How to apply MapReduce() to your #startup #funding process

MapReduce comprises of 2 parts – Map() –  filtering and sorting and Reduce () performs a summary operation. The “MapReduce System” orchestrates by marshalling the distributed servers, running the various tasks in parallel. This speeds up the entire process dramatically.

I met with a startup founder who made the rookie mistake of “talking” to 3 angel investors, focusing his discussion on only 1 person, who was going to lead. He then realized after 6 months that the lead investor was in, but others had gone sideways and were not going to invest. He did not spend enough time with the other investors, assuming that the lead investor would corral them.

You will need a lead investor for your angel round. As the founder you will have to recruit, manage and keep the lead investor engaged. There are other investors who may not lead, but are going to be a part of that round.

Your first priority is to identify the lead. Then you have to soft circle and get the rest of the folks to pony up commitments.

Most founders talk to investors who are not leading in serial fashion, going after then one at a time. I would suggest you MapReduce the process.

I know that many folks recommend you have one person in your team responsible for fundraising. I would suggest you filter your investors and assign one person in your team -Map() – to keep other investors “in the loop” – emails, scheduled phone calls or in person briefings.

You (the person responsible to raise the round from investors) should be responsible for the collation and summary – Reduce ().

This reduces risk of waiting for 6 months to finally figure out that you need other co investors and also “involves” your co founders in your company to help with fund raising.

If you go about it in a serial fashion, (i.e. one investor at a time), the elapsed time to get investment done increases dramatically but your risk of closing the round is still the same.

What do you think? Anyone tried this yet?