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Behold the Power of Superforecasting

This podcast first appeared and originally published at https://soundcloud.com/user-454088293/behold-the-power-of-superforecasting on August 26, 2020.

 

In just 2 minutes, you’ll learn why superforecasting is so much better than forecasting. Hear how automated, data-intensive AI with no human bias can help make predictions and adjust strategy on the fly, and how startup Complete Intelligence is making it happen.

 

Is forecasting enough when you need to analyze and take action? Meet the startup that says “no.” What’s needed is superforecasting.

 

Hi, it’s Mike Stiles, and this is Meet the Startups for the week of August 26th, brought to you by Oracle for Startups.

 

How can you be happy with forecasting when there’s something out there called superforecasting?

 

Startup founder Tony Nash and his company, Complete Intelligence are making super forecasting possible with a highly automated, data intensive A.I. solution.

 

Part of what makes it so SUPER is there’s zero human bias. No spin or wishful thinking allowed.

 

Complete intelligence is helping organizations visualize financial data, make predictions and adjust strategy on the fly. That gets you things like smarter purchasing, better supply chain planning, smarter cost and revenue decisions.

 

But it’s intense.

 

More than 15 billion data points are run on Complete Intelligence’s platform every day.

 

To get where they needed to be on performance and price, the company moved from Google Cloud to Oracle Cloud. That did it. Computing is at peak performance and Complete Intelligence’s global customers are reaping the benefits. That’s super.

 

We asked Complete IntelligenceCEO Tony Nash what this pandemic has done to forecasting and supply chains.

 

”We’ve seen a big shift in how managers are looking at their supply chains. As a result of Covid-19, companies are eager to understand their cost and revenue risks, things like concentration risk and the timing of their cost, that sort of thing. We’re helping our customers with timely and accurate information to make smarter cost and better revenue planning decisions.“

 

What startup doesn’t like better performance and lower costs? Oracle has a startup partnership for you at Oracle.com/startup.

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What is Complete Intelligence?

Tony Nash, CEO and founder of Complete Intelligence, explains what the company’s platforms do. This video is produced by Real Vision. For more information, visit our website at https://completeintel.com/

 

Complete Intelligence is an artificial intelligence platform that forecasts assets, currencies, commodities, equity indices, and also does advanced procurement and revenue for corporate clients.

 

What we’re doing is we’re using reinforcement learning, which is effectively a number of neural networks. We use right now about 21 different neural networks to test every single asset.

 

Let’s say you have a bill of material for a mobile phone and you’ve got 7,000 items in that mobile phone. We’re integrating with an ERP system to put all of that data out of the ERP system for that mobile phone and we’re telling that manufacturer exactly how much every element is going to cost them for the next year.

 

If you look at everything as a bill of material, a portfolio is effectively a bill of material. We do the same thing for portfolios. We do the same thing for product revenue forecast.

 

We look at the world as a math problem. It doesn’t matter if it’s gold, or a diode or plastic or crude oil, or Japanese yen. It’s a number that behaves a certain way.

 

And there are anomalies, there are inflections, there are any number of things. But we don’t have any causal conviction on any asset the way it trades. Whether that’s traded through a procurement team, or whether that’s traded through an exchange, it doesn’t really matter to us. We’re looking at the behavior of numbers.

 

We have billions of data items in our platform. We’re running billions of calculations within our platform, and we’re testing more than a million different potential drivers for that element.

 

We’re not enforcing any causality or any driver environment on anything.

 

The underlying hypothesis of what we’re doing is very simple. The world is a closed system. And when we say that to people, they say, “Well, of course it is.” But the way they think of the world doesn’t necessarily align with that.

 

From day one, the way we built our approach, the way we built our platform, all has the underlying assumption that the world is a closed system, and everything is a tradeoff.