Ned Brody: Developing Businesses and Driving Value Utilizing AI and Data Science
Ned Brody has led a variety of technology businesses over the last 20 years, having been Yahoo's Head of the Americas, CEO of AOL Networks, Chief Revenue Office of AOL, and CFO of LookSmart. Previously he started and led Mercer Management Consulting's (now Oliver Wyman) Internet Practice and San Francisco Office. Ned holds a MBA and a BS from the Wharton School of the University of Pennsylvannia with concentrations in decision theory and finance.
Ned is the founder of Foundry.ai along with Jim Manzi (a fellow alum), which is a technology studio focused on data science. The company utilizes small teams and data to rapidly iterate and launch concepts and companies. We sat down and asked him what he's up to and how life has been since his consulting days.
What are you currently up to?
Foundry.ai is a technology studio focused on developing businesses that utilize artificial intelligence and decision science to drive value. So what does that mean? Think of the metaphor of a movie studio in the 1930s where studios produced movie after movie with the same set of directors, actors, cinematographers who were all on contract. Instead of creating movies, we have a team of developers and data sciences, and we ideate, prototype and then launch technology businesses. If the ideas work, we bring in a separate management team and outside funding to grow the businesses further. We have or are building businesses in healthcare, consumer internet, financial services and energy.
The structure allows my partner and me to work on multiple companies across a range of industries in a variety of roles, e.g. from co-creator to product manage to fund raiser to board member. Perfect for experienced people with A.D.D.
What led you to your current line of work? Did your background at Oliver Wyman help?
Oliver Wyman certainly helped. I learned very early in my consulting career the value of data in proving hypotheses and creating value. In the late 1980s, when I started in consulting, most companies had managerial and "I.T." distinctions. A company's data existed and was manipulated by IT people who almost never spoke to management on strategic or tactical decisions. Canned reports aided decisions, but test and learn or rapid iteration really didn't exist in the way it does today. In the geekiest move ever made, I had the firm buy a 6250 tape drive (look it up) that could be attached to a PC. It was the only way to get large amounts of data from a client. We could construct algorithms and model results in almost real time for things like pricing models, inventory storage requirements, fully-allocated cost modeling, etc. These allowed the firm to create real value for clients.
The intellectual leap from then to what I do now is not hard to see. The internet, APIs and cloud infrastructures offer the greatest test and learn environment ever seen. The costs of trial are tiny, the insights scalable. That leads to great opportunities for value creation. Think of the new data sources coming online. In healthcare, electronic health records create an enormous data set providing the opportunity to drive new insights, better outcome and new operational efficiencies. In other industries you can create data: natural language processing makes scanned material like contracts, payment terms and SLAs into real data. Add intelligent algorithms, which are often applicable across data sets, and you can create value.
What was one of your most important experiences at Oliver Wyman?
Honestly, the most useful experience was the exposure to a network of very smart people who can adapt quickly to solve a variety of problems. Jim Manzi, my partner at Foundry.ai is also a Oliver Wyman alumni. One of our businesses, Vizual.ai is now funded by John Borthwick, another Oliver Wyman Alumni. Our second business, Supplier.ai, is actually a JV with a UK company run by two other Oliver Wyman alumni, Ed Ainsworth and Peter Marson. We'd love for this pattern to continue, so anyone reading this who knows of an interesting area where AI could help, please reach out!
How is what you're doing now similar to what you did at Oliver Wyman? How is it different?
In many ways the role is similar to consulting:
- Exploit what you've learned on one project or company to apply to a problem in a different industry
- Learn the new jargon and industry-structural issues as quickly as you can to become credible
- Devise a set of hypotheses and test them using a combination of data science and business planning
The difference is that in consulting, where you rarely get to cross the line from advising to doing, this is all about doing as even the best planning and testing doesn't guarantee success in the market.