Triangulation: Predictive Algorithms and Crowd Wisdom
When work is interesting!
One of the most interesting aspects of my job, well they are all interesting, but I do find the AI components i.e., Predictive Analytics, Algorithms, and Machine Learning especially interesting in our context. Where we are trying to ‘predict’ the future we need to rely on something to do so. I put predict in ‘’ as we cannot really predict an event, however, we can benchmark a series of desired outcomes against probability factors that might lead to a probable outcome.
What are Predictive Analytics?
IBM defines it as: “Predictive analytics is a branch of advanced analytics that makes predictions about future outcomes using historical data combined with statistical modelling, data mining techniques and machine learning. Companies employ predictive analytics to find patterns in this data to identify risks and opportunities”.
How does this relate to ‘predicting’ the success of a company?
As futurists we always do a deep dive into the past to try and define a probable outcome. This means that we look at the history successful companies and failure companies. This is the Data Mining Process whereby we can identify predictive factors.
We then create algorithms to take supplied information about a start-up company and benchmark that to the predictive factors.
This gives us a technical score i.e., one based purely on information. This is our algorithm that we use in the i3D Protocol.
Let’s use an example:
If company A with a founder aged 45, and a company B with a founder aged 28, are both competing for the same amount of funding in a similar tech sector, and they both seem to be worthwhile supporting, how do you decide which company to fund?
This is where a predictive factor can sway the decision. A prime example is that of the Founder’s age. Research shows that a founder who is +40 has a much greater chance of success than a founder who is <30. So, if the only difference between A and B companies was the age of the Founder then the unemotional choice would be to fund Company A.
This is of course very simplified. However, if you expand the number of predictive factors to dozens, for example, i3D Protocol currently uses 11 Factors and 62 Sub-factors, then your predictive analytics and algorithms become more robust.
Is this enough?
Due to the unpredictability of human thought processes, simply using a predictive algorithm to define success is not enough. Imagine we all thought the same? Life would be entirely predictable but so boring.
While assigning ‘experience’ a predictive factor, utilizing the gut feel and expertise of a network of experts, make the combination far more powerful. Countless research has shown that independent analysis of the same data by different cross sector experts is more powerful than an echo chamber of experts who sit side by side daily. This is because independent thought taps into different and multiple levels of experience i.e., different, and informed viewpoints. This is what we do in the i3D Protocol’s Arena. We use structured formats that allow our experts to independently assess the same data.
Using predictive analytics and wisdom of experts thus brings us closer to identifying success!
But is this enough?
History is littered with examples of well researched predictions that have failed miserably. A massive reason for this is the lack of the research into whether there will be adoption by the end users. Will a population support a war that seems winnable? Will a population adopt a new technology? Will a population use a new product?
This is where tapping into the Wisdom of the Crowd comes into play. Timing to market is crucial for any start-up company. If there is no uptake from the Crowd, the product is doomed to failure, or needs to wait some time before entering the market. This is undoubtably one of the most difficult phases for any company – crossing that chasm from ready to go to market, to enough user adoption to make the company sustainable.
This is what we do in the i3D Rapid where we use a summary of the information/data (often called an elevator pitch), and we send that data to the Crowd for their Wisdom. They follow a similar but smaller structured question set which can be rapidly completed via the mobile app.
Using predictive analytics and tapping into the Wisdom of Experts & the Crowd and benchmarking them all against each other takes us closer to that holy grail – identifying the next big success!