Lean startup in ehealth 5/2015 Pauliina Smeds, Forum Virium Helsinki Jaakko Ikävalko, Forum Virium Helsinki
The lean startup model aims at increasing the odds for success for startups, by reducing the market risks
The goal is to eliminate wasteful and inappropriate traditional new product development practices
This means among others not writing elaborate business plans
Also, this signifies avoiding expensive product trials, launches and failures
Consequently, one goal is to diminish the need for high level of initial funding
The key methods of lean startup philosophy are business-hypothesis-experimentation iterative product releases validated learning
The objective for experimentations, iterations & learning is to guide new ventures to only launch products that customers actually want
In the lean startup approach, a startup is viewed as an experiment within the context of massive uncertainty
Extreme uncertainty: in the beginning both the problem and the solution are unknown. Thus, in the beginning, a startup doesn t know who is the customer or what is the business model
Yet, a startup exists only to create a new sustainable business model
The primary goal is to discover a business model that works before running out of money & time. And then scale it.
The business model or the scaling of a business should not be based on assumptions but instead be built on tested hypotheses and validated learning
In the search for a sustainable business model, it s crucial that before running out of money, the startup has the ability to either pivot or persevere
Pivoting is productive failure for a startup. Pivoting signifies learning something useful. Pivoting means staying grounded in the initial vision, but changing one dimension of the business at a time.
A startup should always consider how many opportunities to pivot is left
Therefore, it is especially essential to reduce time between pivots
This is done by accelerating validated learning by the build-measure-learn feedback loop
Most startups are drawn apart by two approaches of building a product when maximizing the chances for success building the most perfect product or releasing early, releasing often
minimum viable product (MVP) is a synthesis of these two extremes
Most startups consider an MVP too big: including too many features. MVP should contain only critical features
In order to deliver an MVP a startup needs to be willing to iterate and experiment
An easy formula what you think an MVP is, cut it in half
Customer feedback loops during product development help to eliminate features or products that the market doesn t want.
Customer Development Customer Discovery Customer Validation Customer Creation Company Building Problem- Solution fit Product Market Fit Proposed MVP Business Model Scale Execution Scale Organization Proposed Funnel(s) Sales & Marketing Roadmap Scale Operations Pivot Source: Steve Blank`s Customer Development by Brant Cooper; custdev.com
Experimenting means testing the ideas against reality. experimenting is NOT about asking the customers
Instead, experimenting means testing hypothesis, setting metrics and measuring how customers behave
Setting up the metrics requires also identifying what is crucial in order to establish a sustainable business model
Questioning the assumptions Is the problem worth solving? Who s problem is being solved? Does anyone care about the solution? Will the customers buy the solution? How are the target customers solving the problem now? How will the startup grow? What is the unit cost model? What is the unit revenue model? What are the acquisition costs per customer? What channels will be used to get to customers? What is the startup s unfair advantage that cannot be easily copied or bought?
Product - market fit: the point at which the startup can scale profitably The customer is willing to pay for the product The unit of cost per customer is smaller than the unit revenue per customer There is sufficient evidence indicating the market is large enough to support the business The sales model is repeatable and scalable
Lean Startup Unit of progress: validated learning Customer Discovery Customer Validation Customer Creation Scale Company Customer Development Problem: unknown Hypothesses, Experiments, Insights Solution: unknown Data, Feedback, Insights User stories Architectual Spike Release Planning Requirements Bugs Iteration Latest Version Acceptance Tests Small Releases Spike Next Iteration Agile Development
Canvas tools, one example Key Partners Key Activities Value Proposition Customer Relationship Customer Segments Key Resources Channels Cost Structure Revenue Streams Source: Strategyzer.com
Summarizing the lean startup approach
The focus is on business model, not on business plan fast learning loops: build-measure-learn avoiding investing in a bad idea: a quick death is a good death
What Lean Startups Do Differently Lean start-ups don t begin with business plan but with the search for a business model Quick rounds of experimentation & feedback reveal a model that works. Then, lean startups focus on execution. Lean Traditional Strategy Business Model Hypothesis-driven Business Plan Implementation-driven New-Product Process Customer Development. Get out of the office and test hypotheses Product Management. Prepare offering for market following a linear, step-by-step plan Engineering Agile Development. Build the product iteratively and incrementally Agile of Waterfall Development. Build the product iteratively, or fully specify the product before building it
Lean Traditional Organization Customer and agile development teams hire for learning, nimbleness, and speed Departments by function Hire for experience and ability to execute Financial Reporting Metrics That Matter. Customer acquisition cost, lifetime customer value, churn, viralness Accounting, income statement, balance sheet, cash flow statement Failure Expected. Fix by iterating on ideas and pivoting away from ones that don t work Expection Fix by firing executives Speed Rapid Operates on good enough data Measured Operates on complate data
ehealth specific aspects with the lean startup approach
ehealth related aspects lots of regulation getting to product/market fit potentially expensive: even MVPs have usually to meet certain standards and often need approval from administrators & regulators important stakeholders can be hard to reach health providers can be conservative & reluctant to try new things, resulting in slow adoption often complex ecosystems & value chains
Regulative aspects in ehealth Within ehealth, there are requirements & directives for Privacy, security, language support SW development process Quality management system Risk management process Clinical investigation Validation Registration Placing on the market Incident reporting Suitability for the intended use Performance and reliability
When commercializing an ehealth innovation if regulation concerns your product, think for ways to avoid regulation
An example: Case Owlet avoiding regulation in an ehealth startup See video on the case: https://www.youtube.com/watch?v=rs6fhw9prek
More info http://bit.ly/1aa2xhk