Limiting Truck Rolls When Providing Service
Even the smallest improvement in establishing service for a new customer can lead to substantial savings, especially in an organization that is servicing millions of customers across a region. In the process of serviceability (establishing new customers) for a utility or telecom, sending a truck out to check for service availability to a specific location (aka “rolling a truck”) can not only delay service and revenue to an organization but also become costly. Though it is sometimes necessary to roll trucks, inconclusive outcomes from these initial truck rolls can lead to repeat truck rolls further adding costs. On the other hand, focusing on a specific area of data improvement, locational accuracy of streets, and facilities can help reduce the number of truck rolls per day, returning large dollar savings to a company’s operational bottom line.
In a perfect world, any utility or telecom cable customer service representative would field a request for new service, verify the location of the request, and quickly register the requester for new service without a delay. In practice, this involves the coordination of a multitude of business units and/or systems including geographic information systems (GIS), service agents, construction groups, accounts management, regional operators, surveying groups, etc. The process and interdependencies of a new service request can be complex and daunting to change in any utility or telecom despite potential cost savings. But can there be any value to focusing on one aspect of the process for signing up new service? Just by improving aspects of location data accuracy, a utility or telecom can reap sizable savings simply by updating features in their GIS data.
A good example of this is street and facilities maps. The locational relationship between streets and facilities is one of the primary factors for serviceability. In this day and age of expanding operational regions, company consolidations, and simple organic growth, improving the locational accuracy of a utility’s or telecom’s GIS data can fall to the back burner. On the ground, discrepancies between street and facility maps can creep in on a weekly or monthly basis further antiquating the data that these companies use as the basis of their operations. In regions experiencing growth, entire subdivisions may be included in the street’s GIS database but not in the facility GIS database or vice-versa. These deviations can hinder the customer service representative’s efforts to extend service to a new customer. This all can lead to an incomplete picture of the service territory, driving up the cost of acquiring new customers and putting the utility at a competitive disadvantage.
Blue Line (Previous Street Map) vs. Green Line (Updated Street Map)
Before Asset Map
After Asset Map
Imagine Cable Company X provides utility or telecom service for a region of three million subscribers. On a daily basis, Cable Company X receives 2,500 calls for new service within its operating region. Conservatively, Cable Company X can accurately locate the site of needed new service 95% of the time. Meaning, Cable Company X can instantly check on the address of the particular request and know that service can be provided without issue. As a result, Cable Company X is unsure if new service can be provided to 5% of customer inquiries (250 calls per day).
Cable Company X would now need to roll a truck to that location to see if and how service can be established. With inaccurate or incomplete street or facility GIS data, rolling a truck can sometimes lead to inconclusive findings. The field operator may not be able to find the correct address or may not be able to locate the assets needed to connect a house for new service with pin point accuracy. This becomes a wasted truck roll, and wasted money, as it leads to no conclusions of serviceability due to inaccuracies in location data. The truck would have to come back, raise an exception flag, and at some point, another truck will have to roll for the same service request.
$6 Million Lost Annually to Inaccurate Data
If this occurs in 10% of Cable Company X’s truck rolls a day and each truck roll costs $1,000 (industry average) that amounts to $25,000 a day and over $6 million a year is lost to the bottom line all due to inaccurate locational data for streets and facilities. Simply by calibrating and auditing its GIS data, Cable Company X can reduce wasted truck rolls and enable customer service representatives to accurately determine viability of more new service requests, saving millions on its overall operations annually.
So how can utility or telecoms get better locational data?
With options ranging from automated GIS data re-alignment to comprehensive GPS-based field surveying, Avineon can tailor a solution to ensure a greater return on your investment in GIS. Just like limiting truck rolls, sometimes small actions can lead to surprising results.