When I was at Zynga, we shipped a game that had marginal success. And in the deep dive the product management lunch lead said:
Engagement is really tough to move
At Zynga, Mark would demand game-changing features, demanding that we change the product in place and if we could pull that off the theory was we could change the retention curve.
And being an engineer, and surrounded by entrepreneurs, my assumption was that through the application big data and science we could change this number.
Then I had the opportunity to try and drive machine learning models into games to improve core metrics of the game.
The theory was that auto-tuning the game would improve engagement and retention.
And it worked, to a point.
And what I realized was that the hard problem is building a fabulous product. And a great product has high engagement. Everything else we do is about tuning or improving the excellent product at the fringes. And that changing engagement is equivalent to creating a new product.
And that got me thinking as to why that is impossible. And what I realized is that big data collects information about the product that is. And can only answer questions about what your product is doing.
To change engagement, you have to build a new product with new features and net new capabilities. And the data for that product doesn’t exist in any of your big data systems.
The short version of this story is the following, engagement is what it is, and if it isn’t what it needs to be, you need to scrap the damn thing and start all over.
Great post here by Mark Suster at Bothsid.es
Lots of good stuff here.
My key takeaway is here:
The vast majority of this recent boom in prices is not being driven by VCs but rather by hedge funds, mutual funds, corporate investors and other sources of non-traditional venture funding. In the chart below you can see that a decade ago for every dollar a VC raised from LPs a dollar went into a startup. Now for every dollar a VC raises $2.50 goes into a startup.
Many moons ago, I wondered where the hell the money was originating. Mostly non-VC money chasing yield has descended on the valley. And like the sub-prime mortgage crisis, the non-VC money figured out that using preferential terms allowed them to invest in riskier assets with less risk.
Shifting risk, and increasing the value of assets without increasing their value never ends well.
A friend of mine and I have been debating unicorns for months. And what we concluded is that there are two stories.
The first story is that there are a bunch of excellent businesses that are worth billions. These are the true unicorns. I won’t hazard a guess of how many or which companies fit that bill.
The second story is that there are a bunch of donkeys with horns that are using creative deal structures to acquire valuations that are questionable. And that the story of the true unicorns is hiding the story of the donkeys.
The recent article on TechCrunch tells us that the number of potential donkeys is on the rise.
And so my buddy and I debated the impact of these potentially faux-Unicorns.
The first narrative, dominating the press, is the effect of faux-Unicorns on investors. After a lot of discussions, we concluded that the recent faux-Unicorn phenomenon of artificially constructed valuations is benign to positive. Positive because it mitigates the downside risk, and because it captures more of the upside if an acquisition occurs at the cost of investing more capital in a business that has achieved a certain amount of success.
If you take a unicorn job in 2015 and never say the words “liquidation preferences”, you are the sucker at the table https://t.co/cbh3lPRA9a
— Alex Stamos (@alexstamos) December 24, 2015
The second narrative that is emerging is the impact of faux-Unicorns on employees. There we agreed that the story is downright appalling. The shift of risk from investors to employees who find themselves locked in, or worse, have their interests misaligned with the core investors, or even worse is not positive.
The derisking for investors and founders is increasing the risk of employees.
And so what?
The danger is that employees eventually figure this out. And they start demanding higher salaries, longer periods between when they quit and when they have to sell their shares or just plain refuse to work for any private company.
Furthermore, as more employees figure out that a Unicorn or a startup is not a path to riches, and that the investment strategies are being used that minimize their already minimal chances of wealth, people will over the long-term lose interest in working at startups.
And worse, because employees are not investors they have a hard time disambiguating faux-Unicorns from real Unicorns.
If a startup is a job where you work long hours, at low pay, to change the world, there are a lot of options that are not working in tech.
We can talk about culture, and opportunity and learning and if there is no money, then people will go elsewhere.
The people who work in the tech sector have the ability to do anything they want. And eventually, they figure that out.
There are two fundamental approaches to building products, a technology first and a customer first approach.
The technology first approach examines what is possible and based on what is possible builds something.
The customer first figures out what customer need is required and then builds something to satisfy that need.
I have had the opportunity to pursue both approaches in my career. And what I have observed is that they can both result in poor results.
The technology first approach can produce something that no one wants.
The customer first can produce a few deals that never grow past a certain point.
At one of my jobs, the GM had the head of product management and myself at each other’s throats. The head of product was very customer centric. I was very technology focused. And the GM would only approve a new project if we both agreed. Sometimes, the head of product would wear me down, and I would grumpily agree with his ideas. Sometimes, I would wear the head of product down and he would grumpily go along with mine.
And those ideas had marginal success.
The best products, the ones that were huge successes were the ones where we both could see how this would satisfy the customer need and that there was real technology innovation.
When releasing a major new piece of functionality, I have this theory that it takes three major releases actually to deliver what the customer wants.
The first version is what you could build within the time and resource constraints available to you.
The second release is a set of bug fixes and desperate hacks to make the product more attractive.
The third release is the product the market wants.
Because it takes three releases to build a product the market wants, getting that first version out as fast as possible is so important. And not to get too anxious about whether the product is actually what the market wants.
Once you ship, then you get customer feedback and fix the thing you shipped. And while fixing issues and selling the product you learn the thing the customer wanted.
And then you build that.
Most products fail because we spend too much time and resources trying to make the perfect product or fail because we never get to version 3.
In my career, I’ve chosen to work at larger companies instead of smaller ones. Or maybe, a better way to describe it, is that I have joined small sized businesses that became enormous.
And I was reflecting on the differences.
My favorite game of all time is Civilization II. Some players, like the beginning game:
The point is that you have the fewest pre-existing constraints. You can only make a small number of decisions. And each decision is a matter of life or death. You can very easily get destroyed if you make the wrong choices.
That part of the game is the most intense because every decision is, of course, critical, every moment obviously a life or death moment. You choose to explore a village, and if it turns out to be barbarians and you don’t have an army you lose the game.
In the later phases of the game, you have many cities and an accumulation of decisions. You can quickly destroy other civilizations, build wonders, and typically there is no existential threat. No decision is obviously existential. No crisis is obviously critical.
There are existential threats; they are just not obvious.
The challenge in this part of the game is how to marshall resources and make decisions to win the end-game while ignoring things that are not important.
When you join a large company, you are essentially being given someone else’s Civ game. Your job is to figure out what decisions your predecessors made that are prescient and build on those while figuring out what new decisions need to be made to win.
The funny thing about joining a Civ game in the middle phase is that you may have already lost. Some decisions made early on may have put your civilization in a terrible spot that are only obvious now.
And for many folks, this makes starting a game more attractive than taking on an existing game.
The funny thing is that when you launch a new game, the computer makes decisions for you, and those decisions, when combined with your preferred strategy, will doom you just as much.
The thing about the early part of the game is that when you lose you’re just a historical footnote, a leader of a small tribe. When you lose later on in the game, you may have a large thriving civilization that just didn’t make it to the finish line. You fail as a CEO of 10 person startup, and only your web page records your failure. You fail as the CEO of Yahoo, and it’s front page news on the WSJ.
The later part of the game in Civilization II can be more thrilling. You get to do more stuff, try more things, you are on a bigger stage and you are playing for all of the marbles instead of a chance at all of the marbles.
Why should you join a startup if the probabilities are not in your favor?
Startup L. Jackson writes a great note as always.
Mr. Mehta does an excellent summary.
And they capture the essence of the theory, joining a startup is a lifestyle choice and an opportunity to short-circuit the career advancement ladder. Or a way to learn new skills.
I joined Zynga because I wanted to work on hyper-scale infrastructure. And I got that opportunity in spades.
Without going into it, into too much detail, I lead a web-property, built out a 200 person dev-ops function, had a team that delivered many products that were used to operate games. And under my watch, we had less than 30 minutes of planned down time and delivered over 4 9’s of infrastructure availability. And got to build out a 3rd party API platform and kicked started an effort to create a gaming optimized mobile programming language
And I met a whole bunch of amazing people who are friends.
You don’t get that kind of crazy experience in 4 years at a large company. And I made the choice to go to Zynga to learn and I got that.
And this might make the backers of these deals happy that the employees got a first class education, and it doesn’t change the reality that there is something fishy with those deals.
Yesterday, I wrote about the problems with Unicorns and their preferential treatments of investors.
Today, I wanted to make the asymmetry realer.
Consider the decision facing the board when it had an 825 million dollar deal on the table.
The board was considering four options in that order
- Go public and be valued at more than 1 billion
- Accept an 825 million dollar deal
- Sell at a lot less
- Keep struggling alon
The board, probably feeling optimistic decided to skip the 825 million dollar deal because the board felt that the upside of an IPO was worth the risk.
The question is what risk was the board considering and are these aligned for all stakeholders.
For the preferred investor, option 3 is more valuable than option 4 and for the employees option 3 is not an option worth considering.
Let’s explain it with numbers.
If the deal closes at 825 million, preferred investors make ~4$ a share. If the deal closes at 425 million, the preferred investors make 3$ a share. If the IPO happens, the preferred investors may make 5$ a share.
If you think that an IPO has a 20% chance of happening and a 425 million dollar deal has a 70% of happening then what you are doing is saying I am taking a chance at 20% upside with a 25% downside. Not a bad bet. Especially, if the downside bet is still a positive outcome. Option 4, continue to go at it is the worst option because the downside risk is to lose everything.
For the employees, however, an 825 million acquisition is worth 4$ a share, and a deal at 425 million is worth 0.44$ a share and is no different than struggling along. Your stock is worthless at 425 million so you might as well keep trying.
And if I were an employee, I would like the choices the board to be 1, 2 and 4, whereas the board is incented to choose between 1, 2 and 3.
And because the employees are not a stakeholder and not even a shareholder, the right decision for the preferred investors was made.
In all of my posts, I keep pointing out that the problem with a Unicorn is that the board structure and ownership structure is not aligned with the interests of the employees who are not senior investors. For the most part, employees are junior investors. And in any liquidity event, the senior investors will be made whole before the junior investors.
The latest Unicorpse, Good, is a good example of the problems with boards. The employee interests and board interests are not aligned.
Preferred stock is different from common: Since Good’s venture-capital investors were first in line to be paid back, turning down the deal in March was less risky for them than it was for common-shareholder employees. Both the preferred shareholders and the common shareholders would do much better at $1.5 billion than at $825 million, but the preferred shareholders wouldn’t (and didn’t) do too much worse at $425 million than at $825 million. The common shareholders did much, much worse. As Felix Salmon says, “the huge problem is divergent incentives between common and preferred,” and the board of directors was aligned with the preferred.
Remember the preferred investors have different interests than employees. Employees want to maximize their investments. A startup is an attempt to make a lot of money. An investor has other interests and may want to liquidate a position.
For example, a preferred investor may want to free up capital for better investments, or may want to return money to LP’s or get out of an investment. And in those scenarios the Good exit, is a reasonable exit.
And so we have the perfect storm. The Good preferred investors took a calculated risk with limited downside when they turned down the 825 million deal, unfortunately, for the employees, the downside risk of not taking the 825 million dollars was much larger. When the deal closed, the preferred investors didn’t do badly. The employees got screwed.
The current funding environment is very dangerous to the valley and to employees.
As always, double check the fine print, understand the board motivations and make sure that you go into any situation with your eyes wide open.