TNT EXPRESS

Introduction

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Q1(a). TNT Express Company Background

  • Thomas Nationwide Transport (TNT) was founded in 1946 by Ken Thomas, who started the company with only a single truck
  • Originally, the company started out in Australia, but was acquired by the Dutch national post and telecoms company then called KPN in 1996
  • This takeover led to the transfer of its headquarters in the Netherlands, but the management decided to retain its name
  • TNT Express is now a global company operating in 200 countries around the world. Weekly, TNT Express delivers approximately 4.7 million packages using a network of more than 2,600 facilities, a fleet of about 30,000 road vehicles, 50 aircrafts and has a workforce of approximately 77,000.

Q1(b). Nature of the problem

  • In 2015, TNT Express recorded a revenue growth of 3.5% to reach €6914 million and a €50 million reported loss attributable to the equity holders (TNT annual report 2015).
  • Due to a worldwide financial crisis towards the end of 2008, there was a sharp decline in volume, which extended until mid-2009.
  • Owing to this decline, there was a fall in air network performance. Therefore, an immediate solution was imminent.
  • To find a solution to this problem, TNT Express decided to build the DELTA supply chain model, an end to end supply chain optimization project with the aim of reducing aircraft use, preserve growth capabilities and most importantly preserve the quality of service, TRANS for network optimization, and SHORTREC for pickup and delivery optimization.

Q 2(a). Problem context discussion

The three subprograms were particularly complex given the following challenges:

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  • Development of the DELTA supply chain model was difficult because the model covers the whole of Europe, which consists of 650 depots, 90 hubs, and 150,000 origin-destination combinations. This makes it difficult to acquire the accurate level of details to facilitate the board in decision making.
  • Because of the size of the networks that TNT Express operates, using a combined problem to determine the routes and tours was too complex for the TRANS subprogram.
  • Optimizing the pickup and delivery process to minimize pickup and delivery costs while meeting all service-level requirements which is challenging given that millions of deliveries have to be picked up and delivered each week.
  • Issues of calculating distance and travel duration considering the size of the problem, which would require a lot of memory to store all the results.
  • Data gathering was another major challenge because it was supposed to be done in 8 weeks, an activity that would normally require months just for one country.
  • Gaining the trust of the decision makers in using the model mainly because some details had been overlooked from the calculations of the initial results.

They were also interesting because:

  • They enable TNT Express to optimize their complete supply chain for a fixed depot and hub infrastructure under varying volumes and ways of working; for example, cutoff times, road and air transport
  • TNTs model is the only model in the express delivery industry that covers a complete air and road supply chain.
  • The model allows TNT Express to test supply chain operation improvement ideas without having to experiment in practice.
  • The TNT Express network is vast; hence, covering the whole of Europe.

Q2(b).

Compared to the Economic Order Quantity (EOQ) and Newsvendor models TRANS, SHORTREC, and DELTA were made more complicated by the following factors:

  • It takes a lot of time to convince analysts, network managers, and depot managers. This is mostly because most of them are not familiar with optimization; hence, difficult for them to adopt new tools that they initially see as reducing their control.
  • Volume fluctuations in the deliveries highly affect the optimization of SHORTREC.
  • A high number of deliveries, which is in millions weekly
  • Large network size because the models cover all Europe and a single depot, for example, the Rome depot handles up to 90000 stops per week.
  • The available data is spread across many information technology systems, thus reducing the quality of the data and making it hard to retrieve.
  • It is hard to develop a standard decision support solution because it is supposed to cover all countries in which TNT Express operates and each country has its way of working with varying volume profiles and different local regulations.
  • Objectively, tracking results is difficult since managers might not be transparent with their results considering the company policy of decreasing the budget of managers who meet their optimization targets.
  • New users are resistant to change despite demonstrated successes because they feel their business is not comparable.

Q3.

In conclusion, the network optimization model (DELTA in this case) was the best choice of model for solving TNT Express’s problem.

Q4.

As a result of their various program interventions, TNT Express was able to save 207 million euros in the following avenues in the period from 2008-2011:

  • 132 million euros from the supply chain sub-program
  • 48 million euros from the networks subprogram
  • 27 million euros from the pickup and delivery (PUD) subprogram
  • In addition, the Global Optimization (GO) program also enabled TNT Express to reduce Carbon dioxide emissions by 283 million kilograms, which is an equivalent of 1,000 trucks traveling around the world seven times.

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