Morgann Carlon is fascinated by taking various events, points in time, and seemingly disparate data points to make informed decisions and predict outcomes.

Can you share the most interesting part of your career journey?

That’s tough! I think just the variety of projects that I’ve been on. I’ve led the build and implementation of algorithms for a health provider to help reduce hospital length of stay, designed contact center whisper and virtual agents, built new AI organizations, developed company strategies across nearly every industry, worked with startups to help them build product strategies, moved to Japan for a short-term analytics strategy, designed new assets for Deloitte, built data modernization recommendations to move to the cloud, and advised hundreds of analytics and AI clients.

My diverse teams across all of these projects have taught me so much, and I think bringing each project learning to the next project has been extremely interesting.

What excites you most about working with data and AI?

Honestly, data and AI just make sense to me. I love how we can take all these events and points in time and seemingly disparate data points and, from that, we can make informed decisions and predict outcomes.

And, while building proof of concepts is exciting from a technical perspective, I love seeing AI in the hands of end users.

And, while building proof of concepts is exciting from a technical perspective, I love seeing AI in the hands of end users. It is so satisfying to see a patient health care coordinator be able to use predictions to give better care to patients or for a call center agent to be more informed (and less stressed) about a consumer’s needs and help anticipate how best to help. As a consumer of AI, I love seeing it work and benefit my friends and family.

Describe an interesting project that you have worked on.

All of my projects are interesting, so it's hard to choose just one. But I’d say one of my more recent projects has been a truly amazing project due to the really strong team, the potential impact of our AI, and the client's energy.

At a national health care provider, we were trying to understand big problems that, today, are dealt with using gut and intuition. One that bubbled to the top of the pile was that in some cases, patients in a hospital could be medically discharged, but due to one or another reason operationally, the patient has to have another night in the hospital.

I loved how this project was so impactful to our client, patient outcomes, healthc are affordability, and it brought together so many of the great teammates at Deloitte to tackle a problem together.

My team brainstormed, hosted workshops, interviewed stakeholders, built hypotheses, and then wrote algorithms to test if we could predict patient outcomes (which we did with >96% accuracy). We had team hackathons and mini-competitions to get the best results in our algorithms. We brought in advisory panels to advise us on the ethical considerations. We met with domain specialists to discuss implementation considerations. I loved how this project was so impactful to our client, patient outcomes, health care affordability, and it brought together so many of the great teammates at Deloitte to tackle a problem together.