The Stanford Lean LaunchPad class was an experiment in a new model of teaching startup entrepreneurship. With one week and one more updates to go, this post is part seven. Parts one through six are here, Syllabus is here.
With a week to go the teams are starting to look like opening night before the big play. Teams are iterating and pivoting right and left, one team threw their entire business model out the window and did a complete restart, and another team was having a meltdown over personalities.
Week seven of the class
Last week the teams were testing their hypotheses about their Channel (how a company delivers its value proposition (i.e. its product or service) to its customers. This week they were testing their hypotheses about Revenue Models: what are customers really willing to pay for? How? Are you generating transactional or recurring revenues? Is it a multi-sided market, and if so who's the user versus who's the payer?
The Nine Teams Present
The first team up was PersonalLibraries the team making a (reference management system for discovering, organizing and citing researchers' readings). Oops. No more. The team looked at the potential revenue and concluded that the outlook for this business with this customer segment was dismal. They decided to do something more dramatic than just a Pivot. They did a restart. They moved from "Reference Libraries" to "Product Libraries" -- an online social shopping system. (If this had been a real startup rather than a class we would have had the team test many more variants on customer segment, revenue models, channels, etc before such an extreme move.)
They quickly came up with a new business model canvas, value proposition and customer segment.
The team hasn't been getting much sleep as they have a week and a half to make meaningful progress. Lets see what they can pull off.
Autonomow, the robotic farm weeder, had a busy week. In talking to their sales channel (farm equipment dealers) and customers (organic farmers) they realize they have an opportunity to come up with a unique revenue stream. Instead of selling or leasing the equipment they are going to charge for leasing according to weed density in the farm fields. The denser the weeds, the higher the rental price per day. Customers and dealers agree that it's a fair deal. Wow.
On the way to the WorldAg Expo their Carrotbot (their research platform they built to gather data for machine vision/machine learning) hit the farm fields near Avenal, California.
The videos of the robot in the field were priceless.
CarrotBot hits the ground
Where are we?
At the World Ag Expo in Tulare the team encounters its first potential competitor -- "Robocrop." (No kidding, I couldn't make this up.)
The next team was D.C. Veritas, the team building a low-cost wind turbine for cities and utilities. Last week the team pivoted and their wind turbine is now embedded into street and highway light poles.
This week the D.C. Veritas team put it into overdrive and did mass interviews of city officials across the United States. In Palo Alto they talked to the financial and utilities mangers. In Williamstown, West Virginia, they spoke to the city planner and a member of the budget committee. In Oklahoma City, Oklahoma, it was the city engineer and director of public works. In Amarillo, Texas, they had interviews with the head of the bidding process, the Street light manager, Director of Public Works and the utilities engineer.
They quickly got a good handle on the canonical project approval process inside a city.
They combined their understanding of the city approval process with the data they gleaned from customer interviews and developed preliminary archetypes.
These represented the different customers in the approval cycle inside a city.
Agora Cloud Services
The Agora team, (a marketplace for cloud computing), (a relative island of calm in a turbulent sea of other teams) now believed their business was providing a tool set for managing Amazon Web Services cloud compute usage. They believed they could build tools that would save customers 30% of their Amazon bill by providing service matching, capacity planning and usage monitoring and control.
The team was a paragon of steady and relentless progress. They had another four interviews with potential customers and consultants.
The Week 7 Lecture: Partners
Our lecture this week covered partners. Which partners and suppliers leverage your model? Who do you need to rely on?
Our assignment for the teams for next week: what partners will you need? Why do you need them and what are risks? Why will they partner with you? What's the cost of the partnership? What are the benefits for an exclusive partnership? What are the incentives and impediments for the partners?
The pressure was on. The other five teams were also furiously iterating and pivoting. The JointBuy team (the one that sent out 16,000 emails last week) realized that the low-fidelity website they used to test key concepts needed to get real to attract buyers and sellers in volume. The team pulled a week of all-nighters and turned the wireframe prototype into a fully functioning site.
In almost every entrepreneurship class with a team project there's a team that can't figure out how to work together. These are the same problems one sees in real startups (disagreements over who controls the vision, team members not pulling their weight, disillusionment with the team direction, individuals uncomfortable in rapid decision making with less than perfect data, etc.) We give the students an escalation path if they're having interpersonal problems (mentors -- to teaching assistant -- to professors) to see if they can first work through the issues without our intervention. While these are always painful we try to teach that they are part of the learning process. Better you encounter the problems in a classroom than after you raised a venture round.
At this point in the class almost all the teams are in a full sprint to the finish line. Next week, the last lecture. Then the final presentations.
Steve Blank's blog: steveblank.com