Saturday, May 30, 2015

Team Structure For Building Predictive Analytics and Intervention Products Based On Big Data For the Enterprise

I have been an enterprise application product manager for many years. Most applications I built automated processes, enabled collaboration and integrated applications. Recently I started leading teams building predictive analytics applications based on big data. There was no established training program or team structure I could follow. So I observed the way my product team worked and arrived at the following structure. 

I assume that the user of any such product will want to derive insights from large volumes of data, take action based on the data and monitor the results of their action.

Team One
Problem formulation, predictive model design, testing. This team requires problem formulation experts and data scientists.

Team Two
User experience design for consumers of insight. 
Intervention Design and testing
Consumer experience design

This is the team that simplifies the consumption of insights derived from big data. This team also enables the consumers of insights act on those insights.

Team Three
Builds monitoring tools and reports on performance of the interventions. This team requires analytics product managers and analytics engineers.

Team Four
Web Application programming.

I may have missed some roles and responsibilities. But this broad structure seems to work. I will have a better understanding in the coming weeks and months.

Monday, May 18, 2015

I Am Going To Help Employers Manage Healthcare Costs and Improve Employee Wellness

In the 1990s, I bet my career on multimedia technology, co-founded an eLearning company with a few others and successfully sold the company for $60 Million to DigitalThink, a cloud learning company in San Francisco. In the 2000s, I bet my career on cloud technology by working at DigitalThink for a few years. That experience brought me to SAP where I managed SAP Enterprise Learning, designed SAP Career OnDemand and then was the solution manager for SuccessFactors Integration with SAP. In early 2014, I realized that the coming years are going to be about making sense of data and taking actions based on the insights derived from data. Any business or professional who does not understand data will be at a disadvantage. So I enrolled in a data science course in Johns Hopkins University to understand the basics of data science and got a certificate. I did not become an expert in the field. But I was knowledgeable enough to talk to and work with data scientists. I also developed basic hands-on data science skills.

A few weeks back Peter Diamandis, the founder of the X-Price Foundation came to Cafe 1 in the Palo Alto campus of SAP and spoke about the profound changes awaiting us in the next few years. He talked about the $1000 human brain, the trillion sensor economy, 8 billion hyper-connected people, disruption of healthcare, augmented reality, artificial intelligence and block chain. I was inspired by his talk and walked away wondering if I could play a part in any of those areas.

Around the same time, a small company  that is doing some innovative work to make the cost of healthcare transparent to everyone reached out to me and asked me if I will lead a team that will build products to help employers in the US manage their healthcare costs and employee wellness. They explained to me that there is a criminal lack of transparency in the healthcare industry. For example, a blood test could cost $10 at a lab and $200 at a doctors office. A surgery could cost $3000 in one hospital and $20,000 in another in the same city. The patient would not even know about the actual cost of the procedure until several weeks later, even if they care to look at it.

It sounded ridiculous to me. My company would not let me book a flight or hotel without knowing how much it costs. It even has limits on how much I can spend on a flight, hotel, meal or taxi. But the same company does not care about me signing up for a medical procedure, even an unnecessary one, with out understanding the cost involved and spending tens of thousands of dollars more than necessary.

Such behavior is affecting individuals by reducing their disposable income and their quality of life, affecting employers by decreasing their profitability and affecting governments by increasing healthcare costs and hence increasing taxes for everyone. Some experts estimate that we are wasting $180 Billion every year because of such inefficiencies. If this continues this will make US businesses less competitive. This is a potential disaster that will bring the US economy down soon, if something is not done about it.

The good news is that we have the ingredients such as data, predictive models, cloud technology, software product design principles and persuasion techniques to build solutions that can chip away at this problem. I have skills and some experience in this area. So I agreed to join this small company and help them build this product. This is not a wild and crazy bet. This is a calculated, level-headed and genuine attempt to apply my skills to a problem that affects every one of us, including our family members who do not work outside the home. I am cautiously optimistic about this assignment. I might share more once I understand the culture of the company and their social media policies. Time will tell if I took the right decision.
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