Managing Uncertainty is H.A.R.D.

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Founders bet on success. That is their job. However, this is a poor bet because 90% of startups fail to survive beyond three years. This is because so much needs to go right: funding, people, customers, product development, timing. If only one aspect goes wrong, the whole venture can collapse. 

The key to successful scaling is managing uncertainty while maximizing execution. Unfortunately, managing uncertainty is problematic because scaling is full of unknowns. And it is the unknowns you must fear – then overcome by making them visible and actionable.

The most popular type of risk analysis is SWOT: Strengths, Weaknesses, Opportunities and Threats. Although SWOT helps to get founders to look outside their bubble, it is not an adequate risk assessment tool for two reasons:

  1. SWOT tends to reinforce biases. SWOT is based on what you know or what you think you know. Whether because of optimism, hubris or ego, founders put too much faith in the positive: their Strengths and their Opportunities. They do not pay enough attention to their Weaknesses and their Threats.
  2. SWOT is not actionable. It does not lend itself to making decisions, assessing the level of risk, the impact of weaknesses or threats, or assigning responsibilities to reduce risk.

Uncertainty happens because you are moving outside of your comfort zone into a state where everything is unknown. You have never experienced this before. The more you are outside your zone, the more uncertainty you will experience. If you are a technical founder, business aspects will cause you to crash. If you are a business founder, it will undoubtedly be the technical unknowns that will cause you to stumble and fail. No amount of training can prepare you because the threat comes not from what you know but from what you do not.

Managing uncertainty requires awareness of what is known and unknown. Uncertainties can be grouped into four categories:

  • Hypothesis: what is guessed to be known;
  • Assumptions: what is known to be known;
  • Risks: what could go wrong that I can control;
  • Dependencies: what could go wrong that I cannot control;

Looking at each point separately:

Hypothesis: A hypothesis is a potential explanation based on a general feeling or intuition. A hypothesis can also be based on observation or third-party data. A hypothesis requires validation through real-world testing such as customer discovery or Lean Startup. Otherwise, it is only a guess. If you have not done your own testing, hypotheses are the most dangerous form of uncertainty.

Assumption: An assumption is what is taken to be true based on practical experience. Assumptions are only as reasonable as the data that backs them up. Assumptions become dangerous when you extrapolate them beyond your personal experience. Assumptions should come with confidence levels to better assess how they influence your uncertainty.

Risks: What elements and constraints under my control could go wrong, what is the cost if they go wrong, and how can I mitigate these costs.

Dependencies: What elements and constraints outside of my control could go wrong, what is the cost if they go wrong, and how can I mitigate these costs. 

Risks and dependencies are the most controllable types of uncertainty. For each, look at the probability of something going wrong (high, medium, low probability), the impact or cost if it should happen (high, medium, low impact) and the effect of mitigation (high, medium, low effect).

This H.A.R.D. framework should then be applied to the five main areas which are critical to early scaling success:

  1. Product – technology readiness level (proof-of-concept, functional prototype, initial deployment or fully operational), robustness, architecture, data quality, development process…
  2. Market – the validity of problem-solution and product-market fit, positioning, market trends, customer discovery and validation…
  3. Business Model – value proposition, profit proposition, customer relationships, channels, pricing strategies…
  4. Financial – cash flow, cost structure, resources, access to debt, access to capital (non-dilutive and dilutive)…
  5. Execution – foundation, skills and systems, team resources, internal value creation chain (Porter’s nine activities), external value creation chain (stakeholders, suppliers, partners, competitors), supply chain…

A comprehensive uncertainty canvas looks like this:

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There should be at least two or three points in each box, including predicted severity levels, validation actions (Hypothesis and Assumptions), and mitigation actions (Risks and Dependencies). In addition, I’ve seen canvasses that assign a specific person responsible for each box, which improves execution accountability. This canvas should be a living document that you and your team regularly revise, usually monthly. The tool can then be used to build actionable OKRs (Objectives and Key Results).

Startups fail when actions based on hypotheses, assumptions, risks, and dependencies with too high a degree of uncertainty lead to losses that are too large to survive. Therefore, a fundamental principle of scaleup strategy is only to risk what you can afford to lose while executing to maximize the probability of success.

Uncertainty mapping using H.A.R.D. is critical to making decisions based on an honest assessment of what you know and what you don’t. Too much is at stake to close your eyes, roll the dice, and hope for the best.

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