052 - Reasons Automated Decision Making with Machine Learning Can Fail with James Taylor

In this episode of Experiencing Data, I sat down with James Taylor, the CEO of Decision Management Solutions. This discussion centers around how enterprises build ML-driven software to make decisions faster, more precise, and more consistent-and why this pursuit may fail.

We covered:

• The role that decision management plays in business, especially when making decisions quickly, reliably, consistently, transparently and at scale.
• The concept of the "last mile," and why many companies fail to get their data products across it
• James' take on operationalization of ML models, why Brian dislikes this term
• Why James thinks it is important to distinguish between technology problems and organizational change problems when leveraging ML.
• Why machine learning is not a substitute for hard work.
• What happens when human-centered design is combined with decision management.
• James's book, Digital Decisioning: How to Use Decision Management to Get Business Value from AI, which lays out a methodology for automating decision making.

Quotes from Today's Episode

"If you're a large company, and you have a high volume transaction where it's not immediately obvious what you should do in response to that transaction, then you have to make a decision - quickly, at scale, reliably, consistently, transparently. We specialize in helping people build solutions to that problem." - James 

"Machine learning is not a substitute for hard work, for thinking about the problem, understanding your business, or doing things. It's a way of adding value. It doesn't substitute for things." - James

"One thing that I kind of have a distaste for in the data science space when we're talking about models and deploying models is thinking about 'operationalization' as something that's distinct from the technology-building process." - Brian

"People tend to define an analytical solution, frankly, that will never work because[…] they're solving the wrong problem. Or they build a solution that in theory would work, but they can't get it across the last mile. Our experience is that you can't get it across the last mile if you don't begin by thinking about the last mile." - James 

"When I look at a problem, I'm looking at how I use analytics to make that better. I come in as an analytics person." - James

"We often joke that you have to work backwards. Instead of saying, 'here's my data, here's the analytics I can build from my data […], you have to say, 'what's a better decision look like? How do I make the decision today? What analytics will help me improve that decision?' How do I find the data I need to build those analytics?' Because those are the ones that will actually change my business." - James 

"We talk about [the last mile] a lot ... which is ensuring that when the human beings come in and touch, use, and interface with the systems and interfaces that you've created, that this isthe make or break point-where technology goes to succeed or die." - Brian

Links

• Decision Management Solutions
• Digital Decisioning: How to Use Decision Management to Get Business Value from AI
• James' Personal Blog
• Connect with James on Twitter
• Connect with James on LinkedIn