Category Archives: Uncategorized

Google is the new Microsoft – musing on the meme

By | Google, Uncategorized | 2 Comments

We have just learned that over half of Google searches are now on mobile which has got me reflecting on where the company is going.

Before I go any further I should say I’m a massive fan. Google has had an amazing run as a company, built many amazing products, is pursuing lots of super interesting and brave projects, and generally handles itself well. Moreover, I’m a very happy customer both professionally and personally and I have many friends who work there.

However, the world has turned decisively in directions that don’t favour them. The Apple driven smartphone revolution has taken attention from the open web where Google is strong to apps, the Facebook inspired social media revolution has taken traffic from the open web to closed ecosystems which Google can’t access, and they are haemorrhaging search volume to Amazon.

Microsoft’s monopoly on desktop software looked unassailable until the internet came and similarly Google’s monopoly on desktop internet looked unassailable until a couple of years ago. Microsoft invested big in the internet with Internet Explorer and their MSN portal (remember that?) and now Google is investing big in Google Maps and Android and has numerous failed attempts in social. In an interesting parallel, Microsoft’s internet products were free just as Google’s mobile products are free. Both wanted to protect their core business model.

In another interesting parallel both launched lots of new projects in an attempt to build new revenue streams. Prosaically they both moved into enterprise and more radically Microsoft achieved good success with Xbox whilst the jury is still out on Google’s self driving cars and other Alphabet projects.

Despite all these similarities the companies feel very different. In the 1990s Microsoft was an aggressive monopolist and few people liked them. In 2015 Google has a mix of supporters and detractors but to my mind at least the company has many endearing qualities, as I’ve said.

It’s unclear how much that will matter though. In the arena of business profits count, and whilst feelings might buy Google some loyalty from people like me that won’t be enough to save them from being the next Microsoft. In fact, as I write this it’s difficult to see what will.

I would love for their autonomous cars to become a serious business, or maybe project Loon, but if they do they will become Google’s equivalent to Microsoft’s Xbox, thus completing the parallel.

Finally – being the next Microsoft is far from a fate worse than death. As of June 30th they were still the world’s second most valuable company, and on top of that they are now enjoying a resurgence.

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.

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.

Tips for productive advisor-entrepreneur conversations – argue intelligently and criticise kindly

By | Startup general interest, Uncategorized | 4 Comments

A couple of days ago I wrote that startup advice should focus on the ‘why’ and the ‘what’. Today I’m going to write more about how to do that.

A common pattern is for advisors to pattern match with something they’ve seen before and come quickly to a piece of advice that feels right to them. That’s great and hugely valuable when it chimes with the entrepreneurs intuition, but when it doesn’t the dialogue can deteriorate to brute force persuasion and sullen acceptance or passive resistance.

Focusing on ‘why’ the advice is appropriate is a big help, as I wrote about last time, but getting into the right frame of mind emotionally and attitudinally is also a big deal:

  • Think of areas of disagreement as opportunities to learn. Don’t avoid difficult conversations for fear of getting advice you don’t wan’t to implement or having your advice ignored.
  • Make it your goal to find the best solution, not to win the debate.
  • Listen first and then debate second. If you can summarise what you’ve heard in words the other side would use, list your points of agreement, and note anything you’ve learned before you go to say your piece.

Not every conversation can end productively, but the hit rate can be increased, and with that comes learning, better insight and ultimately business success.

This post was inspired by a summary of philosopher Daniel Dennett’s thinking about arguing intelligently and criticising kindly.


Using The Path Forward to determine fundraising strategy

By | Forward Partners, Startup general interest, Uncategorized | 2 Comments


As you might have seen we launched The Path Forward last week as a guide for ecommerce and marketplace entrepreneurs in their first year (diagram above). We’ve been using it internally for a while and we’ve noticed that we find it easiest to get excited about startups that are at Step 1: Valid Idea, and Step 3: Valuable Business. When we meet new companies at Step 2: Valued Product, entrepreneurs have made choices and started down a path which inevitably shuts off some opportunities that were there earlier but they haven’t got far enough along to know whether those choices are good.

It turns out we’re not alone. I saw this on Founders Notebook earlier today:

You can only raise money by pitching the “Dream” or by selling “Traction”. So either bootstrap your startup, or raise money in the early “dream” (no code, no plan, just a dream) phase or in the “traction” (the model is working) phase of your business.

The Path Forward is a good tool for understanding what makes a good dream and what qualifies as good traction. To summarise what’s on the site, pitching a “Dream” works best when the need has been proven with customers and a prototype really resonates, whilst pitching traction works best when the business looks set to scale. If you want more detail go to The Path Forward, click on the ‘About the Path Forward’ button and check out the definitions of Step 1: Valid Idea and Step 3: Valuable Business and associated Waypoints. (“Waypoints” is the name we’ve given to the sub-steps you can see in the graphic above.)



Volume of global ecommerce exits growing nicely

By | Ecommerce, Startup general interest, Uncategorized | No Comments

CB Insights posted this chart on Twitter today. As you know at Forward Partners we’re ecommerce and marketplace investors, so we like to keep tabs on all aspects of the ecommerce market.

Historically there haven’t been many exits in ecommerce, so it’s good to see the number rising. I think this trend has some way to go because ecommerce penetration is still only in the low teens in the UK and US and is lower still in many other countries.

To really kickstart the exit market we need a few more huge ecommerce businesses to compete with Amazon. That would unlock the sort of strategic exits we’ve seen in software and consumer internet over the years.

Until then it’s important to make sure the fundamentals of a company add up so that they will be able to make substantial profits once they hit scale.

Making sense of the bubble talk and the impact on startups

By | Startup general interest, Uncategorized, Venture Capital | No Comments

There’s a lot of contradictory advice out there at the moment. On the one hand you have the ‘entrepreneurs should just do their thing and not pay attention to the markets’ folk and then on the other hand there are plenty of observers saying that a bubble has burst.

Many people I respect are in the former camp. Tomas Tunguz said it clearest with his recent post Why the bubble question doesn’t matter which lists the things good companies do and points out that they are the same in bull markets and bear markets. I’ve read posts from Brad Feld in the past saying he doesn’t pay attention to bubble talk and in a post earlier this week Fred Wilson quoted someone else quoting him saying “Markets come and go. Good businesses don’t.” (although he did also point out that if companies need to raise money then the capital markets can affect them).

I have sympathy with this view. Startups and venture funds run for 5-10+ years, are likely to see a recession at some point in their lives (maybe two) and hence need to be able to survive and prosper in both recessionary and growth environments. Moreover, predicting when crashes and recessions will happen is nigh on impossible so trying to manage according to where we are in the cycle is a fools game.

But at same time market crashes changes things for startups. I saw that in 2000 and then again in 2008. When the macro economic climate is tough less money flows into venture funds and startups, so fewer deals get done, valuations are lower and more companies fail. On top that everyone is nervous and deals take longer to complete. Making things worse still, consumers and enterprises have less money to spend and startups find it harder to grow revenues.

It takes time for the impact of crashes to be fully felt in the startup market though. I remember this most clearly from 2000 when I was in a fund that was investing heavily pre and post crash and the VC adjustment took 8-9 months. I think the reaction is slow because VC funds aren’t directly linked to the stock market, VC deal cycles are long, because LPs don’t want VCs to try and time markets and because VCs have staffed up to deliver multi-year investment plans. After a while though VCs find themselves spending more time with portfolio companies struggling with the new environment and the amount of new money in the market drops, and these forces combine to stretch out deal times, reduce the number of deals done and reduce valuations.

Mark Suster set out a number of the dynamics at play in his post Making Sense of the Stock Market Drops in Relation to Venture Financing

Pulling it all together I think the difference between the camps is that the ‘pay no attention to the markets’ folk are talking about best practice startup management in general whilst Suster and others are talking about the impact of crashes in the here and now.


I have no idea if the stock markets will continue to go down or recover but it’s pretty clear to me (and probably to you too by now) that if things don’t get better we will get the negative impacts described above, and if they do recover late stage VC markets will continue to get frothier and that will eventually trickle down to Series A and seed.


I think the best outcome is that the bear market continues long enough to take the heat out of late stage venture but isn’t severe enough to create a rout.

Until we find out founders should follow the old adage ‘hope for the best, but plan for the worst’, prepare themselves for longer fundraising cycles, and think seriously about taking any offers of cash that are on the table, even if the valuation is lower than hoped for. (And, in case you’re wondering we don’t have any low valuation termsheets out there at the moment. Our valuations have remarkably consistent over the two year life of Forward Partners.)

Advice on changing organisational culture

By | Startup general interest, Uncategorized | 3 Comments

I’ve written a lot in the past about how smart entrepreneurs harness company culture as a tool to drive success. Most of that work has centred around being clear on vision, mission and values and it’s never too early for founders start thinking about these things. Sometimes things go awry though and the culture needs to be changed. That’s a difficult thing to do and I’ve just come across a brilliant 2011 post by Steven Denning which sets out the problem and provides a framework for finding solutions.

If you’ve got time, go read the whole thing. For the attention starved amongst you, what follows is a summary.

Culture change is hard and often fails because culture resists change. Here’s why:

an organization’s culture comprises an interlocking set of goals, roles, processes, values, communications practices, attitudes and assumptions.

The elements fit together as an mutually reinforcing system and combine to prevent any attempt to change it. That’s why single-fix changes, such as the introduction of teams, or Lean, or Agile, or Scrum, or knowledge management, or some new process, may appear to make progress for a while, but eventually the interlocking elements of the organizational culture take over and the change is inexorably drawn back into the existing organizational culture.

But if the culture isn’t working then the company won’t work until it’s fixed, and this framework lays out the tools at a manager’s disposal to create a solution.


The best approach is to start at the top and systematically work down, only using the pure ‘Power Tools’ of coercion, threats, fiat and punishments as a last resort. Common mistakes are to use the ‘Power Tools’ too early and to articulate a new vision without putting in place the management tools to get buy-in and re-enforce the message.

Those mistakes are common, but so easy to make, particularly as an investor. Just writing these sentences is bringing back painful memories of working with CEOs to articulate a new vision, strategy, or direction and then watching as months rolled by and little changed. With the benefit of this diagram it’s clear to me that when things didn’t work it was because I didn’t do enough to make sure the management tools were in place, particularly those designed to ensure top-to-bottom buy-in. That contrasts with companies where we successfully used OKR type structures to get full alignment.

Three common mistakes founders make when analysing other companies

By | Startup general interest, Uncategorized | 3 Comments

Drawing inspiration from other companies is an important part of every entrepreneurs toolkit. To misquote Isaac Newton, we all stand on the shoulders of giants. It’s easy to get it wrong though, and there are three common mistakes that founders make.

1. Assuming mistakes made by competitors are because they are dumb. This is from Aaron Harris’s Presumption of Stupidity

I’ve noticed a common bias that shows up in some founders: they believe that their competitors are stupid or uncreative. They’ll look at other businesses and identify inefficiencies or bad systems, and decide that those conditions exist because of dumb decisions on the part of founders or employees.

This is a bad belief to hold. In truth, competitors in the market are usually founded and run by intelligent people making smart and logical decisions. That doesn’t mean that all the decisions they make are necessarily the right ones, but they’re rarely a function of outright stupidity.

Where companies do things that diverge from what seems smart from the outside, it’s a much better idea to ask why those companies are doing things from the presumption of intelligence and logic rather than the presumption of stupidity.

2. Assuming everything that successful companies do can be copied. Every successful company makes mistakes, and some successful companies have habits they hold out as drivers of their success which it doesn’t make sense to copy. Apple is the best example here, great as he was, Steve Jobs’ management style and his insistence on relying on his vision and not talking to customers aren’t things that will port well to many other companies.

As Paul Graham wrote in a recent article advising startups that can’t secure the .com domain for their name:

There are of course examples of startups that have succeeded without having the .com of their name. There are startups that have succeeded despite any number of different mistakes.

The most common version of this mistake is to cite a habit of another successful company as justification for bad or lazy behaviour – e.g. Steve Jobs had the courage to rely on his own vision of what’s best for customers and so do I.

Another, more insidious, version of this mistake is to copy startups that have had some early success but haven’t definitively succeeded yet. Often this is European startups copying American startups that have reached the Series B or Series C stage. The problem here is that you might be copying something that fundamentally doesn’t work (as with many of the GroupOn clones) or where the reasons for the success they are enjoying aren’t apparent.

3. Success can come from copying others rather than being different (which takes more courage). In The Possibility for Outrageous Failure Max Wessel wrote:

Warren Buffet has famously stressed for folks to be greedy when others are fearful. Clay Christensen has cautioned that profitable markets face the greatest pressure towards commoditization. Even inside today’s tech landscape, we have Peter Thiel appropriately pointing out that there is only likely to be one Google, one Salesforce, one Facebook, one Uber, and so on. The next conquerors of industry are likely to arise in surprising spaces where there isn’t a clear opportunity.

Summing up, the overall message is that getting to know your competitors and what drives success at other companies is a great thing to do, but use that as the basis for your own critical and ‘from first principles’ thinking. Then don’t rely on your ability to out execute the competition, but be bold and above all seek a source of competitive advantage. Often a piece of information you have or something you believe that others don’t can be that source of competitive advantage.

Hat tip to Mattermark’s daily newsletter today which had links to the three articles I quote here. It’s a great source for content.

Three success criteria for ‘Assistant-as-app’ companies

By | Startup general interest, Uncategorized | 2 Comments

Nir Eyal recently wrote a great post speculating that ‘Assistant-as-app’ companies might be the next big tech trend. I think he’s right – it’s a trend that has legs, but it’s also a trend that has been going for a couple of years already but hasn’t yet been given a good label. Magic and Operator are the companies in this space that have made the biggest splash recently but companies like and Big Health from our portfolio and like Native and Vida Health that Nir mentions have been pursuing variations on this theme for a while.

In another post Nir proposes the following definition:

I’ve proposed “assistant-as-app” to mean: an interface designed to enable users to accomplish complex tasks through a natural dialogue with an assistant.

He emphasises ‘natural dialogue’ because the first success criteria is that users don’t have to learn a complicated interface. Few people can be bothered to do that for anything, let alone when there’s a simple option available which will probably get you to a result faster on the first couple of times through. Complicated interfaces are in effect asking people to make an investment of learning time against a highly uncertain outcome – not an attractive proposition.

However, the key point is that there is no learning curve, so rather than ‘natural dialogue’ I would use the more inclusive term ‘easy to use interface’.

The second success criteria is that the service delivers something more than the fully human equivalent. That doesn’t mean it’s better on all dimensions, but that it is demonstrably better on at least one important dimension. For example Big Health is a therapy service for insomniacs that offers 24-7 access to an AI therapist called The Prof. Human therapists typically see their clients for an hour per week, whist The Prof checks in multiple times per day and if you wake up in the middle of the night he’s there (in his dressing gown) to help you get back to sleep.

It seems to me that the main ways that ‘Assistant-as-app’ services can be better than humans are:

  • 24/7 presence and immediate response
  • Price – high levels of automation bring some services to a price point that works for consumers (although note the third success criteria below)
  • Access more information about the user and use better analytics to deliver the service – e.g. data from wearables, activity diaries, transaction history
  • Access more components to build a customised solution – human services are limited to what the human operator knows, Assistant-as-apps can access all the inventory on the web

If you can think of more ways ‘Assistant-as-app’ services can be better I’d love to hear them.

The third success criteria for ‘Assistant-as-apps’ is that the economics work. To get to a price point that’s attractive to consumers typically requires some heavy duty automation on the back end, often leveraging AI. Most companies in this space start out delivering the service manually and initially lose money on every transaction. Predicting the extent to which those manual activities can be automated and can be difficult at the outset, but it’s critical to the business model and should be addressed early on. It’s easy to build an amazing service that will never make money and I suspect we will see some high profile companies make this mistake.


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