5月 112012

I had the pleasure to sit in on a panel discussion at the  the 9th Annual SAS Health Care and Life Sciences Executive Conference focused on the topic of understanding and managing customer behavior in the changing health care landscape. This panel was moderated by Dipti Patel-Misra Senior Manager in the Center for Health Analytics & Insights at SAS, and included executives from Blue Cross and Blue Shield of North Carolina, Physicians Pharmacy Alliance and the University of North Carolina at Chapel Hill School of Medicine.

Many business segments provide services similar to health insurance to consumers on a renewable, annual contract basis. However, the understanding that those other industries have of consumers is different and more advanced compared to a health plan’s understanding of its customers.  This panel explored how rising health care costs and consumer value priorities are affecting how health care is sought and provided, and how health plans are looking at new ways to engage with their members to retain them and attract new ones.

A recurring theme in the sessions at this event is that the individual plays a critical role in any potential "fixes" to spiraling cost of healthcare. Another recurring theme is that technological advances in recent years provide the possibility of harnessing various forms of technology to drive innovation and positive change, including customer analytics among others.

Michael Parkerson from BCBSNC began with an optimistic view of our exciting times in terms of technological innovation as being a potential source of the problems we face in our current healthcare situation.

UNC Healthcare's Dr. Rubinow emphasized the potential of the individual patient as an interested stakeholder in helping shape what the future looks like for healthcare.  He proceeded to highlight the new collaboration between BCBSNC and UNC Healthcare, called Carolina Advanced Health, which not coincidentally differentiates itself as being patient-centered. The emphasis at Carolina Advanced Health is on one-stop shopping, access and convenience, self-management and technological support, effective encounters and coordination of care.

Ron Smith from the Physicians Pharmacy Alliance highlighted problems with information and communication as one source of issues.  Healthcare information is often incomplete and it's fragmented. Their observations from studying patients with complex medication regimens showed a significant disconnect whereby patients are generally doing what they think they are being asked to do, but they don’t generally understand what they are being asked to do.

 The view from the panel is that analytics can play a key role in helping change the system from one where the patients with conditions have to seek the solution providers to one where the solutions are instead provided in ways to meet the patients where they are. Marketers, of course, recognize that kind of talk as "music to our ears." It's all about customer centricity, which is not a simple matter in an industry where the patient as a consumer of healthcare services deals with health insurance companies, healthcare providers, pharmaceutical companies, pharmacies and other entities. Not simple at all, but decidedly necessary and perhaps long overdue.

More broadly, we need to have a cultural change away from the idea that there's a relationship between good quality care and a large number of tests and procedures. Other good nuggets from this panel included:

  • A statement that UNC's Dr. Rubinow made that HIPAA has been one of the biggest obstacles imaginable to enabling an integrated healthcare system.
  • Social Networking holds great potential to drive desired behaviors and cultural change. Dr. Rubinow highlighted an "offline" example of a boomerang club in Chapel Hill and how its members all had life-altering weight loss experiences.
  • Incentive systems can be very powerful at driving healthy behaviors.

Closing thoughts includes the idea that individuals, data, communications and driving understandings with patients are together what holds the most promise for driving positive change. It all comes back to the patient/member /customer.  Customer-centricity certainly sounds good to most marketers. What do you think?


tags: customer analytics, events, health insurance, healthcare
5月 112012

I am at the 9th Annual SAS Health Care and Life Sciences Executive Conference, an extraordinary event that draws the best and the brightest leaders as both speakers and attendees from the pharmaceutical, health insurance, health care and related industries.  One session featured speakers from Independence Blue Cross sharing their experiences in predicting attrition in the small group market.  Christine Colombo, Senior Director of Informatics and Consultative Business Services presented along with Anna Sickler, Research Analyst.

Christine Colombo of Independence Blue Cross

Colombo leads a team that consults with functional areas within Independent Blue Cross (IBC), as well as customers and providers, to improve performance using data and analytics. This includes program design and evaluation, risk stratification, marketing models, predictive modeling and analytics, and return on investment studies. Sickler is responsible for marketing analytics and has experience in data mining, predictive analytics and segmentation analytics. Since joining Independence Blue Cross, she has helped increase membership by building and implementing predictive models. 

The path to using customer analytics began with a request from the marketing department, hoping to gain a profile of individuals most likely to enroll in individual coverage. Their initial models used a combination of both internal and external marketing data, with the goal to improve on the previous work done by an external vendor.  That project resulted in driving enrollment rates that were double of what the vendor was getting.

Those encouraging results paved the way to applying the same methodology to the small group segment.  In that market, customer retention rates had been declining, so the goal was to create a model that would predict the likelihood of small group customers to terminate.

They focused on 2010 customers with a group size of 2 - 50 individuals, and they found that the segment had about 24,000 customers.  They approached their model with two samples - one for development and one for validation (which is used to show the true results) and they were able to identify key predictors of their cancellation. Membership metrics were averaged at the customer level, and then they used a logistic regression model and group customers with membership in 2011 were scored and used as targets.

The models had seven variables, and two variables were found to be significant when predicting termination: group size (lower number of subscribers had a higher rate) and lower risk scores.  Other factors showed that customers with lower premiums and lower tenure also had a higher attrition rate.

As a direct result of using customer analytics, marketing at Independence Blue Cross will be more effective because they will drive forward-looking behavior.  They will score customers with upcoming renewals and communicate it through regular reporting.  Once they have the data, they will be able to identify the target segments and tailor the communications with those segments with meaningful messages.

They will be able to tailor their marketing in this way through indirect channels, such as brokers and producers, as well as direct channel outreach with messages that might highlight different products, or emphasize value, based on the profile of the segment. 

 The experience of Independence Blue Cross is a great illustration of how the use of customer analytics can drive excellent business results. During the Q&A at the end of the session, one audience member said that as a marketer, if they were able to achieve a doubling of results with this kind of collaboration with their internal analytics group, they would quickly become their new best friends.  I'd love to hear any other stories of data-driven friendships marketers are building.  I know they're out there...

tags: customer analytics, customer segmentation, database marketing, events, health insurance, healthcare
4月 172012

How big does big data need to be before it is valuable?

High Performance Analytics levels the Big Data playing field

High Performance Analytics levels the Big Data playing field

The value in big data is within reach of everyone.  It could mean wanting to mine a couple of extra fields about the customer or wanting to improve the customer profile using unstructured data about customer interactions using Hadoop. Most articles and hype about big data surround the three Vs;  Velocity, Variety and Volume.  However, we should never lose sight that big data is relative to your business plan. The real conversation to be had is about the value in being nimble. 

The 4th (V)alue: The intersection of big data and high performance analytics
High performance analytics is the next generation of analytical focus as we work our way through the era of big data looking for optimal ways to gain insight in shorter reporting windows. It is all about getting to the relevant data quicker and delivering that information in real time. High performance analytics is equipping David-sized organisations with the tools to level the playing field.  Examples include:

  • How a bank determines credit risk assessment in seconds instead of hours.
  • Where a government agency improves social welfare by analysing unstructured citizen interaction data.
  • An insurance company that uses census data to improve marketing response rates.
  • How an online business analyses social data to understand sentiment, and behavioral data to improve campaign targeting.

Regional healthcare provider and an insurers point of view

I recently listened to an Australian healthcare customer discuss their version of big data and high performance analytics. It went like this.

Through some acquisitions we have increased our data base size by approximately 15 percent.  This has resulted in our marketing teams being frustrated with longer than usual time-to-market for gaining customer intelligence and executing campaigns.  Further compounding the issue is the competitive pressure coming from recent changes in government legislation, which is driving customers to shop around.  This increase in competition means marketing needs to be more nimble.  Meaning more campaigns to fewer people with more relevance.

Another example is a local Insurance customer I met with to discuss their version of big data, high performance analytics and real-time analytics.

We have issued our sales force with iPads.  The challenge we face is, how do we deliver intelligence to our sales representatives in a manner where we know it is relevant, timely and contextual?  We know they are meeting with prospects and customers but how do we analyse customer data, analytical data, transactional data and interaction data to provide a Next Best Offer in seconds?

If we understand how to beat Goliath, do we know what to beat him with?  A high performance approach leads us to think about the problem differently and look for a solution that optimises the analytical jobs and the way they were architecturally executed.  I expect there is a target value proposition heading my way, now.

Under the hood: high performance analytics is not that scary

We often think of new technology as being like a Ferrari, always thinking it is out of reach or too complex for the average David.  The reality is high performance analytics provides various approaches that span the spectrum of your maturity and size, from:

  • Moving existing analytical models into operational processes for real-time decisions.
  • Optmising analytical jobs to leverage your existing in-database power.
  • Using in-memory analytics to take advantage of cheaper hardware.
  • Building an enterprise analytical platform to drive down TCO while always prioritising business value using a grid based approach.
  • Visually exploring big data using high-performance, interactive, in-memory capabilities to understand all your data, discover new patterns and publish reports to the web and mobile devices.

The democratisation of analytics, especially high performance analytics has allowed every company whether Goliath or David-sized to benefit from big data.  Over the next few weeks we will be discussing the impact of the intersection with big data and high performance analytics.  In particular providing examples relevant to the world we live in left of the date line. Join the discussion to find out what the innovators are doing and lessons we can learn locally.  You can see some more examples here.

What is your big data opportunity? Tell us in the comments below.

tags: big data, customer intelligence, Hadoop, healthcare, high performance analytics, HPA, in-memory analytics
11月 012011
When discussing fraud and abuse, it often (very often) becomes a philosophical discussion of whether aberrant activities are fraudulent or abusive. The quick difference being that fraudulent is intentional and abuse is not.  The distinction quickly becomes an issue of legal and illegal as opposed to right and wrong. What [...]