Evening out watching Rambo, last blood

From Sujit on trading

  • not necessary to get numbers further back than six months
  • stock market subjected to fractal distribution
  • it is possible to generate returns of up to 140% per year by trading on stocks that are moving within a range
  • going all in on each position each time leads to a very low Sharpe ratio
  • Sharpe ratio should be calculated separately for method and for SnP benchmarked against US treasury interest rates. The difference is the actual returns

On Rambo Last blood

A movie is a reflection of the culture and attitude of an age. Rambo was a very popular cultural icon during the eighties and the early nineties when memories of the Second World War and the Cold War against the communist were still very fresh in the minds of the people in America.

If you looked at the world today through the eyes of someone like Rambo, you would have been able to easily draw facts to back the narrative painted by Trump prior to being elected president.

When operating in an environment of uncertainty, a decision maker formulates multiple often competing narratives in the head that best explains majority of the facts presented. He calibrates the weightage assigned to the probability of each narrative as new pieces of data become available. He simultaneously utilizes multiple ones that are assigned high plausibility in his decision making to strive for the best possible expected outcome . It is a cognitively demanding iterative activity that goes on indefinitely.

  • common themes between movie and Trump’s narrative
    • Mexico drug cartels
    • Mexico prostitution rings
    • The world is a dark place
    • illegal border crossing
    • poor border fence
    • white male
    • Rust belt
    • Protagonist is in his 70s
    • Freedom fighter who fought the communist in Vietnam and Russia
    • guns and lots of blood
    • man of steel
    • manifest destiny
  • Cognitive biases
    • Narrative fallacy
    • Framing bias
    • selective bias

Related readings

  • Expert political judgement, Philip Tetlock

Thoughts on avoiding the greater fool theory

Once a project’s mission statement is defined, it becomes easy to determine when to stop further iterations. 

Below are the listed of statements I periodically revisit when pursuing GetData.IO’s mission to help people make good decisions by making data gathering simple and affordable. 

Hypothesis 1: People no longer need make good decisions.

Hypothesis 2: People no longer need data to make good decisions.

Hypothesis 3: People no longer find it hard to get data.

Hypothesis 4: We have exhausted all known approaches to lower the cost of data gathering to an affordable range. 

Hypothesis 5: We have exhausted all viable approaches to reach people who need to make good decisions.

Hypothesis 1 and 2 are existential questions, while hypothesis 3 focuses on substitute availability. These are out of our control. The only thing we could do is monitor for changes.

Hypothesis 4 and 5 focuses on economic feasibility. These we will fully focus our efforts on. Once we eliminate all none viable options, whatever remains will be the limitations we must accept and live with. 

It is useful to note the lack of any mention on funding. The underlying assumption is that every successful iteration necessarily unlocks resources from the environment which is then fed back to further the compounding process. The discipline is to minimize wastage. 

Relying on external funding is like utilizing margins during day trading. While earnings get amplified, failures tend to be really spectacular. One additional drawback is that they tend to mask critical flaws in the short run leading to the commonly observed greater fool phenomena in the financial markets.

https://GetData.io/about-us 

Learnings on enterprise sales – SVB and SalesForce workshop

General observation on networking

  • There were a total of 40 attendees and we received a total of 2 name cards – net conversion rate 5%
  • Social expectation during a networking session is that you can approach people to talk
  • Start with a clearly one liner if asked about your project
  • actively direct the conversation to them and spend more time listening
  • make sure to bring name cards

Compare and contrast small businesses and medium sized businesses

  • Small businesses
    • acquiring new customers
    • accessing to investment capital
    • not enough time
  • Medium sized business
    • acquiring new customers
    • achieving work life balance
    • not enough time

Sales best practices for founders n SMB sales leaders

managing leads process

  • Develop a concrete definition of a lead and make sure all employees understand it.
  • Install an effective Customer Relationship Management (CRM) Tool.
  • Track the source.
  • Distribute your leads quickly.
  • Nurture your leads and get your Sales team excited about every prospect.
  • Treat your prospects like customers.
  • Measure everything you do.
  • Hold regular meetings with your sales staff and anyone else involved in the sales process.

build out sales stages n codifying it

standardized sales process see up to 28% increase revenue

  • A consistent schedule: You should know when and how often you are going to be
    performing your sales activities.
  • A strong message. You should know what you are going to say and at what point in the
    process you are going to say it.
  • Mixed media plan. Use multiple channels to convey your message and mix it up – emails and phone calls are the most common, but perhaps it’s appropriate to reach your potential customers on a favorite social channel.

focus on boosting sales rep productivity

  • Make ongoing sales coaching a priority.
  • Advance prospects faster with Value.
  • Evaluate & re-evaluate sales processes.
  • Embrace Automation and technology.
  • Use Analytics to always be improving.

Observations on Sales force

  • UVP helps users get data from spreadsheet into systems that allows easy sharing within the sales team
  • Sales force comes with Gmail integration
    • disrupted CollaSpot’s business model
  • Social proofing: Video where users talk about the benefits they get using a tool
  • Extending existing business lines
    • current base – market segment with higher margins using enterprise sales acquisition strategy
    • new business line market segment with lower margins using self service model
      • USD25/user/mth package self service tier
      • acquisition strategy is not well defined yet
  • partnership with companies to value add for their customers
    • sales force partners with SVB to throw event to teach SVB clients how to better do sales.
    • Helps with SVB retention.
    • tap into Silicon Valley Bank’s extensive distribution network

Alessandro Chesser, VP of Sales Carta

Key regrets

  • Not investing early enough in sales operations.
    • CRM system very important. Cleaning up the mess later is going to be a headache
    • Dealing with duplicate accounts are pretty painful
  • Don’t over engineer sales process up front.

Enterprise sales versus organic adoption

Organic signup forces u to put your whole pitch online for easy copying. A sales rep can sell the vision to extract higher margins. Deliberate back and forth. Use the demo form to generate leads for sales rep

Getting the enterprise sales engine started

  • The more data you have the better your decisions. Create baseline and iterate over it over time.
  • Marc Benoff on Closing. When he joined eshare there was no product. His job was to get potential customers excited about the future of their own company. The vision and the pitch is so important. Get their feedbacks.
  • Don’t sell to far ahead and can’t deliver. Need to spend time with engineers to know what can be delivered. Always keep in mind a 1 to 2 months implementation cycle. Only sell ahead when is early stage company but don’t over promise. If failed to deliver, will create bad PR
  • Always iterate on the vision of the company and the pitch to figure out what resonates with your potential buyers
  • Early stage startups can utilized VC to generate inbound leads. The more money raised the more inbound happens with PR that follow each fund raising events

Scaling the sales organization

  • Make sure one person can bring in 100K ARR before replicate and scale up sales process
  • When is Sales cycle replicable? Use revenue as signal. Driving 100K ARR per month is a good signal. Gut feeling. When deals leads are starting to slip through the cracks
  • Charge via ACH instead of credit cards. ACH is more scalable, since the latter tends to expire.

Structuring and managing the sales team

  • For smooth transition from inbound sales to outbound sales first create demand from SDR first before hire sales team.
    • Not all sales people are comfortable with generating sales leads
  • Extremely important to make that SDR hire early. Utilize tools like OutReach.IO
  • SDR – handle email marketing and phone calls. Uses pitchbook. Scrape Startup names and email addresses. Thousands of emails a day to generate leads.
  • Ensure at least sales development representatives hit at least 60% their quota. If hitting below, it means u have over hired. It’ll create very bad culture like sales leads stealing if not hitting above quota.
  • Have sales people prioritize and focus on closing and not be the jack of all trades.
  • Promote Successful SDR  to become sales reps. They will be well positioned for success.

Mapping the hiring process for the sales leader.

The mistake is hiring really experienced and expensive people who are not willing to roll out his sleeves. You need someone who is really willing to get his hands dirty to go out to close sales. Industry experience is important, will ensure sales leader motivation level. Since he knows what is broken

Balancing the functions of marketing and sales

  • Early in startup marketing and sales goes hand in hand. How to ensure no stepping on each other’s toes?
  • Marketing organization should have good process too
  • Need to balance load of marketing and sales organization. Make sure invest more heavily in marketing to generate more leads than sales can handle to ensure good culture.

On Pricing

Pricing is important. Need to make sure not too cheap. Perceived value is very important. Need to be more expensive than competition and explain the value clearly to targeted subset of customers.

Learnings from Loominance

 UVP to attract customers via word of mouth: They need us when they are drowning in data.
Account based marketing
  • Scrap company websites, identify and recommend similar companies as sales leads to clients

Related readings

Differences between decision making and execution

The decision maker and the executor operates with different cognitive models.

The decision maker

The decision maker operates within an environment of incomplete information. He takes in conflicting signals from the environment to figure out the underlying Markov Chain that holds his environment altogether.

A successful decision marker minimizes the price paid for knowledge of each section of the Markov Chain.

Each success unlocks more resources that could be redeployed to this activity.

Inner fortitude is the primary trait required to navigate the high failure rate inherent to the nature of this activity.

Perpetuate accumulation of mental models from different domains reduces taken to form judgement while  increasing overall batting average.

The executor

The executor operates within an environment that has been made predictable by the activities of the decision maker.

He is predisposed towards systems, structures and processes. A successful executor measures and optimizes with the goal of increasing yield from a well defined process while minimizing costs.

Disciplined consistency is the primary trait required to ensure continued excellence in this repetitive activity.

Concerns

A strong decision maker profile with a weak executor profile will feel repressed/bored when forced to operate as an executor in a structured environment.

An strong executor profile with a weak decision maker profile will feel overwhelmed when required to operate within an unstructured environment.

Related references

Book summary: The essential Drucker

Management: make people capable of working together to respond to change in the environment through:

  • common goals
  • common values
  • the right structure
  • proper training and development

Reasons for failure

  • Not innovating
  • inability to manage innovation

The goal of any business is to create a customer. A business does so by producing generate products and services the community wants in exchange for profits to sustain continued operation.

The goal of marketing is to know understand and know the customer so well the product sells itself

The Purpose of a business is the change it wants to effect in the community

The Mission is what it wants to do to effect the change

The Objectives are key tasks it will execute upon to achieve the mission.

Types of innovation

  • Product innovation
  • Social innovation
  • Management innovation

Waste as little effort as possible on areas of low competence.

First figure out how you learn to figure out how you perform.

Number two person often fails in number one position because top spot requires a decision maker.

Effective people are perpetually working on time management.

The first rule of decision is one does not make a decision unless there is a disagreement.

Determine the right organization size to fit the requirements of the mission.

Insights on managing Big Data from meet up with Dean and Ved

From Dean (Reputation.com)

  • Enterprise sales as an acquisition strategy is feasible because revenue per account ranges in the USD millions – e.g. 70 million USD
  • Once an auto company like Ford or GM signs up, they will start bringing their dealerships in
  • The infrastructure needs to be able to support the size of the data which can be up to billions of rows
  • Scaling of infrastructure to handle load ever increasing data becomes critical for the continued growth of the data company
  • Data Product will appear broken when user attempts generate report while the data is still being written into the database
  • The key challenge is that different solution is suitable for different operation
  • Types of data operation include
    • writing into the database
    • reading from the database
    • map reduce to generate custom view for data in the database to support different types of reporting for different departments in the client companies.
  • Successful data companies will create different layers of data management solutions to cater to the different data needs
    • MongoDB
      • good for storing relatively unstructured data
      • querying is slow
      • writing is slow
      • good for performing map reduce
    • Elastic Search
      • good for custom querying for data
  • Dev ops become a very important role
    • migration of data between different systems can extend up to weeks before completion
    • bad map-reduce query in codes while start causing bottlenecks in reading and writing causing the data product to fail
    • dev ops familiar with infrastructure might on occasion have to flush out all queries to reset
    • The key challenge is the inability to find bandwidth for flushing out bad queries within the codebase
  • Mistakes in hindsight
    • In hindsight lumping all the data from different companies into the same index on MongoDB does not scale very well
    • Might make better sense to create separate database clusters for different clients
  • Day to day operations
    • Hired a very large 100 strong Web Scraping company in India to make sure web-scrapers for customer reviews are constantly up
    • Clients occasionally will provide data which internal engineer (Austin) will need to look through before importing into relevant database
  • Need to increase revenue volume to gear up for IPO
  • The Catholic church has 10 times more money than Apple and owns a lot of health care companies.

From Dan (Dharma.AI), the classmate of Ved

  • Currently has 15 customers for their company
  • Customers prefer using their solution versus open source software because they can scale the volume of data to be digested and solution comes with SLA
  • Company provides web, mobile and table solutions which client companies’ staff can use in the field to collect demographic and research data in developing countries
  • The key challenge is balancing between building features for the platform and building features specific verticals:
    • Fields differ between industry: fields in the survey document for healthcare company will be very different for fields in the survey document for an auto company
    • Fields differ between across company size: survey format for one company might be different as compared to another in the same industry but of different size
    • Interface required is differs between companies
  • Original CEO has been forced to leave the company, new CEO was hired by PE firm to increase revenue volume to gear up for IPO

From Ved

  • As number of layers increase in the hierarchy, it becomes increasingly challenging for management to keep up to date on the actual situation in the market
  • New entrant of large establish competitor might sometime serve as an opportunity to ride the wave
  • when Google decided to repackage Google Docs for Education, it was a perfect opportunity for Edmodo to more tightly integrate into Google and ride that trend rather than being left behind
  • Failure to ride the wave will result in significant loss of market shares
  • It takes a lot of discipline to decide on just focusing on the core use case and constantly double down on it.
  • Knowing that a critical problem, which could potentially kill the company, exists versus successfully convincing everyone in the company that it is important to address it are two different things.

Book summary: Thinking in Bets

Thinking in Bets
Decision Theory Model

Overview

  • Good quality decisions do not always yield good outcomes
  • All decision makings in real life are made under uncertainty. All decisions are essentially bets about the future
  • Decisions made in Chess are not made under uncertainty because every single permutation can be pre-computed unlike Poker.
  • Most real life decisions are not zero-sum games

On outcomes

  • Real life outcomes are probabilistic
  • Outcomes are influenced primarily by the quality of our decision (skill) and luck
  • While the outcomes might not always be positive, having a process in place to constantly improve the quality of decision making will tilt the odds in our favor

Implications

  • Do not change strategy drastically just because a few hands did not turn out well in the short run
  • For each premise understand what the base rate is
  • Learn to be at peace with not knowing
  • Recognize the limits of our own knowledge
  • A great decision is a result of a good process. A good process attempts to accurately represent our own state of knowledge
  • Watching: It is free to learn from other people’s experience

Cognitive biases that impede good decision

  • Decisions are the outcomes of our beliefs
  • Hindsight bias impedes against quality decision making
  • Guard against black or white decision making
  • Availability bias means lagging any prior conflicting data, our default setting is to believe what we hear is true
  • Selective bias and consistency bias, means we are unwilling to change our mind despite contrary signals from the environment
  • Avoid attribution bias

Related Readings

  • Theory of Games and Economic Behavior, Jon Von Neumann
  • Ignorance: How it drives Science, Stuart Firestein
  • Stumbling on Happiness, Daniel Gilbert

Insight from dinner with Sujit

  • hard to find experienced PM with data background in the Bay Area
  • Mountain View just issued permit to build more houses. Price of existing houses got depressed by 10%
  • Dressing well allows ability to charge USD75 per hour more
  • Most data scientist hang out at twitter, vidhya analytics and Kaggle
  • Growth frameworks is the easy part, its getting everybody to row in the same direction that is hard.

Reflections on communicating with your users via email

While sending a personal email to each individual user who directly uses our API just now, it occurred to me the main difference between talking with someone you have relationship with (like your mum/girlfriend/wife…?) versus simply doing a mass email blast to a group of “strangers”, is the potential lack of warmth and empathy in the latter on the sender’s side.
 
No one really likes being treated like a number on a Excel sheet. It sucks.
The key challenge becomes how do you scale your communication as the amount of people you need to communicate with increases without alienating them. Or does it even matter?

Related Reference

  • Permission Marketing, Seth Godin