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One of the great things about optimisation modelling is that its use is 100% measurable. It is either producing demonstratable financial and operational results or it isn't. The business benefits are measurable, the gains can be significant and return on investment (ROI) large.


The ROI can be especially high in capital intensive industries, where optimisation modelling can result in large savings for money not spent. Given the cost of capital, these savings will often exceed the margin improvements from greater efficiency in the use of existing assets. Operating efficiencies can produce lower unit costs & increased revenues.

Delivered Savings and Returns

Package Delivery Company
US$87m reduction in operating costs


A subsidiary of a package delivery company operates as one of the largest airlines in the world. The airline is the backbone that enables the package delivery company to provide expedited package delivery services. Here, the optimisation problem was to determine the minimum cost set of routes, fleet assignments and package flows that still satisfied a number of key operating contraints, including:


  • Limits on the number and capacities of each type of aircraft.

  • Landing restrictions at airports.

  • Aircraft operating characteristics such as range, speed and load capacity.

  • Continuous aircraft flow requirements (ie. balance of flow).

  • Time window for pick-up and delivery.

  • Sorting capacities and hours of operation for each hub.


In addition, packages needed to arrive at the hubs in a staggered manner so that packagevolume could be spread acrtoss the entier sorting period, and the next-day-air network flying at night needed to interface with the daytime aircraft network used for the standard second-day-air network. The optimisation model the company built had a direct financial impact:


  • Operating costs in the first 2 years were reduced by US$87 million.

  • Major additional aircraft owenership costs were avoided. IN early results, the optimisation model reduced by 16 the number of aircraft nedded to operate the network. With each plane costing in excess of US$100 million, the long-term savings in aircraft ownership costs exceeded the savings in operating costs.


  • Road Materials Supply

  • Mining Equipment Costs

  • Procurement Management

  • Crew Re-Scheduling

  • Network Recovery

  • Force/Equipment Planning

  • Scheduling and Pricing

  • Portfolio Optimisation

  • Timber Harvesting

  • AUD $15m/year saving

  • AUD $7m/year saving

  • US $100m/year ROI

  • US $40m/year saving

  • 35% reduction spare capacity

  • US $100m/year ROI

  • US $100m/year ROI

  • US $4m/year saving

  • US $20m/year + 30 fewer trucks


Example 2

Example 3

Japanese Carmaker
30% Increase in productivity


Broadcasting Company
US$50m p.a revenue increase


Considered among the most efficient automobile plants in Europe, this carmaker's UK factory was able to make more than 20,000 cars per year, building two models on two different production lines. Despite this outstanding record, top management wanted to begin production of a third model without constructing a third production line.


Ordinarily, a like this would seem impossible. But by building a custom scheduling system, the factory was able to accomplish the goal. In addition, the "straight through ratio" - the precentage  of cars produced on schedule jumped from 3 to 95 percent. Productivity increased by 30 percent without a major investment in plant retooling.


The project also reduced the time needed to produce a schedule by a factor of 10 - from one week to four person hours. Needless to say, the value of the efficiency gains was dwarfed by the savings associated with avoiding the US$500 million cost of a third production line.

A U.S television network had an advertising inventory management problem and a pricing problem. Advertising slots on certain television shows are always more or less valuable than slots on other shows. And certain weeks are more or less valuable than others. Individual advertisers purchase blocks of advertising time and have negotitated terms and demographic coverage requirements. The network needed a scheduling system that would fill contractual obligations at lowest cost in terms of slot inventory consumption. The effect of the system was to enable the network to maintain or even raise prices while preserving some of the best slots for enticing new customers.


By generating better ad schedules, the network increased revenues by over $US million per year. The sales staff, backed by an efficient and nimble pricing and allocation system was able to compete for new customers while meeting contractual obligations to existing customers.


Example 1

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