Category Archives: Startup general interest

Repitition is important to leadership because of cognitive bias

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Cognitive biases are a great tool for understanding human behaviour, particularly our more irrational behaviours, and although the meme is in danger of getting overdone I continue to find new value in the concept.

Today it is in the bias ‘cognitive ease’ and how it explains why repetition is important for leadership. Jack Welch, the legendary CEO of GE in the 1980s and 1990s is famously a big advocate of repeating key messages. In an interview with Alastair Campbell he said “You have to talk about vision constantly, basically to the point of gagging. There were times I talked about the company’s direction so many times in one day that I was completely sick of hearing it myself.”.

Aside from the observation that effective constant repetition is a rare talent (although learnable) the interesting question here is ‘why is it so important?’.

I had assumed that repetition works because it cements memories. The more times someone hears something the more likely they are to remember it and the more likely it is to subconsciously help with decision making.

I’m sure that’s true, but there’s something else too, and that is the concept of ‘cognitive ease’. We are drawn towards and believe more in things that are more familiar because they are less taxing on the mind. Conversely we shy away from that which is hard to understand.

Strategies which are constantly repeated become more familiar and hence more believed and accepted.

From survival to excellence

By | Startup general interest | One Comment

Much of this week I’ve been thinking about how the life of successful startups falls into two phases: survival and excellence.

In the early life of a company success is all about getting to the next milestone. The team is small, everybody has to turn their hands to multiple tasks, cash is short,  and time is short. In this environment survival is the name of the game. There’s no time to build systems or perfect process, rather everything should be done so that it’s good enough. For sure there should be half an eye on the future and ‘good enough’ means ‘good enough for now’ and ‘won’t cause us problems down the line’, but the emphasis is very much on getting things done.

When Reid Hoffman advises that if the first version of your product isn’t embarrassing you’ve shipped too late, he’s making this point.

When Paul Graham and YC say ‘do things that don’t scale’ they’re making this point.

When Eric Reis talks about minimum viable products he’s making this point.

However, when companies go from being early stage to growth stage then the emphasis changes. The team is bigger, there are specialists for every task, there’s more cash, and whilst speed is still critical the constant need to get stuff done fast to avoid failing has passed. The challenges now are to keep growing really fast and maybe (hopefully) to start making progress towards profitability. In this environment excellence is the name of the game. Success becomes about getting all the little things right and at scale that requires great systems and processes.

The transition from survival to excellence doesn’t happen overnight, but happens piece by piece across the company. For most companies it starts somewhere between the seed round and the Series A and then never really finishes, at least not for the very best businesses.

Update on Clayton Christensen’s theory of disruption

By | Startup general interest | One Comment

Clayton Christensen’s book The Innovators Dilemma, originally published in 1997, changed my understanding of innovation, the evolution of value chains and gave me a theory of disruption that has served me very well over the years. His theory of disruption states that large companies are most often disrupted by small competitors who release products which are cheaper and initially inferior but good enough to take the low end of the market, after which quality improves to the point where they take the whole market. Incumbents initially ignore the threat because they are happy to cede the low end of the market and because they make the mistake of thinking that inferior products can ever be a threat.

For startups the beauty of this theory is the simple instruction: targeting the low end of the market with a much cheaper product is a winning strategy. Successes with this strategy over the year have been numerous – Skype, MySQL (and nearly every open source company), and Salesforce spring to mind.

So when I saw that Vivek Wadwha had written a post titled Tech successes are disrupting disruption theory I clicked straight through.

His argument is that disruption no longer starts at the low end of the market. He cites Tesla and Uber as examples of a disruptive business that started at the high end and worked down and he makes the bigger point that for many incumbents the threat is not so much from startups attacking the low end as from other industries. Apple is disrupting the entertainment business, Uber’s UberEats and UberFresh are disrupting the takeaway food and grocery markets, and Tesla’s PowerWall battery technology will disrupt the home energy market. Meanwhile Google and Apple are both moving into healthcare and payments.

Wadwha is right. I’m still holding onto the idea that disrupting from the low end is a great strategy, but the key point for startups is that exponential improvements in technology are creating opportunities for 10x better products at the high end as well. Our portfolio companies Spoke (great fitting mens clothes) and Lost My Name (amazing personalised children’s books) are good examples.

The modern management mindset

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I’m a keen follower of Steve Denning and his writing on strategy, leadership and the future of work. He writes in what might be described as ‘strategy speak’ and is rarely a quick read, but there’s a lot of insight in his words for those that take the time to look for it.

In a post earlier this month he wrote a list of ‘common characteristics of the modern management mindset’ which emerged from a study by the Learning Consortium for the Creative Economy:

  • Goals, attitudes and values that focus on added value and innovation for customers and users, rather than a preoccupation with short-term profits.
  • Managers seeing themselves, and acting, as enablers, rather than controllers, so as to draw on the full talents and capacities of knowledge workers.
  • The use of autonomous teams and networks of teams, in some cases operating at large scale with complex and mission-critical tasks.
  • The coordination of work through structured, iterative, customer-focused practices, rather than bureaucracy.
  • Embodying on a daily basis the values of transparency and continuous improvement of products, services and work methods.
  • Communications that are open and conversational, rather than top-down and hierarchical.

For many of you there won’t be anything new in this list, but it’s power comes in having all these characteristics in one place. I like that it eschews buzz words in favour of easily understandable plain English.  Would be modern firms who look at  their practices and compare it with this list will have little doubt how they are getting on.

I also like that this list explains why mission driven businesses often enjoy a lot of success – they score highly on the first bullet about goals and values. Companies like Google, Facebook and more recently (and at a smaller scale) Transferwise here in the UK, or a number o companies in our portfolio, including Unbound and Big Health have missions which are focused on doing something for important customers. Big Health, for example, wants to make billions of people healthier without pills or potions.

The internet shrinks industries – auto is next up

By | Startup general interest | 4 Comments

This morning I was talking with an investor in our fund about how when the internet disrupts industries it often makes them smaller and, from the perspective of incumbents, less attractive. Amazon is doing that to much of retail, MySQL and other open source companies have done it to large swathes of the software industries, Craigslist did it the classifieds industry, and I could go on.

Two forces typically combine – automation takes out cost and the internet is used to displace middlemen – allowing new entrants to offer a radically cheaper product which incumbents don’t want to compete with because it means shrinking their companies. The new product typically starts out inferior in some way allowing incumbents to dismiss it as a competitive threat, but then it gets better and incumbents notice too to mount an adequate response. This is disruption in the Clayton Christensen sense that the word should be used.

Something similar is about to happen to the auto industry.

Autonomous cars will be

  • smaller because they don’t need the padding to protect passengers (look at the latest Google cars)
  • simpler electronic drive systems
  • shared more and/or sold direct

This will put massive downward pressure on car sales, both in volume and $ terms. Smaller is cheaper to produce, simpler is cheaper to produce, shared means fewer cars are sold, sold direct means dealer margins get passed onto the consumer.

What’s interesting now, and this was the main point of our conversation this morning, is that smart execs at incumbents know this future is coming and that it poses an existential threat to their businesses, but are struggling to find a good path forward. Execs at Mercedes, BMW, Ford, GM etc have all read Christensen and I would bet my house they have people shouting at them to wake up, but it’s super hard for them to respond to what is no less than an existential threat. That’s partly because they don’t have the data and software capabilities to succeed in this future and partly because the bulk of management and shareholders have become adept at finding reasons for not embracing strategies which would shrink their revenues, profits, teams and returns for shareholders.

Parallels between data science and traditional scientific observation

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Reading The Art of Observation and Why Genius Lies in the Selection of What Is Worth Observing on brainpickings (which seems to be the source of much inspiration for me at the moment) I was struck by the parallels between what data scientists do at tech companies and the traditional scientific observation.

Hence these descriptions of scientific observation are relevant for data scientists and their managers.

  1. There are two types of observations – (a) spontaneous or passive observations which are unexpected; and (b) induced or active observations which are deliberately sought, usually on account of an hypothesis
  2. One cannot observe everything closely, therefore one must discriminate and try to select the significant.
  3. Most of the knowledge and much of the genius of the research worker lie behind his selection of what is worth observing. It is a crucial choice, often determining the success or failure of months of work, often differentiating the brilliant discoverer from the … plodder. [NB – track the right metrics]
  4. Powers of observation can be developed by cultivating the habit of watching things with an active, enquiring mind. It is no exaggeration to say that well developed habits of observation are more important in research than large accumulations of academic learning.
  5. Effective scientific observation also requires a good background, for only by being familiar with the usual can we notice something as being unusual or unexplained. [NB – know your benchmarks]


Each compute platform is 10x its predecessor – what’s next?

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Benedict Evans of A16Z used this chart to illustrate his point that each new compute platform brings a step change in scale when compared with its predecessor. Smartphones will soon be 10x PCs, PCs were a step in scale up from mini-computers and mini-computers were a step in scale up from mainframes. In the title to this post I used 10x to describe all the changes because I think that’s approximately right and implied by Benedict’s post, but I don’t have data.

The other thing to note is that the time between each of these platforms hitting scale is falling. Mainframes came to prominence in the 1950s, mini-computers hit their stride in the 1970s, PCs were in the 1990s and smartphones were in the 2000s.

If this pattern is to be extended the next compute platform will soon be upon us.

Which leads to the question: what will the next platform be?

The only thing I can conceive of which could evolve into a compute platform with 10x more nodes than smartphones is a meshed compute network which distributes computing into the fabric of life – our watches, our white goods, our bedroom alarm clocks, as well as our thermostats, alarm systems and everything else. To me that sounds about as fanciful as an iPhone 6s would have at the peak of the PC era 15 years ago.

This vision of the future points to early investment opportunities in point products – e.g. thermostats and watches – and then into closed ecosystems, and the into infrastructure that builds an open ecosystem before a new generation of apps emerges.

As I write these words it feels highly likely to me that this sequence of events will occur, with the primary short term benefit being that we are saved from carrying computers with us the whole time. Maybe the odd inter-generational tech question my grandkids will ask my kids (their parents) will be “what, you used to carry computers with you?”.

Startup ups and downs – Friday fun

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relative joy of entrepreneurship

I’ve seen lots of diagrams over the years that depict the ups and downs of startup life, but this is the best.

It’s from a post by Scott Belsky, and as he says the ups and downs are inevitable. The only thing to hope for is that the best fit line has a positive gradient.

He also wrote:

The science of business is the things that scale, the art of business is the things that don’t.

I love that too. A large part of what we’re doing at Forward Partners is building processes to make the ‘art’ piece of starting a company more reliably successful. We often describe that as ‘bringing science to the art of building a company’, but I’m now thinking that an analogy with learning how to create art might be more appropriate. Just as there are techniques which enable skilled artists to more reliably create great drawings/paintings/music/movies etc. so there are techniques which enable great entrepreneurs to more reliably create great companies.

Two areas of opportunity in ecommerce

By | Ecommerce, Forward Partners, Startup general interest | No Comments

Kara Nortman of Upfront Ventures has just published an interesting and well grounded post on the future of ecommerce which got me thinking about where we see opportunities. I think there are two broad areas (Kara lists four, but I merged her four into two).

Brandtech – new brands that change stodgy industries

Simplified formula for success:

  1. target a large and valuable segment with poor product or unsustainably high margins
  2. deliver a great product and brand

As Kara notes this formula has played out well for numerous companies, including Warby Parker, Transferwise,, Just Eat and many others, but there are still many verticals with space for innovation, including food, soft home goods, furniture, toys, and educational products.

Forward Partners investments in this area include Lost My Name, Spoke, Zopa, Wool and the Gang, and Makers Academy.

Modern merchandising – new services that revolutionise how we shop

Simplified formula for success:

  1. target a large and valuable segment with a poor customer experience
  2. deliver a wow customer experience

This formula has also played out well for numerous companies, including Netflix/Lovefilm back in the DVD days, MoneySupermarket,, Uber, and many others. Once again there are other verticals that are still ripe for disruption, including many of the ones listed as open under Brandtech.

Forward Partners investments in this area include, Top10, Appear Here, Edge Retreats, Snaptrip, Live Better With, and The Gifting Company.

There’s obviously a lot more to building a business than the two simple steps I’ve listed hut the themes of great and/or radically cheaper product and radically better customer experience are big ones for Forward Partners.


Musing on inevitability, timing, and use cases

By | Startup general interest | No Comments

I’m at the Web Summit in Dublin this week and attended two interesting talks today. One was an interview with Palmer Luckey, founder of Oculus VR and the other a panel with Rana el Kaliouby, founder of Affectiva and Ebbe Altberg, CEO of Linden Labs (creator of Second Life).

All three of these people have an incredibly high level of conviction that the technologies they are working on will become become ubiquitous. Luckey believes that virtual reality will, for many use cases, be superior to what the physical world can offer and when the price and quality are right we will all carry a virtual device. Kaliouby believes that when our devices can sense our emotions they will be able to serve us better so we will all choose to let them read our feelings via the camera. Altberg believes that virtual worlds will allow people to meet, maintain relationships and be more productive than the physical world and that when they get easy and cheap enough to use we will all flock to them.

I think there’s a very good chance that all three of them are right.

But it’s hard to say when.

As I’ve written before being too early to a market is as bad as being too late, and that generally the idea of first mover advantage is a chimera.

There are two strategies investors can employ in these situations.

The first is to back the early visionary in a space with large rounds to solve the technical problems and create the market. That is the ballsy and arguably most exciting play. Occulus was that play in virtual reality. Makerbot was that play in consumer 3D printing. Fitbit was that play in wearables. Affectiva may be that play in emotionally aware computing.

The second strategy is to wait until the use cases become clear and back companies solving clear customer problems. This approach is more conservative but, I believe, ultimately more rewarding for both entrepreneurs and investors. Most of the biggest startup successes have followed this route and the odds of success more generally are higher. Facebook came after Myspace and others had established the social networking use case. There were many search engines before Google. Oracle was not the first database company. The same is true of the hundreds if not thousands of companies that have gone on to achieve exits in the hundreds of millions.

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