A standard rule of thumb for startup selection processes in Latin America is 100/10/1. Out of every 100 startups reviewed, 10 are selected for further evaluation and 1 receives financing. These ratios can be observed across the capital stack – from accelerator programs to later stage venture capital funds.
Real life examples:
Seedstars Lima Regional Summit reviewed 95 startups and out of 30 startups that made the first cut, 8 were selected as finalists. Only one startup, ManzanaVerde, was selected as best startup.
MassChallenge Mexico selected 35 out of 745 startups across the region. Out of these startups, only one will receive equity free funding.
From a founder’s perspective, this means you will hear “no” a lot, as Andres Benavides wrote. But, having these ratios in mind can help you strategize.
Know where you are in the funnel and act accordingly. Work to get to from 100 to 10, and then from 10 to 1.
First, get from 100 to 10:
Take a long term strategy. Applying this year can increase your chance of acceptance in future years
Apply to programs whose purpose and selection criteria match well with your startup
Use current relationships and investors to provide warm intros
Ask where you are in each stage of the process and next steps to gauge probabilities
Next, get from 10 to 1:
Get into selection round/due diligence with a few potential programs and investors in parallel
Refine you pitch and get ready to present to an investment committee or panel of judges
Be responsive to requests for further information
Have a reference list ready for current investors or clients
Reach out to current portfolio companies to inquire about the program or fund
Be proactive in showing interest and sharing how you will get the most out of the program or what you hope to add to the accelerator batch or fund portfolio
If it doesn’t work out, apply again next cycle. Your startup will be in a much different (and better!) place than 12 months ago. If you can show progress between cycles it will do wonders to getting from 100 to 1!
The 1-10-100 Rule was born from this research. In data quality, the cost of verifying a record as it is entered is $1 per record.The cost of remediation to fix errors after they are created is $10 per record.The cost of inaction is $100 per record per year.
Out of every 100 startups reviewed, 10 are selected for further evaluation and 1 receives financing. These ratios can be observed across the capital stack – from accelerator programs to later stage venture capital funds.
The 1-10-100 rule is crucial because it highlights the significant cost implications of poor data quality. When data quality issues are not detected and corrected at the point of entry, they can propagate downstream, causing errors and inaccuracies in downstream systems and impacting business decisions and outcomes.
The '100-hour rule' is not just an arbitrary figure. It's anchored in the concept of deliberate practice. Researchers have illuminated that deliberate, feedback-driven practice is far more effective than mere repetition. This targeted approach to skill acquisition and improvement is what the '100-hour rule' embodies.
The Rule of 100 says that under 100 percentage discounts seem larger than absolute ones. But over 100, things reverse. Over 100, absolute discounts seem larger than percentage ones.
The 1-10-100 Rule is related to what's called “the cost of quality.” Essentially, the rule states that prevention is less costly than correction is less costly than failure. It makes more sense to invest ₹ 1 in prevention, than to spend ₹10 on correction.
In statistics, the one in ten rule is a rule of thumb for how many predictor parameters can be estimated from data when doing regression analysis (in particular proportional hazards models in survival analysis and logistic regression) while keeping the risk of overfitting and finding spurious correlations low.
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