True University – A School for Startups

by Chris Christensen Add comments
categories: Business

true-universityMy new employer, PayNearMe, had an investment from True Ventures. One of the interesting programs True runs is a two day educational program once a year called True University. The 250 students at TrueU come from the 70+ startup companies that have had investment from True. There are 39 classes led by 52 instructors over the course of the two days plus a number of opportunities to network.

I attended the Engineering track. There were also tracks in Design, Customer Experience and Operations/Culture.

Sessions

The specific segments I attended were:

General Sessions

Jon Callaghan: True Story
Jen Pahlka: Disrupting Government (and Citizenship)
David Vik: Building a Culture that Attracts Customers and Employees
Josh Elman: Thoughts on Growth

Engineering Sessions

Agarwal/Oppenheimer/Ramsay/ McKenty: Where to Focus Your Business – Public, Private, or Hybrid Clouds
Allan Leinwand: Gaming the Hybrid Cloud: Lessons from Zynga’s zCloud
Sudhakar Muddu, Christos Tryfonas: Technology & Architecture Choices to Improve Product Delivery
Armon Dadgar, Mitch Hashimoto; Scaling MongoDB and Riak at Kiip
Driscoll/Chowdhury/Skomoroch/Hellerstein/Migurski: How to Train a Data Scientist
Patrick Ewers: Network Resource Management for Startups
Andy Grignon: How iPhone Failed its Way to Success, and Other Tales of Woe from the Engineering Trenches

here are my take aways:

Just Cool

The work that Code for America is doing to use Silicon Valley lessons and modern web and mobile technology to improve local governments is inspiring.  Of course, it also made me glad I don’t work for the government because of how hard it is to get things done there and thus how antiquated some of the IT systems are. On the other hand, for those willing to endure that pain, the government IT budgets drwarfs industries like computer games, mobile apps, etc. If I had more copious free time I would start volunteering for Code for America.

Scaling Web Infrastructure

Much of the discussion in the engineering sessions were around scaling services.

  • We are not anywhere close to the bleeding edge of scalability
    • One of the people who had worked on government projects talked about cloud solutions for projects like Nasa creating petabytes of data daily
    • Zenga is deploying up to 1000 new computers a day in their private zCloud service
  • A number of providers are moving away, at least in part, from traditional SQL databases in high capacity situations
  • NoSQL databases like MongoDb are getting increasingly popular but are not yet turn key solutions, some pain should be expected
  • Some of the high capacity options rely on requirements where 100% accuracy is not expected, like one company that was serving web ads
  • How you can shard your data / database is going to be a key to scaling to large capacity
  • There is a growing trend towards a hybrid cloud, some of your servers owned and hosted by you and some in the cloud. But the actual mix depends a lot on your business model and usage model.
    • Netflix is mostly in the public cloud because they are bandwidth limited and Amazon can get bandwidth cheaper than you.
    • Some companies are clearly limited on their use of the public cloud by regulation.
    • Companies like Zenga are using servers in the public cloud (Amazon, etc) to be able to handle surges since Amazon can rake and stack servers faster than you can, but use their own cloud for the bulk of their traffic that is predictable.
    • Zenga has an interesting strategy of making the interface for provisioning new servers the same for their local cloud as for Amazon so that it is simpler for their employees, especially for the non-technical staff.

Scaling Companies

  • Company cultures are grown over time through a series of intentional and unintentional actions and are fragile. How you actually behave and not what you say creates your culture.
  • Larger companies make it easier to “pre-fail”, so decide some projects cannot be done before they even try.
  • Treat your employees like you want them to treat your customers.
  • When people get to the point of saying they want to hire a data scientist they often just mean “I don’t care about this data, so we should hire someone who does”. That is probably not the right approach. Instead first figure out what problem you are trying to solve with the data.
  • When starting out you need to focus your company
    • Interview your prospective customers for their problems.
    • Frameworks don’t sell, solutions to problems sell. So go away and build a framework if you need to but sell solutions.
    • find out what the fortune 100 companies want but sell to the mid market global 5000 / fortune 1000 companies to start with as the sales process is faster.
    • Get marquee customers for references.
    • Focus on functionality before scalability.
    • If customers have a DYI solution to the problem you are trying to solve that just means there is a need.

Scaling Communities / Customer Bases

  • Your customer flow is as important as your cash flow and should have as much tracking. You should know how many new users you are getting, how many are going inactive or reactivating over time.
  • What do your new users see when they go to your site. Your sign-up rate may be higher if you have a short sign-up form but if you use the signup for user education of how they should behave or how they can use the service you may improve your overall long-term retention. “Use the startup sequence for inception, to get across the idea of the product”.
    • Sites like Twitter have serious start-up issues with new users and have had to invest a lot of time and a lot of experimentation into the initial customer experience.
  • There are a variety of strategies for scaling a company via social media:
    • LinkedIn was one of the more pure viral growth companies where people joined because they were invited.
    • LinkedIn learned people needed on average more than 3 invitations.
    • Twitter made heavy use of traditional PR and celebrities to grow.
    • Instagram made heavy use of twitter for the growth, and made it very easy for people to share.
    • SocialCam made heavy use of FaceBook’s Open Graph API to grow. The more people watch the more their friends are invited (without them specifically doing the inviting which is a bit controversial).

Scaling your Personal (or Company’s) Network 

  • The longer it has been since you have connected with someone the less likely you are “top of mind” when that opportunity happens that you want them to refer to you.
  • Focus on a small set of people that you want to remember you and create some useful, relevent contact with them every month or so. It might be lunch, a call, or be as simple as forwarding a relevant article or making a relevant introduction.
  • Be helpful to be memorable.
Conclusions
  • True University is cool. The networking alone would be worth the investment of time.
  • True Ventures is cool. I have been at startups before and have helped raise about $100 million from a variety of investors and the approach True is taking is one I have never seen before. I had already started to get the impression of being in the “True family” from other things people had said at PayNearMe, but now I have a clearer idea what that means.

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I am the host of the Amateur Traveler. The Amateur Traveler is an online travel show that focuses primarily on travel destinations and what are the best places to travel to. It includes both a weekly audio podcast, a video podcast, and a blog.



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