How do I know that I even want to pursue that dream?
What? That sounds weird. You won’t believe how many people approach me and ask — “How do I get my startup Funded?” or “Can you match me with an investor? for my…”.
These kind of questions hold some basic underlying assumption, that in my opinion is undeniable — Those people truly believe that what they are offering is at least amazing and the world not only should, but must have their product, service Etc…
How I view it, there is this human tendency for people to fall in-love with their ideas and “solutions”. But the sad truth about blindly falling in-love with your solution is now you don’t see your sweethearts defects. There is no real perceived need for “Validation” because isn’t the best validation an emotional one?
Once you get over that basic understanding that on day one you know nothing. That all you have are assumptions that need to be validated through a “Validated learning” process. Once they are over that, most people ask a very very fundamental question which I believe should be asked “Light years” before the first one — “Is this worth the next 3–4 years of my life?”. Trivial right?
Well apparently most first time(and some serial) entrepreneurs don’t have the itch to answer that question before even starting. This leads to a somewhat philosophical question, well what is worth?
I will avoid going all philosophical on you and leave that part for you to work with yourself, but there is a common agreement for the term worth in popular culture and that is money, “How much money is this worth if get all market share?”, are we in a 10 Million or 2 Billion market. Shocker, but It doesn’t really matter if we are correct about the numbers or not. As long as we are right to a degree of a power of ten.
So a very nice and useful method I use is a “Fermi Estimation” sometimes called Fermi Calculation. Out of Wikipedia:
The estimation technique is named after physicist Enrico Fermi as he was known for his ability to make good approximate calculations with little or no actual data. Fermi problems typically involve making justified guesses about quantities and their variance or lower and upper bounds.
The most chewed on example which they use in Wikipedia to is “How to estimate the amount of piano tuners in Chicago”. So I am going to run an example here “live”:
So let’s say I want to develop an app that finds me local handyman in my area and brings me my friends feedback on them, and I have identified that my Beachhead niche are plumbers(I had this terrible leak last week, so yeah plumbers…) Before I continue it’s important to state that this should be “quick and dirty” If you can’t find somethingquickly make a logical rough estimation, the theory behind how this works is that you are making these estimations with an error range of a power of ten and the over-positive assumptions cancel out the over-negative assumptions.
Before I even start running customer discovery interviews isn’t it smart to know how many plumbers are there? OK so let’s use Israel for this case. First assumption, How many households in Israel — A quick check in the Central bureau of Statistics website and I find that there are 2,417,700 households.
OK so at my current apartment there are 3 sinks and at my friends home there are 5 sinks — let’s go for a rough estimation of 4 sinks per household. that gets us to around 9,670,800 sinks in Israel. For me, it makes sense that around once a year every sink needs a fix. and taking into consideration driving time I guess each plumber can address about 3–4 sinks per day.
There are roughly 250 work days in Israel, So each plumber can manage around 850 sinks per year. It’s important to note that I am making a basic assumption based on supply and demand that there should be roughly the amount of plumbers there should be to take care of all the sinks in Israel.
So 9,670,800/850 = 11,377 Plumbers is the number I got. It’s important to note that I know plumbers don’t just fix sinks and to be honest I guess each sink “survives” more the a year, but the whole concept is keeping it light and fast and if you make logical incremental steps over-negative assumptions will cover for the over-positive ones.
So I looked for some online data to see if I got it quite right. Found this government database and behold:
In my own opinion that is a very good margin of error. Now, there is no chance that this replaces customer discovery interviews or a rigours process of turning assumptions into hypotheses and coming up with MVP experiments to validate them. but it is a very practical and efficient tool to do ballpark calculations that are critical to know before starting pursuing anything. Your personal time doesn’t fluctuate. it is the only resource you own that goes one way only.
What kind of back-of-the-envelope calculations have yous done and how did they help?
I would love to hear feedback about this piece, feel free to PM or email me about this article or on any other subject.