Nic Brisbourne's view from London on technology and startups

Think of your company as an organism

By | Startup general interest | No Comments

When I started work in the mid 1990s enlightened companies had moved from hierarchical command and control structures to a more empowered model for the enterprise, and more and more companies were headed in that direction. Then, in 2003 Lou Gerstner, former CEO of the famously hierarchical IBM, published Who says elephant’s can’t dance?, the story of how he revitalised the company by delegating power to employees, and we all knew the revolution was complete.

But now the wheel has turned again.

 

The hierarchical model broke down under two forces:

  1. The pace of change increased and nimble companies that didn’t have to go back to the centre for instructions started winning
  2. Something about late stage capitalism meant more and more employees wanted autonomy rather than to follow orders – particularly the more capable ones

These trends have continued apace and we’re reaching the point where the empowered enterprise model of setting a vision, building consensus, and managing by objectives is breaking down. The pace of change is such that even 1-2 year articulations of the company vision needs to change frequently and best people now want to be co-creators at every level of the company. We are now moving from the empowering employees to putting them in control.

Wolff Oins just published a report into management attitudes which captures this shift brilliantly:

  • The Premise of the organisation shifts from Motivation and delegation to focus and liberation
  • The underlying belief shifts from workers are willing and best motivated by a vision and rewarded with a career to workers are individualists who want to be their own leaders
  • The management style shifts from painting vision, building consensus and managing by objectives to suggesting purpose, designing culture and encouraging experimentation
  • The company shape shifts from network to ecosystem
  • The company spirit shifts from rational brain to organism

For me the notion of ‘company’ as ‘organism’ captures the modern firm brilliantly. Organisms can be directed, but they have a life of their own and are comprised of an ecosystem of cells, each of which has its own agenda. Organisms can do marvellous things, but they are messy and hard to control. That’s a much more accurate view of today’s companies, and especially today’s startups, than an orderly rational brain or a network.

Lessons for startup ecosystems from the history of Silicon Valley

By | Venture Capital | 5 Comments

I just read Nicolas Colin’s Brief History of the World (of Venture Capital). It’s a great romp through the history of entrepreneurial ventures and how they were financed – starting with loan deals brokered in coffee shops and ending with the PC boom which established venture capital as an asset class in 1970s and 1980s. The bit I liked the most described the role of Stanford in getting Silicon Valley going in the late 1950s. Provost Frederick Terman (who I hadn’t heard of before) went after large military research budgets as part of his mission to make Stanford a leading university in the sciences, and created a four pillar system that kicked off entrepreneurialism in the Bay Area:

  1. reach out to military prospective customers to better understand their needs, then offer to craft them a prototype in Stanford’s research laboratories—this generated substantial revenue for the university and strengthened its trusted relationship with key military figures;
  2. if the prototype satisfies the customer, encourage one of your students to found a company and manufacture the product at a larger scale—this inspired an entrepreneurial spirit among the students and contributed to stimulating their hard work in the university’s laboratories;
  3. make sure a member of the Stanford faculty (if not Terman himself) becomes a board member or consults with that newly founded company—this contributed to training Stanford scholars in business and turned them into better teachers and researchers;
  4. provide office space in the Stanford Technology Park, which was made possible by the fact that the university was the primary land owner in Palo Alto—this ensured that the upstart company stayed close and helped the nascent entrepreneurial ecosystem reach a higher density.

We can generalise this into a blueprint for ecosystems generally:

  1. Find a vertical market where there is a comparative advantage – Silicon Valley started with military technology, in London fintech and ecommerce are good candidates. We focus on ecommerce and marketplaces.
  2. Inspire entrepreneurialism – highlight the positive effects of startups and make ‘founder’ a popular career choice. The UK government’s support has been important for our startup ecosystem.
  3. Promote learning and knowledge sharing – startup ecosystems only work if old-timers pay it forward by sharing content, speaking at events and taking meetings with newer entrants.
  4. Encourage entrepreneurial density – business becomes more efficient and 2 and 3 above work best when startups congregate in the same place. Silicon Valley started in the small district of Palo Alto and the emergence of Tech City here in East London has been similarly important.

This is a ‘do the right things and the money will follow’ plan, which is a bit simplistic, but better that way round then pushing to much money out before the ecosystem is ready.

Forecasting in venture capital

By | Startup general interest, Uncategorized | One Comment

Good VCs need to be good forecasters. We need to predict which companies are going to succeed and second guess future trends so we can develop our firms to stay ahead of the curve. Deloitte have just published an interesting synopsis of Tetlock’s Superforecasting which gives us some insights into the types of people we need to recruit and the habits we need to cultivate to be good at the forecasting game.

The main and most surprising insight is that deep expertise doesn’t produce more accurate predictions. Tetlock ran prediction competitions over five years with multiple teams and found that the best predictions came from people with the following characteristics:

  • broad expertise
  • open minded
  • sceptical of deterministic theories
  • cautious in their forecasts
  • quick to adjust their ideas as events change
  • embrace complexity
  • comfortable with a sense of doubt
  • highly numerate (but don’t use sophisticated mathematical models)
  • reflective
  • learn from their mistakes

This is a good list for VCs too. One thing that stands out as a little different for me is that the best investors get behind big themes – e.g. the internet, open source software, SaaS, ecommerce, mobile, marketplaces – which feel a bit like the deterministic theories that super forecasters are sceptical of. However, even with these it’s important to keep an open mind and back off quickly if they aren’t playing out as planned. Mobile is a great example. As a category it’s yielded some amazing companies and investments, but many investors went too early and lost money – me included. I made my first mobile internet investment in 2000 in a business that was years ahead of it’s time helping banks to get their services on WAP phones. I’m not saying I’m a super forecaster, but I did learn from that and backed off from mobile until after the iPhone.

The other interesting point from Tetlock is that prediction skills can be improved by good sharing and debating within teams and by training focused on thinking in terms of probabilities and removing thinking biases.

 

 

 

 

Two types of intelligence and the current state of AI

By | Startup general interest | No Comments

paintings

These pictures were painted by a robot called Pix18. He or she (it doesn’t feel right) is a decommissioned factory robot trained to paint by picking up a paintbrush and painting on canvas. That’s pretty remarkable and shows how advanced AI is getting.

However, despite what we see here creativity is still largely beyond non human intelligence. Singularity Hub just published a great interview with Hod Lipson, professor of engineering at Columbia University and the director of Columbia’s Creative Machines Labs, who is pushing the next frontier of AI.  He posits that there are two types of intelligence:

  1. Convergent intelligence – Taking in large amounts of information and making a decision – e.g. whether to invest in a stock or pull out at a roundabout
  2. Divergent intelligence – Starting with an idea, or with a need, and then diverging to create many new ideas from it- e.g. designing a new robot different to anything we’ve seen before

You’ve probably guessed the punchline already. Machines are good, and increasingly better than humans, at convergent intelligence but not so good (yet) at divergent intelligence. That’s why we have automated trading and self driving cars, and will soon see robots flipping our burgers and slowly taking over all routine tasks, but still need humans to solve messy problems where there’s fuzziness around goals – e.g founding a company.

More interestingly Lipson contends that to crack divergent intelligence our AIs must become self-aware and reflective. That’s the key to the creative process. And once machines are self-aware and reflective they are arguably conscious. Some of them will certainly seem conscious.

The moment when we have divergently intelligent machines is perhaps the moment when the AI explosion occurs, with all of it’s massive potential upside, downside and uncertainty. I’m hugely excited by this future. If you are I recommend reading Hod Lipson interview in full.

Fundraising is a numbers game

By | Startup general interest, Uncategorized, Venture Capital | 5 Comments

These are Forward Partners dealflow stats for the first four months of 2016

  • 832 leads
  • 47 first meetings (6% of leads)
  • 8 second meetings (17% of first meetings)
  • 2 deals (25% of second meetings)

We met an additional 53 companies at FP Office Hours. In some ways they are like first meetings and they do sometimes lead to deals, but they are only 15 minutes long and many of them are speculative in nature so I excluded them from the analysis.

I imagine other investors have a similar leads:meetings:deals ratios and the headline here is that it’s only once you’ve got to a second meeting that there’s a reasonable chance of getting investment, and even at that point it’s only 25%. Getting a first meeting is an achievement in itself which often makes it feel like the prospects of getting investment are better than they are, but that feeling can lead to dangerous complacency. The numbers say you need four second meetings and as many as 24 first meetings to have a good chance of a deal.

Raising money is best thought of as selling equity in your business, and the fundraising process is a sales process. Unless you have strong relationships it’s a numbers game.

If you do have strong relationships then it’s about how strong they really are – e.g. if you know investors well enough that you are in effect coming in at second meeting level then you only need 4.

The smartest founders have a strategy for their fundraising and build a plan which they execute with discipline. They know who their targets are and which investor is their favourite, and they make sure they have enough names in their pipeline.

 

The consistency of Amazon’s revenue growth is amazing

By | Amazon | No Comments

Amazon just posted strong Q1 results and investors sent their share price up 11%. If you’ve been reading this blog for some time you will know I’m a huge admirer of the way Jeff Bezos has built his business. One of his mantras has been to re-invest profits to drive growth and the growth he has achieved is remarkable for it’s consistency over the last ten years. As you can see from the chart below Amazon has delivered on the proverbial hockey stick that startups put in their business plans, and they’ve done it at serious scale.

Screen Shot 2016-05-03 at 20.51.56

One unfortunate side effect of prioritising growth over profits is that it’s never been totally clear whether Amazon could make profits if it wanted to. Believers believed they could, and sceptics sold their stock. What’s new is that in the last couple of quarters Amazon has posted record profits. That could be because they have run out of good investment options, or it could be, as Benedict Evans speculated, that Bezos wanted the increase in share price that profits would bring so that his employees’ options are worth more.

Screen Shot 2016-05-03 at 20.52.40

Being a VC isn’t about having all the answers

By | Startup general interest, Uncategorized | One Comment

This tweet really hits home for me. As VCs and board directors we’re often assumed to have great knowledge about startups, and that’s fair enough given we’re there to help. However, we end up feeling under pressure to live up to the assumption, i.e. to look competent and to be able to help.

As I remember all too clearly, that pressure is particularly intense for younger VCs who are building their experience. We all know that sometimes the only route to success is to ‘fake it till you make it’ – and that applies just as much in venture as in other industries.

None of this is to say that it isn’t great being a VC, it is. Just not great all the time.

So what should we all do?

  • Investors: take Steve Schlafman’s advice and realise that going and finding an answer from someone else is almost as good as knowing it yourself, and a lot better than guessing. CEOs can usually tell anyway. Believe me.
  • CEOs: instead of asking for opinions or advice ask investors for examples of similar situations to the one you’re facing.

 

The world’s most successful pivot

By | Facebook | No Comments

Screen Shot 2016-04-28 at 13.17.10

Facebook has just posted another impressive quarterly result, and that comes on the back of relentless innovation in their consumer facing and advertising products. Bots running on Messenger make the headlines, but the speed and regularity with which they release new services to help advertisers target better is breathtaking. It’s good for startups too, because it takes a while for larger companies to wake up to the new tools. With Instagram, Whatsapp and Oculus they are also building up a track record of visionary M&A.

So there’s lots to admire about Facebook.

But most impressive of all is the way they pivoted from desktop to mobile in 2012 – you can see the results in the chart above. Desktop to mobile is a massive shift, and not only did Facebook transition their audience, they made the product better, as evidenced by the increased amount of daily usage. Most companies fail to make the switch entirely but for Facebook it was the catalyst for a 5-6x increase in revenue.

Apple is now like Alphabet and Microsoft – it’s core product is ex growth

By | Apple | No Comments

The wires this morning were full of stories about Apple’s Q2 results. iPhone unit sales were down 16% on the year ago quarter and there is widespread speculation that the growth might be over. We talked about it a bit in the office earlier on and whilst a few of us think the iPhone 7 might have something cool about it that could revive growth none of us think there’s much further for the iPhone to go. It’s already been improved through nine versions since 2007 and there simply isn’t much left to do.

iPad and Mac computer sales were also down and there’s little reason to hope for a return to growth in either of those two product lines.

Alphabet and especially Microsoft, the world’s second and third most valuable companies have been in this position for a while. They have responded by pushing into whole new areas to generate revenue growth, but with patchy success. Microsoft had massive hits with the Xbox and enterprise software, but missed with Bing, MSN, and mobile. Google has a similar record with Android and Google Apps counting as big hits, but repeated misses on social. Meanwhile both companies have newer projects aplenty.

Facebook, the world’s sixth most valuable company has arguably moved into a similar position recently and is making big bets like Oculus and Whatsapp (although the latter is arguably an extension of its core business).

Historically Apple hasn’t made many big acquisitions, which is why the world was surprised when they bought Beats for $3bn. Going forward I expect their M&A strategy to become more like the other tech giants, because without bold plays their revenues and profits will decline and their share price will suffer. Badly.

If I had to guess I would say many of these acquisitions will fall into their ‘services’ category, which is Apple’s one area of growth right now. It’s where Beats sits and cross selling services to their loyal customer base is a very obvious thing to do.

Knowing your customer is key to conversion rate optimisation

By | Startup general interest, Uncategorized | No Comments

Conversion rate optimisation is a hot topic these days. Google Trends identifies it as an official “breakout” term meaning searches for that phrase are up over 5,000% over the last few years.

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We’re looking at an arms race here. Most of these people searching will be improving their conversion rates which will enable them to pay more for traffic and still hit their customer acquisition cost targets, and unless you match them you will find it hard to compete.

The chart above comes from an article I was reading this morning with nine principles for conversion rate optimisation. They are principles you can use before you have enough traffic to run meaningful AB tests.

  • Speed – Amazon estimates that for every 100ms increase in page load time there’s a 1% decrease in sales, and more generally page load times over 2-3s leads to massive customer drop off.
  • Singularity/Simplicity – pages with only one goal and no clutter convert much better. A Whirlpool email campaign improved clickthrough by 42% when they reduced the number of calls to action from four to one.
  • Clarity – meet your audience’s expectations with a plain language statement of how the customer benefits from the call to action and clear design
  • Identification – know your audience’s aspirations, lifestyles and opinions and reflect them in your design and copy
  • Attention – sites have eight seconds to grab a user’s attention. Headlines are the most useful tool and should generally be less than 20 words.
  • Desire (a subset of attention) – show the user what’s in it for them. Likeability, social proof, hero images and customer logos are good tools.
  • Fear (a subset of attention) – show the user what they lose by not taking the call to action, particularly effective when the pain of the customer problem has been made clear. Urgency (order in 40mins to get delivery by Wednesday) and scarcity (only 5 left in stock) fall into this category.
  • Trust – people trust sites that look good, show customer service contact details, and have customer testimonials. They make their minds up on trust in 50 milli-seconds.

The eagle eyed amongst you might have noticed there are only eight items on the list, that’s because I combined a couple. There’s much more detail and lots of good examples in the original post, which is well worth a full read.

 

Six of these eight tips (singularity, clarity, identification, attention, desire and fear) require that you know your customer, yet a remarkable number of founders start building their products and sites without developing that understanding. Your intuition probably isn’t good enough. What’s more remarkable still is that every entrepreneur we talk to knows that understanding their customer is important and most of them have done some superficial research, but only a minority have a deep enough understanding to make the calls that will give them the conversion they need to kickstart their business. That’s one of the reasons many businesses founder just after launch.

The tools to get the understanding are available to everyone so there’s no excuse. All it takes is well some well structured customer interviews.

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