Software startups: Beware ‘magic’ bullets

By | Startup general interest, Uncategorized | No Comments

I just read ‘Need More Time’? Guideposts For Tech Founders Going To Market When No Market Exists which is full of great tips for what they call ‘pre-chasm’ enterprise startups. The term ‘pre-chasm’ is a nod to Geoffrey Moore’s 1998 classic Crossing the Chasm and refers to companies that may have sold to early adopters, but haven’t yet found a way to sell to the mainstream. Getting sales going in those early years is terrifically challenging and requires great product and great sales. There are lots of common pitfalls that founders fall into and the whole post is well worth a read, but I want to highlight two sections which cover mistakes that in my experience many founders are prone to making.

  1. Over-value conversations and even deals with large enterprise customers. Here’s how they put it:Surely people paying you money for expertise is a strong signal you’re heading towards product-market fit? The twist is: In much-hyped new technology areas, before there’s a big market, it’s not uncommon for startups to close high dollar PoCs and even some large contracts simply because companies are happy to be educated by startups.This practice is particularly common in fintech.
  2. Believe that channel partners will accelerate sales. Here’s how they put it:I see this play out in new markets again and again: Pre-chasm enterprise startups throw time and resources at indirect sales channels (including OEMs, etc.) in the hopes that someone else’s sales team can do a better job than your own. Or, assuming it will accelerate sales, they will spend a lot of time with technical or channel partners … [but] rarely will indirect channels for enterprise devote real resources to help push someone else’s product to market. As for VARs, they typically only provide fulfillment in the early days (and if you’re really lucky, deal registration for qualified leads) because they aren’t structured to carry pre-chasm products — i.e., pitching, educating, hiring the right sales force. They’re good at distributing things where there’s already an educated customer base.Nine times out of ten (or more) direct sales is the only way for early stage startups.

As easy as… AI

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Google is pushing hard to make artificial intelligence as easy to access as cloud computing, building services that reduce both costs and the technical skill required from users. To my mind, there is a strong parallel with how Amazon Web Services made it easier and cheaper for companies to build web apps.

Throughout 2017 they made steady advances, releasing Google Cloud Machine Learning Engine and grew Kaggle, their community of data scientists and ML researchers, to more than one million members. They now have more than 10,000 businesses using Google Cloud AI services, including companies BoxRolls Royce MarineKewpie and Ocado.

And now they are introducing Cloud AutoML, which promises to:

Help businesses with limited ML expertise start building their own high-quality custom models by using advanced techniques like learning2learn and transfer learning

Google seems to be in the vanguard, but Amazon and Microsoft are pursuing similar agendas. For AI startups this means that machine learning expertise will become relatively less important whilst access to data and customer understanding will rise in significance. Given that ML expertise has been in short supply we can expect to see a sharp rise in the number of high-quality startups using machine learning to make better products (as distinct from low-quality startups that claim to use machine learning but don’t really). It also means that the opportunity space will tip towards applications and away from infrastructure.

At Forward Partners we’ve had “Applied AI” as one of our two focus areas for investments for around six months now. We define Applied AI as anything that mimics human cognition (that’s the AI bit) in an application applied to real-world problems using well-understood technologies. We insist on ‘well-understood technologies’ because as an early stage investor we want to be funding companies that can get products to market in predictable time-frames rather than what I sometimes unkindly refer to as research projects. From our perspective, services like Cloud AutoML are great because they add to the available suite of well-understood technologies and therefore increase the range of startups we can back. This is a trend we can expect to continue as Google, Amazon and Microsoft offer more services in this area as they compete to keep people inside their ecosystems.

Forward Partners Code of Ethics Regarding Sexual Harassment

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Earlier in the year, there were a significant number of victims who came forward to share stories of sexual harassment by investors. Some of those investors were prominent VCs.

At Forward Partners we were really saddened by the reports – clearly, any abuse of an asymmetrical power relationship for sexual gain is wrong. Doctors have been held to a high standard in this regard for as long as I can remember and investors should be no different.

So a couple of weeks ago we adopted a new Code of Ethics for Sexual Harassment, with a link at the bottom of our homepage and a new question in our FAQ. The code identifies four different levels of sexual harassment and is based on a template that TechCrunch published in July.
We don’t want to make a big deal of this announcement, but it is important that people know our code of ethics exists.
All feedback welcome and if anyone wants to copy or adapt our code for their organisation we’d love that too.

The importance of being an expert-generalist

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I am in the Elon Musk fan club. It’s hard not to be in awe of what he’s achieved – four multi-billion dollar companies and he’s only in his forties. I’ve even read his biography, not something I’ve done for many people.

Lots has been written about why he is successful, mostly focused on his drive, vision, tenacity, resilience and intelligence, but I happened on a post morning which highlighted something that was new for me. Forbes columnist Michael Sims was seeking to understand how he has been successful across a wide range of very different industries – auto, space travel, energy and software.

The answer, he believes, is that Elon Musk is an expert-generalist:

Expert-generalists study widely in many different fields, understand deeper principles that connect those fields, and then apply the principles to their core specialty.

That struck a chord with me because that is what good venture capitalists do. In his book The Second Bounce of the Ball, Ronald Cohen, who has a good claim to being the first true VC here in the UK, wrote:

[investors] have to be financially trained and to have an understanding of management, but you also have to have a strategic brain while being sensitive to tactical and people issues

To that I would add empathy, patience, grounding, creativity and hustle. So we have to be generalists in that sense. Then on top of that we need to master multiple areas of investment – at least if you are to have a long career. In my seventeen years in this industry, I have invested in enterprise software, semiconductors, SaaS, social media, adtech, and ecommerce across multiple sectors. That has required a lot of reading! Then right now I am getting to grips with Bayesian Networks, Hidden Markov Models, Convolutional Neural Networks and back propagation as Forward Partners investigates whether to have a big push in what we are currently calling “Applied AI”. Further, all of this applies across multiple industries, from fintech to fashion to healthcare (one of my colleagues is up to his neck in microbiome research as we speak).

You can see the need to be an expert-generalist.

All this begs the question of how one becomes an expert-generalist, or if you are already an expert-generalist, how you become a better one.

The answer is to get good at learning. Fortunately Sims spells it out for us. Here is what he describes as Musk’s two stage process for learning:

  1. Grasp the fundamental principles
  2. Reconstruct those fundamental principles in new fields

There are no short cuts here. Musk used to read 60 books per month. But when, and only when, you understand the fundamentals you can more quickly learn and apply things in new areas. Returning to AI – Bayesian Networks are much easier to understand if you grasp the fundamentals of statistics, and once you grasp the fundamentals of Bayesian Networks (and all the other components of AI) it is much easier to understand where they can be successfully employed and where they can’t. Similarly with regard to human behaviour, a solid grasp of behavioural psychology makes it easier to predict how people will react to new products and services.

And getting good at learning isn’t just important for VCs. It’s important for everybody. The world is changing so fast now that one area of knowledge is most unlikely to be enough to build a career. A quick look at this Wikipedia article on the history of programming languages shows what developers have to deal with, but something similar is true for just about everyone else.


Uncertainty: startups’ unfair advantage

By | Startup general interest, Uncategorized | One Comment

I just read a review of a new Wiley book Design a better business which argues that:

better businesses are ones that approach problems in a new, systematic way, focusing more on doing rather than on planning and prediction

For them, of course, the point is that design thinking is that ‘new, systematic way’, but this sentence made me think of startups, where the emphasis is very much on doing rather than planning. Since Eric Ries wrote The Lean Startup in 2011 smart founders have understood that the best way to progress is to get onto the ‘build-measure-learn’ loop and iterate to success. That’s doing rather than planning.

Whilst doing rather than planning has been a hugely successful tactic for entrepreneurs and their investors, before I go any further I want to note that as with everything you can take it too far. To get the best chance of achieving huge success, and avoid getting stuck at a local maxima, a certain amount of thinking should be done before building starts. There’s a balance to be struck and whilst best practice is definitely to maintain a bias towards action in our experience an increasing number of f0unders are starting to build product before they’ve done enough thinking, sometimes encouraged by investors who want to play with product before they invest. Many of these founders end up failing when with a little more customer research they might have built a slightly different product which would have resonated much better and allowed them to iterate to success.

The reason that Design a better business advocates doing rather than planning is that the world is becoming increasingly uncertain. Consumer habits, technologies, and other trends are uprooting once-thriving businesses and disrupting entire markets with an ever increasing cadence. In this environment every year gets more difficult for those who like to plan, whilst it gets easier for those with a bias to action.

The increasing engagement of big business engagement with the startup ecosystem through accelerator programmes, incubators and acqui-hires is a reaction to this trend. However, these small-scale programmes don’t solve the fundamental challenge of every business leader, which is deciding which actions to endorse. At good startups it’s easy (or easier..), all action is directed towards achieving their vision. Larger companies have a much more difficult challenge. They need to launch new products, attack new markets, or take radical steps to defend existing revenues, they can only put significant resources behind a small number of projects, and anything that won’t reach the scale to impact their financial statements isn’t worth doing. Historically planning has been the tool they used to figure out which projects have the best chance of moving the needle for them, but as planning is becoming less effective they have increasingly less confidence that putting resources to work will generate the scale of returns required.

That’s a problem startups don’t have. At least not to the same degree. Most founders want their companies to be huge successes, but if it turns out to be a medium sized success that’s still a worthwhile endeavour. A business that grows to £10m in revenues over five years and sells for 1-3x that amount can still be a life changing event. For large companies that’s not the case. If a £200m turnover business goes after a new market and it only adds £10m to the top-line after five years the project will not have been worth the effort.


This is one of the reasons why companies are increasingly buying back shares instead of re-investing profits.

In summary, increasing uncertainty is an unfair advantage for startups. And it’s an advantage that gets stronger every year.

How we can find our ‘flow’

By | Startup general interest, Uncategorized | 3 Comments


‘Flow’ is the almost magical state of extreme creativity and productivity. Most often associated with artists and developers, but I believe applies to a lesser extent to all of us.

What follows is an extract from How anyone can enter flow state for maximum focus. I wanted to get these tips for enabling ‘flow’ down in one place that I can refer back to.

If you want more detail on what ‘flow’ is from a neurological perspective or much more detail and colour on the subject generally then please read the article above. It’s good. The most important point for me is that the more people work in a flow state, the more productive and happy they are.

These tips work for individuals and managers.

  • Find work that is in the ‘flow channel’ – flow only comes after a struggle with a difficult task, so the work should be stretching enough that it’s genuinely challenging, but not so difficult that it  creates fear that ultimately blocks creativity. This is a matter of balance – some boring work is inevitable in all day to day roles, but too much creates disengagement.
  • Create the right environment – all necessary tools and information should be at hand, to minimise distractions and excuses for not focusing on the task in question.
  • Remove distractions – Slack, emails, team meetings, colleagues wanting a quick chat and a cluttered desk all detract from focus, making it harder to enter flow state. Again, this is a matter of balance, but eliminating necessary distractions and giving people long periods of uninterrupted time will help. Permitting people to say ‘don’t interrupt me now’ is a good trick, maybe just by wearing headphones.
  • Break difficult tasks into smaller chunks; my dad used to love the following joke: Q. “How do you eat an elephant?” A. “One steak at a time”. Now that’s chunking! It’s an old productivity hack, but very relevant here because it helps break through the struggle.


Dollar Shave Club and the bull case for eCommerce

By | Ecommerce, Uncategorized | 3 Comments

The cue for this post was Harry Stebbing’s 20MinuteVC interview with David Pakman, the partner at Venrock who led the Series A and Series B rounds at Dollar Shave Club and recently had his faith justified with a $1bn exit to Unilever.

He said that when he made those investments in 2012 and 2013 eCommerce wasn’t a hot sector with VCs and that remains the case now, but here at Forward Partners we’ve made a number of ecommerce investments and, like David and his partners at Venrock, think there will be more Dollar Shave Club scale exits going forward. We are happy investing in sectors where we see opportunity, even if others don’t.

If you poll investors for reasons not to invest in eCommerce you will generally hear three things: low margins, low multiples on exit and high working capital. Some will also throw in the threat of competition from Amazon for good measure.

These are all great points. There are plenty of eCommerce companies where these characteristics are risks and realities. Great care is advisable before investing in them. Without some extra bit of magic they will be unlikely to achieve huge exits.

But there are also eCommerce companies that escape some or all of these issues and many of them are good investment prospects. Here are three reasons why:

  • Consumers are hungry for direct relationships with the brands they buy. That’s part of the story behind Dollar Shave Club, Nike, Apple and many other iconic brands today. However, most traditional brands (think P&G, Unilever, much of traditional fashion) have never dealt directly with their customers and don’t know how. Meanwhile sales through their traditional retail channels are falling fast: creating the opportunity for upstart brands to steal significant market share. These direct-to-consumer eCommerce brands are often able to leverage their relationships and data to win on the basis of superior product. Example companies: Dollar Shave Club, Bonobos, Warby Parker and amongst our partners Spoke and Lost My Name.
  • Few traditional retailers are nailing it online. Their skills of supply chain management, curating a catalogue of product to fill their shops and in store merchandising are less important in the current online and omnichannel era. Today, inventory can be an order of magnitude larger and there are huge opportunities for curation and re-imagining supply chains. All the while, declining High Street revenues and high fixed cost bases are starving them of cash to invest in innovation. In their place what you might call eCommerce 2.0 businesses are offering consumers compelling personalised selections from massive inventories with marketplace, no-stock or stock-light models. They are able to scale rapidly and go global quickly. Amazon is the proto-typical example in this category, others include, ASOS and amongst our partners Thread.comLive Better With, Hubbub and Patch.
  • Consumers have a range of preferences, styles and budgets and it’s hard to picture a future in which we don’t buy from a range of online retailers. Shoreditch locals don’t want to shop in the same places as investment bankers a mile south of here. As you might have read on this blog I have a ton of respect for Amazon but they aren’t going to take the whole market. In particular they aren’t good at the product categories where people don’t know what they want and traditionally look to retailers to help them make choices.

Online penetration of retail is now pushing 20% in the UK, so there is still a long way to go in this market. In his interview David said that after little interest in Series A and Series B rounds at Dollar Shave Club the Series C and Series D rounds were hotly contested. I think we will see a similar turnaround in investor appetite for eCommerce more generally.

Q2 US investment data suggests fears of a slowdown are overdone

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“Keep calm and carry on” is so deeply ingrained into the British psyche that we’ve made a national joke out of it, but that’s how I feel about business at the moment. Many in the venture world fear for the future following the slowdown in investment activity last year and the Brexit vote two weeks back, but in my opinion there’s a high chance that in the startup world the next couple of years will be similar from a prosperity perspective to 2010-2012. In other words, times will be good, but not crazy.

I say that because the fundamentals are still strong. Change is happening faster and faster which is pushing innovation into smaller and smaller companies, and the overall economy is in reasonable shape.

There are risks to this scenario, to be sure, including a messy divorce from Europe and a crash in the venture market, but I don’t think these risks are worse than other systemic risks we’ve seen in recent times – e.g. the Greek debt crisis.

I’m writing all this now because the June investment data from Mattermark is out for the US. Their post is titled Series A Rounds Slip in Q2, but to me the chart below shows that activity is pretty much flat over twelve months. That’s better than the picture looked at the end of May when we feared activity might be trending down. We shouldn’t over-egg the significance of what is so far only a one month pick up in June, but to me this data says we should keep calm, and carry on.


Top 100 venture VC investments each year average $100-150m gain

By | Uncategorized, Venture Capital | One Comment

Screen Shot 2016-05-31 at 15.12.06

This chart is from a Cambridge Associates research report into where VCs make their returns. Cambridge Associates is a service provider to the Limited Partners that invest in venture capital funds that’s known for the quality of its research.

The conclusion of the report is that returns in venture capital are distributed across a larger number of companies and across a wider number of venture capital funds than is widely believed. Their advice to LPs is to catch these distributed returns by investing in emerging managers outside of traditional US venture heartlands. That’s good news for newish funds in the UK.

I reproduced this chart because it shows what a great VC investment looks like. Looking at 2011 and 2012 the top 100 investments created c$10-15bn in value. That means the average top 100 investment created $100-150m in value. One way of creating $100-150m is to invest early, take a lot of risk to get a meaningful stake and hope to get a massive multiple on a small investment. That’s the Forward Partners way. The other way of creating $100-150m is to invest more money a bit later on when the required multiple will be smaller, but the exit value will be higher. Running the maths early stage investors with healthy stakes can get into the top 100 with exits at half the level Series A investors require and maybe 10% of what very late stage investors require.

One of the things I like about the early stage investing we do is that there are many many more $300-500m exits than $1bn+ exits, so we are swimming in a pool with more targets. Another good thing is that if we’re lucky some of our $400m companies will hold out for bigger exits and will end up at $1bn or more, which will drive the returns even higher.

I’m going to finish with a caveat. The dangerous thing for early stage investors is dilution by later stage investors. That’s why smaller funds and angels have a preference for capital efficient companies. In the maths above I’ve assumed that everyone follows their money to protect their stake. That can be challenging for very small funds, although is getting easier with the rise of AngelList special purpose vehicles.

Evaluating the prospects for life changing inventions

By | Startup general interest, Uncategorized | One Comment

This morning Chris Dixon posted The typical path of life changing inventions:

  1. I’ve never heard of it.
  2. I’ve heard of it but don’t understand it.
  3. I understand it, but I don’t see how it’s useful.
  4. I see how it could be fun for rich people, but not me.
  5. I use it, but it’s just a toy.
  6. It’s becoming more useful for me.
  7. I use it all the time.
  8. I could not imagine life without it.
  9. Seriously, people lived without it?
  10. It’s too powerful and needs to be regulated

That’s pretty accurate, but with the exception of 10. maybe not that surprising. It reminds me of the Mahatma Ghandi quote “first they ignore you, then they ridicule you, then they fight you, and then you win”, but extended and ported to a different context.

However, most would be life-changing inventions don’t make it all the way to number 10 and the interesting thing for future gazers, including VCs, is assessing how far a product will get. That requires an understanding of customers, use cases, ecosystems, cost trajectories and distribution, and it’s definitely not sufficient to think that if a product is at one stage it will progress to the next. For example, most products that people know about but don’t understand it (i.e. at stage 2) whither and die, and to know that any given product is different requires a hypothesis about how people will come to understand it and see how it’s useful.