Social Performance Management and Customer Data: FitBit

I stumbled upon this website over the weekend: FitBit, and wouldn’t have thought about it again until I read this morning’s Wall St. Journal short piece on them and their $2M USD first-round funding led by True Ventures.  When it comes out early next year, it will measure how much you exercise (with some limitations) and how much you sleep (and the quality of your sleep).  It’s unobtrusive and automatically downloads whenever you are within 25 –…

I stumbled upon this website over the weekend: FitBit, and wouldn’t have thought about it again until I read this morning’s Wall St. Journal short piece on them and their $2M USD first-round funding led by True Ventures.  When it comes out early next year, it will measure how much you exercise (with some limitations) and how much you sleep (and the quality of your sleep).  It’s unobtrusive and automatically downloads whenever you are within 25 – 50 feet of to your computer.

Imagine the impact on business if enough people used FitBit and the data were aggregated by age, geography, occupation, an so on:

• Health insurers could notice positive and negative demographic trends adjust premiums and preventative care programs accordingly.  “Adult Males in this zip code exercise regularly and get an average of 7.5 hours sleep per night – they get a 10% healthy-lifestyle discount on premiums.”  “Students in this area are sleep deprived, send out sleep-kits/how-to brochures to their parents.”
• Employers could require the use of FitBit and use the aggregated data to negotiate better health care policies for their employees
• Health clubs could include this data in their new-club site selection criteria (open news clubs first in areas of higher or lower activity),
• Mattress resellers could target direct advertising into low/poor sleep areas

I’m sure there are 100’s of applications.

I had a similar conversation with Safeway CIO, David Ching, last year about the possibilities of using and re-selling point of sale purchase information from their loyalty program.  Obviously the main concern is individual privacy, yet if the data is anonymously aggregated, consumers could benefit from targeted discounts and other programs.

For more on the personal benefits of this kind of Business Intelligence, see Frank Buytendijk’s blog entry on “The Best BI Tools in the World”.

The “ah ha” for Performance Management is to take this information we’ve gathered, analyze it to understand the root causes for the performance, debate ways to improve it,  and then plan for better performance in the next cycle (day, week, month, quarter, year), and putting those decisions into our systems and processes.

Link to original post