Common Lessons from running Growth teams, Investing and Genomic Biology - a hypothesis is a liability

 “When someone is seeking, it happens quite easily that he only sees the thing that he is seeking; that he is unable to find anything, unable to absorb anything, because he is only thinking of the thing he is seeking, because he has a goal, because he is obsessed with his goal. 

Seeking means: to have a goal; but finding means: to be free, to be receptive, to have no goal. You, O worthy one, are perhaps indeed a seeker, for in striving towards your goal, you do not see many things that are under your nose.” - Hermann Hesse

There is a hidden cost to having a hypothesis. It arises from the relationship between night science and day science, the two very distinct modes of activity in which scientific ideas are generated and tested, respectively. With a hypothesis in hand, the impressive strengths of day science are unleashed, guiding us in designing tests, estimating parameters, and throwing out the hypothesis if it fails the tests. But when we analyze the results of an experiment, our mental focus on a specific hypothesis can prevent us from exploring other aspects of the data, effectively blinding us to new ideas. A hypothesis then becomes a liability for any night science explorations. The corresponding limitations on our creativity, self-imposed in hypothesis-driven research, are of particular concern in the context of modern biological datasets, which are often vast and likely to contain hints at multiple distinct and potentially exciting discoveries. Night science has its own liability though, generating many spurious relationships and false hypotheses. Fortunately, these are exposed by the light of day science, emphasizing the complementarity of the two modes, where each overcomes the other’s shortcomings.

The gorilla experiment

Many of us recall the famous selective attention experiment, where subjects watch a clip of students passing a basketball to each other. If you have not seen it, we recommend watching it before continuing to read. 

As you watch the two teams in action, your task is to count the number of passes made by the team in white. About halfway through, a person dressed up as a gorilla enters the foreground. The gorilla pauses in the center, pounding its chest with its fists, before exiting to the opposite side of the frame. Surprisingly, half of us completely miss the gorilla, as we are focused on counting passes, even though hardly anyone overlooks it when simply watching the clip without the assignment.

We believe that a similar process happens in various phases of life. 

Growth teams

Growth teams are laser focussed on hypothesis building, executing on the hypothesis, tracking progress against goals measured using metrics assumed to be impacted by the hypothesis. Some of these experiments lead to metrics wins and some of them not so much. It is equally important to distill learnings from the wins and the failures and articulate them to build the next hypothesis. This kind of learning at the project level, aggregated produces the future direction of the team and informs the organization level strategy in growth companies. Hence, the failures even though they seem innocuous or wasted opportunity at certain points serve the valuable purpose of informing future roadmap direction and strategy for the organization. This helps form the future organization level hypothesis, goal and metric. Also in committing to a hypothesis based on these learnings, there is also a pseudo commitment about not investing on other hypothesis (in case of limited team bandwidth). Hence the process of distilling the learnings in growth teams and the quality of the learnings serve the lifeblood of the organization. 

Investing

Similar idea can also be applied to active portfolio managers who are making certain bets driven by hypothesis. It is very important to shed biases and question each and every assumption behind hypothesis building. 

Interestingly this concept formalized appeared in this journal on genome biology. I merely tied this concept to other spheres of life. 

Comprehensive vs Interesting tradeoff

 Being comprehensive vs interesting:

You might want to give all the details, explain all the things fully in one breath. But you risk overwhelming your audience.

Optimize for being interesting instead. If you hook their interest you’ll earn the chance to share more later. 

How to ask great questions as a PM ?

 1)

Less “How will we build this?”

More “How will we differentiate?”

2)

Less “How to enforce accountability?”

More “How to foster ownership?”

3)

Less “What problems can we solve?”

More “What problems are worthwhile?”

4)

Less “What is the 3-yr roadmap?”

More “What is the 3-yr strategy?”

5)

Less “How to run growth experiments?”

More “How to get more distribution?”

6)

Less “What is the process for X?”

More “What is the purpose of X?”

7)

Less “Does this team run well?”

More “Does this team learn well?”

8)

Less “What are top user requests?”

More “What are top user needs?”

9)

Less “What is the template for Y?”

More “What is my goal with Y?”

10)

Less “What is the schedule?”

More “What are the priorities?”

11)

Less “Are all stakeholders happy?”

More “Are all stakeholders aligned?”

12)

Less “How many resources do we need?”

More “What is the marginal impact?”

14)

Less “How can I use metrics?”

More “How can I use psychology?”

15)

Less “Who will write the blog post?”

More “How can we create excitement?”

16)

Less “What will get me promoted?”

More “What will get the buyer promoted?”

17)

Less “How did Google solve this?”

More “How are we different?”

18)

Less “What does the CEO want?”

More “What does the CEO know?”

19)

Less “What are competitors saying?”

More “What is their strategy?”

20)

Less “What is rational for users?”

More “What is natural for users?”

For the original content and discussion, please read Shreyas's thread

Ellsberg Paradox and Option value of investing

 Ellsberg Paradox 

People prefer to take risks in situations where the odds are known, rather than a scenario where the odds are unknown - even when the latter scenario has the guarantee of a positive outcome (its just that the magnitude of the outcome is unknown). Its often used to evaluate how people have an aversion to ambiguity. 

Where do the traditional financial tools fall short ? 

In traditional investing, the most common financial tool for valuing a company is DCF model (discounted cash flow model). Under this methodology, investors attempt to accurately model out the discrete financial metrics of a company over a finite period of time, and discount the cash flow generated to determine the appropriate valuation for a company.

The issue is though that in real investing, businesses have embedded options which have unknown outcomes everywhere. DCF is terrible at valuing these businesses which have both : 1. uncertain payoff magnitude and 2. uncertain timing as to when it will occur. Examples of such options : 

• Amazon is able to extend its dominance on one ecommerce category(books) to multiple categories
• Amazon is able to extend its dominance in ecommerce to build the largest retail search engine in the world and draw advertising dollars
• Google is able to leverage its technology prowess in building scalable and reliable search infrastructure to build Google Cloud and democratize building distributed systems technology. Same for AWS and Azure
• Apple launching Wearables segment (Watch, airpods, etc) using its expertise in building iphones

For each of these successful options, there are multiple failed investments like Fire Phone, Google's communication apps, etc. However, in net all these embedded options have generated multiples of shareholder value which would not have been able to be correctly valued through DCF. 

This paper articulates this concept in detail : Get real, using real options in security analysis

This diagram illustrates how the valuation breakdown of such companies progresses

Some of the parameters to evaluate such businesses are

Management 

• Superior capital allocation 
• Access to cheap capital from markets or through high profit margin businesses
• Execution track record
• Ability attract top talent in the industry

Business

• Strong moat
• Economies of scale
• Economies of scope

Evolving markets

• New trends of user behavior and patterns
• Uncertainty

No wonder FAANGs check several of the above boxes and continue to generate superior returns for their shareholders. 

References

1. Hayden Capital Quarterly Letter Q3 2020

2. Get real, using real options in security analysis

Return to India - Financial Guide

Scenarios

- Planning to return to India 

- Keeping US accounts as a non-resident alient

What are the implications of moving on brokerage accounts ? 

• Allow reasonable access, under non-resident alien terms (with a W-8BEN). There may be some restrictions on the type of thing you can trade, and you may have to send paper forms in for some things that could otherwise be done online, but overall the account functions relatively well. Buy and sell, and things like 401ks, IRA rollovers and Roth conversions are still available.

• Limit activity as noted upthread. That is, you can sell existing holdings on your own schedule but not buy any new ones. Over time, that makes the account hard to manage (rebalancing, for example).

• Force you to close your account and move your money out.

Which occurs seems to to depend heavily on which country you move to, its tax treaty status and regulatory framework, and so on.

What are the tax implications ? 

It depends which country you live in. If it has an income tax treaty with the US, you will pay US tax on dividends at the treaty rate. It's typically 15%, but could be higher, perhaps 25%. A few countries have a 10% rate. If it has no income tax treaty, you will pay 30% in US tax on dividends. Vanguard will take the correct rate automatically through withholding once you've sent them a W-8BEN. It's a flat rate tax, so you cannot recover any of it from the IRS. You might however be able to use it as a credit against local income tax on these dividends.

No US capital gains tax implications. The US does not tax capital gains for nonresident aliens. Watch out though for US estate tax. If you country lacks a US estate tax treaty, your heirs could face 26%-40% of the balance of your holdings above $60,000 should the worst happen. This applies also to any IRA or 401k accounts you hold in the US. The US estate tax treaties with Ireland and South Africa are reportedly deficient, so best not to rely on those.

What about tax returns ? 

If you're neither a US citizen (or resident) or a green card holder, if you have to file anything it's always a nonresident alien return, so a 1040-NR.

In general though, you should have no need to file one. Provided Vanguard applies the correct US tax withholding on dividends, your US tax liability will exactly match your US tax withholding, and in that case you don't need to send any US tax return. See 1040-NR instructions for more.

If for any reason you do have to file a 1040-NR, perhaps Vanguard overwithheld relative to your treaty rate, you'd only have to declare your US source income on that. You don't tell the IRS anything about your non-US earnings, interest, or anything else financial happening in your (non-US) country of residence on that form. 

The IRS will only issue tax refunds in USD, either as a cheque or ACH payment to a US bank account.

Some tips

1. Remittance from brokerage accounts to directly foreign accounts through transferwise if possible. I am not sure this works. Seems like a hassle. 

2. Interactive Brokers seems to have a global presence

3. 

Appendix Links

1. United states income tax treaties 

2. India tax treaty documents 

3. US Estate and Gift tax treaties

4. Interaction of Indian and US tax laws

5. Keeping vanguard accounts as a non-resident alien

6. Bogglehead link on non-residen alien taxation

7. Beware the taxation angle if you want to invest in direct foreign equities from India - Reddit thread

8. Taxation for international residents

9. Non-US investors guide to navigating US tax traps

10. A guide to selling US property for foreign residents and expats

Outlook for the Cloud Market

Satya's description of why Cloud is a secular trend from Microsoft earnings call

The way I think about the computing landscape going forward is if you sort of said at the highest of levels today as a percentage of GDP, tech spend is 5%. We think it will double in the next 10 years. And if anything, this pandemic perhaps has accelerated that doubling.

And in that context, what's the large — the most secular need, it's the need for distributed cloud infrastructure. It's both needed for modernizing existing applications you have, and so that's why, by the way, 20% penetrated so there's more 80% that needs to move. But more importantly, there's going to be new application starts which need infrastructure. And so if you sort of add those up, I think that we're still in early innings.

There will be, between quarters, volatility, all of the points that Amy made even earlier. But we think distributed cloud infrastructure is the most important layer. But the way we have approached it is not to just think of that layer in isolation but the data layer work we do composes, the AI layer composes and more importantly, our SaaS applications, whether business applications, Power Platform, Microsoft 365, all reinforce that same modern tech stack. So I would still say that digitization in its — this new tech stack is in its very infancy. - Satya Nadella

Milestone moment

This is the first year when Azure revenue is larger than Windows revenue. Azure revenue has grown to 17% of the revenue. 

Google's Cloud Strategy

• Six priority industries : healthcare, retail, media, finance, manufacturing, public sector
• 5 major geographies
• 4 customer segments
• Data processing, analytics, AI/ML - differentiation
• Migration of legacy datacenters to google cloud and cut in IT spending and infrastructure. eg : Nokia migrating 30 data centers to the cloud across 12 countries
• Google meet saw a peak of 7.5 billion daily video call minutes

How Big Tech Makes Money - Q3, 2020

Apple 

• Net sales : 64.7 billion
• Product : 50.1 bn
• iPhone : 26.4 bn (33bn in Q3, 2019)
• Mac : 9 bn (> Q4 2019 revenue 7.56 bn)
• iPad : 6.7 bn (> Q4 2019 revenue 5.9 bn)
• Wearables :7.8 bn
• Services : 14.6 bn (> Q4 2019 revenue 12.6 bn)
• Cost of sale : 40 bn
• Operating expense : 10 bn
• Operating Income : 14.7 bn
• Net Profit : 12.7 bn
• Cash in hand ~50 bn
• Commentary : Overall revenue and profit is constant from 2018 and 2019. However, stock price has gone up as the company has reduced the number of outstanding stocks through buy backs. However, PE has gone up from 12 to 35 and future growth seems to be priced in, until Apple opens up new revenue streams. Apple shared no revenue guidance for Q4

Amazon

• Net sales : 96 bn
• Operating Income : 6.1 bn
• Net income : 6.3 bn
• All the above figures are higher than Q4 2019
• Investing in Amazon provides significant international exposure : NA 62%, International 26% and AWS 12% of net sales. YoY net sales grew by 39%, 37%, 29% across those 3 categories
• Online stores 48 bn, Physical stores (includes whole foods) 3.7 bn, Third party seller services 20 bn, subscription services 6.5 bn, AWS 11.6 bn, Ads 5.3 bn
• Online stores grew at 37%, physical stores at -10%, third party seller services at 53%, subscription services at 32%, AWS at 29% and ads at 49% YoY
• Commentary 
• Physical stores slowdown is expected due to Covid, but all other categories grew faster than AWS. Net sales increased 37% YoY. With Covid-19 expediting Amazonification of the world, this will be an unprecedented holiday season. Amazon expecting 112bn in net sales in Q4. 
• Some of the demand from COVID like grocery, gloves may not recurring next year. But COVID is increasing engagement, retention of the Prime membership program and usage is growing across different categories
• Prime videos is a very good acquisition channel for Prime members - > higher membership renewal rates and higher engagement
• International has been profitable for 2 quarters now

Microsoft

• Revenue 37.2 bn (12% growth)
• Productivity and business processes : 12.3 bn (11% growth)
• Office commercial products revenue growth of 9% (Office 365)
• Office consumer products revenue growth on 13%
• Linkedin 16% up
• Dynamic products up 19%
• Intelligent cloud 12 bn (20% growth)
• Azure up 48%
• Personal Computing 11.8 bn (6% growth)
• Windows OEM down 5%
• Windows commercial products up 13%
• XBox content and services up 30%
• Surface revenue up 37%
• Search advertising down 10%
• Net income : 13.9 bn
• 9.5 bn returned to shareholders, 5.3 bn share repurchases and 4.2 bn dividends

Google

• Revenue - 46 bn (up 14% from Q3 2019)
• Search ads 26.3 bn
• Youtube ads 5 bn
• substantial growth in direct response
• brand advertising (create brand and interest)
• YTs strong watch time growth enables advertisers to reach people who they cant reach on TV
• Google network 5.7 bn
• Cloud 3.4 bn
• Data processing, analytics, AI/ML
• Migration of legacy datacenters to google cloud and cut in IT spending and infrastructure. eg : Nokia migrating 30 data centers to the cloud across 12 countries
• Google meet saw a peak of 7.5 billion daily video call minutes
• Six priority industries : healthcare, retail, media, finance, manufacturing, public sector
• 5 major geographies
• 4 customer segments
• Other revenues (YT subscriptions, Google play) 5.4 bn
• Other bets 178 mn
• TAC : 8.16 bn
• Net income - 11 bn (operating margin 24%)
• Losses on other bets : 1 bn, nicely masks the operating margin from 27% to 24%
• Cash on hand : 133 bn
• International exposure : US 21.4 bn, EMEA 13.6 bn, APAC 8.4 bn, Other americas 2.6 bn
• Google has greater than 50% ex-US revenue exposure
• PE (1.1 tn / 50 bn) ~ 22. Alphabet looks cheap going forward given it is growing revenue at double digits compared to the rest of big tech. 
• Youtube music has 30 mn paying customers and Youtube TV has 3 mn paying customers
• In Q4, 2020 GCP will be its own reporting segment
• Commerce
• Shopping listings available in 48 countries
• Google checkout option opened the platform to paypal and shopify integration
• advertisers in Youtube at the mid-funnel level
• Earnings call transcript

Facebook

• Revenue : 21.4 bn (22% growth)
• Operating income : 8 bn (operating margin 37%)
• Cash on hand : 55 bn
• 200 mn businesses, 10 mn active advertisers, 40 mn people viewing a business catalog every month, more businesses are doing things online due to COVID
• Earnings call transcript

Commentary

• Big Tech companies are generating revenue worldwide. All of them have considerable international revenue exposure. 
• Amazon (37%), Facebook (22%), Google (14%), Apple (~flat) - revenue growth
• Facebook (37%), Google (24%), Microsoft (37%) - operating margin
• 265 bn in revenue, net profit of 52 bn, operating margin of ~20%, market cap ~7.5 tn
• Cloud is an extraordinary secular trend and all cloud players are gaining from IT spending and cost cutting
• Digital advertising continues to be a secular trend - TV dollars, CPG marketing budgets, retail goods moving online all driving this trend, organic small businesses trying to reach customers online

The Firehorse Effect

• In the early 20th century, a horse pulling a wagon would all of a sudden gallop towards a burning building nearby, endangering itself, the driver, & the passengers. What was the reason for this peculiar phenomenon? And why does this matter today?
• Fire has been one of the biggest dangers that humans have faced ever since they started living in structures. In the olden days, firefighting was a community responsibility. When a fire broke out, the people in a town or a village would form a "Bucket Brigade". 
• Visualize a double-line of people passing buckets of water from a nearby water-source to the fire, and sending empty buckets back to be refilled. That’s a Bucket Brigade. Eventually, tanks of water, hand pumps, & hoses became the preferred firefighting equipment. 
• Then came steam pumps, more powerful & efficient. Great, but the equipment got heavy & it became difficult for firefighters to pull it to wherever the fire was. What to do? 
• Enter horses. It wasn’t an easy change. Horses had to be trained to reliably run towards a fire. They also had to be strong. As horses became more commonly used to pull fire engines, places like Detroit even created a Horse College, along with report cards for each horse (!) 
• What happens when one is trained to do a job well, is systematically evaluated, & rewarded or punished based on job performance? One often gets rather good at that job. Same with these firehorses. 
• At some point, a firehorse would be retired from the firefighting job & given the job of pulling wagons on the street. A new job! Things were generally fine in the beginning. 
• But whenever a former firehorse heard a fire alarm or felt the presence of a fire nearby, it instinctively galloped towards the fire: terrorizing its drivers, passengers, & owners. 
• This firehorse did a rather poor job in its new context due to the very behaviors and patterns that were reinforced in its old context. Twitter, this is the Firehorse Effect. 
• The Firehorse Effect is why some accomplished business leaders fail to inspire, create a compelling strategy, eliminate drama, or rebuild the culture when they take on a leadership role in a new organization. The Firehorse Effect is also why a manager with a string of prior successes is just unable to execute at your startup. 
• What can be done about the Firehorse Effect? As with most such things, the solution needs to be grounded in Self-awareness, Organizational-awareness, & Sound Management. Leaders in a new setting should regularly think about the Firehorse Effect. 
• Leaders in a new setting should take the time to observe & learn. Doing is important, but doing without a deep understanding of one’s new role can be frustrating or even fatal. 
• The leader should invite people to challenge them. Ask "X has worked for me in the past, will it work here?" And the leader's managers & mentors need to help accelerate this process by candidly sharing organizational context & feedback during the leader's early days. 

This term is coined by Shreyas Doshi, I heavily recommend reading his writing for organizational and leadership development.  

Product Metric Primer

 Metrics are key ways to track progress against north star missions half over half. When conceiving your metrics, consider each of these categories & pick the right metrics across them.

Product metrics categories

1. Health metrics

2. Usage metrics

3. Adoption metrics

4. Satisfaction metrics

5. Ecosystem metrics

6. Outcome metrics

Health metrics

Is the product available & performing in the manner that users would reasonably expect?

Examples:

latency, initial load time, uptime, data loss rate, error rates, cpu utilization, memory utilization

Usage metrics

How are users using the product?

Examples:

time-of-day/day-of-week trends, top N actions, funnel metrics, help docs usage, retention, password reset, queries per second, queries per caller/channel

Adoption(Growth) metrics

Is the product (along with its key features) being used as much as we’d hope and in the ways that we’d like?

Examples:

active users, dap:map:wap, N of M day usage, strategic feature adoption trends, free-to-paid conversions, number of callers, retention

Satisfaction(Engagement) metrics

What is our customers’ overall sentiment towards the product or its main features?

Examples:

overall CSAT, new feature CSAT, support CSAT, weekly active thread, time spent per day, likes per user, comments per user, riders taken per day, weekly riders per rider, weekly rides per driver

Ecosystem metrics

What is the macro state of the product within the domain in which it operates?

Examples:

share of wallet, 3rd party integrations, industry rank, marketshare within target segments, % of TAM, category rank, ratio of buyer and seller side in 2 sided marketplaces that define the ecosystem health

Outcome metrics

What overall results are we seeing from this product?

Examples:

revenue, margin, revenue per user, active users, marketshare, transactions, % of Fortune 1000 covered,...

How to be likeable as a leader

"Some people cause happiness wherever they go; others whenever they go" - Oscar Wilde

People respond not only to the message but the messenger. Being likeable attracts, being unlikeable repels. Dont fake it, find your version of it.

1. Develop the right mindset of valuing the person and having the right mindset of exercising positive influence. Smile more than you frown, encourage more than you criticize. Before every meeting, say to yourself, I am happy to be here and I am happy to see you and then act that way. 
2. Seek and highlight similarities. Similarities in background, experiences and values tend to have the strongest effect. Similarities tend to be more impactful, the more rare the commonality. When you do find similarities, look for authentic ways of using inclusive terms like we, us, our. That subtly and positively reinforces your connection. 
3. Look for positive qualities and highlight them in a genuine way. You can highlight it by framing it as a question. If you admire their perseverence, that sounds like a significant ordeal you got through, how did you manage it ? 
4. Give credit to relevant qualities necessary to advance your priorities. If you expect someone to be dismissive of their priorities, you can say something like this : I have heard you are an open minded person who weights all the facts. That will spark their association to be open minded and you bring that quality to the front of their mind and trigger their tendency to act more consistently with that quality.