relatively easy to analyse the structure of their collaborative networks. This type of network is useful to us because it has many of the same qualities as the professional networks we need to develop.

An Erdõs number is a guide to an individual’s proximity to Erdõs, based on published papers. So Erdõs himself has a number of 0, whilst all the people who co-wrote with him have a number of 1 (there are 507 of them!). Those who wrote with his collaborators, but not with him, have a number of 2, and so on.

The game for mathematicians was to find out their own Erdõs number. In his book “Six Degrees”, Duncan Watts describes how his colleague Steve Strogatz needed two days of concentrated effort to find out his (it was 4). The problem is that the range of potential links expands geometrically at each stage. It is difficult enough simply to establish who your own collaborators have also worked with, while the task of exploring the next level is overwhelmingly complex.

CLUSTERS, WEAK TIES AND STRUCTURAL HOLES

The next diagram, which is simplified, highlights two different styles of networking behaviour. Bill and Adam are, respectively, Sales Director and Head of New Product Development for a niche consumer audio products manufacturer. Both are highly effective in their roles. Bill is very gregarious and manages his team in detail, regularly socialising with them (and with key customers). The ties within this cluster are very strong and information passes freely, quickly and effectively. His success as Sales Director is built on his ability to motivate his staff and develop close links with his customers; it owes more to maintaining high levels of energy than to creative or original thinking. Adam on the other hand is more remote, an austere individual who prefers to work alone. His talent for innovation centres on an ability to spot promising technologies and incorporate them into products that attract consumers. The diagram shows his links with external component suppliers, whom he keeps at arms length and interrogates about new developments by exchanges of e-mails and technical papers.

Diagram 4. Bill’s highly clustered Sales Department on the right is in stark contrast to the sparse set of distant links that Adam maintains with the component suppliers whose new technologies enable his own product development.

When the company is acquired by a larger competitor which has no need of Bill or Adam, they both decide that their futures lie in building portfolio careers as  consultants and non-executive directors. Which of them is better positioned to build a new network on which to find these roles?

In 1973, sociologist Mark Granovetter published a ground breaking paper called “The Strength of Weak Ties”. In this and subsequent research he demonstrated that the valuable connections are those that link us, perhaps tenuously, with distant groups or networks. When it comes to moving on, it is not those to whom we are closest that can help, rather those we know less well but who can open the door to new opportunities. For example he demonstrated that white collar workers achieved much greater success in finding new roles through connections with people they barely knew, and that social activist movements in Boston (acting against urban development) were far more effective when they established links across different communities.  His paper triggered a slew of further research, which showed that: Complex networks have “Structural Holes” – that is, areas where interconnectedness between clusters is very low. In our diagram we can see such a hole between the sales team and the new technology / product design area. Members of each group are well aware of the other, but tend to focus on their own activities (e.g. hitting the month’s sales target);

Those who own or control the links across the holes are in a powerful position, as this ownership gives them a competitive advantage. Because they control a flow of information, they are of interest to people across a wider range of groups than those who operate inside a tight cluster. In essence, Adam has a great store of Social Capital which he can transfer to a new role, whereas Bill’s social capital derived from leadership of a group of which he is no longer a part, set in an environment in which he will no longer operate.

Social Capital as a concept is in its infancy, and definitions vary, but it can be thought of as a metaphor for an individual’s competitive advantage arising from their position in a network structure. When he had his job, Bill’s social capital arose from a high degree of Closure; by this we mean that his actions were highly visible to his immediate contacts (colleagues and customers) and hence he built trust and respect. Adam operated in a looser network with a far lower degree of closure (people didn’t know him well enough to develop trust) but the social capital he possesses as a function of his ownership of a range of weak ties linking separate but related networks is of much greater use as he contemplates life outside the corporate cocoon.

The tsunami of research which followed Granovetter’s work provides overwhelming evidence that individuals whose networks span structural holes achieve greater degrees of success. Ronald Burt, whose Network Structure of Social Capital has already been cited, identifies survey after survey reaching this conclusion.

Hence a foundation of our approach to Transition Networking is that we do not rely on contacts to whom we are close, hoping that they in turn will know somebody who knows somebody who will want what we have to offer. Nor do we simply try to make as many new contacts as possible in the hope that one in a hundred will pay off.

We are looking instead for structural holes in networks, areas in which we are clearly qualified to add value. It is highly likely that in order to position ourselves to add value, we will be relying on weak ties – contacts who know us little or even not at all – to make introductions and to convey messages. By definition weak ties offer little in the way of closure, and therefore the messages we send across these links must be Robust and Sticky.

• Identify your key strenghts and weaknesses and apply these to the workplace
• Learn personal branding and marketing techniques
• Develop practical action plans for a successful transition into a new role

Next steps

Your first textbook, Po Bronson’s what should I do with my life will be sent to you within the next 5 days, this book provides 50 vivid profiles of people searching for “their soft spot–their true calling” tackling thorny, nuanced issues about self-determination. Among them: paradoxes of money and meaning, authorship and destiny, brain candy and novelty versus soul food.

Student profile

You should also set up your student profile at http://campus.rusdens.com this will be the central point for your course and will be where you meet other students, discuss the books you have been send and receive your assignments

An overview of Open Education, the long tail and Learning 2.0  [Link]

Skate to where the money will be

The theory of disruptive innovation [Link]

The Future of Universities

How technology will shape learning.  A report from the Economist Intelligence Unit [Link]