Presentation I did for ProductCamp Utah on what it means to be a product manager at a startup. It can be summarized by saying it is a scientific endeavor.
2. Travis Jensen
Most of my career at small companies
Started as a developer
First PM experience was an enterprise
software company
Currently PM at ClickLock, a very small startup
Have moonlighted with several other startups
as a PM
18. Verifying Hypotheses
Question: Who is my buyer?
Experiment
Hypothesis 1 2 3
Tal
Talk to 10 Talk to 10
Bank CSO bank CSOs bank CMOs
insu
CS
Talk to 10 Talk to 10
Tal
Hospital Administrator hospital office
doc
admins managers
19. Good Habits
Getting out of the building
Customer validation
Prioritization
Decisions by data
Managing chaos
20. Good Habits Gone Bad
Return on investment
Strategic direction
Big, important releases
Chasing competitors and being market
driven
21. New Habits
R&D: Rip Off and Design
Sharpen the Angle
Chasing customers and being market
drivers
Teaching product management to the team
37. Bill Campbell on the
First Hire:
I know that sounds like a strange answer, Product
Marketing, some people call it Product Management,
but somebody who can really understand the
dynamics of what goes on in a marketplace, apply
technology to that marketplace, see how the
technology can work, and continue to advise brilliant
scientists so they can adapt their products to make
sure customers are happy.
This is the normal world of product management, with the various stages feeding into each other in a (hopefully) virtuous cycle. Things are a bit different at startups...\n\n(Build 1) There isn't enough information to generate a real business case. Instead, early decisions are often made by gut feel. It is really important for a PM to recognize this and work to correct it by gathering real data.\n\n(Build 2) Plan on doing more than crunching numbers about ROI on features. You are often the best user experience person on the team. I spend time in mockup tools and in photoshop to save the capital a designer would cost.\n\n(Build 3) One really nice thing about the startup environment is small teams means management is just chatting, not so much gandt charts.The downside is everybody needs to be exceedingly versatile to cover staff shortages. Plan on doing QA work, but that is a good time to review features.\n\n(Build 4) Proof. Yeah, that's funny. Like there is anybody else to write it.\n\n(Build 5) Very early on, there isn't much training because there isn't much of a sales staff. At this point, sales are often happening by pre-committing features. At this stage, that is OK! Cash flow is king early, so don't be afraid of sales leading the product; it means there is a market. Your job is to understand *why* so you can begin leading that market.\n\n(Build 6) Many PMs think in terms of the "perfect" release, with all the right features laid out just right. That kind of thinking kills startups. Instead, think of the minimum it takes to make your product's value understood. You want quick releases and early feedback from customers, so you don't spend time building useless junk and allows you to pivot earlier if things aren't working out. Eric Ries and Lean Startups.\n\n(Build 7) Depending on the stage of the startup, don't be surprised if you are making sales calls. I'm not a sales guy, but I've been out there. I look at them as great opportunities to understand the real customer pains I'm trying to solve. Even if you have sales people, make sure you are going with them very regularly for those reasons.\n\n(Build 8) The previous step and these two really all combine into what is known as customer development. Startups don't really understand who their customers are, what exactly their pains are, nor why they would buy from you. Think of a startup as a science experiment: every feature, every communication, every interaction is a data sample. You have a hypothesis about the experiment, your job as the PM is to prove or disprove the hypothesis. That can only be done outside the building and needs to be done as cheaply as possible to give you as many iterations on the experiment as possible.\n\nAnd with the results of those experiments, we are back at the beginning of the circle, but now armed with knowledge for the next arguments.\n
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R&D: Rip Off and Design: 2/3 of successful startups use this method. Start by copying somebody else, but tweak it until you find blue ocean.\n\nSharpen the Angle: how you present your idea matters. This is from a book called BoomStart from BYU professors. UPMA had a wonderful presentation a few months ago.\n\nNeed to believe\nReason to believe\nBlows away expectations\nQuantifiable support\nUnique product claim\n\nChasing customers and being market drivers: Only when we have customers will we have a hope of finding a market. Therefore, chasing customers takes priority. The goal, though, is to do it in a way that opens anew market. When Canon got into copiers, they did it by finding customers who didn't want to go wait for the big Xerox, so they made small office copiers, opening a new market.\n\nTeaching product management to the team: everybody on the team needs to understand the discovery process, if for no other reason than to keep them from thinking you and the company are schizophrenic.\n
If I had one take away to leave you, it is startups are a big science experiment.\n
Confirmation Bias: Proving your hypothesis correct instead of proving it incorrect. I have a sequence of numbers (2,4,6). Ask me questions to find the patterns.\n\nMisaligned motivations: what you are expecting to see greatly colors what you actually see. How many times do you notice the bad calls by a ref against your team but not the other? \n\nOverconfidence in our capabilities: The more confident we are in our abilities and our knowledge, the less we will question ourselves. This can be particularly troubling in startups because it takes a certain amour of hubris to start a company.\n\nFamiliarity (being too close): We overemphasize variables we see often and underemphasize variables we see infrequently. The classic example: are you more likely to die by shark or by bee? In startups, we see this exhibited often as looking at a subset of solutions based on the space we already know. Poloroid had great digital technology, but they " knew" film, so that's what they focused on, right up until film put them out of business.\n
It is massively important that you monitor for confirmation bias here. It is easy to test for which shade of blue is perfect and lose out altogether on the fact that red is really the "right" color.\n
It is massively important that you monitor for confirmation bias here. It is easy to test for which shade of blue is perfect and lose out altogether on the fact that red is really the "right" color.\n