Finding the perfect black dress is no small feat, but it's gotten a whole lot easier. Instead of spending a good chunk of my Saturday morning at the mall, I can browse online or tap an app and be presented with the right dress for the right occasion, in the right size, and - thanks to Rent the Runway, given the option to rent and not buy - at the right price.
It's not just the fashion industry that has figured out what I need, when I need it. It's Amazon, which is able to predict my taste in books, movies and television, and Uber, which can predict not only the intersection where I'm headed, but my destinations' exact addresses. On most days, these companies may know me better than I know myself.
How? These and many other innovative companies have wisely adopted predictive analytics, which rely on sophisticated algorithms to turn our data - from what web-sites we visit, to what zip codes we call home - into insights. In fact, almost every major retailer has made it a priority to learn as much as possible about its customers and to create a perfectly tailored experience-so much so that shrewd shoppers now expect it.
As a cancer survivor, I have wondered many times: Shouldn't we be able to do the same for people with cancer?
Sure, selecting the optimal treatment options is far more complex than choosing the right dress, but doctors are already using whole genome sequencing, super computer processing power, and machine-learning algorithms to tackle a handful of the toughest, most deadly cancers. Making this routine for people with all cancers - that is, tailoring treatments to an individual based on his or her genetic make-up and other unique characteristics - will require new and creative ways to reach patients and encourage them to share their data. After all, teasing out the role that genetic mutations and other abnormalities play in cancer's onset and progression, if any, relies on the extensive analysis of a massive number of patients' genomic and other health data. It also requires advanced analytics to recognize patterns and make sense of the vast amount and vast array of these data.
Several efforts, including the federal government's Cancer Moonshot programs, have taken on this lofty task, but the challenges of engaging patients as partners in the research process threaten to slow their momentum. What can we learn from other industries with a proven track record for transforming data insights into incredible value? A recent meeting convened by the Harvard Business School (HBS) Kraft Precision Medicine Accelerator, which aims to speed breakthroughs in precision medicine, brought together some of today's most innovative companies, from Uber and Under Armour to Rent the Runway, with disruptive healthcare companies, such as PatientsLikeMe and Google's Verily. The goal: to determine the best practices that made them leaders in their respective industries and share and apply those insights to the world of oncology. Several rose to the top:
- Under Armour focuses on making athletes perform better and Rent the Runway democratizes fashion. We too must develop emotive brands that communicate benefit to the consumer - in this case, the patient.
- Just as potential customers are more receptive to a brand if they hear about it from their peers, patients may be more responsive to learning about research efforts from fellow patients. We must use brand ambassadors to build trust, increase reach and build a community.
- Member loyalty programs retain consumers over time. Similar incentives - for example, patients who opt to "check in" may get premium information about treatment centers for their specific cancer types - may help patients stay engaged and motivated.
These are but a few of the recommendations put forth at the meeting. I have no doubt that taking a cue from these innovators, even those with seemingly little overlap with the healthcare industry, will prove critical in efforts to make patient treatment more effective. Only then can I be certain to not only find the perfect dress, but seek the perfect treatment.