How To Validate Your Startup

Problematic issues with the existing validation practices

Business validation serves two main purposes, which are ensuring innovation effectiveness (doing the right things) and reducing uncertainty (risk of failure). In most industries, business validation is perceived as a process of testing assumptions by collecting opinions of a group of potential customers. If a large group of customers has accepted your business assumptions then your business is validated.

However, this practice of validation won’t tell the full story and ensure the success of a business startup due to the following reasons:

  • This practice actually tests the product-pioneer fit; but, it is not testing the product-mainstream customers. This validation process likely results in unreliable outcomes.
  • This practice also fails to test business traction and viability. Business traction and viability will be successfully tested if only the validated business profitably sells to mainstream customers and not to pioneer customers (i.e. techies and early adaptors).
  • Feasibility of a new business concept is not really validated. Earlier-stage testing processes are usually less concerned about testing how to create and deliver the business value of a startup. Feasibility test includes testing production facilities, resources management, corporate governance, supplies chain, and others.

In reality, a startup will be transiting from a business-concept phase into a scale-up phase through successful testing processes of startup assumptions. However, business validation practices are showing little evidence of effectiveness and it won’t serve the purpose of validation.

Brief on existing validation practices

  • Design Thinking Design: Design Thinking is a powerful method to identify and validate opportunities. It starts by setting the problem space. The team will then observe potential customers with an unbiased, open mind to gain a deep understanding of their underlying problems and unsatisfied needs. In the third phase, the team condenses the findings into a short and crisp problem statement, formulated from the customer’s view. It then generates and prioritizes ideas for solving the identified problem. In the subsequent ‘Prototyping’ phase, the team turns ideas into artefacts of the intended solution. These are then validated with customers. However, the way that many companies are using Design Thinking does not provide a comprehensive validation for business startups. Most startups apply it with a heavy skew on Desirability (whether customers acceptance the value of the startup) and put little emphasis on Viability (whether the business profitable or not) and Feasibility (how to develop and deliver the value of a startup).
  • Google Sprints: In his book ‘Sprint: How to solve big problems and test new ideas in just five days’, Google Venture’s Jake Knapp outlines the process by which his company develops and validates innovation concepts. The Google Sprint process basically follows the logic of the Design Thinking process but is tightly time-boxed. Since a Google Sprint is a strictly time-boxed Design Thinking process, the same arguments as the above hold for why this approach does not provide a comprehensive validation.
  • Outcome-Driven Innovation / Jobs-to-be-done Outcome-Driven Innovation (ODI): It is based on the premise that people buy products and services ‘to get jobs done’. Usually, there is more than one solution to get a job done. Like Design Thinking, ODI has a focus on customer needs. ODI does not provide guidance on Validation but it adds valuable prioritization methodology, e.g.: Identification of innovation opportunities by highlighting jobs that are important but poorly served or alternatively unimportant but the over-served ranking of innovation opportunities via comparing the importance of the job versus customer satisfaction with current solutions. ODI has its strong points when it comes to Desirability and ranking innovation opportunities. However, there is little guidance on how to validate Viability and Feasibility. It should also be noted that ODI does not outline how to scale up validated innovation concepts.
  • Lean Startup: It combines principles from Lean Manufacturing with Design Thinking (e.g. ‘Build-Measure-Learn’ and ‘rapid prototyping’).  Lean Startup introduced the concepts of MVP (Minimum Viable Product) and PMF (Product-Market Fit). PMF, which in Lean Startup methodology is the trigger point for Scaling-Up, can be achieved via one or a series of MVP. Lean Startup has –like Design Thinking and Google Sprint –its merits in establishing customer-centricity (i.e. Desirability) and an agile ‘Build-Measure-Learn’ process until ‘product/ market-fit’ has been achieved. However, it is with no proper validation of Viability.
  • Leanstack: In his two books, ‘Running Lean and ‘Scaling Lean, Ash Maurya augmented Lean Startup with two major contributions. Firstly, he introduced the ‘Lean Canvas’ as a tool for developing innovative business models and for identifying those parts of the business model which should be validated most intensively. Secondly, he introduced the ‘traction’ concept. Traction is defined as ‘the rate at which a business model captures monetizable value from its users. By applying the ‘traction’ approach, they can increase certainty that the innovation concept will indeed be ‘crossing the chasm’. Validating Feasibility is not an explicit part of Leanstack. It should be noted as well that Leanstack provides only limited guidance on how to scale up a validated innovation concept.
  • Growth Hacking: Recently, Growth Hacking has gained popularity among our clients. This is an approach to extend the customer base once desirability has been validated. Like Design Thinking, Google Sprints, Lean Startup and Leanstack, Growth Hacking builds on an agile Build-Measure-Learn approach. As in the Leanstack approach, Growth Hacking builds on measuring traction metrics. The major contribution of Growth Hacking is that it outlines organizational provisions and tools for winning the market, once PMF is established. Therefore, Growth Hacking is not a validation approach in the narrow sense. It assumes that Desirability and Viability have been validated. If these assumptions are wrong, a lot of resources will go into scaling something that should not be scaled at all. Growth Hacking supports one of the four dimensions of Scaling-Up but is not a comprehensive Scaling-Up framework.
  • Traction Gap framework: The Traction Gap framework is a relatively new addition to innovation management theory. Developed by the Private Equity firm Wildcat Venture Partners, it focuses on the phase which starts with Minimum Marketable Product –and ends with when the ability to generate traction in the market has been demonstrated. Like most of the other approaches mentioned, the Traction Gap framework builds on an agile Build-Measure-Learn approach. Its goal is to show ‘Minimum Viable Repeatability’ (MVR), which is made up from (a) an industrialized product or service, (b) a validated business model, (c) a repeatable and scalable go-to-market approach and (d) proven traction. At MVR, the corporate startup has a solid understanding of the overall market (not just ‘Pioneers’ and ‘Early Adopters’) some understanding how to acquire customers, including a working product positioning, marketing, and lead generation capability and a reasonable sales pitch a few reference customers product release repeatability implementation success repeatability. The Traction Gap framework is quite a solid validation framework. However, it does not address Feasibility sufficiently. It should also be noted that the Traction Gap framework does not provide guidance on how to scale up a validated innovation concept.

The business validation framework

Frank Mattes, in his book ‘Scale-up corporate startup’, has defined the validation framework for a business startup to include core dimensions (desirability, feasibility, and viability), and the value inflection points (problem-solution fit, MVP, minimum marketable product, and minimum scalable venture).

The core dimensions of validation:

  • Desirability: Does the concept provide enough value for the customer –as seen from his perspective.
  • Feasibility: Are there show stoppers (e.g. technical, regulatory, Intellectual Property or market access) that prevent industrialization of the innovation (creating and delivering the sought value) and winning a large market share?
  • Viability: Does the underlying business model support a profitable and sustainable business?

The value Inflection Points:

For every core dimension, four value inflection points must be tested. The value inflection points are Problem-Solution Fit PSF, Minimum Viable Product MVP, Minimum Marketable Product MMP, and Minimum Scalable Venture MSV. The following is a brief description of the value inflection points:

  • Problem-solution fit: Is there a valuable problem to be solved? It is relating to (1) the importance of the problem for the customers and their dissatisfaction with existing solutions and (2) the size of the corresponding market. 
  • Minimum Viable Product: Is it accepted by a large group of customers? MVP is a version of the intended solution which allows collecting the maximum amount of validated learning with least effort.
  • Minimum Marketable Product: Is it acquired or monetized by a large group of customers? MMP is a version of the intended solution which has the smallest possible feature set that solves the problem.
  • Minimum Scalable Venture: Are customers repeatedly acquire and refer to other customers the Minimum Marketable Product? Traction of the business model becomes apparent with first paying customers (i.e. first revenues) and a growing sales funnel. Based upon this traction, the pathway-to-profitability becomes apparent. Value creation and delivery partners are defined. The Scaling-Up concept and budget are established.

The operational framework for business validation

Value Inflection Point 1: Problem-solution fit

  • Desirability
    • A customer problem worth to be solved has been identified.
    • Customers have confirmed in discussions around a rapidly developed demonstrator/mock-up that the intended solution solves their problem, fits within their context, they might switch from existing solutions and they are willing to pay.
  • Viability
    • An outline of the pricing model and the business model have been validated by customers.

Value Inflection Point 2: Minimum Viable Product:

  • Desirability
    • A rapid ‘prototype i.e. a ‘version of the intended solution which allows collecting the maximum amount of validated learning with least effort’ has been validated by customers in a protected and controlled environment.
  • Viability 
    • The right side of the Business Model Canvas (BMC), i.e. value proposition, go-to-market (channels and customer relationship) and customer segments, and the pricing concept have been validated. 
  • Feasibility
    • Major potential show stoppers (which could be related to e.g. IP, market access, regulatory aspects, resources etc.) have been identified and assessed to be surmountable.
    • An initial outline of the associated innovation ecosystem and the value chain are assessed to be supportive and scalable.
    • Creation facilities, technology, supplies chain, and resources for the sought value are tested to be successful.

Value Inflection Point 3: Minimum Marketable Product:

  • Desirability
    • A ‘version of the intended solution which has the smallest possible feature set that solves the problem’ has been developed and delivered via the defined channels in the market.
    • A significant number of customers use it in their own environment with a support level that is in line with the business model.
    • Repeatable demand can be generated.
  • Viability
    • The right side of the BMC is built in a minimum version.
    • Traction metrics show a meaningful initial uptake
    • A detailed business case has been established and is seen as positive.
  • Feasibility
    • For all potential show stoppers, elimination strategies have been defined and validated.
    • A shortlist of ecosystem partners and partners for value creation and value delivery has been established and is seen as supportive and scalable.
    • Value-creation inputs are tested successfully.

Value Inflection Point 4: Minimum Scalable Venture:

  • Desirability 
    • The sales funnel fills up and there are first paying customers in the intended business model. 
    • Repeated sales are evidenced.
    • Growing sales are evidenced.
  • Feasibility 
    • The Scaling-Up concept, in particular, industrialization and ‘crossing the chasm’ to win mainstream customers has been defined and validated.
    • Ecosystem and value delivery partners are defined.
    • All high-risk issues have been identified and seem surmountable.
    • Value-creation inputs under growing sales conditions are tested successfully.
    • The value delivery and the innovation ecosystem have been defined and validated.
    • The Scaling-Up concept and the associated budget have been established.
  • Viability 
    • Traction and scalability in the target market have been validated.
    • A detailed business case, which includes the Scaling-Up budget plus the expected margins from the scaled-up venture, suggests the commercial viability and an acceptable pathway-to-profitability.

Last note-KPIs and metrics

It is important for the startups to set KPIs and metrics ahead of time for every testing process of the value inflection points based on the core dimensions of validation. The importance of such KPIs and metrics is to enlight startups with a defined criterion for testing assumptions and provide threshold metrics for accepting or rejecting assumptions and completing the testing cycle.

 

Prepared by: Munther Al Dawood- Enterprise Development Professional

Grow Enterprise

www.growenterprise.co.uk

maldawood@growenterprise.co.uk

My Linkedin Profile

Reading, UK

Source: Mattes, Frank, 2018. Scale up corporate startup

 

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