KDnuggets Interview: Inderpal Bhandari, IBM Global Chief Data Officer on 4 key ideas of Cognitive Computing
In this wide-ranging interview, we discuss the role of IBM global chief data officer, 4 key ideas of cognitive computing, risks of AI, IBM Data Science Experience, healthcare, basketball, sports analytics, and more.
GP: Q5. Before IBM you were Chief Data Officer at several health-related companies. What are the key issues today in medical and health care data ? Will the main impact of better data analysis be to reduce health care costs or to improve individual health?
IB: All stakeholders in the Healthcare system desperately need data driven strategies aimed at improving quality of care while managing cost, as we transition from fee-for-service to fee-for-value in the post ACA era.
There are several key challenges - and opportunities - in healthcare today.
1. There's rapid digitization where volumes of health-related data from a variety of sources have created data management and integration challenges.
2. Regulatory complexity - due to complex and rapidly changing regulations, healthcare organizations face growing compliance costs as they struggle to deliver services within rigid limits.
3. Improved access to data and insights could help the industry more confidently navigate the world of regulatory compliance without stifling medical exploration and discovery.
4. And of course there's increasing cost pressure.
In this environment, healthcare providers are challenged to find new ways to manage costs and efficiency without compromising service quality. Finally, consumers are becoming much more savvy and requesting personalized, high quality, affordable, and convenient care. Healthcare organizations have to explore new service models to meet rising customer demand.
Better data analysis should do both - reduce healthcare costs and improve patient outcomes.Data really drives population health management. Already, cognitive systems help enable enhanced patient care, advanced discoveries, and better decisions for providers around the world. New discovery tools and capabilities can help unearth insights and ideas buried in the masses of data available today, thereby facilitating research and innovation. And better decision capabilities will allow for more personalized, evidence-based recommendations at the point of care, resulting in enhanced care management.
GP: Q6. Back in 1990-s at IBM Research you developed a program called Advanced Scout, which did Data Mining in NBA Data. Tell us what it did and what effect it had on NBA.
IB: Yes, I was a Research Staff Member at the Thomas J Watson Research Center from September 1990 - August 1997 (7 years). Before the practice of analyzing Major League Baseball stats led to the popular book and movie, "Moneyball," IBM Research was helping National Basketball Association coaching staffs with Advanced Scout, a data mining tool to help defeat opponents.
The application helped NBA coaches make game-day decisions, including the best positions for players and best match ups of player combinations. Advanced Scout used an algorithm to find patterns among statistics and video tape to devise new strategies. It also changed the NBA. Traditionally, they had video analyst as part of the coaching staff of every team. Post Advanced Scout, they broadened the role to Video and Data Analyst. Advanced Scout is often viewed as the precursor to the capabilities featured in Moneyball and the growing sports analytics field. At one point, 25 NBA teams used Advance Scout.
As the lead IBM Researcher who developed it, Advanced Scout was a very early application for data analysis users who weren't in technical fields. It's great to see how this field has developed.
I like to joke that after Advanced Scout I went on to start my own company when really I should have written a book such as Moneyball.
GP: Q7. What do you think about the impact and usage of analytics / data mining in sports today?
IB: It has only grown in importance and impact - from predicting the best players, to drawing up recommended plays, to assigning probabilities to expected match outcomes.Arguably every major sports team now has an analytics department contributing to decision-making, and teams that aren't making this investment may find themselves at a competitive disadvantage. Building player profiles - who to draft, sign as a free agent, acquire in a trade, what play call to make, applying a range of stats like prior matchups, win-loss records, even non-traditional data like weather, travel schedule, arena venue, can all be applied to predict the outcome of a future sports match-up. Recommendations can be counter-intuitive and require coaches and their staff to dig into the data to uncover what's driving the insight.
For basketball specifically - it's really interesting to see how some of the research and tools we started back in the late 90s have grown. The NBA's "Player Tracking" tool for example - fans can now see an incredible range of player statistics at the individual level - from touches broken down by position, elbow, post, paint, to speed of all forms of movement from standing, sprinting and everything in between, along with traditional offensive and defense stats. These individual stats are rolled up to evaluate the efficiency of the team as a whole. Sports analytics is an exciting application of data-driven decision-making.
GP: Q8. After you left IBM Research you started a company called Virtual Gold. Tell us about your startup experience and what are some interesting lessons you learned from it.
IB: Starting my own company was where I grew from researcher to executive. My startup experience was very positive, and certainly informs my leadership style today. We very much work in the open - I invite my teams to participate in decision-making and expect that we will respond quickly to keep up with changing demands of the business and needs of our customers. The importance of being able to crisply define your company's value proposition, business plan, and roadmap to achieve milestones are relevant lessons. Also, being able to differentiate yourself from a crowded competitive landscape. And, having the very best talent and domain expertise on board. In the startup world - the whole team has to be nimble, willing to jump in and tackle a variety of challenges in short order, and focused on moving the company forward quickly. We're certainly applying many of those tactics today.
GP: Q9. What do you like to do for fun when away from data and computing? What book you recently read and liked?
IB: Some may question whether it qualifies as fun, I picked up martial arts about 15 years ago. I'm now a third degree black belt in Tae Kwon Do and have even been teaching classes for the last couple of years.
I'm often reading many books at once. I recently finished a book by renowned tennis champion Novak Djokovic. In Serve to Win, Djokovic talks about a holistic approach to fitness and performance optimization that has real implications for maximizing energy and performance in many areas of your life.
IB: All stakeholders in the Healthcare system desperately need data driven strategies aimed at improving quality of care while managing cost, as we transition from fee-for-service to fee-for-value in the post ACA era.
There are several key challenges - and opportunities - in healthcare today.
1. There's rapid digitization where volumes of health-related data from a variety of sources have created data management and integration challenges.
2. Regulatory complexity - due to complex and rapidly changing regulations, healthcare organizations face growing compliance costs as they struggle to deliver services within rigid limits.
3. Improved access to data and insights could help the industry more confidently navigate the world of regulatory compliance without stifling medical exploration and discovery.
4. And of course there's increasing cost pressure.
In this environment, healthcare providers are challenged to find new ways to manage costs and efficiency without compromising service quality. Finally, consumers are becoming much more savvy and requesting personalized, high quality, affordable, and convenient care. Healthcare organizations have to explore new service models to meet rising customer demand.
Better data analysis should do both - reduce healthcare costs and improve patient outcomes.Data really drives population health management. Already, cognitive systems help enable enhanced patient care, advanced discoveries, and better decisions for providers around the world. New discovery tools and capabilities can help unearth insights and ideas buried in the masses of data available today, thereby facilitating research and innovation. And better decision capabilities will allow for more personalized, evidence-based recommendations at the point of care, resulting in enhanced care management.
GP: Q6. Back in 1990-s at IBM Research you developed a program called Advanced Scout, which did Data Mining in NBA Data. Tell us what it did and what effect it had on NBA.
IB: Yes, I was a Research Staff Member at the Thomas J Watson Research Center from September 1990 - August 1997 (7 years). Before the practice of analyzing Major League Baseball stats led to the popular book and movie, "Moneyball," IBM Research was helping National Basketball Association coaching staffs with Advanced Scout, a data mining tool to help defeat opponents.
The application helped NBA coaches make game-day decisions, including the best positions for players and best match ups of player combinations. Advanced Scout used an algorithm to find patterns among statistics and video tape to devise new strategies. It also changed the NBA. Traditionally, they had video analyst as part of the coaching staff of every team. Post Advanced Scout, they broadened the role to Video and Data Analyst. Advanced Scout is often viewed as the precursor to the capabilities featured in Moneyball and the growing sports analytics field. At one point, 25 NBA teams used Advance Scout.
As the lead IBM Researcher who developed it, Advanced Scout was a very early application for data analysis users who weren't in technical fields. It's great to see how this field has developed.
I like to joke that after Advanced Scout I went on to start my own company when really I should have written a book such as Moneyball.
GP: Q7. What do you think about the impact and usage of analytics / data mining in sports today?
IB: It has only grown in importance and impact - from predicting the best players, to drawing up recommended plays, to assigning probabilities to expected match outcomes.Arguably every major sports team now has an analytics department contributing to decision-making, and teams that aren't making this investment may find themselves at a competitive disadvantage. Building player profiles - who to draft, sign as a free agent, acquire in a trade, what play call to make, applying a range of stats like prior matchups, win-loss records, even non-traditional data like weather, travel schedule, arena venue, can all be applied to predict the outcome of a future sports match-up. Recommendations can be counter-intuitive and require coaches and their staff to dig into the data to uncover what's driving the insight.
For basketball specifically - it's really interesting to see how some of the research and tools we started back in the late 90s have grown. The NBA's "Player Tracking" tool for example - fans can now see an incredible range of player statistics at the individual level - from touches broken down by position, elbow, post, paint, to speed of all forms of movement from standing, sprinting and everything in between, along with traditional offensive and defense stats. These individual stats are rolled up to evaluate the efficiency of the team as a whole. Sports analytics is an exciting application of data-driven decision-making.
GP: Q8. After you left IBM Research you started a company called Virtual Gold. Tell us about your startup experience and what are some interesting lessons you learned from it.
IB: Starting my own company was where I grew from researcher to executive. My startup experience was very positive, and certainly informs my leadership style today. We very much work in the open - I invite my teams to participate in decision-making and expect that we will respond quickly to keep up with changing demands of the business and needs of our customers. The importance of being able to crisply define your company's value proposition, business plan, and roadmap to achieve milestones are relevant lessons. Also, being able to differentiate yourself from a crowded competitive landscape. And, having the very best talent and domain expertise on board. In the startup world - the whole team has to be nimble, willing to jump in and tackle a variety of challenges in short order, and focused on moving the company forward quickly. We're certainly applying many of those tactics today.
GP: Q9. What do you like to do for fun when away from data and computing? What book you recently read and liked?
IB: Some may question whether it qualifies as fun, I picked up martial arts about 15 years ago. I'm now a third degree black belt in Tae Kwon Do and have even been teaching classes for the last couple of years.
I'm often reading many books at once. I recently finished a book by renowned tennis champion Novak Djokovic. In Serve to Win, Djokovic talks about a holistic approach to fitness and performance optimization that has real implications for maximizing energy and performance in many areas of your life.
