Decision Science doesn't have to be Rocket Science

As we have said before, AI is a label. Just as 'car' is a label. To make a good decision, you need to know if you are talking about a Toyota Prius or a Dodge Hellcat. If you don't know which is which, for a decision maker, picking one or the other may be a disastrous mistake.

To make better decisions and be able to effectively put the underlying mathematics (which is what AI, machine learning and software is based on) to work, it's important to link the proper tool to the proper application and it needs to be understood and applied in the right context.

Our engineering, data science and decision science team members think in terms of the underlying models and math. That's their job. They need to understand the rocket science, and to push the boundaries. They need to understand and be confident in the 'Art of the Possible' but also be able to learn from other models and disciplines, like neuroscience, psychology, sociology, and quantum physics to name a few.

But, that doesn't mean our customers and those who use our tools need to focus on those things. Instead, they should be focused on the hard work they do as brand and retail professionals...making sure that the right products, promoted in the right way get to the customers who want and need those items most. Delivering on their own 'Art of the Possible'.

The brand and retail professionals we work with should be able to tell simple and powerful brand stories and create amazing experiences, delivered consistently for their customers, across the channels they feel are important.

They need to work hard to convert 'Light Buyers' into 'Frequent Buyers' and also to introduce their brand, products and experience to new customers who have not yet purchased, but will benefit from engagement. Ask any of them and they will tell you this is no easy feat. And, it is only getting harder and harder.

But that is their job, which they do well. Our job is to enable them by helping to separate the signal from the noise in the marketplace and identify the often invisible connections between people, products, places and content.

To do this, we created our own simple story to introduce DecisionArts and our Knowledge Engine, FELIX.

Why call our Knowledge Graph FELIX? Well, Felix is name is latin for 'Happy' or 'Lucky'. DecisionArts' Mission is:

"What if you could learn from mistakes without ever actually making them?"

So, FELIX seemed appropriate. Take a look at this short introduction video on how FELIX works and why, if you are a CPG brand or retail executive, it may matter to you and your team.

Either click on the above image or this link to watch how FELIX delivers value.

DecisionArts. Using Decision Science to move AI from Cool to Commercial. If you are interested in learning more about FELIX or DecisionArts, drop us a line at hello@decisionarts.io to set up a time to have that discussion.