The role of matchmaker, famously sung about in “Fiddler on the Roof,” is one of many roles made obsolete by technology. Today, those seeking a mate are far more likely to consult match.com or okcubid.com, where data is crunched by ever- improving algorithms and learning systems. The community matchmaker with his/her special skills and wisdom inherited from prior generations has become a quaint idea as databases fill with information on online dating successes and failures and maturing algorithms create ever-improving outcomes.
If you’re unfamiliar with the scientific side of matchmaking, I suggest viewing Hannah Fry’s TED talk on The Mathematics of Love. She provides a fascinating glimpse into this world, presenting three mathematically verifiable tips. She reveals surprises (attractiveness does not dictate online dating success), challenging advice (reject the first 37% of interested suitors and then fully commit to the next option that exceeds the quality of all previous), and mathematical validation of what might be instinctively predictable (the most effective predictor of divorce is each partner’s influence on the mood of the other during conversation).
Why might this be important to serious businesspeople like ourselves? It turns out the data science we apply to assisting love seekers can be applied to business-oriented matchmaking with little or no adjustment.
We recently applied similar algorithms to a telecom giant’s matching of customers calling customer-response centers with agents who are ready to serve them. A real-time computation of goodness scores, based on data known about customers and available agents, managed to save this company more than 24% of customer-response center cost while improving satisfaction and increasing upsell by more than 20%. Many other methods of enhancement had been previously tried. None were as effective as a modest investment in data and analytics.
This experience doesn’t just highlight the value of mathematics in successful business improvement, it shows the importance of creativity in applying that math. I doubt I would have thought of this customer-response center connection, but someone more imaginative realized the data science behind finding compatible life partners could be applied to callers and agents. Brilliant.
Our command of technology has reached the point where this type of creativity has become the most elusive ingredient. We need to realize that if a bit of data about element A and element B can be analyzed to discover patterns of success, and those patterns can be captured within systems that learn and used to predict the best decision within an instant, that many possibilities exist. Matching sales leads to sales personnel? Matching product assortments to store demographics? Matching campaigns to customer-loyalty profiles?
Let’s get creative, imagining all the places that better matches would improve business, and then simply apply the math. Just adding a splash of creativity to a shot or two of business understanding could change our song lyric to, “Mathematics, mathematics, make me some money.”
Fecha de publicación: 09/12/2015