Janet Iwasa: Animate Your Hypothesis to Explore Its Viability and Implications

Written by Sean Murphy. Posted in Design of Experiments

I found Janet Iwasa‘s Ted Talk on “how animations can help scientists test a hypothesis” to be extremely thought provoking.

Animation enables you to visualize process that are too small to be seen, even with sophisticated instruments, such as the biological phenomena that that Iwasa shares in the talk. But more importantly, it can  allow you to get a hypothesis out of your head in a way that it can be shared with others, reviewed and annotated.

As she observes near the end of her talk (excerpt from transcript of her talk)

Over the years, I found that animations aren’t just useful for communicating an idea, but they’re also really useful for exploring a hypothesis. Biologists for the most part are still using a paper and pencil to visualize the processes they study, and with the data we have now, that’s just not good enough anymore. The process of creating an animation can act as a catalyst that allows researchers to crystalize and refine their own ideas. One researcher I worked with who works on the molecular mechanisms of neurodegenerative diseases came up with experiments that were related directly to the animation that she and I worked on together, and in this way, animation can feed back into the research process.

Implications for Startups

I think we need to develop first diagrams and then modeling languages to allow us to visualize and animate some key aspects of the challenge startups face:

  • The product roadmap, especially modeling it as a collection of options to manage a set of potential and likely prospects. Discovery Kanban may provide some useful metaphors here.
  • The new product introduction problem: selection of a niche market and insertion and scale inside of a prospect’s firm.
  • The likely paths a negotiation may take, in particular how to sequence negotiations across players and within a firms’ buying cycle.
    In particular how to we model the different facets: you typically have one more contracts or agreements that are written as legal documents, a system diagram, a list of requirements, and a timeline for implementation/roll-out/proliferation to name just a few of the critical but often disjoint definitions of a deal.
  • The evolution of the incentives and outcomes from a business relationship over time. This would extend the timeline and overlay product or feature roadmaps with the customer’s perspective on the likely (or even a range of) requirements over time.
  • The evolution of a market structure over time: what will be the axes of competition and what will be standardized (and commoditized).

I think we will need to start with pencil and paper or a whiteboard sketch just as the biologists did. Roam’s “Back of the Napkin” certainly offers some very useful visual metaphors, as do decision tree models, tornado diagrams, and traditional spreadsheets to name just a few more. We are talking to several teams that are exploring different ways to combine numbers, words, and diagrams that are integrated into responsive models that can be explored (e.g. parameters changed, relationships varied).

Request for Information, Comment, and Proposals

If you are working on something that will allow a team to sketch and animate one or more critical aspects of a business we are interested in talking and exploring how to incorporate your capabilities into one or more of our offerings. In particular if it would enable hypotheses to be modeled and explored, and experiments defined to test or refine the hypotheses.

We will also be offering some on-line workshops, starting with key aspects of Discovery Kanban. If you would like to take part, in particular if you have real business issues that you are wrestling with that you are interested in seeing modeled in a small group setting, please contact us.

Startup Stages: Survive, Explore, Focus, Refine, Grow

Written by Sean Murphy. Posted in Customer Development, Design of Experiments, skmurphy, Startup Stages

Survive first. Explore second. Build third.

  1. Survive: It’s good to fail small and fail fast. But also make sure to survive the failure. It’s no good to fail if you can’t get up again.
  2. Explore: True exploration feels like zero progress. Everyone around you will tell you to focus. To stop messing around. To get on with it. The problem is, you need to find it first. This takes time and mistakes. In theory, this is all about fail fast, fail small. In reality, this is slow and painful.
  3. Build: Find a great solution to a small pain point. Then use that to grow bigger.

Tyler Michalski in “The Basic Basics

This reminds me of Rob Saric’s “Solvency First, Consistency Second, Growth Third”

2. Solvency First, Consistency Second, Growth Third
If you don’t have enough money to survive you die. [...] focus on ‘Minimum Viable Cash flow (MVC)’. Once you determine what the MVC is for both you and your team, work towards achieving that by whatever means you can. Consistency allows for predictability and the more predictable your business (‘X inputs results in Y outputs’) the faster you’ll grow.
Rob Saric in “Startups Are Hard

I think they are both right, I have tried to put integrate these two insights into our startup stages mode:

  1. Survive / Stay Solvent: This can involve the work/work balance of services and product development, the important thing is to generate enough cash flow to give your team the time to explore the market to find the right opportunity. This spans the “open for business” and “early customers” stages.
  2. Explore: I think you are looking for a fit with your talents, interest, and experience. Any opportunity has to pass the “why you, why now?” test. What is it that your team brings to the problem that will allow you to differentiate your offering? The fastest iteration cycle is to build as little as possible and simply measure (observe) and learn. Always start from measurement and observation so that you understand the problem and the customer before you worry about your solution. This also involves asking the right questions, talking with many people, and taking time to integrate all that you have learned. This spans the “idea and team formation” and early customer stages.
  3. Focus:  This is the first part of the “finding your niche” stage; selecting a candidate niche to focus on.
  4. Refine (Make Consistent and Predictable):  This is the critical step in finding your niche that allows you to leave exploration mode, or at least substantially reduce your exploration efforts. You have enough knowledge of your teams capabilities to build predictable processes and of the customer’s needs to predict their reactions and identify prospects you should focus sales efforts on early in the engagement process.
  5. Grow: now you enter the scaling up stage because you have useful diagnostics and predictable processes.

Distilling Rules of Thumb From Entrepreneurial Experience

Here are some additional blog posts on distilling rules of thumb from entrepreneurial experience:

More From Rob Saric

More from Rob Saric’s (@RobSaric) blog, his core beliefs linked to relevant articles on his site:

Q: We Already Have a Prototype, Can We Still Do Customer Development?

Written by Sean Murphy. Posted in 3 Early Customer Stage, 4 Finding your Niche, Design of Experiments, skmurphy

Q:  We have already implemented the first prototype of our product, but we need to know that we are either on a good course or need to change.

A: If you long for certainty you should not be doing a startup, pick a regulated utility or government bureaucracy as a career. Lean Startup and Customer Development techniques can help you to reduce risks by identifying them and developing mitigation strategies but it’s not a guarantee. Any real market attracts competitors and you don’t get to write their plans so it’s not just a question of understanding the prospect’s status quo but being able to identify and react to competitive threats. The view that product-market fit is a ratchet that you cannot fall back from neglects the impact of competitive response, new entrants, and continued changes in technology and customer preference.

Q:  Perhaps I overemphasized our desire for certainty; we understand a startup is uncertain. Should we use our current prototype as an MVP?

Yes. I would  start with what you have and use it as a probe to refine your understanding of the market and customer needs.

Make a distinction between the product, your message, and your target customer. You can talk about your product in different ways, adjusting your message to highlight and test key hypotheses. You do not have to make any changes to your product to this. Any product by definition–or at least any short enough for a prospect for prospect to listen to willingly–of necessity highlights some aspects omits others. You can also use different messages on different target customers or present different message to different prospects of the same type as a way of refining your understanding of what they view as important.

It’s critical that you have conversations with prospects and not simply present messages and see what they react to. It’s only in conversation that you can truly be surprised (you have to be listening, it’s not a monolog) and often the most surprising and useful thing a prospect can do in a conversation is to ask you a question you have not considered before (that’s why it’s called a conversation not an interrogation). When you are looking for early customers the value hypothesis is critical. You may reach them using non-scalable methods that don’t address your first real growth hypothesis.

My take on the distinction between hypothesis and assumption, your mileage may vary: A hypothesis is what is being tested explicitly by an experiment. An assumption is tested implicitly. By making your assumptions as well as your hypotheses explicit you increase the clarity of your approach and the chance for learning. The two things that can trip you up most often is an unconscious assumption that masks a problem with your hypothesis or an unconscious bias in whom you are testing the value hypothesis on. In particular you may have defined your target customer by certain selection criteria but your actual choices for whom to speak to (or who will speak with you) are not sampling from the full spectrum of possibilities.

Q: Or should we build another or several other smaller MVPs to  test only the most important  assumptions? Should we build various tests in parallel to test the needs of different types of customers?

I have come around to the approach of testing several hypotheses in parallel, I think you learn faster and are more likely to identify a good opportunity more quickly. After you take your current prototype and use it to have conversations,  I would explore a few different potential customer types in parallel. One good article on this is by David Aycan, “Don’t Let the Minimum Win Over the Viable,” where he offers a comparison between three approaches:

Traditional linear approach:

linear
Standard sequential pivot approach:
pivot
His recommended approach:
recommended

I am also a huge fan of Discovery Kanban  as a way to manage a set of options and experiments in parallel with managing commitments to customers and other execution targets. It actually gets harder as you start to gain some early customers and need to continue to explore the market and refine your understanding in parallel with keeping your current customers satisfied.

Discovery Kanban Allows Firms to Balance Delivery and Discovery

Written by Sean Murphy. Posted in 5 Scaling Up Stage, Design of Experiments, Video

I believe that Patrick Steyaert’s Discovery Kanban offers critical perspective on how large organizations can foster the proliferation of Lean Startup methods beyond isolated spike efforts or innovation colonies.

I think Patrick Steyaert has come up with an approach that builds on what we have learned from customer development and Lean Startup and offers an orchestration mechanism for fostering innovation and operational excellence. I think  this will prove to be a dynamic approach to managing innovation that will be as significant as Saras Sarasvathy’s Effectuation, Christensen Innovator’s Dilemma and Innovator’s DNA, and Ron Adner’s Wide Lens. I believe it’s going to become part of the canon of accepted principles of innovation because it offers not only a way to frame the challenge of balancing discovery and delivery, but a mechanism for planning and managing them in parallel.

Discovery Kanban is a synthesis of a number of distinct threads of entrepreneurial thinking–Lean Startup, Kanban, OODA, PCDA, and Optionality–into an approach that helps firms address the challenge  of executing and refining proven business models in parallel with exploring options for novel business opportunities. The reality is that you have to manage both current execution and the exploration of future options whether you are in a startup that is gaining traction and needs to develop operational excellence (or an innovation colony that now wants to influence the existing enterprise) or and enterprise that needs to avoid the “Monkey Trap” of escalating investment in a business model that is reaching the end of life instead of parallel exploration of a number of options for new business units.

At the extremes startups are viewed as scout vehicles–suitable for exploration to find sustainable business models–and established enterprises are viewed railroads, very good at moving a lot of cargo or passengers along predetermined paths. The reality is that almost all businesses need to manage both excellence in execution while not only keeping a weather eye on new entrants fueled by emerging technologies and disruptive business models but also exploring for adjacent markets that can leverage their established competencies and new competencies required by current customers.The Lean Startup and Customer Development models have fostered a broad understanding of the need for iteration and hypothesis driven product probes. Kanban models have shown the value of making work visible to enable the shared understanding that makes cultural change possible.

We Help You Design Experiments That Move Your Business Forward

Written by Theresa Shafer. Posted in Design of Experiments

While there are many challenges to master in building a new business, technology entrepreneurs have to balance three primary aspects:

  • Team: can you assemble the talent required and keep them together and moving forward?
  • Technology development: can you build a working product?
  • Customer development: can you solve a problem that people will pay for?

There are many more unknowns than these basic ones. A good advisor does not have all the answers but is familiar with the challenges of getting a new company started and a new product launched. A great advisor can help you design experiments to reduce risk and uncertainty and find answers that are “good enough” to keep moving forward.

We help you make sense of the market by correlating what you have observed with stories you have collected and data you have gathered. We help you form hypotheses and design experiments that tinker with your initial product concept so that you can explore the boundaries and depth of a prospect’s problem.

We offer accountability groups and consulting to help you design, test and learn from your experiments.

Interested in checking us out?  Contact us to book a free office hour conversation to get started.

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