SCAR: a 4-steps framework to solve strategic ambiguity
"Our goal is to get to €100k MRR and then raise a series A".
I've heard (and said!) this exact phrase or a variation of it many many times. I have some thoughts.
Revenue is a continuous variable. Why is €100k MRR the goal? Why not €80k? or €120k? Why is that a meaningful number in the context of a series A round? And why are you raising that round in the first place?
If you don't have a clear answer to such questions you're lacking strategic clarity and that's hurting your ability to raise and most importantly allocate capital.
Founders should strive to look at their company journey as a series of discrete turning points the team is working towards.
The ideal goals are discrete in nature and measurable in numbers or booleans (yes/no).
They should also make sense collectively: as pieces of a puzzle, your array of goals, when achieved, should paint a clear picture. There should be a before-after.
Back to our example: say that €100k MRR is how much you need to get to breakeven. In that case, getting to €100k MRR qualifies as a turning point as being profitable is certainly a meaningful goal as the company's downside risk is massively reduced.
There's a clear discrete quality to being profitable or not.
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But that only really matters if you believe that matters for the series A investor you want to work with. You could end up discovering capital markets now value efficiency (certainly now more than in ZIRP times) but not at every cost.
You'll likely have to sacrifice something - a bit of extra growth, or some new features - to get to profitability at that (any) run rate and that tradeoff may ultimately get you to not raise capital.
So what do you do? How do you solve for strategic ambiguity and avoid going down the wrong path or an undefined one?
The SCAR - Set, Check, Align, Review - framework can help you out. Here's how it works:
Important caveat: the SCAR framework is designed to help founders sketch a light on blind spots but can't help you come up with an objectively good strategy nor help you make something people want.
For that - nobody can really help but your own entrepreneurial capability and talking to customers.
Let me know if you find the SCAR framework useful - and how I can improve it!
Cheers
Data Products | ML/AI Consulting | Autonomous agents | Verifiable computing | Megaprojects forecasting
1 年It's more a general rule to navigate uncertainty, not particularly tied to startups or management. In Data Science and AI, we follow the same methodology for lean experimentation: measurable success, proceed sequentially, learn, adjust, iterate. This is also how some optimisation algorithms walk through complex high-dimensional spaces toward a local minima.
No fluff growth strategist ?? | Taking B2B SaaS startups from 0 to ?? | My heart beats faster for data and croissants ?? | Reforge Alumni ?? | Sea creature ??
1 年Assume you’re ignorant’ - that is a gold nugget right there. We tend to ‘assume we’re wise’, and base our actions on that assumption. And that often gets in the way of learning what will actually move the needle and get us to that ‘ideal end state’.
?? Founder | Flutter Enthusiast | EMBA Ambassador @ Polimi | Digital Transformation | Business Advisor
1 年Very good approach. Anyway, this is not confined to startup approaches, it should be a normal approach in any business, very useful in any situation. It’s very similar to the PDCA (Plan Do Check Act) cycle, a leverage on which every continuous improvement should be based.