NEBCO’s operations span the state of Nebraska and supplyconcrete-related building materials to the construction industry. Products include sand and gravel, limestone, concrete block and pipe, rebar and steel, precast concrete and ready mixed concrete.
In 2013, NEBCO began installing TrackIt GPS devices and today they are in all 200 of their concrete mixer trucks. While these units provide the basics of any GPS system--location and navigation, they are one of the primary sources of BigData used by the operation. The tight integration of these units with NEBCO’s ready mixed concrete scheduling and dispatching system gives us near real-time status of each delivery. When a flashing red truck appears on his monitor, the dispatcher can contact the customer immediately to let him know that the load is going to be late. We can also receive alerts when a truck is being held too long on the job before the customer is ready to unload.In our business truck hold time is critical because it can negatively impact another customer’s on-time delivery. Last, but not least, we know within seconds when a truck has left the job site, allowing us to begin scheduling its next load.
These devices are also connected to the trucks’ engines, generating data that allows us to be proactive with repairs. Other data captured can be used to analyze truck idle time and fuel economy. With event-triggered alerts, supervisors can be notified at the time of an infraction, such as speeding, and use this information to coach drivers and improve the safety of our vehicles on the road.
Our drivers’ typical day starts with them logging into the device in their truck and effectively clocking in. The clock in and out times are significant pieces of data that can be used to help close the gap between “clocking in” and the driver’s first load, and the time from when the driver returns to the plant after his last load to the time the driver “clocks out.”
BigData brings big challenges... or a: real-time systems integration, highly available systems, and additional staff necessary to support new tools that have taken mobile to a whole new level
In addition to capturing valuable data for operations, the device server another purpose: they have eliminated the use of time clocks and manual time collection, resulting in additional cost savings.
In all of these situations, Big Data can be used to optimize our day-to-day operations: providing near real-time status of each truck in the delivery cycle, collecting diagnostic information from the engine to minimize down-time caused by unexpected repairs, analyzing fuel economy and idle truck time, and even improving safety by providing immediate feedback on driver errors.
Using the Big Data that has been collected to support decision making processes is key. According to Jim Wagner, a subject matter expert with over 50 years of experience in the Ready Mixed Industry, “Driver utilization, a leading performance indicator averages 65 percent. This represents delivery time verses paid time. Non-productive time is composed of start up in the morning, shut down at night, waiting in the plant for a load and waiting on the jobsite to be unloaded. The national average cost per hour of a driver and truck is $65. In an 8-hour day, the driver is productive (delivering) 5.2 hours. Increasing efficiency by just 5 percent would reduce paid hours by 24 minutes per day, a savings of $26 per truck per day. A 200 truck fleet can see realize an astonishing savings of $5,200 per day, a direct impact to the bottom line.”
So, that’s how Big Data has added value to our operations, by giving us concrete information that we can use to reduce costs. Now, let’s shift the focus on how Big Data can be used to maintain our position as market leader and give us an advantage over the other concrete providers. In the construction industry, our customers—primarily contractors, may not have the most sophisticated bag of tools when it comes to technology. However, most of them do have smart phones. With Big Data that comes from our batch plant, we know exactly what time the truck is loaded. Consider the value of sending a text message to the contractor at the job site to let him know our estimated time of arrival so that he can have his crew ready. In cases where we are running late, we could send a text message to the job site, giving the contractor the opportunity to adjust his schedule, instead of having his crew waiting around for our truck. Sending an alert, a couple of hours before his scheduled delivery, could allow the contractor to confirm that he is on track, eliminating last minute changes to delivery times, which affects all customer orders for the day. There’s value to our customers to provide access to signed delivery tickets, time stamped with when we arrived on the job, started the pour and ended the pour. We would then be able to show our customers our high performance percentage of on-time deliveries to his job. All of these value-added services are made possible with Big Data.
Good things come to those who wait, but we all know that this often requires time and patience. And, Big Data brings big challenges: real-time systems integration, highly available systems, and additional staff necessary to support new tools that have taken mobile to a whole new level Technology is just one piece of the Big Data puzzle, however, and in fact, the human factor is probably the one that has been the greatest challenge throughout this mission of turning Big Data into big dollars. It is a work in process. Capturing Big Data without truly understanding its value to the organization is futile. In our business, like many others in this industry, many decisions are based on gut and experience. In today’s technological environment, even in the construction industry, in order to maintain our edge in the future, we have to become a data driven organization that utilizes the data at our fingertips. Information Technology enables us to turn data (big and small), into actionable information for optimizing our operations and exceed our customers’ expectations. At NEBCO, we are turning data into an asset that positively impacts the bottom line.
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