Author Archives: Mukund Mohan

About Mukund Mohan

My discipline will beat your intellect

Leveraging your advisors for understanding the market dynamics before your customer development

One of the most effective ways to get smart advice early is to get a trusted advisor. Most companies I know get up to 3 advisors on board with different competencies, skills and expertise. Typically you’d like one advisor who has entrepreneurial background for customer and investor introductions, one for go to market expertise and one for technology excellence.

Once you have selected and recruited your advisors, I’d highly recommend a scheduled cadence to meet and consult your advisors (early on, once a month is good). Typically, most startups will (if all goes according to plan, which it never does, but nonetheless) need a new set of advisors every 18-24 months. Most advisors are paid in equity. Your advisor’s main role is to give you confidence, but many help with their strategic thinking or insights as well.

In this post I am going to talk about market dynamics using an example to help share a concept that I think you need to get advice from an external person for.

Let’s say you are trying to build a mobile application that replaces Siri or Google Now. This has been attempted before by many folks, so it is not a new idea, but I am taking a crack at shaping and outlining the landscape for discussion.

This will be a “smart assistant” that allows consumers to get personalized recommendations for many of their daily questions based on observed patterns on their phone – including usage of other applications.

Mobile Market Dynamics

Mobile Market Dynamics

In this particular case, there are 5 major “interested parties” – the consumer, who wants personalized recommendations, and needs the service, the app developers who have the data, the app store and platform which control the experience, the phone manufacturer, who makes the phone and the mobile carrier who provides the service.

Even though the first pass suggests that you should build the consumer service, focus on acquiring users and then get the app developers on board, it turns out unless you have the data (either from the platform or from the 3rd party app developers) you don’t have a valuable service.

Distribution might be easier for your product via the mobile carrier (if they choose to bundle it with the phones on their network) or even from the phone manufacturer, but unless you have many users, the carriers and the manufacturers don’t want to take a risk.

Consumers find that without their favorite applications (services) integrated into the platform, the assistant is of not much help.

So you realize it has to be the platform (Android, IoS, Windows phone, etc.) or the 3rd party app provider.

Since most consumers are using their favorite apps – such as Yelp, Uber, etc. the data is proprietary to that 3rd party app providers, who have little incentive to give you their “crown jewels”.

The best way to get the 3rd party app developers is to find a way to give them value, so they get consumers more engaged with their app, or acquire new users or monetize better.

While you still have to get consumers after you get the 3rd party app developers on board, that’s the “next problem” – the sequencing matters. Getting app developers quickly and the key (right ones, not anyone that will listen) ones is critical.

This is a good example of a market dynamic that typically you can get from an “insider”. Many of the seasoned investors will help you understand and navigate this landscape as well.

I would highly recommend you talk to potential advisors and help outline the problem statement so they can give you their perspective before you sign them up as an advisor. That way, you are able to gauge their expertise and understanding of strategy as well.

What do you think about this landscape? How would you analyze this better or differently?

Some awesome quotes from Pete Sampras’s letter to his younger self

Peter Sampras wrote a letter to his younger self. Great read.

Pete Sampras

Pete Sampras

“There will be times when you wake up in the middle of the night before a match craving crazy things like hamburgers and pizza. It’s because your body is missing something.”

“One day, everyone will be a nutrition freak. Be ahead of that curve.”

“Play hard, do it on your own terms and stay true to yourself. Do that, and you can’t go wrong.”

“It’s the people in your life — people like Tim — that will shape you. Appreciate them.”

How 3 peace-time founders are laying the foundation to transition to a war-time role

I have been at 3 board meetings this week. It is very apparent to me that we are in an environment where money is easily available to both the best and not so good performers. There are exceptional cases when the awful performer is also getting funded, but I want to avoid judging performance at the earliest stages.

Ben Horowitz popularized the term Peacetime CEO and Wartime CEO’s. We are at a really good peacetime – so the tactics for hiring, fund raising and customer acquisition are different than those when the market will turn – and it will. I cant predict when that will happen, and wont even know when it will start to turn.

I wanted to highlight the change in compensation strategy that’s being used by 3 companies who are preparing for when money gets more constrained, hiring is easier and customers are more cautious about their spending.

Most of the companies I know are moving from 60/20/20 split of base salary, performance bonus (based on individual goals) and stock options to

50/40/10 for marginal performers and

for the superstars, the compensation is 70/10/20.

The superstars have a total compensation that’s greater than the marginal performers.

PeaceTime CEO and WarTime CEO

PeaceTime CEO and WarTime CEO

What is being optimized is the bonus – for the marginal performers a lot more is being paid out on bonus – variable pay based on performance.

The logic behind the thinking is that the key players should not be poached – hence they are given a higher base than they would get outside, and are to be kept for the longer term – hence the incentive on the stock, whereas the marginal performers do not care about options that much.

Who are the marginal employees? Most of them are putting the “6 months, course at a coding academy” folks in the marginal employee pool. Not sure that’s correct, but that’s the approach being taken right now.

Going beyond “I have an idea” – a rigorous design of your experiment

The first step to your experiment is usually an idea. Either you or someone at your startup has an idea, which you want to determine is a good one or not. Having tried a framework to experiment your ideas, I’d say the crucial firs step is designing the experiment.

Brainstorming the idea over a casual conversation is usually the first step. The tendency among most startup oriented people is to complicate it and think of all the edge cases and 100% coverage, which is why documenting all the ideas is important.

This documentation need not be long drawn out or format, but needs to be written down.

The best way to do this is to continue using your multi-user messaging solution as before – Slack or HipChat, or Google docs suffices.

To design your experiment, you need to write down the 3 most important aspects of it.

a) Hypothesis b) Outcomes, c) Learning Objectives and d) Time frame

I mention hypothesis vs. assumptions for a reason.

Something that has yet not been proved to classify as a theory but believed to be true is a hypothesis.

An assumption is any statement that is believed to be true.

Until you know your idea will work or not, it is an experiment which has certain items you have to prove.

For example: If one of your customer service people have an idea – they believe as a startup you should send a summary email of the usage of the product every month so the customer understand how valuable your product is to them.

They believe this will reduce churn – the outcome you desire from this experiment.

Your hypothesis may be many all or some of which might be proven, yet others may be false – a) email summary reduces churn b) customers would like the email summary c) your email summary captures key pieces of information about the usage that customers care about and others.

Finally the learning objectives – this is important especially for failed experiments, but it will be useful if it succeeds as well – It helps plan future experiments and creates filters for ideas that come next.

Designing your experiment involves documenting these 3 important items, usually by the person who has the idea. Even an email will suffice, but documenting it is key – even an email will suffice.

Finally in designing the experiment, the time frame how long you are going to run it is important. First so you dont have too many experiments running at the same time, which might skew results, but second so that you can give each experiment the due time to determine if it truly failed or succeeded.

I was thinking of an acronym – HOTEL – Hypothesis, Outcomes, Time Frame, Experiment Design and Learning objectives, but it does not quite fit. I’d love some suggestions on if you can come up with a better acronym of if you believe I have missed documenting anything.

How to design Experiments

How to design Experiments

Is just being exposed to interesting things enough for curious kids? #parenting #personal

My friends and I have an ongoing debate about programming. They would like their kids to learn programming, but they say their kids dont enjoy it. Regardless of gender, they seem to have an aversion to development.

I am a geek at heart and love programming. I am not good at it, but I enjoy it. I dont get enough time to do it, but it shows on my face when I am developing something or learning a new language.

I have 4 kids, and we are a very geeky family. My daughter, 13, loves mockups, is building apps and is a pretty decent (for a 13 year old) front end dev – She does HTML and CSS with ease and is okay with Javascript. She would ask me to do most of her database development, which I was happy to do.

Kids still love selfies

Kids still love selfies

She recruited my son to learn SQL and he has been tasked to write the DB schema – for someone that does not understand the difference between Integer and Date, much less the phrase datatype, he seems to be struggling through it, but enjoying it.

All 4 of our kids have a laptop and the older ones have their own cell phone – they are all the same, except for my oldest daughter. They all have Surfaces, while my daughter has a MacBook Pro.

This is a point that many of our friends dont get – she’s only 13 or he’s only 11.

They are too young to have a phone and they will be addicted to it all the time is what I hear from them.

That’s a risk for sure. I know that. It is a risk we have chosen to take, since the exposure and benefits far outweigh the negative consequences.

Although my kids are 13, 11, 9 and 9, they seem to enjoy learning to code. They got started without Scratch, I would take 30 min to explain a few concepts, then turn them loose on a bunch of videos.

Then of course there’s Google. When they found out their dad’s limitations – syntax, libraries, etc. – they discovered that Google was their friend. Their first instinct is to Google and cut and paste. Apparently, according to my son, even the best programmers do it – so there.

Many of the basic concepts of computer science are not clear to them. They “kinda” understand that there’s a database and a user interface and a “middle layer”, but that’s as far as it goes.

Their programming skills are very basic (no pun intended), but I enjoy talking to them about programming.

The one thing I have learned is that if you just expose them to various activities and ensure that they are curious enough to learn, they will.

The fact that I dont monitor their PC usage (We do have a basic filter to make it child friendly, but we dont restrict usage) is also a big point of debate among my friends.

I dont, because I believe it does not matter. If you keep talking to them daily about the positives and negatives, they will learn to make choices. Sometimes, they make the wrong choices, for sure, but that’s unavoidable.

The only thing I do to give them the love for programming and coding is to be passionate about it when I explain things to do (since it comes naturally to me that’s easy).

I am sure if I were a finance person on Wall Street, my passion for that would show as well, which means they’d get that instead of programming.

The “problem” is that they have multiple interests – my daughter loves her piano and singing – she’s a good vocalist, my son is really passionate about his cricket. My youngest loves drawing and is a better artist than I am even now and the middle one loves sports of any kind.

I call it a “problem” with air quotes since they dont get enough time to spend on programming. So I make it a point to have them see me do some coding and development once a while. Which gets them excited again to do something new.

I am not sure if exposure, wearing your enjoyment on your sleeve and unrestricted learning models is sufficient, but it seems to work for us.

The first step to disciplined experimentation is to capture all possible ideas

When you have a great startup culture and hire awesome people at your startup, you will attract a talent pool that has tons of ideas all the time. Many of those ideas may not be relevant to your startup, but I firmly believe that it is not only the product managers, engineers or marketing folks that can have ideas that have an impact on your startup.

If you create an environment that encourages active listening, experimentation and risk taking, you will have a good mix of innovation all around at your startup.

One of the most effective ways to encourage is the impromptu “Lets just chat” weekly sessions that I see at many new startups. These are not larger company-wide all hands sessions, but smaller sessions usually hosted by a very junior, but engaged individual at your startup.

Most times they are held with 5-7 people at your kitchen or during lunch or casual drinks in the evening. The ideal size of the team is less than 10 is what I have found.

Ideas pop into people’s heads at all times. I tend to get most of my ideas when I run. Many people get them when they are stressed, others during vacation, and still others in the shower.

Ideas require a stimulant, and while I have not read the research yet, I believe one of the key ways to stimulate ideas is to exercise or rest your mind.

Capturing these ideas to whoever it occurs is possibly the best start you can have. Many people use idea management software like User Voice or Brain Storm.

I think more people are starting to use Slack for idea capture at their startup. I have seen it with 3 different startups and it is starting to become a thing.

Slack for Ideas

Slack for Ideas

The challenges with Slack are that idea rating, idea management, voting, tracking deployments are pretty challenging.

I would highly recommend you use the one app / messaging platform that EVERYONE in the company uses (possibly email, and if you have Gmail, then use plugins to manage emails to ideas) and put them into a single place.

The best way to review the ones that will have impact is to understand the value of that idea in the context of your key milestones. Some of them will impact your milestones immediately, others will improve aspects of your stated goals. Still others may do neither.

The most important framework I have used is to understand the effort and impact.

Impact versus Effort Matrix

Impact versus Effort Matrix

I think putting the ideas generated into the matrix and focusing on the ones with most impact and low effort (has to be delegated) tends to give you the ability to have good value.

A framework to think about experiments for your startup

Experimenting is at the core of building and tying new ideas. A opposed to having a clear problem to solve, experiments are designed to “try” out ideas that you have and yet know if they will work or not.

At most startups, I notice two primary “ends of the pendulum” issues. Most (over 90% of startups) dont run enough experiments. The rest (< 10%) run too many experiments in parallel.

If you fall into the first category, then my only suggestion is to think about experimenting and commit to doing one. The AirBnB blog is a great place to start, in terms of understanding the user experiments they run. They actually have a experiment reporting framework, which shows how evolved their thinking is in terms of this facet of work.

I also am a fan of the “test and learn” mindset. Since I believe that working on your startup is more a journey in self realization than of markets, problems and customers, it is important to keep learning. I do also believe the best way to learn is to try and do small experiments which you can scale.

I have been a fan of disciplined experimentation.

This post is about the < 10% who run too many experiments in parallel. That’s the biggest challenge I see with startups that hire amazingly entrepreneurial talent for their first few hires.

Since each of the first 5-10 employees are entrepreneurs themselves, they all tend to run multiple experiments, either with product, marketing, customer acquisition, sales, etc.

The framework I have for thinking involves 3 “sets of steps”. I call it “Trail, Nail, Scale”.

The “Trail” comprises of 5 steps, the “Nail” comprises of 3 steps and the “Scale” comprises of 2 steps.

Here is a visual to think about it.

Trail Nail Scale Disciplined Experimentation

Trail Nail Scale Disciplined Experimentation

Obviously this is very early thinking, but I’d love your feedback.

The way to think about experiments is you to pass through gates and assign the appropriate resources at each stage and have a “rough sense” of what you are trying to achieve. If you know exactly what you want to get out of your experiments, you are not “experimenting”.

What I have noticed is that the 3 stages end up being a funnel. There are many experiments you run, a few of them you will nail and a fewer of them you will scale.

If you have 100% of your “experiments” when you start, (on the left of the graphic), then 20% (or less) will be nailed and 10% you will scale.

In terms of allocating time and resources (if you dont have a large team as a startup, allocate your time), 10% is spent on “Trailing”, then twice that time or 20% on nailing and 70% on scaling.

There are many questions that this throws up, which I want to address over the next few days.

1. How many experiments should you run at the same time?

2. How do you define the success of an experiment?

3. How do you internalize and document the learning from your experiment?

4. How much “money” should I spend on trailing? How about in nailing?

5. How do I leverage lean principles into this thinking of Disciplined Experimentation?

Anyway, I’d love your feedback on this framework. As I share more of my work, which I am interviewing people in larger (Unicorn) startups at, I will also give you some case studies to see what they learned.