How Cox Communications Uses SaaS Scheduling Software to Get the Cable Guy to Show Up On Time
SaaS scheduling software combined with analytics helps the $9 billion company reprogram customer service.
CIO — We’ve all been there. Your TV channels go on the blink, your DVR won’t R, or you can’t connect to the Internet no matter how many times you flick off that blasted modem, wait 15 seconds, then turn it back on. You call for a repair appointment. Then you take half a sick day or work from home to—you know it—wait for the cable guy. Who may or may not show up.
Like other telecommunications providers, Cox Communications has tried to deal with the cable-guy problem. Last year, the $9 billion company, which provides TV, Internet and phone services to more than 6 million residents and businesses, launched an IT project to address it.
Telecom companies generally score low in customer-satisfaction rankings, and people are quick to share their poor experiences on the Internet, says Jeremiah Owyang, a partner at research firm Altimeter Group. Comcast’s (CMCSA) “Comcast Cares” outreach program is, in part, a response to bad online word of mouth, he says, adding that Cox is smart to address this “very real, human issue” of waiting for technicians to arrive.
In ratings from the American Customer Satisfaction Index, Cox falls behind Verizon (VZ), ATaannddT, Dish Network (DISH) and DirecTV (DTV), among subscription TV companies. However, Cox gained four points this year compared to 2008, when its rating had remained unchanged for the prior six years.
There When They Say They’ll Be
To improve customer satisfaction even more, last year Cox deployed Time of Arrival (TOA), a software-as-a-service job scheduling application from TOA Technologies. Each morning, the system designs a route matched to each technician’s skills and location. At every stop, the technician uses a laptop or BlackBerry to log his start and end times and the tasks he performed, says Catherine Mitchell, vice president of corporate field services.TOA stores the data from all the technicians, along with variables such as workers’ skill levels and past performance. By analyzing this history for patterns and combining it with events of the day, the software refines predictions of when a given worker will finish a job and get to the next one.
So instead of the familiar vague promise, “Someone will be there between nine and noon,” Cox can predict arrival to within one hour, with 96 percent or better accuracy, Mitchell says. In Louisiana, Cox workers arrive within five minutes of the scheduled appointment 98.5 percent of the time.
Unlike other job-scheduling software, the TOA application, Mitchell says, “learns how long it takes to do a job, validates our assumptions or corrects them. Over time, that will let me be even more likely to be there on time.”
