Nic Brisbourne's view from London on technology and startups

Sustainable engineering – avoid big re-writes

By | Forward Partners | 3 Comments

Last week friend of Forward Partners Douglas Squirrel published a post about Sustainable engineering on The Path Forward in which he advises founders on how to scale their engineering effort. When the focus is on validating the idea and building first versions of the product it usually makes sense to take shortcuts in code and process quality to accelerate learning, but when the focus shifts to scaling the company it’s important to shift to scalable and sustainable software development practices.

Squirrel’s advice is to eschew ‘big bang’ changes such as re-writing in a new language or framework in favour of incremental changes using techniques like ‘inline’ refactorings and ‘spike stories’. ‘Big bang’ changes nearly always come in late, over budget, and under specification whilst incremental techniques have lower risk and keep the feature set moving forward. Interestingly given he’s an experienced startup CTO himself, Squirrel says to be wary of the advice of developers who “always want to re-write everything”.

If you are in this situation, or think that you might be I highly recommend you read the full post.

Our plan is that more and more authors like Squirrel will become Pathfinders and contribute to The Path Forward. Squirrel is actually our second Pathfinder, the first was Matt Buckland, who used to work here but is now Head of Talent at Lyst. He wrote a about How to read a CV and we have more articles from him coming in the near future.

If you would like to become a Pathfinder let me know via the comments or otherwise reach out.

Transport for London’s ‘Private hire proposals’ make me mad

By | Announcement | One Comment


Many of you will have seen this already, but Transport for London’s ‘Private hire proposals’ are so loaded in favour of protected interests and against consumer choice that I’m cross enough to have a moan here. Hopefully this post will make a small contribution to the debate and increase the chances of a sensible outcome.

There are 25 proposals in total. The five below seem to do nothing for the consumer and are only explainable as an attempt to make Uber less attractive. If they go through 10m+ Londoners will have less choice, wait longer for their cabs and probably pay higher prices so that a small number of taxi drivers can be better off.

How can that be right?

  1. Operators “must provide booking confirmation details to the passenger at least five minutes prior to the journey” – should be a matter of consumer choice, and who wants this when you can have a car in 2-3 minutes?
  2. Companies “must not show vehicles being available for immediate hire either visibly or virtually via an app” – hard to see how this hurts anybody, and again should be a matter of consumer choice
  3. Operators “must offer a facility to pre-book up to seven days in advance” – consumers should be able to decide whether they value seven day advance bookings 
  4. Drivers may only work for one operator at a time – doesn’t seem very fair on drivers to restrict their employment options
  5. There should be “controls on ridesharing in public vehicles” – targets UberPool, a ridesharing service

This list is taken from an article on the

Bill Gurley’s insights into the future of ecommerce – know your customer and personalise

By | Startup general interest | One Comment

A Fireside Chat with Bill Gurley of Benchmark: The Future of Ecommerce — September 15, 2015 from Sailthru on Vimeo.

Gil Dibner recommended this video with Bill Gurley in a recent post about the five forces of venture capital. It’s 50 minutes and I very rarely watch videos this long (the opportunity cost is too high), but I’ve been consistently blown away by Bill’s insights on his blog and decided to at least start this one. That was a good decision because I stuck with it to the end.

If you’ve got the time and you’re interested in ecommerce I highly recommend watching it yourself.

If not these were the points that stood out for me:

  • Google is vulnerable to Amazon because Amazon has become the first place people search for products. Bill calls this ‘funnel reversal’. Google used to be at the top of the funnel, but Amazon has now taken that place for ecommerce searches. That’s significant because the top of the funnel is the most valuable place to be.
  • Future ecommerce opportunities are in areas where the customer experience can be so radically better that people similarly go around Google. Amazon Prime is a night and day better experience than starting on Google. Creating new experiences like that going forward requires a deep understanding of the customer. That experience can manifest itself in product customisation (Bill gave the example of Warby Parker, Spoke and Lost My Name are good examples from our portfolio) or in amazing services (Bill gave Uber as an example, Thread is a good example from our portfolio). He noted that Uber has succeeded in going round Google to the extent that the search term ‘limousine’ is tracking at 20% of it’s peak seven years ago (probably for San Francisco searches).
  • One key to understanding customers is what Bill calls ‘money balling’, i.e. knowing everything that every customer does in your business, running the deep analytics and employing data science to draw insights.
  • Customer retention is where a lot of companies could do better. Many businesses are great at acquiring customers, but leave money on the table when it comes to keeping them. This comes back to knowing your customer.
  • Anxiety relief – humans will love it when you take anxiety away, and offering anxiety relief is a key benefit that ecommerce companies can offer. When we order from Amazon anxiety is minimal because we have a very high degree of trust that the price will be fair and the delivery will arrive on schedule.
  • He mentioned a couple of times that Google playing is playing defence in important areas and that large companies are much stronger when they play offence. There’s a growing number of smart people who are concerned about Google’s prospects.

Old European brands aren’t cool anymore

By | Startup general interest | No Comments

Screen Shot 2015-09-29 at 16.10.55

This is Coolbrands 2015 list of the top brands, chosen by a panel of experts and 2,500 members of the British public. They don’t disclose the weighting.

What’s striking about this list is the prevalence of new(ish) digital brands and relative absence of classic brands, particularly big fashion houses. It really is out with the old and in with the new. I make it seven tech brands and, being generous, five classic brands (Ray Ban, Alexander McQueen, Chanel, Aston Martin, and Liberty). Sony, Bose, Rolex, Dom Perginon, and Selfridges all fell out of the list.

There’s also a shift towards US brands. Apple has been top for four years in a row now.

Looking at the types of brands that are doing well I’m struck by the extent they are rooted in great product. I like to say that the essence of a strong brand is a good promise delivered and companies like Apple, Instagram, YouTube and Spotify all deliver in spades. That contrasts with some of the brands that are falling off this list which are rooted in prestige.

Ad-blockers and product quality

By | Advertising, Startup general interest | One Comment

The rights and wrongs of ad-blockers have been debated for years. My view is that people who block ads are choosing to free-ride on users who don’t, and whilst I would stop short of calling it immoral, I don’t think it’s good behaviour. However, the number of people blocking ads has always been relatively small and the subject has mostly been of academic interest. The interesting thing now is that post iOS 9 that might change.

Three forces are at play here:

  • The trend to mobile – smaller screens and slower connections make ads more intrusive
  • Growth in support for the the anti-ad/pro-privacy meme
  • It’s getting easier for users to block ads

The Apple vs Google battle is an important part of the backstory. As Jason Calacanis details here, Apple’s assault on ads and its pro-privacy position helps in the iPhone vs Android battle and is a direct attack on the core of Google’s business.

Also important is that the online advertising industry still hasn’t got it’s act together. Ten years ago I was hopeful that the adtech was on a trend to become more about product, less about relationships and in the process would shed a lot of it’s shadier practices. That manifestly hasn’t happened and we still have an over-complicated landscape characterised by opaque relationships and misaligned incentives that doesn’t serve advertisers as well as it could.

Meanwhile larger advertisers have been moving an increasing percentage of their budgets online (they have to go where the audience is) which is crowding out startups.

It’s still early days for iOS 9 ad-blockers, but it seems likely we will see an acceleration of the trend of startup founders focusing on product quality as a way of rising above this mess. Since the advent of social media native advertising, earned media, and customer referrals have been growing in importance as part of the startup advertising mix and they work best for high quality products.

Moreover, the products that really win in this environment aren’t simply of high quality, they are also noteworthy, delivering moments of ‘wow’ that stick in the mind.

The mindset of a good investor

By | Uncategorized, Venture Capital | One Comment

There were two articles on my Twitter list today about the mindset of good investors. The first was a Techrunch article explicitly about bias in VC decision making. They identified six cognitive biases investors suffer from (similarity bias, local bias, anchoring, information overload, and gender bias) and offer some tips for making bias free decisions. I’m fascinated by cognitive bias because by definition it’s hard to weed out, and reading the Techcrunch article this morning I wondered if that fascination is rooted in a subconscious desire to keep working on myself to be a better investor.

Stepping up a level, the conclusion I’ve come to over the years is that the key to avoiding bias and making good investment decisions is total objectivity. No emotions, thorough analysis, and clearly understood reasons.

The tips in the Techcrunch article are in fact all tactics for keeping discipline in these three areas. Documenting decision making processes, establishing and constantly refining investment criteria, and following principles are all ways of taking the emotion out, making sure the analysis is thorough and the reasons understood.

I haven’t thought of it in this way before but a number of the things we do at Forward Partners serve to bring thoroughness and clarity to our investment analysis. The most important are clearly understood deal criteria (top of the list: every deal must have the potential to return the fund), standard format investment papers, and a culture of open debate and shared ownership of deals.

The second article was an Economist review of Superforecasting: The Art and Science of Prediction. By Philip Tetlock and Dan Gardner, which details the characteristics of people who are good at predicting the future. They drew on a contest run by American spies in the wake of the Iraq debacle:

Begun in 2011, it posed hundreds of geopolitical questions (“Will Saudi Arabia agree to OPEC production cuts in November 2014?” for instance) to thousands of volunteer participants. A small number of forecasters began to pull clear of the pack: the titular “superforecasters”. Their performance was consistently impressive. With nothing more than an internet connection and their own brains, they consistently beat everything from financial markets to trained intelligence analysts with access to top-secret information.

Tetlock analysed the superforecasters and found they shared the following characteristics:

  • clever, but “by no means geniuses”
  • they viewed the world as complex, requiring different approaches to understand different areas (no simple rules or models)
  • comfortable with numbers and statistical concepts like regression to the mean, but not statisticians
  • hungry for information
  • willing to revisit predictions in light of new data
  • able to synthesise material from sources with very different outlooks on the world
  • self aware and reflective
  • willing to learn from their mistakes
  • more interested in why they are right or wrong than whether they are right

All of these traits are learnable and for the investors amongst you this is a good checklist of things to be doing and/or to work on. Investing, after all, is about predicting the future.

More data showing traditional TV viewing dropping fast

By | TV | One Comment

It’s premiere week this week in the US when the new season of TV kicks off and the news is that in key age groups far fewer people are watching (Nielsen data from Ad Age):

  • Number of adults age 18-49 watching dropped by 8%
  • Number of adults age 18-24 watching dropped by 18%

The fact that younger viewers are dropping TV faster than older viewers suggests the decline in TV viewing will accelerate. And it doesn’t take many years of 8-18% declines before there’s nothing left.

The big beneficiaries so far are of course internet and mobile streaming services YouTube, Netflix and HBO Go (the latter is now 2015s top grossing app). That’s old news though. What’s more interesting is where the next opportunities are coming, and with changes of this magnitude to an industry the size of TV there will others.

The one we’ve been thinking about recently is video and commerce. YouTube is on an amazing run and has spawned a whole ecosystem around YouTube stars, but making money on the platform is difficult and commerce isn’t well enabled. It looks like there’s space for something better.

Consistency of thought – vice or virtue?

By | Startup general interest | No Comments

Marc Andreessen once said:

Ask yourself, would you rather be right or successful? That needs to be top of mind at all times because times change and we change. You want strong views weakly held.

And I just read the following advice from Jeff Bezos:

He said people who were right a lot of the time were people who often changed their minds. He doesn’t think consistency of thought is a particularly positive trait. It’s perfectly healthy — encouraged, even — to have an idea tomorrow that contradicted your idea today.

These opinions are striking because they are counter-intuitive and backed up by strong supporting logic.

But are they right?

For me the answer is yes, provided they are used sensibly.

Consistency is important to other people in your life. If they don’t know where you stand on stuff it makes it hard for them to go about their business. If a CEO changes the company strategy too frequently his company will soon be a mess. Moreover, people who change opinion too often lose credibility with their peers.

As a sidebar, it’s interesting that Andreessen stresses that views should be ‘strong’. I imagine that’s because the views and opinions are important because they influence other people, and that other people take strong views more seriously than weak views. There’s a certain paradox here though, which is that one of the reasons people take strong views seriously is because they assume strong views won’t change.

So consistency has it’s place and Andreessen and Bezos shouldn’t be taken too literally. That said, it’s destructive to hold onto wrong views just because we held them before. Bad decisions will result, along with spurious justifications that will undermine our credibility. Moreover, our brains are hard-wired to be consistent and a string of cognitive biases make it hard for us to recognise when we are wrong – e.g. confirmation bias.

As with everything in life the answer is to find the right balance (I find myself saying this so often now it’s starting to get boring….). I think Andreessen and Bezos are saying these things and others, myself included, are remarking on them because most people err too much on the side of consistency and don’t get the balance in the right place. This balance is particularly hard to strike because our unconscious brains are at work pushing us to be consistent. Part of the answer is to make sure our opinions are well thought through, and the other part is to keep the antennae highly tuned for signs we are wrong.

When planning and modelling the process is more valuable than the answer

By | Startup general interest, Uncategorized | No Comments

This morning I was reading from the OSF Playbook about how they have built an ‘open source decision making model’ for investing in deep science startups. That’s a worthy endeavour, but what stood out for me is this quote:

we gained the most insight from the process of building the model, not from an absolute output number

There are two interesting things about this.

Firstly, building a model is the much more valuable than using somebody else’s. If the folks at OSF got value from the process not the answer then anyone who plugs in their own assumptions to the model and gets their own answer will be missing out on the most important insights.

Secondly, it’s also true that when startups build financial models they learn more from the process than from the numbers that come out at the end. A model can be tuned to give any answer its author wants and founders often question why investors want to see them. Here we have the answer – investors value the process of creating the model rather than the output number (although seeing the level of ambition in a startup is important).

In more detail, the value in building financial models mostly comes from being explicit about key assumptions. What are gross margins today and how will they evolve? Same for customer acquisition costs, salesforce effectiveness, account management costs and customer service costs. Eyeballing these assumptions gives a detailed understanding of how the business is expected to evolve and where the risk points are.

In labour marketplaces algorithms might be better for workers than regulation

By | Startup general interest | One Comment

Tim O’Reilly just wrote a great post suggesting that in labour marketplaces, like the one Uber operates, algorithms might offer a better deal to workers than regulation. It’s a complex argument and Tim’s long post is well worth a read if you have the time. For those of you in the mood for a summary the centrepiece of his argument is that Uber allows market forces to determine prices and allows individual drivers to determine when and where they work. Those two features combined result in a more efficient system that works out much better for drivers (and everyone else) than it would if regulators force them to make their drivers employees. As Tim notes, top down micro-management of low cost work-forces to match supply and demand have been ‘a disaster for workers’. Think Walmart or McDonalds.

There are a couple of other factors at play here too. Firstly Uber has expanded the market – people take more cabs because it’s cars are reliably available at short notice. Secondly Uber drivers are in charge of their own lives in a way that salaried employees never are. Uber drivers decide when to work, and where to work. Moreover, Uber’s surge pricing helps them with that decision. As Dan Pink highlighted autonomy is a major driver of job satisfaction.

Nothing is wholly good or wholly bad and there is, of course, a flip side to this. Uber’s algorithm sometimes causes problems, including one case of gouging passengers during a crisis, and overly aggressive behaviour from Uber execs certainly makes one pause for thought, but these seem more like problems that can be ironed out than flaws in the model.

Stepping up a level, ‘Algorithms beat regulation’ is a very radical idea and Tim’s article is a call for academics and policy makers to start thinking about it seriously.

Superficially it sounds to me like it could work and therefore merits investigation. One of the most obvious challenges is that labour marketplaces have huge economies of scale and could end up as natural monopolies, requiring a whole new set of interventions from the regulator. Another obvious challenge is to understand whether the Uber model works in the same way outside of taxis.

In the short term, if it is true that labour marketplaces can offer a better deal for both workers and customers then we should expect the model to become much more prevalent. It’s interesting that despite massive investment in the sector not many of the other labour marketplaces has taken off like Uber has, and there are rumours that a couple of the larger ones are struggling to make their unit economics work. A thorough strategy piece analysing the different players and their models would be a very interesting read.

If this topic interests you check out Azeem Azhar’s email newsletter The Exponential View. It’s where I saw the link to the O’Reilly article.

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