Case Study : Nagpur Golden Transport Company

The case focuses on high truck idle time and the various reasons for the detention of trucks in an Indian logistics company. The case gives an insight into the challenges that small and medium fleet size transporters face because of their conventional methods and the inadequate use of technology in managing their businesses. Though Nagpur Golden Transport (NGT) Company had Global Positioning System (GPS)-enabled trucks, its applications were not utilized efficiently. Breakdowns, driver shortage and truck detention for long hours were everyday problems that occurred in this industry. Given that the market was highly competitive, every single order not fulfilled by the transporter was an opportunity lost. How should Nitin Bagai design and redesign the logistic system to gain and maintain competitive advantage? How can the technological development in this company alter the situation? How could the GPS data help in reducing truck idling time? What needs to be changed in the management information system (MIS) reporting process? How important is it to ensure a proper work environment for drivers in a trucking-based logistic company?

On February 22, 2016, Mahesh (the 25-year-old driver of truck number RJ14GC1567) was scared, exhausted and hungry, having spent two days on the NH11 Jaipur-Agra highway, waiting for the roads to clear. The Jaipur-Agra National highway, the state highway and other service roads were all blocked because of a series of protests in North India. Nitin Bagai, CEO of NGT Company, did not want any driver to be harmed in this critical situation and had asked all operation managers to stop all transactions for and via Delhi, Haryana and other districts which were under curfew, until the situation came under control. This truck reached the consignee location at Agra, Uttar Pradesh carrying the load from Jaipur, Rajasthan. The truck was detained for 20 hours before unloading due to unavailability of laborers at the consignee location. A delay of two days made it difficult for the client to arrange for all the laborers on time.

A few months later, on July 27, 2016, truck number HR5S0474 reached its consignee location at Alipur, New Delhi. The truck had taken a load from Wardhamana, Nagpur, covering a distance of 1065 km in 113 hours from the time of loading. During this trip, the truck had an idle time of 45 hrs 30 min. HR5S0474 was loaded on July 22, 2016, at 18:30 hours at Alipur and unloaded on July 27, 2016, at 11:30 hours at Wardhamana. During this trip, the truck was idle for 4 hrs 20 min before loading and was idle for 1 hr 40 min post loading. The in-transit idle time at Agra was 22 hrs 20 min. Further, before unloading, the truck was detained for 21 hrs 30 min. HR5S0474 reached the destination via Agra and Kosikalan.

Nitin shared this concern with all his representatives; he felt that such high truck idling time led to underutilization of trucks and decline in business profitability. While presenting the GPS data in the meeting, Nitin compared the trip hours for the same route taken by another truck and highlighted the time and location of detention. For the same origin and destination points, the truck numbered DLIG3801 took 63.32 hours to reach Alipur, New Delhi via Mathura with a total idle time of 32.50 hours. Exhibit I shows the GPS data for a round trip between Delhi and Nagpur.
Nitin shared this concern with all his representatives; he felt that such high truck idling time led to underutilization of trucks and decline in business profitability. While presenting the GPS data in the meeting, Nitin compared the trip hours for the same route taken by another truck and highlighted the time and location of detention. For the same origin and destination points, the truck numbered DL1G3801 took 63.32 hours to reach Alipur, New Delhi via Mathura with a total idle time of 32.50 hours. 

Delhi and Nagpur. Nitin was worried about the high truck detention time. He knew that lower truck idling time would result in extra trips during a month, giving better returns.


Clearing NGT Company was established in 1960 by late Shri Lakhmi Chand Bagai with a vision to make NGT the most trusted service provider in transportation services. It began its operations as and forwarding agents in Sindh (now in Pakistan), and gradually expanded its transportation services pan India. With the support of his son, Ashok Bagai, the business expanded manifold (from three offices in 1960 to 40 offices in 2017. With Ashok Bagai’s sons, Nitin Bagai and Sachin Bagai, joining the business, the business decisions were based on system processes and objective performance measures.

The company started its business with only two secondhand trucks with a small capital. In 2017, the company was located nationally and had multifaceted businesses backed by qualified professionals. It had 40 offices and 365 franchisees with a fleet size of 150 multi-axle trucks in which 60 trucks were fitted with a GPS device. It also had a large network of its own offices and crossing points covering whole of Chhattisgarh, Madhya Pradesh, Rajasthan, Punjab, Delhi, Haryana, Uttar Pradesh, Andhra Pradesh, Maharashtra, Karnataka and Tamil Nadu states in India. It had tie-ups with other associate companies in states such as Jammu & Kashmir, thus reaching out to millions of Indians every day. The company provided low-cost transportation solutions, matching the performance benchmarks established by the other big players in the country in terms of digital initiatives, location coverage and customer satisfaction. To handle customer queries and complaints, the company developed a user-friendly helpdesk app for both iOS and Android. Every ticket generated on the goods receipt was linked directly with the head office and the back office via e-mails, which helped it respond to complaints in real time. It set a new benchmark in the road transportation industry by delivering 73,242 consignments in March 2016.

The company started computerized accounting in 1991-1992. All the accounts books, that is, cash book, ledger, journal and trial balance along with the profit and loss statement, were generated by the financial accounting software, FoxPro. This software was developed by Ashok through another family company Golden Software Pvt. Ltd. It provided information on all costs involved in packing, loading and unloading. All office expenses, door delivery charges, local charges and onward expected charges of transshipment were calculated at the time of loading the truck to find the profitability. Before loading the truck for parcel booking, the profitability of the trip was estimated.

The company also participated in the reverse auction of transportation freight, which not only provided them with new business opportunities but also allowed them to benchmark their prices. lead time and quality of services with other competitors. Many known companies such as Procter & Gamble, Marico Ltd., Sun Pharma, Pfizer and Abbot Nutrition used reverse auction to select transport service vendors. Though competition had increased over the years and all major clients had adopted the reverse auction system for freight charges, NGT achieved continuous growth in revenue. The entrance of new players along the same geographical destination over the years had made the market more competitive; for example, in 2006, the number of trucking companies (across India) carrying goods to Delhi, Mumbai, Bangalore and Kolkata was 8, 5, 3 and 4, respectively. In 2016, the number of trucking companies carrying goods to Delhi, Mumbai, Bangalore and Kolkata increased manifold to 18, 15, 8 and 15, respectively. However, NGT created barriers to entry with its efficient service, process and technology, because of which the company was seen as one of the foremost leading transport companies in India. In 2016, NGT was recognized by Raymond (a leading textile manufacturing company in India) for delivering 97 per cent of the consignments within the delivery window and providing consignment tracking capability to the client using MIS.


The goal is to turn data into information, and information into insight. – Carly Fiorina, Former Executive, President, and Chair of Hewlett-Packard Co.

Nitin needed the team to sanitize the existing data. “Accuracy in data gives the right information which results in the right decision. Data accuracy is the key factor that ensures that all business functions are aligned with the company’s objectives such as service, quality, cost and safety,” he said. The company was running on manual data entry and accounting methods. Along with data accuracy, there was a need to make the data available in a timely manner for swift decision making. Manual handling of data such as collecting, sanitizing, analyzing and finding relevant information from the data was time-consuming and did not help in taking timely decisions.

In the early 1990s, the company was growing and a massive amount of data was being collected manually. Up to that point, the company had been recording and collecting all vehicle data in hard copies and maintaining the paperwork in files. Whenever a record was needed to be referenced or retrieved, it would take hours to find the specific document. The thought of going through all the details manually was daunting. Since the data were stored in hard copy, there was no easy way to create reports and compare performance across vehicles or drivers over multiple time periods. Nitin decided to create a process to collect the data and analyze every expense and its trend and also the driver and vehicle safety performances in past trips.

 This MIS module helped to manage consignment MIS was only used for distribution and material management. In 2004-2005, MIS was introduced dispatches such as delivery management and stock management; however, it was not programmed for account-related transactions and was used to manage freight at the delivery office.


Drivers’ driving behavior affected vehicle efficiency. Nitin, together with his management team, was aware that drivers drove slowly to save some money in diesel consumption. They drove slower than the lower speed limits at various places. Sometimes, they also avoided toll routes by taking state highways, which were unsafe and known for truck robberies. When drivers were not satisfied with their earnings, they opted to earn through other means. Very often, order delivery times were affected adversely.

The company had all the information to arrive at the running cost of trucks and whether the drivers complied with the driving speed permitted on the roads. Nitin believed that driver behavior affected vehicle operating cost, which included fuel consumption, maintenance, accidents and vehicle condition, so he re-allocated resources, used the equipment more effectively and started conducting a driver audit.


In some cases, management did not receive the information on time, which created an ambiguous situation leading to late and poor response by the management. For example, a driver was taken to a hospital in a hijacking case and the management was not aware about the condition of the truck and the driver for two days Management was very serious about taking early action and following standard procedure with respect to hijacking or accident or breakdown cases. For NGT. safety and security were the foremost priority and they strongly recommended zero tolerance and no compromise in safety. The company went one step further by integrating its safety and security management program, which resulted i driver and vehicle 95 per cent of the time.


A Question of Accountability

NGT’s clients were not aware about the proper channel to resolve queries and issues. There were few innovations in procedure or technology since everyone was engaged in executing and delivering the order. Neither managers and executives nor drivers were accountable for their actions. Even the head of departments handled multiple roles, which made them busy with multiple tasks throughout the day, further leading to poor results. Exhibit 5 shows the NGT hierarchy structure till 2014.

Waiting Time

Long truck idling times resulted in scarcity of trucks at the consignment point. As a result, several orders were delayed or not fulfilled. Nitin was aware that managers were not sure about the reasons for truck idle time. They could only rely on the explanation provided by the driver. Reasons for delay and locations of every truck on the road were noted manually on a trip chart by calling and asking drivers on their cell phones. There was no way to check the actual truck status. Market trucks often carried high transport risk because the drivers were new to NGT and NGT could only check vehicle registration and driver license validity. There could be numerous reasons for long turnaround times (TAT) such as breakdowns, longer routes, holidays, lack of material, unavailability of driver site, waiting in workshops for repairs, traffic congestion or accidents. Also the flow of information at NGT was very slow in the case of breakdowns or accidents. Managers were informed very late about the incident resulting in increased TAT.

Time was entered in the client’s enterprise resource planning (ERP) system : Fleetable when the truck began loading at t the to get the loading point. Most often the truck got detained at the gate, when the driver waited documents from the client. It often took hours to fetch all the required documents. The ERP system showed only the loading completion time and not the dispatch time from the gate. Sometimes the truck needed to move out of the consignor’s gate to avoid congestion and had to wait outside the gate to get all the papers. This delay further increased the truck TAT. Finally, the driver would leave the consignor’s location. Later, the client would complain to NGT about late delivery, as the client ERP showed low detention time at the client’s premises, despite the detention being high at the client’s gates.

At the unloading point, the date and time was noted in the customer’s ERP (if available) or stamped on receipts after the truck was unloaded and the billing was completed. The time was not entered in the ERP system when the truck arrived at the consignee point. The trucks were detained at the consignee location for hours and sometimes days. For example, a consignee Delhi kept the truck on hold for two days due to its overstocked warehouse. The consignee stated that the order was a pushed order given by the marketing officers to meet their targets and hence did not unload the truck. Another reason was the absence of laborers at the consignee location. The driver waited till all the laborers reached the warehouse to unload the material. A seven-day round trip could often take 9-10 days. The impact of these detentions not only affected vehicle utilization but also driver schedules. Furthermore, toward the end of the trip, the client’s ERP

system showed a higher TAT than the actuals. Trucks stopped for hours in transit, for a variety of reasons-entry restriction period, traffic, at the check post, hilly roads, improper rest breaks during long-haul trips, and so on. Drivers would park their trucks at a safe place and sleep overnight inside the cabin of truck. In such cases, the truck remained idle for 6-7 hours. In case there was no entry period, the driver either waited till the end of the no entry period or took an alternate familiar route to reach the destination. Da to such detentions and added idle times, the driver delivered the consignment late, resulting in complaints, both from internal management and from the customer. In India, drivers sometimes avoided idling time due to no entry by extending monetary favors to officials. In order to deliver sooner, they exceeded the speed limit and overtook other vehicles. Such driving patterns also resulted in accidents.

An important delivery route for NGT-the Grand Trunk Road, New Delhi to Central Avenue Road in Nagpur, Maharashtra. The GPS data of 100 trips along the same route revealed that the total time taken by all trips was in the range 75-350 hours. In 10 per cent of the cases, the idle times were in the range of 30-300 hours, which included the time that the truck was at the workshop bay for repair work. There was high variability in the idle times. Here, the total idle time included the idle time during transit and the idle time before starting the journey either from Grand Trunk or from Central Avenue. A truck could be loading, unloading or idle due to other reasons. In case of the return load, the truck after unloading at Central Avenue waited for other orders from around its destination, loaded the truck and left for Grand Trunk Road. When there were no orders at the same location, the truck either waited for hours to get an order or waited for other reasons. 


NGT provided services mostly in long-haul transport. Long routes were one of the reasons for truck idle time. Long-distance journeys (e.g. 1000 km and above) involved high fuel cost, slow service, fewer trips and therefore, more truck idling time. Drivers faced difficulties in finding diesel and hence often carried high volumes of diesel before starting the trip, which was unsafe. Also, because of long waiting times, trucks lost trips which could have brought in revenue. Trucks often experienced long waiting times for load readiness at the originating depot. In some cases, the truck waited for two to three days which resulted in loss of trips and hence profitability.


In March 2012, NGT installed GPS devices in 60 dedicated (own) trucks to obtain real-time tracking and transparent visibility of truck movement. The ERP system of their client could provide only the time of loading, dispatch, gate-out, unloading (after billing) and gate-in, whereas its GPS provided complete actual tracking of the vehicle. The GPS showed the forward and reverse transit of the trip, the route taken, the current location of the GPS-installed truck and the speed, time, movement status and many other important measures. Yet, Nitin was disappointed with the lack of GPS data usage. He had made a significant investment in installing the GPS devices and used to pay monthly service charges to his vendor. However, he could not see any visible return on investment. So, along with real-time tracking and monitoring truck movement, understanding the reason of detention was also the need of the hour. NGT had its own ERP system which tracked the finance and accounting status. Nitin did not integrate the existing ERP with GPS as it could make it too complex for his operational-level staff to use. As SAP was expensive, NGT had to maintain financial statements in its existing ERP and the truck status MIS through GPS: the rest of the operational, transactional and workshop reports were maintained manually.


Nitin believed that they needed process integration in the NGT management system. How should Nitin approach the issue of reduction in truck detention? What actions can be taken to increase the running efficiency of the truck? How can the GPS data be used to provide insights to the client?

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