Technology

Revisiting What I Know About Efficient Scale, Cost Advantages, & Early Stage Technology Startups

January 9, 2016 by Brian Laung Aoaeh

This is the fourth post in my series of blog posts on economic moats. I have already written about Network Effects, Switching Costs, and Intangibles. In this post I will discuss how Cost Advantages and Efficient Scale might develop as an early stage startup travels through the discovery phase of its life-cycle. ((Any errors in appropriately citing my sources are entirely mine. Let me know what you object to, and how I might fix the problem. Any data in this post is only as reliable as the sources from which I obtained it.))

My goal for writing this post is to provide one example of how I might think about this topic when I am studying an early stage startup that is raising a round of financing from institutional venture capitalists.

To ensure we are on the same page, I’ll start with some definitions. In the rest of this discussion I am primarily focused on early stage technology startups. If you by-chance have read the preceding posts in this series, you would have seen some of these definitions already.

Definition #1: What is a startup? A startup is a temporary organization built to search for the solution to a problem, and in the process to find a repeatable, scalable and profitable business model that is designed for incredibly fast growth. The defining characteristic of a startup is that of experimentation – in order to have a chance of survival every startup has to be good at performing the experiments that are necessary for the discovery of a successful business model. ((I am paraphrasing Steve Blank and Bob Dorf, and the definition they provide in their book The Startup Owner’s Manual: The Step-by-Step Guide for Building a Great Company. I have modified their definition with an element from a discussion in which Paul Graham, founder of Y Combinator discusses the startups that Y Combinator supports.))

A company is what a startup becomes once it has successfully navigated the discovery phase of its lifecycle. As an early stage investor one of my responsibilities is to assist the startups in which I am an investor to successfully make the journey from being a startup to becoming a company.

Definition #2: What is an economic moat? An economic moat is a structural barrier that protects a company from competition.

That definition of a moat is the one provided by Heather Brilliant, Elizabeth Collins, and their co-authors in Why Moats Matter: The Morningstar Approach To Stock Investing.

I take things a step further in thinking about startups and companies with business models that rely on technology and innovation. I think of a good moat as performing at least two functions; first, it provides a structural barrier that protects a company from competition. Second, it is an inbuilt feature of a company’s business model that enhances and strengthens its competitive position over time.

As a result I have arrived at the following definition of an economic moat pertaining specifically to early stage technology startups;

An economic moat is a structural feature of a startup’s business model that protects it from competition in the present but enhances its competitive position in the future.

Definition #3: What is a cost advantage? According to the authors of Why Moats Matter, a cost advantage arises when a company can sustainably lower its costs of doing business relative to its competitors. Such a reduction in costs can be due to process advantages, superior location, economies of scale, or access to a unique asset. In other words;

A cost advantage is a structural feature of a startup’s business model that enables it to maintain sustainably lower overall costs of doing business than its competitors while earning equal or higher margins over time.

Definition #4: What is efficient scale? According to the authors of Why Moats Matter, “efficient scale describes a dynamic in which a market of limited size is effectively served by one company or a small handful of companies. The incumbents generate economic profits, but a potential competitor is discouraged from entering because doing so would cause returns in the market to fall well below the cost of capital.” In other words, from my perspective as an early stage investor;

A startup can scale efficiently if doing so does not drive its customer or user acquisition costs to unsustainable levels over time, and if the startup’s decision to enter that market does not drive returns in the market to levels that are below the cost of capital for incumbent companies in that market over the short term.

Sources of Cost Advantage

For early stage technology startups, these are the most important sources from which a cost advantage may be derived. ((I do not include Materials and Supplies under this discussion because I do not think that is a sustainable source of cost advantage for an early stage technology startup.))

People & Culture: This cost advantage arises when a startup develops a unique organizational culture, management processes, and organizational structures that enable and empower members of the team to consistently generate results for the startup’s business that are significantly better than the results of its direct competitors and that beat the adjusted-performance of more well-established incumbents in that market. This source of cost advantage is intimately connected to the intangibles of Management and Culture, and Research and Development.

Systems & Processes: This cost advantage arises when a startup develops unique organizational processes that enable it to consistently generate comparatively superior results. The key categories of such systems and processes are Marketing and Sales Processes, Operational Processes, Distribution Processes, and Support Processes.

Marketing and Sales Processes focus on the activities that the startup takes in order to create demand for its product or service, and subsequently to satisfy that demand by delivering the product to its users or customers.

Operational Processes focus on the activities in a startup that take inputs and turn them into the final product or service through which the startup’s value proposition is delivered to the market. These are the processes that enable the startup to turn tangible and intangible inputs and turn them into something the market is willing to pay for. I have previously discussed this in: Why Tech Startups Can Gain Competitive Advantage from Operations.

Distribution Processes focus on the channels through which the startup’s product or service will be delivered to its users or customers. A key consideration that has to be made here is the choice between direct distribution and indirect distribution channels, and how the startup’s choice in this respect will affect its ability to maintain an overall cost advantage over its competitors.

Support processes focus on all the activities that make everything else that the startup does possible; for example HR and Talent Management, and Financial Planning and Analysis fall under this category.

This source of cost advantage is intimately tied to People & Culture, since the two combine to create an environment in which unique tangible and intangible assets are developed consistently over time such that the startup’s competitive advantage over its peers increases, and evidence that this is happening is seen in the startup’s historical key performance indicators.

Facilities: This cost advantage is derived from the physical infrastructure that a startup needs in order to operate. For early stage tech startup the hard decisions related to this source of cost advantage begin to be necessary when the startup has scaled to a point at which off-the-shelf hardware products are no longer good enough for what the startup seeks to accomplish. This is often the point at startups must consider the advantages or disadvantages they may derive from building custom hardware instead of relying on what’s available from outside vendors or partners. It can also be tied to a geographic location which gives the startup unfair access to an input that is critical for what it does.

Capital: This cost advantage is determined by the startup management team’s ability to allocate capital in such a way that the startup successfully navigates the path it must travel between being a startup and becoming a company. Cost advantages due to capital are determined by external sources of capital – potential outside investors and sources of trade credit, and internal sources of capital – existing capital raised from investors, financial management of money the startup expects from its users or customers and money it owes to the vendors and business partners with whom it has a working relationship.

Key Considerations for Efficient Scale

Here I am assuming that the investor has determined that the startup’s customer or user acquisitions costs will most likely decline over time, or in the worst case scenario they will stay relatively flat.

How I think about efficient scale for an early stage startup is closely linked to the concept of product-market fit. An early stage startup is approaching the product-market fit milestone when demand for its product at a price that is profitable for the startup’s business model, begins to outstrip the demand that could have been explained by its marketing, sales, advertising, and PR efforts.

When I am chatting with startup founders and I am trying to explain this concept I use the analogy of a cyclist on a steep hill to represent the founder’s startup. It’s probably a poor analogy, but I think it gets the point across in a way that is easy for them to internalize.

Before Product-Market Fit (BPMF) everything takes a lot of effort. Every sale is tough, everything that can go wrong will go wrong, and most of the sales deals will fall apart for reasons that are hard to explain. The cyclist is pedaling very hard to get uphill, and even maintaining balance on the bike is quite a challenge. Every breath brings with it the possibility that the cyclist could fall off the bike. With luck, the cyclist makes it to the top of the hill. Then, there is that moment when the cyclist senses that it is possible to keep going without as much exertion as it required to get to the top of the hill. Now the downhill journey begins. Gravity kicks in. The bike is gaining momentum even as the cyclist is frantically trying not to careen off the path. The cyclist’s exertions are now focused on skillfully applying the brakes at sharp turns and corners on the way downhill, and speeding up when then the path is straight and clear of obstacles. If this is a race and there are other cyclists ahead, then our cyclist must also focus on overtaking then one after another, and must also avoid getting caught in crashes caused by other cyclists in the race. After Product-Market Fit (APMF) demand for the startup’s product threatens to outstrip the startup’s ability to meet that demand. This is when a startup must scale, and scale fast and efficiently. There are two reasons to scale at this point. The first and most important reason is that there is demand for the startup’s product and the startup should meet the demand from its users or customers. The second reason is that APMF is also the point at which copy-cat competition starts to materialize from new entrants, and possibly from incumbents too.

Efficient scale means different things at different points in the startup’s lifecycle: The way a team of 2 co-founders scales the startup’s business is much different than the way that same startup will scale its business when the team has grown to 20 people. In other words the way to pursue scale BPMF differs markedly from the way to pursue scale APMF.

Premature scaling seems great initially, until it leads to startup failure and death: The Startup Genome Report Extra on Premature Scaling reports that startups that scale prematurely tend to start scaling earlier than startups that do not scale prematurely, they often also raise 3x as much capital and have valuations 2x as high as startups that do not scale prematurely. This trend continues till they fail. Also, 74% of startups scale prematurely. I will not go into the details of that report in this post, because I covered that in Notes on Strategy; Where Does Disruption Come From?

The cadence of hiring is important: BPMF hiring should be slow, deliberate and methodical since it is not yet clear what new team members will be working on and if what they will be working on is relevant for the startup’s overall success and longevity. APMF the challenge is to hire the right people for the startup as quickly as is necessary to keep up with demand, and cope with competition. For this reason building sound and cost-advantageous systems & processes, and modifying them as the startup grows is important. Startups that scale prematurely, and then fail tend to hire more people sooner in their lifecycle than startups that do not scale prematurely.

Technology-enabled scaling wins: Whether a startup focused on consumers or enterprises, it is important for the founders to think about ways in which technology can be used to enable and support the scaling process. This should go beyond the obvious area of gaining new users or customers. Rather, as the startup scales thought should be given to how it ensures that:

Teams do not become too large to get critical work done quickly, and that they have the tools to promote communication and collaboration once the startups physical layout is taken into account.
Customer or user acquisition is not slowed unnecessarily by a failure to account for what customers are willing to do in order to get the product.
Sales and revenue generation is not hobbled by a failure to use tools that will make salespeople as effective as they can be, given other existing constraints.
Operations can seamlessly transition from one order of magnitude of scale to another without a deterioration in customer or user satisfaction.

Culture makes a difference: All things being equal, startups with a strong culture will scale more successfully than startups that do not. Why? Culture ensures that as the startup grows by hiring new people, the entire organization continues to solve the problem the startup set out to solve in a consistent manner.

Eventually, most founders must also become managers and coaches: It gets to a point where the founders job evolves into one of mainly facilitating and enabling the work of other people, setting strategy, nurturing a vision, and managing a team of executives. This is how founders gain managerial leverage. Not every founder is cut out for this. Some want to remain as close to building the product as possible because that is where their passion and drive comes from. I prefer founders who are self-aware enough to know if they want to remain close to building the product, or if they want to make the transition from building things to managing people, and setting strategy. Usually, this is not an issue at the Seed or Series A stage, where I am most involved. Still, I like to get a sense of what might happen. I’d rather not invest if this could become an intractable problem before the startup has reached escape velocity.

This wraps up my main posts about economic moats.

As a sector, technology is notorious for being one in which economic moats are hard to maintain. However, every tech startup that was able to build a wide moat around its business earned fantastical returns for its earliest investors. Many have also had a lasting impact on how people live life, and how the businesses that use their products get work done. You would recognize so-called “wide-moat” or “narrow-moat” tech companies if I mentioned names. You might also recognize the “no-moat” tech startups that initially seemed destined for great heights, but then were dragged back down to earth by a combination of market forces.

In either case, I will be thinking about economic moats almost daily.

Further Reading

Notes on Strategy; Where Does Disruption Come From?

July 19, 2015 by Brian Laung Aoaeh

Marc Andreessen’s brilliant explanation of @claychristensen‘s disruptive innovation theory in 15 tweets: pic.twitter.com/3ic1teQbRW

— Vala Afshar (@ValaAfshar) June 24, 2015

Introduction

You can imagine my surprise when I was browsing my Twitter feed one night last month and came across one of Marc Andreessen’s tweetstorms. This time he was tweeting about Clayton Christensen’s Theory of Disruptive Innovation.

Coincidentally, I have been thinking about writing a blog post on the subject since the Fall of 2014 – after a string of successive meetings with startup founders in which it became starkly clear to me that they were using the term “disruption” without actually understanding what it meant, or perhaps I should say, they used the term in a context that differs markedly from my understanding of what it means.

The purpose of this blog post is to; ((Any errors in appropriately citing my sources are entirely mine. Let me know what you object to, and how I might fix the problem. Any data in this post is only as reliable as the sources from which I obtained them.))

Synthesize my understanding of Disruptive Innovation as popularized by Clayton Christensen’s work,
To examine instances in which that process has unfolded in various industries,
To develop a framework by which I can analyze a startup founders’ claims about “being disruptive” during my conversations with them, and
Examine extensions of, and arguments against, Clayton Christensen’s work on Disruptive Innovation

I am thinking of this from the perspective of an early stage Seed and Series A investor in technology startups, not from the perspective of a management consultant advising market incumbents about how to avoid or prevent competition.

To insure that we are on the same page; first some definitions.

Definition #1: What is a startup? A startup is a temporary organization built to search for the solution to a problem, and in the process to find a repeatable, scalable and profitable business model that is designed for incredibly fast growth. The defining characteristic of a startup is that of experimentation – in order to have a chance of survival every startup has to be good at performing the experiments that are necessary for the discovery of a successful business model. ((I am paraphrasing Steve Blank and Bob Dorf, and the definition they provide in their book The Startup Owner’s Manual: The Step-by-Step Guide for Building a Great Company. I have modified their definition with an element from a discussion in which Paul Graham, founder of Y Combinator, discusses the startups that Y Combinator supports.))

Definition #2: What is Sustaining Innovation? A “sustaining innovation” is an innovation that leads to product improvements without fundamentally changing the nature or underlying structure of the market to which it applies; it enables the same set of market competitors to serve the same customer base. ((Clayton M. Christensen, The Innovator’s Dilemma. 2006 Collins Business Essentials Edition.))

In other words; a sustaining innovation solves a problem that is well understood within an existing market. The innovation improves performance, lowers costs and leads to incremental product improvements. The customers are easily identified, and market reaction to the innovation is predictable. Lastly, traditional business methods known within that market are sufficient to bring the innovation to market. ((Brant Cooper and Patrick Vlaskovits, The Lean Entrepreneur. Wiley, 2013, pp. xx.))

Additionally;

A sustaining innovation is evolutionary if it leads to product improvements that are gradual in nature, progressing along what might be described as a gradual step function.
A sustaining innovation is revolutionary, discontinuous, or radical when it leads to product improvements that are dramatic and unexpected in nature, but that nonetheless leaves the market structure largely intact – even if there is a rearrangement of counterparties within the existing competitive hierarchy.
Even the most dramatic and difficult sustaining innovations rarely lead to the failure of leading incumbents within a market. ((Clayton M. Christensen, The Innovator’s Dilemma. 2006 Collins Business Essentials Edition, pp. xviii.))

Definition #3: What is Disruptive Innovation? A “disruptive innovation” is one that starts out being worse in product performance in comparison to the alternative, in the immediate term. However, as time progresses the disruptive innovation leads to a significant and fundamental shift in market structure – new entrant competitors serve an entirely changed customer base. ((Ibid.))

In other words; a disruptive innovation solves a problem that is not well understood by the market, thus creating a “new market” for the new entrant. The innovation is dramatic and game-changing in ways that initially elude the mainstream customers as well as market incumbents serving those customers. The customer is often difficult to identify at the outset, and market reaction toward the innovation is unpredictable – from the perspective of the mainstream. Traditional methods and business models that have served the market can not support the innovation. ((Brant Cooper and Patrick Vlaskovits, The Lean Entrepreneur. Wiley, 2013, pp. xx.))

Additionally;

A disruptive innovation introduces a different and “comparatively inferior” value proposition than the value proposition the existing market is accustomed to; as such
Disruptive innovations start out being attractive only to a relatively “fringe” and “new” but altogether “unprofitable” customer base with products that are;
“Cheaper, simpler, smaller, and more convenient” for the customers that find them most attractive at the outset, and
These products perform so “poorly” that mainstream customers in that market will not use them, and incumbent players are happy to keep “their best, and most profitable customers” while ceding “their worst, and unprofitable customers” to the startup bringing the disruptive innovation to market, but
Eventually the disruptive innovation leads to market shifts which cause leading incumbents to fail as the new entrants supplant them.

Understanding What is Happening When a Market Undergoes Disruption

So what exactly is going on when a market experiences disruption? Contrary to what the term “disruptive innovation” suggests . . . the process is not sudden.

As Clayton Christensen states; Disruptive innovations are generally straightforward technologically. They consist of off-the-shelf components combined in a product architecture that is far simpler than existing alternatives or substitutes in a way that does not meet the needs of the core customers in an established market. They will often be derided and dismissed by incumbents as “inferior” because they offer benefits prized by an emerging class of customers in an emerging, but as yet unnoticed market. The disruptive innovation starts out being unimportant to the mainstream customer and so it is unimportant to the mainstream incumbent. ((Clayton M. Christensen, The Innovator’s Dilemma. 2006 Collins Business Essentials Edition, pp. 16.))

Mainstream customers and mainstream investors hold mainstream incumbents captive – with demands for sustaining innovations, and demands for meeting or beating financial performance metrics like internal rate of return, net present value, return on equity, return on invested capital, gross margins, net margins etc. Faced with the choice between pursuing an unprofitable emerging class of customers or doubling down in the competition for the most profitable mainstream customers in that market, management teams running mainstream incumbents do the rational thing; they double down in heated competition for profitable customers.

The disruptive innovation improves so rapidly, that it soon starts to meet the needs of segments of the mainstream customer base. As the cycle continues, it reaches a stage where the incumbents find themselves squeezed into a tiny corner of the market, driven out of it altogether, or dead.

This process describes a “low-end disruption.”

Disruptive innovation might take another form; in a “new market disruption” the startup initially sets its sights on customer segments that are not being served by mainstream incumbents within a given market. A new market disruption starts by competing “outside” of an existing market; in new use-cases, or by bringing in customers who previously did not consume because of they lacked the know-how or financial resources needed to use the incumbent product. The new market is “small and ill-defined” . . . However, as the new entrant grows and improves its product, customers begin to abandon the incumbent in favor of the disruptive innovation. Usually, the incumbent cannot compete with the new entrant because the new-market disruption is accompanied by a structurally distinct business model which makes it feasible for the new entrant but infeasible for the incumbent, for example a cost structure that is so thin that it could not support the incumbent’s fixed costs. ((Clayton M. Christensen and Michael E. Raynor, The Innovator’s Solution. 2003, Harvard Business School Publishing, pp. 45.))

What Is The Innovator’s Solution; For Early Stage Startups and Early Stage Venture Capitalists?

Of the many dimensions of business building, the challenge of creating products that large numbers of customers will buy at profitable prices screams out for accurately predictive theory.

– Clayton M. Christensen and Michael E. Raynor, The Innovator’s Solution

First: Understand Why Customers Buy What causes customers to buy a product? A startup wishing to disrupt an established market needs to be able to answer this question in a way that existing incumbents have not. The “Jobs-To-Be-Done” (JTBD) framework enables a startup to develop its product at the “circumstance” in which its customers find themselves at the time they need its product, and not directly at the circumstances. As Christensen and Raynor put it: “The critical unit of analysis is the circumstance and not the customer.”

The basic idea behind the jobs-to-be-done framework is that customers “hire” a product when they need to get a specific “job” done. The entrepreneur who understands what job the startup’s product is being hired to do can also develop an understanding of the other jobs that might be related and ancillary to the primary job. The regularity and frequency with which customers need to get that job done plays a role in product development; what features should be prioritized? Which features should be de-prioritized even though they at first seemed important? How should the product’s value proposition be communicated? What other features should be built so that customers need not combine several different products in order to complete the job, or if they do how does the startup capture those markets too? ((Clayton M. Christensen and Michael E. Raynor, The Innovator’s Solution. 2003, Harvard Business School Publishing, chapter 3.))

In my opinion startups stand an even better chance of success if they can combine the JTBD framework with an understanding what broad needs their product satisfies for their customers using the parameters laid out by Maslow’s Hierarchy of Needs. This matters especially in the determination of how a startup should communicate the product’s value proposition to its target customer base. An incongruence between the startups marketing message and the customers’ psychological notions about the product will lead to missed opportunities for the startup. It might also lead a startup to chase after the wrong customer base at the outset. ((Startups building products for the enterprise customer should be able to develop an analogous framework, assuming one does not already exist.))

When new ventures are expected to generate profit relatively quickly, management is forced to test as quickly as possible the assumption that customers will be happy to pay a profitable price for the product.

– Clayton M. Christensen and Michael E. Raynor, The Innovator’s Solution

Second: Be Patient For Growth But Impatient For Profits The investors and founders of a startup that claims to be disrupting a market must quickly test if the market dynamics the startup must confront are such that it can earn a profit given its business model. This is important because it indicates that for those startups that answer those questions positively, it is possible for them to pursue growth in a way that is healthy and sustainable irrespective of the magnitude of the growth.

The Startup Genome Report reached conclusions that support this notion. In an extra to the 2011 version of that report they study the effect of premature scaling on the longevity of startups. They found that 70% of the 3200+ high-growth technology startups scaled prematurely along some business model dimension.

Before delving deeper into the findings from the Startup Genome Report, we should understand “Product-Market Fit“. An early stage startup is approaching the product-market fit milestone when demand for its product at a price that is profitable for the startup’s business model, begins to outstrip the demand that could have been explained by its marketing, sales, advertising, and PR efforts.

Product/market fit means being in a good market with a product that can satisfy that market.

You can always feel when product/market fit isn’t happening.The customers aren’t quite getting value out of the product, word of mouth isn’t spreading, usage isn’t growing that fast, press reviews are kind of “blah”, the sales cycle takes too long, and lots of deals never close.

And you can always feel product/market fit when it’s happening. The customers are buying the product just as fast as you can make it — or usage is growing just as fast as you can add more servers. Money from customers is piling up in your company checking account. You’re hiring sales and customer support staff as fast as you can. Reporters are calling because they’ve heard about your hot new thing and they want to talk to you about it. You start getting entrepreneur of the year awards from Harvard Business School. Investment bankers are staking out your house. You could eat free for a year at Buck’s.

– Marc Andreesen ((Marc Anrdeesen, Product/Market Fit, Jun 25, 2007. Accessed on Jul 18, 2015 at http://web.stanford.edu/class/ee204/ProductMarketFit.html))

In other words, the product-market fit milestone is that milestone at which we start to realize that the startup has an opportunity to grow in sustainable and profitable way. As organic demand for the product starts to overwhelm the startup – i.e. as the market starts to pull the product out of the startup, that is the point at which it makes sense for investors to become impatient for growth. Before Product-Market Fit (BPMF) a startup must “push” its product onto the market – customers and revenue grow in direct, linear proportion to sales and marketing expense. After Product-Market Fit (APMF) the market “pulls” the product out of the startup – customers and revenue grow positively, disproportionately, and exponentially out of proportion to any sales and marketing expense incurred by the startup. Investors and startup founders should become impatient for growth when the startup is in the APMF phase of its life-cycle. This approach should hopefully avoid situations like: Case Study: Fab – How Did That Happen?

According to Startup Genome Report Extra on Premature Scaling:

Note: They use the term “inconsistent startups” to describe startups that scale prematurely and “consistent startups” to describe startups that scale successfully.

74% of startups scale prematurely.
Startups that scale appropriately grow about 20x faster than startups that do not.
Inconsistent startups that raise funding from investors tend to be valued 2x as much as consistent startups and raise about 3x as much capital prior to failing.
Inconsistent startups have teams that are 3x the size of the teams at consistent startups at the same stage.
However, once they get to the scaling stage, consistent startups have teams that are 1.38x the size teams at inconsistent startups.
Consistent startups take 1.76x as much time to reach the scale-stage team size than their inconsistent peers.
Inconsistent startups are 2.3x more likely to spend more than one standard deviation more than the average cost to acquire a customer than their consistent peers.
Inconsistent startups write 3.4x more lines of code and 2.25x more lines of code in the discovery and efficiency stages of their life-cycle. Discovery and efficiency are the first and third stages of the startup lifecycle, as described in the report. ((In their report they describe the stages of a startup’s life-cycle as Discovery, Validation, Efficiency, Scale, Sustenance, and Conversation. The report covers the first four.))
A majority of inconsistent startups are more likely to be efficiently executing irrelevant things at the Discovery, Validation, and Efficiency stages of their life cycle, while a majority of consistent startups seek product-market fit during those stages.
The following attributes have no correlation to the likelihood that a startup will be inconsistent or consistent: market size, product release cycles, educational attainment, gender, age, length of time over which co-founders have known one another, location, tools used to track KPIs etc.

What are some of the mistakes that inconsistent startups make as they travel from launch to dysfunctional scaling to failure? The Startup Genome Report provides some examples:

Customer

Spend too much on customer acquisition BPMF and before discovering a profitable, repeatable and scalable business model, and
Attempt to ameliorate that problem with marketing, press, and public appearances.

Product

Build a “perfect product” before knowing enough about the “Problem-Solution Fit”, and
Investing into scaling the product BPMF, and
Focusing on advanced product features which are later proven to be unimportant to customers.

Team

Growing the team too fast,
Hiring specialists and managers too early and not having enough people who can or will actually do the work that needs to get done, and
Having too much hierarchy too early.

Finance

Raising too little money at the outset,
Raising too much money. ((This is a risk for early stage investors as well as startups.))

Business Model

Not spending enough time developing the business model, and only realizing after the fact that revenues will never support the startup’s cost structure.
Focussing too much on maximizing profit too early in the startup’s life-cycle,
Executing without observing and analysing the input from customers and the market, and
Failing to pivot appropriately in the face of changing market conditions that are relevant to the startups based on its discovery-focused experiments.

The 4 Stages Of Disruption

In his article, Four Stages of Disruption, Steven Sinofsky describes the process of disruption using an analogy to the well known and well understood rubric for understanding the experience of someone experiencing significant loss.

The 4 stages of disruption are:

Disruption: A new product appears on the market but is seen to be inferior to the existing mainstream alternative.
Evolution: The new product undergoes rapid sustaining innovations.
Convergence: The new product is now seen as a plausible replacement for the incumbent mainstream product because it has undergone enough sustaining innovations to make it comparable to the incumbent.
Reimagination: During this stage there is a complete re-examination of the assumptions on which the market operates and new products are brought to market.

Sinofsky describes them as a process, as shown in the following diagram:

The 4 Stages of Disruption (Credit: Steven Sinofsky) — The 4 Stages of Disruption – Process (Credit: Adapted from Steven Sinofsky)

I think the framework is better understood as a cycle; because every incumbent must face a new entrant or new entrants seeking to disrupt the market and eventually every successful new entrant that disrupts a market itself becomes an incumbent facing disruption by a successive hoard of disruptive new entrants. The cycle is ongoing and continuous, and is driven by more than simple advances in technology. Human behavior plays a central role in shaping the cycle that creates room for disruption to occur because our tastes change over time, and as time progresses we begin to value things that we did not value in the past, and it is that insight into the confluence between technology and human behavior that enables certain entrepreneurs to build startups that become industry disruptors.

4 Stages of Disruption - Cycle — The 4 Stages of Disruption – Cycle (Credit: Adapted from Steven Sinofsky)

How Did That Happen? – Disruption in Action; Industries

Digital Cameras vs. Film Photography: Digital cameras threatened to disrupt film photography, but they mainly represented a sustaining innovation – largely improving on existing form factors already in use in that market and fulfilling the needs of people one would consider casual or professional photographers. It was not until digital camera technology was integrated into smart-phones that the photography market started to experience disruption. They appealed to anyone who had the desire to take a picture, photographer or not, it did not matter. As Craig Mod argues in his 2013 New Yorker article Goodbye, Cameras: “In the same way that the transition from film to digital is now taken for granted, the shift from cameras to networked devices with lenses should be obvious.” Standalone cameras are simply no longer good enough because: “They no longer capture the whole picture.” Kodak’s demise follows the classic format of every great incumbent that has fallen into obscurity in the face of an onslaught from new entrants. Kodak was itself a disruptor at one point – taking photography out of the sole preserve of professionals and putting it in the hands of every casual photographer seeking to preserve memorable moments. In his 2012 Wall Street Journal article, Kamal Munir outlines the rise and fall of Kodak in The Demise of Kodak: Five Reasons. It is important to note that Kodak developed technology for a digital camera in 1975, yet it failed to understand why customers bought its products and so failed to shift its business model as aggressively as it could have to avoid the fate that began staring it it in the face in 1975, nearly 4 decades before it filed for bankruptcy. ((Theodore Levitt’s seminal HBR article “Marketing Myopia” first introduced this concept in 1960. You should read the original article as well as this update from 2004.))

Mobile Phones vs. Fixed Line Telephones: One sign that mobile and broadband telephony is disrupting fixed line telephony is the European Commission’s 2014 decision to stop regulating fixed line telephony. The situation for fixed line telephony is no different with telephone companies announcing that they are abandoning their landline telephone infrastructure in favor of mobile and broadband phone service. Their reaction is being driven by consumer’s willingness to rid themselves of landlines in favor of cellphones for individual personal use and/or VOIP-enabled phones at home. Liquid Crystals were first discovered by the Austrian physicist Friedrich Reinitzer in 1888. Nearly 7 decades later, engineers and scientists at RCA were conducting research that led them to file the first LCD patent on November 9, 1962. The USPTO granted them the patent on May 30, 1967. However, RCA did not move aggressively enough to make the LCD technology that had been developed by its employees the center of its business model.

Liquid Crystal Displays vs. Cathode Ray Tubes: The emergence of LCD technology marked the beginning of the end for CRT technology in the TV market. The technology that led to the development of LCD televisions originated in 1888, when an Austrian Physicist, Friedrich Reinitzer discovered the strange behavior of cholesteryl-benzoate. Nearly 4 decades later, scientists and engineers working at RCA filed a patent application based on LCD technology on Nov 9, 1962. It was granted on May 30, 1967. Predictably, RCA did not do much with its head-start in the development of LCD technology, instead it gave up its advantage to Japanese, Korean, and Taiwanese upstarts.

Find more statistics at Statista

How Did That Happen? – Disruption in Action; Companies/Products

Google – Launching Sustaining and Disruptive Innovations:

Google was the 21st search engine to enter the market, 1998. Know your competition, but don’t copy it. pic.twitter.com/NUH8f65Ak8

— Vala Afshar (@ValaAfshar) December 30, 2014

While Google’s innovation in search are impressive, and helped it win that market at the expense of other search engines, it gained near absolute dominance in that market by developing a sustaining innovation in the form of its PageRank Algorithm, which is described in the paper by Sergey Brin and Lawrence Page: The Anatomy Of A Large Hypertextual Web Search Engine.

Find more statistics at Statista

Rather, the industry that has been disrupted by Google is the online advertising market. Describing this in his article “What Disrupt Really Means” Andy Rachleff writes: “It was AdWords, its advertising service. In contrast with Yahoo, which required advertisers to spend at least $5,000 to create a compelling banner ad and $10,000 for a minimum ad purchase, Google offered a self-service ad product for as little as $1. The initial AdWords customers were startups that couldn’t afford to advertise on Yahoo. A five-word text ad offered inferior fidelity compared with a display ad, but Google enabled a whole new audience to advertise online. A classic new-market disruption. Most have forgotten that Google added significant capability to its advertising service over time and then used its much-lower-cost business model (enabled by self-service) to pursue classic Internet advertisers. Thus it evolved into a low-end disruption.” Find more statistics at Statista Salesforce – Launching New Market and Low-End Disruptions: When Salesforce launched in 1999 it did so as a software-as-a-service (SaaS) platform that enabled companies that needed sales management software but could not afford the cost of annual multimilion dollar licenses for the mainstream products of the day. It’s initial product was lacking in features, and unreliable for the mainstream customers of the incumbent players in the CRM software market at that time. It built its business on non-consumption. As time progressed and its product matured in terms of reliability and features, Salesforce caused a low-end disruption as customers adopted its product while abandoning the more expensive CRM products sold by CRM market incumbents like Siebel Systems, Amdocs, E.piphany, PeopleSoft, and SAP. Find more statistics at Statista Apple: Has Apple launched any disruptive innovations? Not if you asked Clayton Christensen in 2006 or again in 2007, or even in 2012. Yet I suspect that Nokia and Research in Motion feel differently about that question. The chart below is instructive. Apple’s products have not been disruptive in the way that one might think of disruption if one adheres strictly to the line of analysis followed by Clayton Christensen and his collaborators. Perhaps one can argue that the iPod, the iPhone, and the iPad, each taken individually represents a sustaining innovation in the personal music player, the mobile phone, and the personal computer markets respectively. However, when one combines each of those products with the other elements in Apple’s product lineup there’s no denying that Apple has been disruptive to more than one industry. The “iPod + iTunes” has reshaped how people consume music, and has upended the music industry. The iPhone has led to a rethinking of what people expect from a mobile phone, and “iPod + iTunes + iPhone + AppStore” is responsible for the demise of Nokia and Research in Motion’s Blackberry as it has redefined how people consume media of all types. The “iPad + AppStore” combination is redefining how people consume media of all types, and redefining the relationship people have with their personal and laptop computers. Apple demonstrates the power of technology + design + branding + marketing as a powerful force in the process of disrupting established industries in consumer markets. ((It is worth noting that Clayton Christensen’s analysis and research focuses on business-to-business markets.)) Find more statistics at Statista You will find more statistics at Statista Netflix: At the outset Netflix seemed like a joke to executives at Blockbuster which dominated the US market for home-movie and video-game rental services, reaching its peak with 60,000 employees and 9,000 physical stores in 2004 after its launch on october 19, 1985. Netflix was founded in 1997 and started out as a flat-rate DVD-by-mail service in the United States using the United States Postal Service as its distribution channel. Presumably, the idea for Netflix was born after Reed Hastings, one of its co-founders was hit with a $40 late-fee after returning a DVD to Blockbuster well after its due date.

Netflix DVD Mailer (Image Credit: Netflix)

Automated Netflix Mailer Stuffer (Image Credit: Netflix)

Order Processing & Shipping Center (Image Credit: Netflix)

Order Processing & Shipping Center: Sleeve Labels (Image Credit: Netflix)

As you might imagine, executives at Blockbuster did not see the threat posed by Netflix and passed on 3 opportunities to buy Netflix for $50 Million. They failed to understand that people would rather not pay exorbitant late fees and that people valued the convenience of dropping the DVD from Netflix in the mail more than they enjoyed driving to Blockbuster’s physical retail stores. In other words; Netflix fulfilled the JTBD of “entertain me at home with something better than my options on TV” more conveniently than Blockbuster. The challenge that netflix must now face is how that original JTBD that it was hired to do by consumers is changing given the proliferation of mobile devices and the shift in consumer preferences away from physical media towards streaming media. You will find more statistics at Statista

But management and vision are two separate things. We had the option to buy Netflix for $50 million and we didn’t do it. They were losing money. They came around a few times. – Former High-ranking Blockbuster Executive ((Marc Graser, Epic Fail: How Blockbuster Could Have Owned Netflix. Nov 12, 2013, accessed on Jul 18, 2015 at http://variety.com/2013/biz/news/epic-fail-how-blockbuster-could-have-owned-netflix-1200823443/))

To anyone that ever rented a movie from BLOCKBUSTER, thank you for your patronage & allowing us to help you make it a BLOCKBUSTER night. — Blockbuster (@blockbuster) November 10, 2013

Blockbuster filed for bankruptcy in 2013. Today Netflix is streamed online through many internet-enabled smart tvs, streaming media players, game consoles, set-top boxes, blu-ray players, smartphones and tablets, as well as personal and laptop computers.

What Common Traits Do the Startup Founders Who Lead Disruptive Startups Share?

Disruptive innovation is built on much more than technology innovation. The startups that go on to disrupt markets combine innovation in technology with innovative approaches to market segmentation, product positioning, marketing strategy, business model innovation, business strategy, corporate strategy, customer psychology, and organizational design and culture.

As an investor in early stage technology startups that are still in the searching for and trying to validate a repeatable, profitable, and scalable business model it is critical that I become good at recognizing startup founders who can successfully see disruption through to a profitable harvest for the founders, and the LPs to whom I am responsible.

According to The Innovator’s DNA, startup founders capable of leading disruptive new market entrants display the following traits:

Association: They make connections between seemingly disparate areas of knowledge, leading them to novel conclusions that elude other people.
Questioning: They exhibit a passion for questioning the status quo.
Observing: They learn by watching the world around them more closely than their peers and competitors.
Networking: They have a social network that is wide and diverse, which enables them to test their own ideas as well as seek ideas from people who may see the world from a distinctly different point of view.
Experimenting: They continuously test their assumptions and hypotheses by unceasingly exploring the world intellectually and experientially.

These skills are echoed in The Creator’s Code, which describes extraordinary entrepreneurs as people who:

Find The Gap: by staying alert enough to spot opportunities that elude other people by transplanting ideas across divides, merging disparate concepts, or designing new ways forward.
Drive For Daylight: by staying focused on the future, and making choices today on the basis of where they see the market going instead of where the market has been.
Fly The OODA Loop: by continuously and rapidly updating their assumptions and hypotheses through the Observe, Orient, Decide, and Act framework. Fast cycle iteration helps them gain an edge over their competition, and catchup with the mainstream market incumbents. ((See statements like: “Move fast and break things.” or “Let chaos reign.”))
Fail Wisely: by preferring a series of small failures over a few catastrophic setbacks by placing small bets to test new ideas in order to gain further insight before they place big bets. By doing this they create organizations that learn how to turn failure into success and develop an inbuilt structural resilience.
Network Minds: by harvesting the knowledge and brainpower from cognitively and experientially diverse individuals they develop unique approaches to solving multifaceted problems, problems whose solution might elude competitors.
Gift Small Goods: by behaving generously towards others they strengthen relationships and build goodwill towards themselves and the organizations that they lead.

In The Questions Every Entrepreneur Must Answer, Amar Bhidé outlines a number of questions the feels every entrepreneur must answer in order to determine fit of the entrepreneur to the startup venture and of the startup venture to its context. ((Amar Bhidé,The Questions Every Entrepreneur Must Answer. From The Entrepreneurial Venture, readings selected by William A. Sahlman et al. 2nd edition, pp. 65 – 79.)) The questions are as follows;

Where does the entrepreneur want to go?
1. What kind of enterprise does the entrepreneur need to build in order to get there?
2. What risks and sacrifices does such an enterprise demand?
3. Can the entrepreneur accept those risks and sacrifices?
How will the entrepreneur and the startup get there?
1. Is there a strategy that can get the startup there?
2. Can that strategy generate sufficient profits and growth within a time-frame that make sense for the entrepreneur and for the startup’s investors?
3. Is the strategy, and the startup’s business model defensible and sustainable? ((I have discussed economic moats here: Revisiting What I Know About Network Effects & Startups and here: Revisiting What I Know About Switching Costs & Startups))
4. Are the goals for growth too conservative, or too aggressive?
Can the founder or co-founders do it?
1. Do they have the right resources and relationships?
2. How strong is the relationship between the co-founders with one another, how strong is the organization’s team cohesion?
3. Can the founder play her role?

The Role of Experts in Predicting The Success or Failure of Disruptive Innovations

Early stage investors often rely on the advice of subject matter experts as part of the due diligence process. Experts are great for determining if the technical innovation works as the founders say it does, however where investors can go wildly wrong is when they rely on subject matter experts for investment recommendations for disruptive innovations.

It should be obvious by now that most experts are poorly placed to offer advice that will be seen as correct when examined in hindsight if they are faced with a disruptive innovation.

The Only things we really hate are unfamiliar things.

– Samuel Butler, Life and Habit

The difficulty subject matter experts face in predicting how markets will evolve is captured in The Lexicon of Musical Invective, where the author captures the vituperous reactions of music critics to works that are now widely considered as masterpieces in the pantheon of Western music history. Why did these experts fail? They did not allow for the possibility that the future might differ from the present in which they were performing their analysis, nor did they allow for the possibility that people’s tastes in music would evolve away from what they had grown accustomed.

Experts experience too much cognitive dissonance when they have to make an investment recommendation regarding a disruptive innovation; what does it mean for their personal career security, what does that mean for the skills that they have worked so hard and so long to accumulate, what does that mean for their employer’s business?

Moreover, the fact that an individual is an expert in the technology behind the disruptive innovation does not mean that the same individual is an expert in all the other disciplines that are required to turn the technological innovation into a disruptive innovation.

Here are a few examples of instances in which experts got things horribly wrong: ((Adapted from Top 10 Bad Tech Predictions, by Gordon Globe. Nov 4, 2012, accessed on Jul 19, 2015 at http://www.digitaltrends.com/features/top-10-bad-tech-predictions/5/))

In 1977 Ken Olson said: “There is no reason anyone would want a computer in their home.” He was an engineer by training, and president, chairman and founder of Digital Equipment Corporation. Microsoft and Apple were startups.
In 1956 Herbert Simon said: “Machines will be capable, within twenty years, of doing any work a man can do.” He made this statement after attending an AI conference at Dartmouth.
In 1946 Darryl Zanuck said: “Television won’t be able to hold on to any market it captures after the first six months. People will soon get tired of staring at a plywood box every night.” He was a Hollywood magnate.
In 1995 Robert Metcalfe said: “I predict the Internet will soon go spectacularly supernova and in 1996 catastrophically collapse.” He co-invented Ethernet technology and co-founded 3Com in 1979 with 3 other people. 3Com develops computer network products.
In 1995 Clifford Stoll said: “The truth is no online database will replace your daily newspaper, no CD-ROM can take the place of a competent teacher and no computer network will change the way government works.” He was an astronomer, a hacker, and author, and a computer geek.
In 2007 Steve Balmer said: “There’s no chance that the iPhone is going to get any significant market share.” He was the CEO of Microsoft. ((Mark Spoonauer, 10 Worst Tech Predictions of All Time. Aug 7, 2013. Accessed online on Jul 19, 2015 at http://blog.laptopmag.com/10-worst-tech-predictions-of-all-time))

Criticisms of Clayton Christensen’s Theory of Disruptive Innovation

In her 2014 New Yorker article; The Disruption Machine: What The Gospel of Innovation Get’s Wrong,JillLepore argues that:
1. The theory is based on handpicked case studies, and it is not clear that these case studies are provide a sound basis upon which to build a theory.
2. What Christensen describes as “disruption” can often be more accurately described as “bad management”
3. The theory of disruption is built on retrospective analysis, it is unclear how useful it is in predicting how events will unfold.
In his 2013 blog post: What Clayton Christensen Got Wrong, Ben Thompson examined the theory of disruption in the context of Apple’s introduction of the iPod, and later the iPhone. He argues that:
1. The theory works well when we consider new market disruptions, but fails when we consider low-end disruptions, in consumer markets.
2. The theory fails because consumers do not behave rationally.
3. The theory fails to account for product attributes that cannot be documented but which consumers prize highly, all thing being equal.
4. Vertical integration is a competitive advantage in consumer markets, because it allows vertically integrated producers to exert control over product attributes that customers value, but which would be near-impossible to control using a modular production framework.

Closing Thoughts

The ideas on which “disruptive innovation” is built are not inviolable and permanent laws of nature. Early stage investors and startup founders should subject them to testing on a frequent basis. Disruption works in different ways in consumer markets than it does in enterprise, or business to business markets.
Startup founders and their investors should combine Clayton Christensen’s ideas with those of Michael Porter in order to build a more complete strategic plan that can stand the vicissitudes of competition from the startup’s peers and the reaction from mainstream market incumbents.
Good strategy is not a substitute for good management. Good strategy does not make good management obsolete.
Building a better mousetrap is not necessarily the path to disruptive innovation and winning the market in which a startup is a new entrant.
Low end disruptions almost always begin with a product that is significantly inferior in comparison to the product embraced by the mainstream market. Low end disruptions also have to be simpler, cheaper or more convenient than the mainstream product.
New market disruptions do not necessarily have to be less expensive than the comparable product that is embraced by the mainstream market.
Disruptive innovation entails much more than technological disruption. Incumbents can compete with technological disruption, and they always win in those scenarios. To succeed, startups seeking to disrupt a market must design business models that support their effort to bring their technological innovation to market and make it impossible for the mainstream market incumbents to respond in a manner that causes the startup to fail prematurely.
The kernel of disruptive innovation is an insight that the mainstream market has ignored.
Beware of investment advice from subject matter experts as it pertains to potentially disruptive startups. Test your biases against what can be proved by the market niche that the startup is first going to enter.

Further Reading

Blog Posts & Articles

What “Disrupt” Really Means – Andy Rachleff
The Four Stages of Disruption – Steven Sinofsky
Marketing Myopia – Theodore Levitt, original 1960 HBR article
Marketing Myopia – Theodore Levitt, 2004 HBR update
How Disruption Happens – Greg Satell
Good Disruption / Bad Disruption – Greg Satell
Did RCA Have To Be Sold? – L.J. Davis
What Clayton Christensen Got Wrong – Ben Thompson
Clayton Christensen Becomes His Own Devil’s Advocate – Jean-Louis Gassée
The Disruption Machine: What The Gospel of Innovation Gets Wrong – Jill Lepore
Disruptive Business Strategy: What is Steve Jobs Really Up To? – Paul Paetz
Clayton Christensen Responds to New Yorker Takedown of “Disruptive Innovation” – Drake Bennet
How Useful Is The Theory of Disruptive Innovation? – Andrew A. King and Baljir Baatartogtokh, MIT Sloan Management Review Fall 2015 Issue
What Is Disruptive Innovation? – Clayton Christensen et al, HBR December 2015 Issue
Patterns of Disruption: Anticipating Disruptive Strategies of Market Entrants – John Hagel et al

White Papers

Books

Industry Study: Nanotechnology

July 12, 2015 by Brian Laung Aoaeh

SUNY College of Nanoscale Science and Engineering's Michael Liehr, left, and IBM's Bala Haranand look at wafer comprised of 7nm chips on Thursday, July 2, 2015, in a NFX clean room Albany. Several 7nm chips at SUNY Poly CNSE on Thursday in Albany. (Darryl Bautista/Feature Photo Service for IBM) — SUNY College of Nanoscale Science and Engineering’s Michael Liehr, left, and IBM’s Bala Haranand look at wafer comprised of 7nm chips on Thursday, July 2, 2015, in a NFX clean room Albany. Several 7nm chips at SUNY Poly CNSE on Thursday in Albany. (Darryl Bautista/Feature Photo Service for IBM)

Note 1: This is an update of an article that I wrote on a whim in December 2006, while I was on a break from business school at NYU Stern. It was published without update at Tekedia in July, 2011. The announcement by IBM about its new 7nm chip prompted me to dig it up from my archives and update it to reflect more recent developments.

Note 2: KEC Ventures does not specifically invest in nanotech startups, although in the past we have examined startups developing quantum crystals and other nanomaterials.

Introduction

I became exposed to nanotechnology during my days as an undergraduate student at Connecticut College, in New London, Connecticut. I pursued a double major in Physics and Mathematics, and had the good fortune of working as a research laboratory assistant in the Tunable Semiconductor Diode-Laser Spectroscopy lab, which was run by Professor Arlan W. Mantz, Oakes Ames Professor of Physics, and erstwhile chair of the Physics Department. My involvement with the lab spanned three years, and that experience played a critical role in my education. ((Let me know if you feel I have failed to attribute something appropriately. Tell me how to fix the error, and I will do so. I regret any mistakes in quoting from my sources.))

What Is It?

The term nanotechnology refers to a group of scientific processes that enable products to be manufactured by the manipulation of matter at the molecular level – at the nanoscale. One nanometer represents a length of 10^-9meters – one billionth of a meter. ((For perspective, 100nm represents about 1000^-1 of the width of a human hair.)) Nanotechnology enables the manipulation of matter at or below dimensions of 100 nanometers. Nanotechnology draws from a multitude of scientific disciplines – physics, chemistry, materials science, computer science, biology, electrical engineering, environmental science, radiology and other areas of applied science and technology.

There are two major approaches to manufacturing at the nanoscale;

In the “bottom-up” approach, nanoscale materials and devices assemble themselves from molecular components through molecular recognition – small devices are assembled from small components.
In the “top-down” approach materials and devices are developed without the manipulation of individual molecules – small devices are assembled from larger components.

Where is Activity Concentrated?

Research into nanotechnology and its applications is growing rapidly around the world, and many emerging market economies are sparing no effort in developing their own research capacity in nanotechnology.

Naturally, the U.S., Japan, Western Europe, Australia and Canada hold an advantage, in the short term.
China and India have made significant progress in establishing a foundation on which to build further capability in nanotechnology – A 2004 listing puts them among the top 10 nations worldwide for peer-reviewed articles in nanotechnology. ((Hassan, Mohamed H. A., Small Things and Big Changes in The Developing World. Science,Vol. 309 no. 5751, Jul 1 2005, accessed on Dec 19, 2006 at http://www.sciencemag.org/cgi/content/full/309/5731/65))
South Africa, Chile, Mexico, Argentina, The Philippines, Thailand, Taiwan, The Czech Republic, Costa Rica, Romania, Russia and Saudi Arabia have each committed relatively significant resources to developing self-sufficient local nanotechnology industries.

Why Should Investors Care?

Fundamentally, investors should pay attention to nanotechnology because of its high potential to spawn numerous “disruptive technologies.” Nanoscale materials and devices promise to be;

Cheaper to produce,
Higher performing,
Longer lasting, and
More convenient to use in a broad array of applications.

This means that processes that fail to provide results comparable to those available through nanotechnology will become obsolete rather quickly, once an alternative nanoscale process has been perfected. In addition, companies that fail to embrace and apply nanotechnology could face rapid decline if their competitors adopt the technology successfully.

The United States Government has maintained its commitment to fostering U.S. leadership and dominance in the emerging fields of nanoscale science. In its 2006 budget, the National Nanotechnology Initiative, a multi-agency U.S. Government program, requested $1.05 Billion for nanotechnology R&D across the Federal Government. ((The National Nanotechnology Initiative, Research and Development Leading To A Revolution in Technology and Industry, Supplement to The Presidents FY 2006 Budget)) That amount reflects an increase from the $464 Million spent on nanotechnology by the Federal Government in 2001.

Applications of Nanotechnology

Nanotechnology’s promise to revolutionize the world we live in spans almost every aspect of human endeavor. Today, nanotechnology is applied in as many as 800 commercial products. ((National Nanotechnology Initiative, accessed online on Jul 12, 2015.))

IBM’s new chip “could result in the ability to place more than 20 billion tiny switches – transistors – on the fingernail-sized chips that power everything from smartphones to spacecraft. To achieve the higher performance, lower power and scaling benefits promised by 7nm technology, researchers had to bypass conventional semiconductor manufacturing approaches. Among the novel processes and techniques pioneered by the IBM Research alliance were a number of industry-first innovations, most notably Silicon Germanium (SiGe) channel transistors and Extreme Ultraviolet (EUV) lithography integration at multiple levels.” ((See the announcement from IBM. Accessed online on Jul 12, 2015.))
Carbon nanotubes and other nanomaterial additives can be used to fabricate stronger, lighter materials for use in automobile bodies, helmets, sports equipment and other products in which stiffness and durability are important features.
Researchers at Stanford University have killed cancer cells using heated nanotubes, while EndoBionics, a US firm, developed the MicroSyringe for injecting drugs into the heart. MagForce Technologies, a Berlin based company developed iron-oxide particles that it coats with a compound that is a nutrient for tumor cells. Once the tumor cells ingest these particles, an external magnetic field causes the iron-oxide particles to vibrate rapidly. The vibrations kill the tumor cells, which the body then eliminates naturally. Other applications in medicine and biotechnology exist.
Cosmetics companies are actively engaged in the exploration of nanotechnology as a source of enhanced products. For example, to produce cosmetics that can be absorbed more easily through human skin and that exhibit longer lasting properties.
Thebreakthrough by IBM will only acceleratethe development ofnanoscale technologies for computing platforms. According to the National Nanotechnology Initiative:”Nanotechnology is already in use in many computing, communications, and other electronics applications toprovide faster, smaller, and more portable systems that can manage and store larger and larger amounts of information. These continuously evolving applications include:
- Nanoscale transistors that are faster, more powerful, and increasingly energy-efficient; soon your computer’s entire memory may be stored on a single tiny chip.
- Magnetic random access memory (MRAM) enabled by nanometer‐scale magnetic tunnel junctions that can quickly and effectively save even encrypted data during a system shutdown or crash, enable resume‐play features, and gather vehicle accident data.
- Displays for many new TVs, laptop computers, cell phones, digital cameras, and other devices incorporate nanostructured polymer films known as organic light-emitting diodes, or OLEDs. OLED screens offer brighter images in a flat format, as well as wider viewing angles, lighter weight, better picture density, lower power consumption, and longer lifetimes.
- Other computing and electronic products include Flash memory chips for iPod nanos; ultraresponsive hearing aids; antimicrobial/antibacterial coatings on mouse/keyboard/cell phone casings; conductive inks for printed electronics for RFID/smart cards/smart packaging; more life-like video games; and flexible displays for e-book readers.”
Nanotechnology is applied in the garment industry to produce stain resistant fabrics, for example.
Nanotechnology companies in the developing world are pursuing solutions to problems peculiar to the developing world – for example, an Indian company is working on a prototype kit for diagnosing tuberculosis. There is great potential for the application of nanotechnology to agriculture.

A more complete listing of the benefits and applications of nanotechnology is available here: US National Nanotechnology Initiative

Threats

In spite of its promise, nanotechnology faces threats that could investors ought to be aware of. Among these;

It is not yet clear how nanotechnology will affect the health of workers in industries in which it is applied. For example, how should we assess exposure to nanomaterials? How should we measure the toxicity of nanomaterials?
Public agencies and private organizations do not have a clear sense of how further progress in nanotechnology will affect the environment, or of the public safety issues that will accompany an expanded use of nanotechnology in industrial, medical and consumer applications. For example, what factors should risk-focused research be based on, and how should we go about creating prediction models to gauge the potential impact of nanomaterials?
The complexity of the science that is integral to nanotechnology makes it a very difficult area to regulate. It is likely that firms involved in the pursuit of nanoscale applications in medicine and pharmaceutics will face long delays in obtaining regulatory approval for the wide scale use of their products.
The complexity of nanotech-related patents could lead to delays in obtaining intellectual property protection for nanotech-enabled products.
It is not yet clear how society can protect itself from the abuse of nanotechnology. The public sector needs to collaborate with the private sector in developing protective mechanisms to guard against “accidents and abuses” of the capabilities of nanoscale processes and materials.

A Note To Would-Be Investors

The average investor must remain keenly aware that firms involved in nanotechnology will have to assign significant resources to research and development. There is no reliable means of predicting the ultimate outcome of such activities, and the probability that any firm can maintain an enduring edge over its competitors is small. Investors should expect the mantle of leadership in innovation to change with a relatively high frequency. As such, pure-play nanotechnology firms will need to pay critical attention to means of sustaining market dominance that go beyond core competence in the science of nanotechnology.

Lux Research estimates that revenues from products using nanotechnology will increase from $13 Billion in 2004 to $2.6 Trillion in 2014. The 2014 estimate represents approximately 15% of global manufacturing output. ((Gosh, Palash R, How To Invest In Nanotech, www.businessweek.com, Apr 17, 2006. Accessed on Dec 22, 2006.))

In 2005, Lux Research and PowerShares Capital Management launched a nanotech ETF – The PowerShares Lux Nanotech Portfolio (PXN). In addition, Lux Research measures the performance of publicly traded companies in the area of nanotechnology through the Lux Nanotech Index^TM, a modified equal dollar weighted index of 26 companies. The companies in this index earn profits by utilizing nanotechnology at various stages of a nanotechnology value chain; ((Adapted from www.luxresearchinc.com))

Nanotools – Hardware and Software used to manipulate matter at the nanoscale.
Nanomaterials – Nanoscale structures in an unprocessed state.
Nanointermediates – Intermediate products that exhibit the features of matter at the nanoscale.
Nano-enabled Products – Finished goods that incorporate nanotechnology.

Companies in the index are further classified as

Nanotech Specialists, or
End-Use Incumbents.

Investors must note that the investment characteristics of Nanotech Specialists are likely to differ markedly from those of End-Use Incumbents. The end-use incumbents that are part of this index include 3M, GE, Toyota, IBM, Intel Hewlett-Packard, BASF, Du Pont, and Air Products & Chemicals. Because these companies have large, well-established and significant operations in arenas that do not rely heavily on nanotechnology, investors can expect them to achieve financial results that are only moderately volatile. In contrast the financial performance of nanotech specialists will exhibit highly volatile swings, because;

With the exception of companies in the “picks and shovels” segment of nanotechnology, much of the work that many nanotech specialists engage in is still in the “trial and error” phase, and
There is no reliable means of predicting the results that heavy investment in R&D will yield.

Finally, it is likely that financial valuations of nanotech firms will fail to capture the true value of the intangible assets that provide the bedrock of each company’s ability to sustain innovation, create economic value, and protect its competitive advantage. If nanotechnology is truly the way of the future, then investors must embrace that future with enthusiasm that is layered with caution by;

Performing an extra amount of due diligence before committing significant funds to investments in individual nanotechnology companies,
Limiting such investments to companies in the U.S., Japan, Canada, Western Europe, and Australia, in the near term, and
Following developments in the nanotechnology initiatives of the BRIC block of emerging market economies without committing any funds until a clear assessment of the future prospects of individual investment opportunities becomes possible.

Individual investors must exercise an extra amount of caution in pursuing nanotech investments, and should not commit more than they can afford to lose. Most individual investors with a desire to invest in nanotechnology should do so through PXN and similar instruments. Institutional investors must bring all their resources to bear in assessing the viability of a nanotech investment strategy prior to committing funds to this nascent area. For added security, individual investors that seek to invest in publicly traded nanotech companies should seek firms with the following characteristics;

No debt, and positive cash flows, and evidence of an ability to sustain profits.
Companies that supply corporate customers must not be too reliant on one customer.

Founders and insiders should have a significant and increasing portion of their net worth at stake in the company, and a track record in multi-disciplinary research.

In a Feb 2014 State of The Market Report update, Lux Research says “Our expanded forecast for nano-enabled products reveals the global value of nano-enabled products, nano-intermediates, and nanomaterials reaching $4.4 trillion by 2018.”

Closing Thoughts

Many risks accompany investments in nanotechnology. However, if nanotech is to be believed, it may yield significant long-term returns to those investors that learn to harness its power while keeping the following caveats in mind;

Many nanotech companies face an up-hill task in converting promising research into products that can sustain a steady revenue stream.
A considerable number of nanotech companies may be surrounded by “more hype than substance”.
There is no guarantee that the price investors pay for an investment in nanotech will be adequate, once all associated risks are taken into account.

Notes on Strategy; For Early Stage Technology Startups

June 23, 2015 by Brian Laung Aoaeh

Alternate Title: What Can 24’s Jack Bauer Teach a Tech Startup Founder About Strategy?

Google Search for "What is Strategy" — Google Search for “What is Strategy”

Running a business without a strategy is like breathing air without oxygen.

The purpose of this blog post is to attempt to synthesize certain fundamental lessons on strategy that are relevant for anyone trying to build a business. ((Let me know if you feel I have failed to attribute something appropriately. Tell me how to fix the error, and I will do so. I regret any mistakes in quoting from my sources.)) As part of the discussion, I will attempt to provide concrete yet easy to use frameworks that founders of early stage startups can use as they work on moving their organizations through the discovery process that takes them from being a startup to becoming a company. ((My target audience is made up of first-time startup founders who do not have any background in business, finance, economics, or strategy.))

To ensure we are on the same page, and thinking about the issues from the same starting point . . . first, some definitions.

Definition #1: What is a Startup? A startup is a temporary organization built to search for the solution to a problem, and in the process to find a repeatable, scalable and profitable business model that is designed for incredibly fast growth. The defining characteristic of a startup is that of experimentation – in order to have a chance of survival every startup has to be good at performing the experiments that are necessary for the discovery of a successful business model. ((I am paraphrasing Steve Blank and Bob Dorf, and the definition they provide in their book The Startup Owner’s Manual: The Step-by-Step Guide for Building a Great Company. I have modified their definition with an element from a discussion in which Paul Graham, founder of Y Combinator discusses the startups that Y Combinator supports.)) As an investor, I hope that each early stage startup in which I have made an investment matures into a company.

Strategy is about making choices, trade-offs; it’s about deliberately choosing to be different.

– Michael Porter ((Keith H. Hammond, Michael Porter’s Big Ideas. Accessed on Jun 20, 2015 at http://www.fastcompany.com/42485/michael-porters-big-ideas))

Definition #2: What is Strategy? An early stage startup’s strategy is that deliberate set of integrated choices it makes in order to create a sustainable competitive advantage within its market relative to rival startups and market incumbents. It is the means by which a startup combines all the elements within its environment to create and deliver value for its customers, while simultaneously capturing some of that value for itself and its investors. Strategy answers questions about what the startup should do and what it should not do in order to find a repeatable, scalable and profitable business model.

Strategy as an Integrated Cascade of Choices: From Playing to Win, by A.G. Lafley and Robert L. Martin. HBR Press (2013)

Some additional observations about strategy;

Strategy can be granular and tangible or broad and intangible. It is granular and tangible as one goes further down the organizational hierarchy. It is broad and intangible as one approaches the top of an organization.
Strategy helps a startup decide how to utilise its internal and external resources and capabilities towards reaching its ultimate goals and objectives.
In a growth stage startup or mature company, effective strategy makes choices and trade-offs in the following areas;
- Supply chain
- Manufacturing, product development
- Distribution channels
- Human resources
- Finance
- Research and development
- Operations
For an early stage startup strategy involves choices and trade-offs in the following areas;
- Value propositions
- Customers – segments, relationships
- Key activities
- Key resources
- Key partners
- Cost structure
- Revenue streams

Alex Osterwalder's Business Model Canvas, from the book Business Model Generation — Alex Osterwalder’s Business Model Canvas, from the book Business Model Generation

Strategic Decision Making Tools for Early Stage Technology Startups

Porter’s 5 Forces: In a 2008 update to his 1979 HBR Article: How Competitive Forces Shape Strategy, Michael E. Porter discusses the “5 Forces” that have a direct impact on strategy.

Michael E. Porter – The Five Forces That Shape Industry Competition Image Credit: Harvard Business Review (2008)

Threat of New Entrants: This is the degree to which a startup can expect to face intense competition because the number of direct rivals it faces keeps increasing. Direct rivals are other startups that enter the market with a value proposition that is nearly identical to that which a given an incumbent startup is offering its customers. High threat of new entrants imposes a ceiling on profitability, limits how much value an incumbent startup can capture for itself, and imposes high costs on the existing competitors within the industry or market. As a result, it is important for startup founders to think about how they might construct an economic moat around their business. Michael Porter discusses seven major sources of barriers to entry; supply-side economies of scale, demand-side benefits of scale, customer switching costs, capital requirements, incumbency advantages independent of size, unequal access to distribution channels, and restrictive government policy.

Bargaining Power of Suppliers: Suppliers become powerful when they form a more concentrated group than the startups that they sell to and do not rely on startups for the significant proportion of their revenues. Additional factors leading to supplier power include; the suppliers offer products that are differentiated and unique, startups face high switching costs in moving from that supplier group to an alternative product, a lack of satisfactory alternatives to the product or service provided by the supplier group. These factors combine to put the suppliers in an enormously strong negotiating position, and enables them to maintain high prices and pass nearly all cost increases on to their startup customers.

Bargaining Power of Buyers: This is the opposite of supplier power. Powerful buyers can have a debilitating impact on the profitability of a group of startups that supply them with goods or services. The factors that contribute to powerful buyers are; a small number of buyers with each purchasing in large volumes relative to the size of each incumbent startup, buyers perceive and experience no switching costs if they switch from one startup’s products to products supplied by one of its competitors, the quality and reliability or lack thereof of products or services provided by suppliers does not affect the buyers’ ability to maintain or improve the quality of their goods or services.

Threat of Substitutes: This has not happened recently, but it used to be that when I would ask a founder “Who is your competition?” the quick response would be “We do not have any competition!” I’d shake my head and think to myself, they must not understand the meaning of substitute. According to Michael Porter “A substitute performs the same or a similar function as an industry’s product by a different means.” For example, videoconferencing is a substitute for travel. The threat posed by substitutes can be camouflaged by the apparent difference between the way an early stage startup perceives its customer value proposition and the way its customers perceive that same value proposition in comparison to the substitute. One way to think of substitutes is to ask “How are customers fulfilling that need or solving that problem now?” Another way to think about substitutes is to ask the question “Where are customers spending less money because they have chosen to buy our product?” Industry profitability is constrained by a high threat of substitutes. Consider the threat posed to social-networking like Twitter and Facebook from the chat and messaging apps. Facebook has been more responsive to those threats, and has strengthened its strategic position through its acquisitions of Instagram, Oculus Rift and Whatsapp. The threat posed by substitutes is high if customers are indifferent to the price-performance trade-offs they have to make if they switch to the substitute. The threat is also high if switching costs to customers are minimal, or non-existent. To find examples of how the threat of substitutes functions, think of the threat that Facebook is posing to Google’s business model of selling ads tied to users’ search activity. Or the threat that the shift from desktop-centric to mobile-centric computing poses to all kinds of businesses that have been built from the desktop centric point of view. Or the current debates around the relationship between startups in the on-demand economy and their employees, and the implications for the startups that are currently on either either side of that debate. ((Annie Lowery, How One Woman Could Destroy Uber’s Business Model – and Take the Entire “on-Demand” Economy Down With It. Accessed on Jun 21, at http://nymag.com/daily/intelligencer/2015/04/meet-the-lawyer-fighting-ubers-business-model.html.))

Rivalry Among Existing Competitors: Think Uber and Lyft, Microsoft’s Internet Explorer and Netscape Navigator, Apple iTunes and Spotify/Pandora etc, Apple’s iOS and Google’s Android, Apple’s iPhone and Samsung’s Galaxy, Apple’s Watch and the burgeoning number of wearables designed and produced by other competitors in that market. Evidence of intense rivalries among existing competitors is found in frequent price-cuts, ubiquitous sales and marketing campaigns, and relatively short product and service upgrade cycles. Combined with the threat of new entrants, rivalry among existing competitors leads to a land-grab by incumbents to access new markets where rivalry is less intense and potentially lock rivals in other markets out of the new markets. A land-grab could also be initiated in anticipation of intense rivalry developing in the future. The on-demand ride-sharing wars that are playing out around the world today provide a text-book example of this phenomenon. High rivalry among existing competitors constrains profitability along two dimensions; the intensity of the competition, as well as the basis on which that competition is taking place. Factors that contribute to a high intensity of rivalry are: Competitors roughly equal in size, slow growth, high exit barriers, high levels of commitment to the market and the industry, and poor signaling. One mistake rivals often make? They engage in mutually destructive price-cuts in succeeding rounds of attack and retaliation. Or, they might engage in other tactics that lead to an overall degradation of the customer experience or user experience for their mutual customers. Particularly destructive behavior is most liable to occur when the individual rivals’ products cannot be differentiated from one another by their target customers, the rivals are each faced with a cost structure characterized by high fixed costs and low marginal costs, it is difficult to make quick capacity adjustments in response to surges or declines in demand, and the product is perishable. ((Consider how the transient, perishable nature of “time” has influenced the behavior of ride-sharing rivals – a ride not delivered today can never be recouped. It is gone forever.)) Ideally, competition among rivals should aim to grow the profitability of the industry or market for all players within it, while raising barriers to entry.

Factors that influence strategy: In debates about strategy with other management theorists, academics and practitioners, Michael Porter has stated;

It is especially important to avoid the common pitfall of mistaking certain visible attributes of an industry for its underlying structure.

He describes the following factors that influence strategy and competition within an industry;

Industry growth rate
Technology and innovation
Government
Complementary products and services

The key is for startup founders and their investors to analyze each of the five forces that shape competitive strategy within the context of each of these factors. The factors are not inherently good or bad, but must be assessed in the context of the the five forces and the impact they have on developments within the industry.

Jack Bauer, the star character in 24 always seems to be thinking several steps ahead of everyone else surrounding him. Image Credit: Wikimedia

You probably think I’m at a disadvantage; I promise you I am not.

– Jack Bauer (24: Live Another Day); speaking to a group of armed men suspected of planning to carry out a terrorist attack on London. He appears ambushed, trapped, outnumbered and outgunned by them.

Definition #3: What is Game Theory? According to Wolfram Mathworld; “Game theory is a branch of mathematics that deals with the analysis of games (i.e., situations involving parties with conflicting interests). In addition to the mathematical elegance and complete “solution” which is possible for simple games, the principles of game theory also find applications to complicated games such as cards, checkers, and chess, as well as real-world problems as diverse as economics, property division, politics, and warfare.

Game theory has two distinct branches: combinatorial game theory and classical game theory.

Combinatorial game theory covers two-player games of perfect knowledge such as go, chess, or checkers. Notably, combinatorial games have no chance element, and players take turns.

In classical game theory, players move, bet, or strategize simultaneously. Both hidden information and chance elements are frequent features in this branch of game theory, which is also a branch of economics.” ((Game Theory. Accessed on Jun 21, 2015 at http://mathworld.wolfram.com/GameTheory.html))

For a flavor of the wide application of game theory;

Playing The Right Game – Using Game Theory To Shape Strategy: In their 1995 Harvard Business Review article – The Right Game: Use Game Theory to Shape Strategy Adam M. Brandenburger and Barry Nalebuff offer advice that startup founders can use to guide the choices they make as they navigate the terrain that lies between their startup’s emergence as an embryonic organization and its hopeful maturity into a company.

Unlike war and sports, business is not about winning and losing. Nor is it about how well you play the game. Companies can succeed spectacularly without requiring others to fail. And they can fail miserably no matter how well they play if they make the mistake of playing the wrong game. The essence of business success lies in making sure you’re playing the right game.

Following are some observations based on their paper:

There are two basic types of games; rule-based games and freewheeling games. Business is a complex mix of both.
To aid them formulate their startup’s strategy, the startup’s founders and investors must think far out into the future to make postulations about how the game might unfold by analyzing how all the players in the game will react to moves by another player in the game. This involves reasoning forward and then reasoning backwards to the present in order to determine what actions taken today will lead to the outcome that the startup wishes to bring into existence in the future. They state: “For rule-based games, game theory offers the principle, To every action, there is a reaction. But, unlike Newton’s third law of motion, the reaction is not programmed to be equal and opposite.”
The startup’s founders must eschew egocentrism and instead embrace allocentrism, i.e. they must focus less on their startup’s actions but rather must focus on the actions, desires, expectations, ambitions, goals, objectives etc. etc. of their rivals. They state: “To look forward and reason backward, you have to put yourself in the shoes—even in the heads—of other players. To assess your added value, you have to ask not what other players can bring to you but what you can bring to other players.”
Startup founders should seek and create opportunities for “Coopetition” – “It means looking for win-win as well as win-lose opportunities. Keeping both possibilities in mind is important because win-lose strategies often backfire.” They cite the example of a price war as a move that ultimately leaves all the players in a game worse off because it reestablishes the status quo, but at a lower price. Starting a price war is a lose-lose move.
It is important to think of the players within a startup’s Value Net; an environment created by the startup’s customers and suppliers – arranged vertically in the Value Net framework, and its substitutors and complementors – arranged horizontally in the Value Net. The startup itself is positioned where the Value Net axes intersect. The startup transacts with its counterparties positioned along the vertical axis – resources and money flow between the startup and its customers and suppliers. The startup does not transact directly with its substitutors or complementors, but it interacts with them nonetheless. Often, strategists do not pay sufficient attention to how a startup’s interactions with its substitutors and complementors can be modified in order to create win-win outcomes for the players in the startup’s Value Net. They recommend drawing the Value Net, and monitoring changes that occur to the elements of the game using that map.
The elements of a game are; The Players – customers, suppliers, substitutors, complementors and, of course, the startup itself. The Added Values – this is what each player brings to the game, and the key task here is to consider means by which the startup might make itself a more valuable player. The Rules – in business these are fluid and likely not transparent, although this is not always so, also the players in the game might agree to change them. Tactics – these are short term moves the startup makes in order to shape how it is perceived by other players in the game, or to maintain uncertainty within the game for its benefit. The scope – these are the boundaries of the game. Founders might consider expanding or shrinking the boundaries of the game in keeping with what they believe works best for the ultimate outcomes that the startups wishes to realize.
The authors discuss “The Traps of Strategy” – briefly outlined;
- The startup does not have to accept the game that it finds itself in.
- The startup does not have to change the game at the expense of other players within its Value Net.
- The startup does not have to be unique to succeed. On its own, uniqueness is an insufficient dimension along which to pursue success.
- Founders’ failure to study and see the whole game can prove expensive and fatal because any moves towards one group of players in the game has counterpart move with the other players along that axis. Draw the Value Net.
- Founders’ failure to think methodically about changing the game can prove expensive, focusing inwardly on the startup instead of outwardly on the other players within the Value Net limits the strategic options available. Use PARTS.

The Goals Grid – A Tool for Clarifying Goals and Objectives: I discovered The Goals Grid in 2009 while working on two turnaround assignments, and feeling dissatisfied with the tools I had acquired in business school – it quickly became clear to me that those tools did not translate readily when I was in the trenches, working with people on the frontlines of fine-dining, and general aviation, who lacked the training in strategy and management that students in MBA programs in the United States receive. I needed something I could discuss with them, but that they could then implement without me. ((Fred Nickols updated it in 2010. Accessed on Jun 22, 2015 at http://www.nsac.org/Endowments/Docs/GoalsGrid.pdf))

The Goals Grid focuses startup founders’ attention by asking 4 questions;

What are you trying to achieve?
What are you trying to preserve?
What are you trying to avoid?
What are you trying to eliminate?

It then connects these questions to the problems the startup’s founders seek to solve by rephrasing those questions;

What do you want that you don’t have? You should be trying to achieve this.
What do you already have that you already have? You should preserve this.
What do you lack that you don’t want? Avoid this.
What do you have now that you do not want? Eliminate this as quickly as possible.

The analyses can be performed using the grid below.

The Goals Grid by Fred Nickols. Image Credit: http://www.advocus.co.uk

Some observations about the goals grid;

It is super flexible, and can be used at multiple levels in an organization. It can be used for corporate-wide strategic planning activities as well as team or individual-contributor level tactical planning.
The ease with which this analyses can be performed make it possible to unshackle the goals grid from our general notions of strategic planning cycles. There is nothing to prevent individuals or small teams within a startup from creating whatever cycle they need to create in order to use the goals grid to accomplish objectives, keep one another accountable. For example in certain circumstances it might make sense to have a monthly goals grid planning and update cycle. In another context perhaps quarterly cycles make more sense. Yet still, in some other context, perhaps weekly goals grid planning cycles make sense.
While they do not explicitly mention using the goals grid at Pandora, this case study published in the First Round Review shows how powerful a system analogous to this can become – The Product Prioritization System That Nabbed Pandora 70 Million Monthly Users with Just 40 Engineers.
If it is used, the goals grid should be applied to each component of a startup’s business model while it is in the search and discovery phase of its existence.

The “Do Not Fucking Do” Framework aka Asset/Customer Reuse Matrix:

Discussing Strategy at KEC Ventures with the founders and management of one of our startups in 2014.

Sometimes people who are unaccustomed to thinking about strategy can become paralysed by the volumes of information they have to consider during the process of developing a strategy for an organization; a startup, a company, a corporation, or a division of a corporation. Any kind of organization can use a form of this framework to narrow down its choices.

The vertical axis represents assets or ” degree of asset reusability” while the vertical axis represents customers or “degree of customer reusability”. In the diagram below I have used assets and customers respectively. One difference is that if I had labeled the axes “degree of asset reusability” and “degree of customer reusability” respectively then I would have also had to label them so that they go from “High” near the origin to “Low” as one moved farther from the origin along each axis.

Generally, activities in Quadrant 1 rely on assets that the startup already owns to create new products that the founders believe will be readily accepted and adopted by the startup’s customers. Activities in this quadrant are comparatively “easy” for the startup to execute. Activities in Quadrant 2 and Quadrant 4 are “easy” along only one axis of the decision matrix, they are “hard” or difficult along the other. In Quadrant 2 the startup has to find new customers, which is harder than selling to existing customers. However, it is relying on assets that it already owns, or can very easily obtain. In Quadrant 4 the startup is selling to its existing customers but it is using assets that it does not own, and cannot easily obtain.

Quadrant 3 is the “Do Not Fucking” do that shit region; in this region the startup is developing a product using assets that it does not own, nor can easily obtain, to sell to customers that it does not already have, nor can easily obtain. In this region the startup’s activities are hard along both dimensions of the decision matrix.

As the diagram illustrates the activities labelled A, B, C, and D should relatively easily be migrated from their respective originating quadrants once they are sufficiently mature. In the case of A & B, the new customers stick around long enough for the startup to develop a close and relatively durable bond with them. We can go through a similar thought process for C & D. The key is for startup founders to figure out how to quickly move A, B, C and D into Quadrant 1 as quickly as possible.

The activities labelled E pose a tougher challenge. Generally it is best to avoid them at all cost. Pursuing those activities places the startup at risk of material and substantial loss. Any decision to pursue them requires careful analysis of what it will take to conduct the R&D required to develop the product, as well as estimates of the costs that have to be incurred in order to create demand and win new customers for that product and for the startup. Sometimes its just a matter of timing, but at other times the issues at play are more complex, creating an opaque environment that makes it difficult to make such assessments, and often making it difficult to move those activities into one of the other three available quadrants. DNFD does not mean “don’t do that under any circumstance” but rather “you better have a really good reason for doing that” and so there are situations under which careful strategic analysis leads to one conclusion and one conclusion only . . . You better fucking do that or you’ll get killed. We’ll look at an example below.

The DNFD Strategy Framework - It is easiest to use existing assets to sell to existing customers. — The DNFD Strategy Framework – It is easiest to use existing assets to sell to existing customers.

Briefly: The DNFD Strategic Framework in Action

Should Apple produce a tablet? Assume you were assessing Apple’s strategic options soon after it became clear that the iPod/iPhone and iTunes/App Store were going to be wildly successful. How would you decide if it made sense to do more work determining if Apple should develop and market the iPad? Very quickly; first, people who buy iPods or iPhones are likely to want a tablet like the iPad for those activities they no longer enjoy engaging in on their laptop or desktop computers, and for which the customer experience on the iPod or the iPhone is unsatisfactory at best. Moreover, the organizational capabilities that Apple has acquired over the course of time as it has developed the iPod and iTunes, and then the iPhone and the App Store and brought those products to market are easily transferable to developing, producing, and marketing the iPad. ((Obviously more rigorous analysis would have been performed at Apple, but one can see how it makes sense to study this course of action very closely.))
Should Facebook create its own games? When Zynga announced that it was going to develop its own platform so that it did not depend solely on Facebook as a distribution channel for its games, some people might have immediately assumed that Facebook would rapidly start developing its own games to compete with its one-time partner turned rival, Zynga. The DNFD Framework would suggest that this is not so obvious, from the perspective of an outsider trying to assess the situation. However, one might have asked the following questions; Can Facebook easily reuse its accumulated organizational capabilities to publish games that go on to become immensely popular amongst Facebook’s users? If yes, would these games have a high degree of acceptance and adoption by Facebook’s users? Next, what trade-offs would Facebook have to make in order to start developing its own games? As you can see, these questions are not so straightforward? For example, even though Zynga’s games became immensely popular, one would have to ask how much, on average, of all user activity in a given year on Facebook was devoted by its users to Zynga’s games? Was it significant, noteworthy, or miniscule? As of this writing Facebook has not made any moves to become a publisher of games like Zynga. However, it bought Oculus Rift, a virtual reality device company – it is not yet clear what that means for the prospects of Facebook/Oculus entering the game publishing business. I would not hold my breath if I were you.
Should Facebook build its own data centers? It is late 2008 and youhave been asked to conduct an analysis on the subject: Facebook should build its own data centers; Yes or No? Your analysis will form the basis of the direction Facebook takes on this issue. What would your conclusion be?
- What is Facebook?
- What is Facebook’s business?
- Why should Facebook be concerned about building its own data centers? Think 5, 10, 15 years out.
- Who is the customer? What are the assets? Will the customer readily and willingly adopt the product?
- Can Facebook afford to fund the R&D and other costs associated with building its own data centers?
- What are the opportunity costs that Facebook will confront if it does this?
- What advantages will Facebook gain? What disadvantages will it face? Does one outweigh the other?

In What Format Should A Strategic Plan Be Maintained? The goal of strategic planning is to create a map that guides the actions of the people in an organization. Good strategy is inextricably linked to execution, and operations. It is management’s responsibility to ensure that strategy is understood to sufficient depth and detail, by everyone in an organization, within the context of the different roles and responsibilities that different people bear and fulfill.

A strategic plan should cover:

Product
- What features of the startup’s product are critical for this stage of the startup’s life cycle?
  - For example, what features should the minimum viable product include? What should it exclude? Why? ((The minimum viable product is the least expensive product that allows the startup to test the most important hypothesis on which its business model depends.))
- How is the startup going to identify its customers? Why do those customers buy the product? Why do those potential who do not buy the product make that choice? What will cause them to change their mind?
- What features does the product need to have if it is going to help the startup win its market?
- What does the landscape of features look like for competitive or substitute products within the startup’s market and Value Net, how should the product be positioned relative to that landscape? Why? What are the trade-offs resulting from those choices?
Finance
- How will the startup increase revenues?
- How will the startup reduce costs?
Operations – see related discussion in: Why Tech Startups Can Gain Competitive Advantage from Operations
- How will the startup get better at creating its products?
- How will the startup get better at delivering its products to its customers?
- How will the startup ensure that its operations infrastructure does not become obsolete?
- How will the startup ensure that its operations become a source of sustainable competitive advantage and differentiate it from its competitors, while protecting and enhancing its current chosen position in its Value Net?
- How will the startup ensure that its operations infrastructure do not lock it into a position that becomes competitively disadvantageous?
Growth
- How will the startup gain new customers?
- How will the startup strengthen its bonds with its existing customers?
- How will the startup win back customers it has lost?
- How will the startup expand into new markets?
- What adjacent markets should the startup consider entering? What risks will it face in doing so?
- What new geographic markets should the startup consider entering? Why? Why no?
- What does the startup need to do in terms of marketing, sales, advertising and public relations as those activities relate to the startup’s growth?
People
- What does the startup need to do in order to attract and retain the best people it can find to help it accomplish its stated goals and objectives?
- How should the startup develop the people on its existing team?
- How does the startup motivate its people, and empower them to accomplish things they previously did not know or believe they could accomplish?

When I have collaborated with others in creating strategic plans in the past those plans started out as notes in my notebook. Then they migrated to notes in a word processor, and finally to a presentation deck that management could use to guide organization-wide conversation about overall strategy, as well as brief summaries, explanations, examples and ideas to help managers communicate the message down the organization. However, the most important work started at the front-lines; studying customers, talking to be people directly doing the work that leads to the creation, delivery and fulfillment of the organization’s value proposition to its customers. That is where the real work of creating strategy occurs.

A strategic plan should be readily and easily accessible to everyone in the organization, and should be updated as frequently as is necessary to suit the startup’s goals and objectives.

Closing Notes

This blog post has covered a lot of ground, not all of which is applicable to every startup at this moment. However, even a startup that is made up of two engineers developing the early versions of a software product needs to make choices regarding what they should build. That startup needs a strategy.
Strategy should not become stagnant once it has been developed, it should evolve and adapt to the changing circumstances that a startup finds itself in.
In thinking of a how startup develops a competitive advantage I am thinking of of how it combines the resources that it controls which help it search for a repeatable, scalable, and profitable business model. These resources might be tangible or intangible.
A related issue is how the startup influences its external environment and the factors that influence competition such that those factors do not cause it harm.
A startup has a competitive advantage when it is implementing a strategy and a business model that cannot simultaneously be implemented by its current or potential competitors. It has a sustainable competitive advantage when its strategy and business model cannot simultaneously be implemented by current or potential competitors, and when those competitors cannot duplicate the benefits of that strategy and business model. ((Jay Barney, Firm Resources and Sustained Competitive Advantage. 1991, Journal of Management, Vol. 17, No. 1. Accessed online on Jun 23, 2015 at http://www3.uma.pt/filipejmsousa/ge/Barney,%201991.pdf))
The startup’s culture is an important source of competitive advantage, and ought to work in concert with its strategy. For example, employees of Facebook should “Move fast, and break things.” within the tenets of its strategy. When Andy Grove “Let chaos reign.” at Intel he did so within the parameters of Intel’s strategy. ((See for example; Jay B. Barney, Organizational Culture: Can It Be a Source of Sustained Competitive Advantage? The Academy of Management Review, 07/1986))

Further Reading: These notes are intended only as a starting point. Below some books that you should consider reading.

The Management Myth: Debunking Modern Business Philosophy – Argues, not unreasonably, that there’s no evidence that competitive advantage can be created in advance, and takes issue with Michael Porter’s ideas about competitive advantage. Personally, I am less interested in arguments between academics, and more interested in understanding how people who need to run a business can get better at day-to-day, and long-term execution. The key is to get better at making sensible trade-offs in the present, in order to increase the odds of success in the future. No one can predict the future. Anyone who makes such a claim is a liar.
The End of Competitive Advantage: How to Keep Your Strategy Moving as Fast as Your Business – Argues that Porter’s ideas lead to a dangerous complacency; eventually creating the inertia that ensures that entrenched incumbents get displaced by nimble upstarts. In other words competitive advantage is transient, not permanent.
Playing to Win: How Strategy Really Works – Practical examples of how to make strategic choices for people managing any kind of organization. Arms readers with a definition of strategy, the Strategy Choice Cascade, and the Strategic Structuring process.
Good Strategy Bad Strategy: The Difference and Why It Matters – Departs from other books on strategy by focusing on a range of fundamental issues that have received little attention. It deals more with the day to day issues strategists must confront, and less with the conceptual arguments about competitive advantage. I wish it existed in 2008/2009 when I needed to translate what I had been taught in business school with real-world scenarios with which I had to contend. Hindsight analysis is easy, developing a forward-looking strategic plan that will work is more difficult. This book focusses on helping illuminate how you can get better at the latter.
Good to Great: Why Some Companies Make the Leap…And Others Don’t & Built to Last: Successful Habits of Visionary Companies (Harper Business Essentials)
Small Giants: Companies That Choose to Be Great Instead of Big

Notes On Early Stage Technology Investing; Art, Science, or Both?

June 18, 2015 by Brian Laung Aoaeh

Conducting market research is an important part of the investment decision making process.

Often when I have asked other people this question I get a response that leaves me feeling dissatisfied. It seems most investors are compelled to take one side over the other, and, at least as far as the admittedly small sample of investors I have asked this question are concerned, insufficient thought is given to the notion that perhaps early stage investing has elements that make it like art in some respects but like science in others.

I am writing these notes on early stage technology investing in order to clarify my own thinking on the subject. ((Let me know if you feel I have failed to attribute something appropriately. Tell me how to fix the error, and I will do so. I regret any mistakes in quoting from my sources.)) Ideally, once I am done I should have a clearer understanding of how my process for arriving at “yes” or “no” decisions should work, in what context certain steps can be truncated or even eliminated altogether, and the risks I am exposing our fund’s limited partners and myself to by the choices I make during the period over which I study and analyse an early stage startup that is an investment prospect.

To ensure we are on the same page, and thinking about the issues from the same starting point . . . first, some definitions.

Definition #2: What is art?

The expression or application of human creative skill and imagination, typically in a visual form such as painting or sculpture, producing works to be appreciated primarily for their beauty or emotional power. ((http://www.oxforddictionaries.com/us/definition/american_english/art, acessed Jun 18th, 2015.))

In an article published in 2010, Marilina Maraviglia says:

This question pops up often, and with many answers. Many argue that art cannot be defined. We could go about this in several ways. Art is often considered the process or product of deliberately arranging elements in a way that appeals to the senses or emotions. It encompasses a diverse range of human activities, creations and ways of expression, including music, literature, film, sculpture and paintings. The meaning of art is explored in a branch of philosophy known as aesthetics. At least, that’s what Wikipedia claims.

Art is generally understood as any activity or product done by people with a communicative or aesthetic purpose – something that expresses an idea, an emotion or, more generally, a world view.

It is a component of culture, reflecting economic and social substrates in its design. It transmits ideas and values inherent in every culture across space and time. Its role changes through time, acquiring more of an aesthetic component here and a socio-educational function there. ((Marilina Maraviglia, What Do We Really Mean By Art? Accessed on Jun 18th, 2015 at http://www.smashingmagazine.com/2010/07/23/what-do-we-really-mean-by-art/))

Lastly, according to Tolstoy:

To evoke in oneself a feeling one has once experienced, and having evoked it in oneself, then, by means of movements, lines, colors, sounds, or forms expressed in words, so to transmit that feeling that others may experience the same feeling — this is the activity of art.

Art is a human activity consisting in this, that one man consciously, by means of certain external signs, hands on to others feelings he has lived through, and that other people are infected by these feelings and also experience them. ((Leo Tolstoy, Art and Sincereity. Accessed on Jun 18th, 2015 at http://denisdutton.com/tolstoy.htm))

I will attempt to extract a few key characteristics that I think qualify something as art on the basis of the preceding quotations. ((Adapted from: What is art? An Essay on 21st Century Art, Sylvia Hartmann. Accessed on Jun 18th at http://silviahartmann.com/art.php))

First, art is initially conceived or imagined entirely in the artist’s mind.

Second, the artist uses an artistic medium to transform what has been an intangible object in the artist’s mind into something tangible that other people can experience.

Third, art evokes a response from the people who experience it.

Finally, art is transformative in nature. Once experienced, art changes how we see and experience the world.

Definition #2: What is science? Conventional, and commonly held notions about what constitutes science often mistake and confuse the “pedagogy of science” with the “practice of science” . . . What does that mean precisely?

When we learn science we do so in a very formulaic manner. This makes sense, the first step in becoming a scientist is learning a sufficient amount of the body of knowledge that man has accumulated over time thanks to the work done by generations of scientists. The same is true for mathematics. That makes sense . . . Structure and process are important if the typical student of science is to make steady progress through the accumulated body of knowledge, until that student has built enough mastery of the subject to begin making new contributions to the knowledge we keep accumulating about the world. Out of necessity, the process of learning science adheres to the “scientific method” . . . It is linear, and simple, and provides structure for how one goes about mastering the accumulated knowledge of science. Generally, the process of teaching and learning science leaves little room for creativity. This leads many to develop and embrace the notion that the practice of science is an endeavor devoid of creativity. The way science is taught and learned also leads to the misconception that science is uniformly precise at every stage, and that it leads to conclusive answers to the questions that scientists investigate.

However, how one learns science is not the same as how one practices science. The following images attempt to illustrate that point.

Real Process of Science (1 of 3) . Image Credit: University of California Museum of Paleontology's Understanding Science — Real Process of Science (1 of 3). Image Credit: University of California Museum of Paleontology’s Understanding Science

Real Process of Science (2 of 3). Image Credit: University of California Museum of Paleontology's Understanding Science — Real Process of Science (2 of 3). Image Credit: University of California Museum of Paleontology’s Understanding Science

Real Process of Science (3 of 3). Image Credit: University of California Museum of Paleontology's Understanding Science — Real Process of Science (3 of 3). Image Credit: University of California Museum of Paleontology’s Understanding Science

In real-life, scientists:

Create knowledge using an iterative process in which new advancements are built on prior work, in relatively small, incremental steps. The process starts with ideas, beliefs, or guesses . . . conceived entirely in the scientist’s mind. Old knowledge is revised, and modified based on new discoveries made possible by advancements in technology.
Conduct research for which there’s no pre-determined outcome. For example, the evidence obtained from observation and experimentation might contradict the researcher’s best before-the-fact guesses and assumptions as well as established and accepted theory.
Always begin with an idea that can be tested through observation, experimentation, measurement, and analysis. Observation, experimentation, measurement, and analysis – together, these constitute the scientist’s medium.
Conduct experiments to test the ideas that they seek to investigate. The process of conducting experiments is the method by which they collect the necessary evidence that leads them to ultimately accept or reject the idea under investigation. To succeed at this they must be willing to reject conventional-wisdom, and scrutinize closely-held and cherished beliefs based on the evidence and observations of the experiments they perform.
Typically work in collaboration with other scientists, or scientists-in-training. For example, as an undergraduate mathematics and physics double major at Connecticut College, I spent three years assisting Prof. Arlan W. Mantz with research on the temperature dependence of molecular absorption line widths and shapes using tunable semiconductor diode lasers. The nature of scientific collaboration can be direct or indirect.
Often say that ” . . . further research needs to be conducted on this topic . . . ” This refrain seems to be a common feature of presentations in which scientists present their work. Yet, if one understands science as the pursuit of a deeper, nuanced, and increasingly sophisticated understanding of the laws that govern the natural world . . . That makes complete sense. Scientific research is ongoing in its search for better answers to questions that non-scientists might consider closed-to-debate.
Transform our understanding of the laws of nature, and in so doing change the relationship that we each have with the world around us.

I can’t find a substantive difference between what we stereotypically call “art” and that which we stereotypically call “science” . . . Can you?

Does science evoke a response from the people who experience it? Each time I use one of the many objects that has become part of modern life, I am filled with awe at what scientists have accomplished. I will grant that there is one difference between “art” and “science”; namely it is that art is related to notions of aesthetic beauty. Yet, one could argue that there is aesthetic beauty in science as well.

Consider the equation:

Let’s set dogma aside, for a moment; Can one argue objectively that this equation is not an aesthetically pleasing way to express the relationship that exists between the energy and the mass of an object?

What are the implications for me as an early stage investor, if “art” and “the practice of science” are more alike than they are different?

Here is a scientist’s code of conduct according to the University of California Museum of Paleontology: ((“Participants in science behave scientifically.” Understanding Science. University of California Museum of Paleontology. Accessed on Jun 18th, 2015 at http://undsci.berkeley.edu/article/0_0_0/whatisscience_09))

Pay attention to what other people have already done. Scientific knowledge is built cumulatively. If you want to discover exciting new things, you need to know what people have already discovered before you. This means that scientists study their fields extensively to understand the current state of knowledge.
Expose your ideas to testing. Strive to describe and perform the tests that might suggest you are wrong and/or allow others to do so. This may seem like shooting yourself in the foot but is critical to the progress of science. Science aims to accurately understand the world, and if ideas are protected from testing, it’s impossible to figure out if they are accurate or inaccurate!
Assimilate the evidence. Evidence is the ultimate arbiter of scientific ideas. Scientists are not free to ignore evidence. When faced with evidence contradicting his or her idea, a scientist may suspend judgment on that idea pending more tests, may revise or reject the idea, or may consider alternate ways to explain the evidence, but ultimately, scientific ideas are sustained by evidence and cannot be propped up if the evidence tears them down.
Openly communicate ideas and tests to others. Communication is important for many reasons. If a scientist keeps knowledge to her- or himself, others cannot build upon those ideas, double-check the work, or devise new ways to test the ideas.
Play fair: Act with scientific integrity. Hiding evidence, selectively reporting evidence, and faking data directly thwart science’s main goal — to construct accurate knowledge about the natural world. Hence, maintaining high standards of honesty, integrity, and objectivity is critical to science.

What are the risks I take if I cling to the notion that early stage investing is “all art” and “no science”? For one, I will not subject my own assumptions, hunches, guesses, biases, ideas, visions, opinions to the level of scrutiny to which they should be subjected. Worse yet, I might fail to subject other people’s ideas and assumptions to sufficient scrutiny and testing. Instead; I might rely on decision-making heuristics like “pattern-matching” and I might engage in “groupthink” or succumb to social-proof bias . . . I might fail to maintain a mind that is sufficiently open and flexible to recognise an early stage startup founder poised to transform the world because that founder does not fit my idea of what such a founder “looks like” . . . I might pass on a great startup investment for reasons that are completely irrelevant simply because I have failed to develop my own thinking and ideas about its prospects . . . I might fail to unlock promising new markets before the greatest returns have already been harvested by other early stage investors because I lacked enough curiosity and discipline to ask nuanced questions and challenge myself to acquire new knowledge and insights from other sources and other people – possibly people outside circles within which I am most comfortable . . . I might spend my career in early stage technology investing in a self-imposed exile to the land of piddling mediocrity.

Leonard Mlodinow on human thought and the evolution of science – podcast by Guardian ScienceWeekly #np #SoundCloud https://t.co/KjJRVOH8wO

— Brian Laung Aoaeh (@brianlaungaoaeh) June 19, 2015

I find none of those possible outcomes palatable; early stage investing is both an art and a science. The best early stage venture capitalists behave in keeping with that belief. It is their trade secret.

Science is Uncertain - Freeman Dyson — Science is Uncertain – Freeman Dyson

Further Reading

The Pleasure (and Necessity) of Finding Things Out

Flatiron School – Brooklyn, NY – February 18th, 2014

February 19, 2014 by Brian Laung Aoaeh

This is an outline of a presentation I gave to students at the Flatiron School in Brooklyn on Tuesday, February 18th 2014.

I talked a bit about my background, and about KEC Ventures. I will not outline that in this post. I discussed: How Software is Changing The World, or more generally How Technology is Changing The World. I decided to focus on Africa as a means of broadening our discussion.

Marc Andreessen’s August 2011 article in the WSJ: Why Software is Eating The World
- There are many more people online
- Technology is getting really good
  - Hardware costs are declining
  - Hardware is getting really good
  - Software tools are improving
- Examples of the dramatic impact that software has had on various industries
  - Retail: Borders, Bestbuy – Amazon
  - Movie Rentals: Blockbuster – Netflix
  - Games: EA, Nintendo – Rovio, Supercell, King
  - Transportation: Taxis, Car Rentals – Uber, Relayrides, ZipCar
It is important to remember that technology is more than just software
- Technology: The combination of tools, skills, methods, and knowledge to solve problems or accomplish an objective. Examples: fire, the wheel, domestication of animals, cultivation of food crops.
- Software: The stuff that makes a computer work; operating systems, utilities, applications.
- Think of: Opportunities to marry software engineering and hardware design. Examples: Canary.
How is Technology Changing Life in Africa?
- Africa is enormous – more than 50 countries, nearly 1 billion people, hundreds of different languages. However, the basic problems are the same across the continent. This map will give you an idea just how big Africa is.
- I like to tie almost every startup I study back to Maslow’s Hierarchy of Needs. Basically, I want to understand why people will buy a product or use a service. What will be the motivation? In the developing world there is an opportunity to solve problems across the entire height of the pyramid.
- One more important framework worth keeping in mind is Clayton Christensen’s Job To Be Done framework. I think it is worth studying. You’ll reach great insights about the products and services you develop if you can connect the dots between the Job To Be Done framework and Maslow’s Hierarchy of Needs.
African Startups
- Discussed
  - Brck – a back up generator for the internet.
  - mPawa – a job portal for blue collar labor.
  - 22Seven – a personal money management tool.
  - Dropifi – a lightweight CRM system for SMBs.
  - Karibu – a modular solar lamp.
  - iCow – a data service for small scale dairy farmers.
  - mFarm – a portal for farmers and produce buyers.
- Other examples:
  - 7 Innovative Products From Africa You Should Know About
  - 15 African Startups To Watch in 2014
  - There are many more working under the radar.
Building An Innovation Ecosystem
- It takes a lot of work to build the systems that support innovation, entrepreneurship, startups and venture capital. Some examples of organizations doing interesting work:
  - AfriLabs
  - MEST
  - VC4Africa
Q&A – what I can remember
- Are there examples of technology from the developing world coming across to the US or other developed markets?
  - Yes – people are testing tablets at $29.99 for possible use in the North American market. Dropifi has customers all over the world. There are other examples.
- How do we learn about opportunities in other parts of the world?
  - Connect with people online, through social networks – I co-authored a blog post for Tekedia with Chao Charity Mbogho. She’s a Ph.D candidate in computer science at the University of Cape Town. Our collaboration started with a retweet from someone I follow. I reached out to Chao with a question, and a short while later we had co-authored a blog post. Lots of tools exist to make collaboration with people in other parts of the world easy.
  - Partnering with people on the ground is important – they understand the local problems more completely than you will.
- What do you look for in the startups in which you invest?
  - I answered that question in this blog post: The Most Important Thing A VC Needs To Know About Your Startup
- What are some of the challenges African entrepreneurs face? Things can’t be easy for them.
  - Not at all. I hope I did not make it sound as if things are easy. Somehow they find ways around the obstacles they face. Here’s one story about a 17 year old girl from Kenya who taught herself to code and has now started a dev school in Nairobi. Here’s another about how an entrepreneur in Nigeria is solving the problem of not having enough people with coding skills.
- How easy is it for African women to get involved in the technology startup community? Is there a difference from the state of affairs in the US?
  - I’d be lying if I told you I can answer that question definitively. I know that in general, across the continent there are cultural barriers that still exist related to the education of girls. However I also know of several African women who are prominently leading the charge in the effort to build startups, and create an environment for startups to flourish in different parts of the continent. Some of the startups we discussed are founded by women.

Revisiting What I Know About Efficient Scale, Cost Advantages, & Early Stage Technology Startups

Notes on Strategy; Where Does Disruption Come From?

Industry Study: Nanotechnology

Notes on Strategy; For Early Stage Technology Startups

Alternate Title: What Can 24’s Jack Bauer Teach a Tech Startup Founder About Strategy?

Notes On Early Stage Technology Investing; Art, Science, or Both?

Flatiron School – Brooklyn, NY – February 18th, 2014

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Alternate Title: What Can 24’s Jack Bauer Teach a Tech Startup Founder About Strategy?

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