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# Lean Startup Cost and Benefits

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The proof that lean startup saves time and money

Dr. Max Völkel, 2016

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### Lean Startup Cost and Benefits

1. 1. Lean Startup Cost and Benefits The proof that lean startup saves time and money Dr. Max Völkel, 2016
2. 2. COPYRIGHTDR.MAXVÖLKEL.,2015 Lean Startup Method ■ You make a plan ■ Be honest, your plan is just a set of guesses and hopes  we call them assumptions ■ Try to validate your assumptions by running cheap experiments, which collect hard data. ■ So you build experiments, measure the outcome, and learn, how you need to adapt the plan (“build-measure-learn”) 2
3. 3. COPYRIGHTDR.MAXVÖLKEL.,2015 Assumptions A ■ A business model can be represented as 9 building blocks in the Business Model Canvas (BMC), from Alex Osterwalder.  9 assumptions ■ Add some assumptions about competition, your team, your sales numbers, market size and you’ll easily have 30-50 assumptions. 3
4. 4. COPYRIGHTDR.MAXVÖLKEL.,2015 Probability p(A) ■ An assumption might be true, or it might not. Let’s say an assumption A is true with probability p(A). 4 p(A) 100% 50% 0% If we have no information whether A is true or not, p(A)=50% (fifty-fifty). If p(A) is < 50%, we have the weird situation that our plan is based on an assumption, which we ourselves already think is rather not true. If p(A)=70%, there is a 30% risk of A being false.
5. 5. COPYRIGHTDR.MAXVÖLKEL.,2015 Cost(A) ■ If A turns out to be wrong, you need to “adapt your plan”. That can be finding another customer segment, choosing a new (hopefully better) channel, tweaking the product, … in all cases, you need to do extra work. ■ Extra work for “fixing” your risky project has a cost. ■ Cost can be quantified in Dollars or Euros, or in person-work-days. Choose a unit and stick with it. Let’s measure in work days. And we really mean time spent working, not waiting. ■ So every failed assumptions has a cost(A), which is really the cost that happens only if A is not true. 5
6. 6. COPYRIGHTDR.MAXVÖLKEL.,2015 Ecost(A) ■ Now we turn to statistics. We need a concept called expected value.  Example: The expected value of a dice showing numbers 1,2,3,4,5,6 is 3.5. ■ Ecost(A) = (1-p(A)) * Cost  If an assumption A has p(A)=50% and cost(A)=80 days, Ecost(A)=40 days. • If we would do the same risky project again and again, on average we would spend 40 days doing extra work due to failed hypotheses. Of course, in reality, we only do a startup once, but as we have 30 or more assumptions, they average out and we will spend, on average the expected value of cost. ■ Ecost is really just the expected value of cost. 6
7. 7. COST AND BENEFIT WITHOUT LEAN STARTUP 7
8. 8. COPYRIGHTDR.MAXVÖLKEL.,2015 Without Lean Startup ■ We have 30 Assumptions  Yes, could be any number, but a range 30-50 is common ■ We estimated for each assumption the probability of being true, and the cost of extra work, if the assumption is wrong. ■ During out project, some assumptions will turn out to be wrong. We just don’t know which. ■ At the end of the project, we will have spent approximately the sum of all Ecost values for doing extra work. 8
9. 9. COPYRIGHTDR.MAXVÖLKEL.,2015 Example with only 5 Assumptions Assumption A p(A) Cost(A) in days 1-p(A) Ecost(A) =(1- p(A))*Cost Assumption 1 50% 20 0,50 10,00 Assumption 2 70% 5 0,30 1,50 Assumption 3 66% 5 0,33 1,65 Assumption 4 80% 1 0,20 0,20 Assumption 5 50% 8 0,50 4,00 Sum 39 17,35 9 Everything else: CalculatedGuessed
10. 10. COPYRIGHTDR.MAXVÖLKEL.,2015 Example with only 5 Assumptions 10 Assumption A p(A) Assumption 1 50% Assumption 2 70% Assumption 3 66% Assumption 4 80% Assumption 5 50% ■ If all assumptions are right, nothing goes wrong, we have 0 extra days of work – very unlikely. • Probability of nothing going wrong for our example is 0,5*0,7*0,66*0,8*0,5 = 9,24%. This number if much smaller for more assumptions. ■ If absolutely everything goes wrong (Murphys Law), we have 39 days of extra work – very unlikely. ■ We should expect extra work of 17,35 days = sum of Ecost values.
11. 11. COST AND BENEFIT WITH LEAN STARTUP 11
12. 12. COPYRIGHTDR.MAXVÖLKEL.,2015 Experiments are costly, too ■ Right, so let’s call doing experiments validation and let Cost_V be the cost of doing an experiment (planning, doing, evaluating data, learning). ■ The whole purpose of the experiment is to move our vague estimated probability p(A) closer to 100%. ■ Let’s accept that we don’t always achieve that.  Maybe we had p(A)=60% and after talking to 100 potential customer we now believe A is true with p = 90%. ■ Let’s call the probability after the validation p_V(A).  Note that even though p_V(A) > p(A), the cost(A) remains the same. If things go wrong, we need to do the same amount of work, no matter how sure we have been, that a particular assumption would be true. 12
13. 13. COPYRIGHTDR.MAXVÖLKEL.,2015 Is the experiment worth it? ■ The expected cost Ecost_V(A) after running an experiment for validating assumption A is Ecost_V(A) = (1-p_V(A)) * Cost + Cost_V  Note how we add to cost of running the experiment (Cost_V) to the expected costs. ■ The benefit of running the experiment is Ecost(A) - Ecost_V(A)  On average, we should spend less time on extra work now, because we have a plan that is based more on true facts and less on wishful thinking or naïve assumptions. Of course, if an experiment shows an assumption is wrong, we remove the assumption from our plan and adapt the plan. 13
14. 14. COPYRIGHTDR.MAXVÖLKEL.,2015 Test every assumption? 14 Assumption A p(A) Cost(A) in days 1-p(A) Ecost(A) Cost_V p_V(A) Ecost_V(A) Assumption 1 50% 20 0,50 10,00 4 95% (1-0,95)*20+4=5,0 Assumption 2 70% 5 0,30 1,50 1 80% (1-0,80)*5+1=2,0 Assumption 3 66% 5 0,33 1,65 6 80% (1-0,80)*5+6=7,0 Assumption 4 80% 1 0,20 0,20 2 90% (1-0,9)*1+2=2,1 Assumption 5 50% 8 0,50 4,00 2 90% (1-0,9)*8+2=2,8 Sum 39 17,35 18,90 Everything else: CalculatedGuessedGuessed
15. 15. COPYRIGHTDR.MAXVÖLKEL.,2015 A Shock! ■ As you saw on the last slide, the expected cost without doing any experiments was 17,35 days, and with doing the best experiment we could imagine for each assumption, our sum of expected costs is 18,9 days. Higher! So Lean Startup is just causing extra work? ■ We should certainly not run all possible experiments. ■ Can we do better? 15
16. 16. COPYRIGHTDR.MAXVÖLKEL.,2015 Do only some Experiments Assumption A p(A) Cost(A) in days 1-p(A) Ecost(A) Cost_V p_V(A) Ecost_V(A) Assumption 1 50% 20 0,50 10,00 4 95% (1-0,95)*20+4=5,0 Assumption 2 70% 5 0,30 1,50 1 80% (1-0,80)*5+1=2,0 Assumption 3 66% 5 0,33 1,65 6 80% (1-0,80)*5+6=7,0 Assumption 4 80% 1 0,20 0,20 2 90% (1-0,9)*1+2=2,1 Assumption 5 50% 8 0,50 4,00 2 90% (1-0,9)*8+2=2,8 ■ For A2, A3 and A4 we should not run the experiments we came up with. ■ Only our experiments for A1 and A5 improve the expected costs. In total, we expect 7,8 days of work instead of 14. So we gain 6,2 days, just for being smart.
17. 17. COPYRIGHTDR.MAXVÖLKEL.,2015 Summary ■ Lean Startup is about doing experiments which reduce your total expected cost. ■ You invest extra work (the experiments) and in return you get either  a) a plan based on true assumptions, with data to proof it (which in turn can convince partners and investors) – or –  b) a new plan, because you found out early where your plan was based on false assumptions before you went ahead and spent a lot of time and money building the product. 17
18. 18. COPYRIGHTDR.MAXVÖLKEL.,2015 Thank You ■ Version 1 published on 2016-02-15 ■ Copyright 2016 by Max Völkel, www.xam.de ■ Licensed under Creative Commons CC BY-NC-SA 3.0, see https://creativecommons.org/licenses/by- nc-sa/3.0/ 18