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I. Objectives - must be quantified and measured
To be successful, you must have a clear goal. To optimize, you must know how to be optimized. Quantifying the goal makes it possible to use a computer to determine whether a logistics planning solution is better than another. Managers can measure whether the optimization solution has a return on investment. For example, a courier company may target: daily minimum maintenance costs, fuel costs, and labor costs, which are easily quantified and measured.
Second, the model - must truly represent the logistics process
Models are the way to translate optimization requirements and constraints into computer-acceptable languages ​​and programs. For example, we need a model to represent the process from shipment to warehouse to truck. The simplest model such as the total weight and volume of the shipment must accurately represent the shipping requirements. If a weight and volume model is used to represent the shipment of another new vehicle, the model is distorted because it does not truly represent the actual shipping situation. If the model does not represent the real situation then the entire optimization will be impractical and inefficient.
Third, the data - must be accurate, time-sensitive and easy to understand
The data guides the entire optimization process, and if the data is inaccurate or not included in the entire optimization process, the designated logistics plan is clearly unconvincing. The optimization process includes an implementation plan, and the data must be easily understood and accepted so that there is good communication and the entire system will be coordinated. For example, if trucking has volume restrictions on certain goods, it is obviously not enough to just grasp the weight of the goods being transported.
Fourth, integration - must support all data conversion
Data integration is very important because a large amount of data is collected around logistics optimization. For example, optimizing the transportation process from warehouse to store requires relevant orders, customers, vehicles, drivers, and road information. Some of these large amounts of feedback data are useless data, some are erroneous data, need to be re-integrated, and filter out optimization. Valid data.
V. Communication - The optimization plan must be communicated to the executive officer and manager in a certain form.
Providing a logistics optimization solution without specific implementation is not a success. Only providing management with a solution and ultimately achieving the desired return on investment is a success. Therefore, the optimization plan must be communicated to the managers and performers in the simplest and clear way. The managers need more comprehensive and centralized information to implement the whole plan, and the network is an important medium for information transfer.
Algorithms - Solving a single problem with an independent structure
The biggest difference between logistics optimization techniques is the algorithm that computers seek for logistics optimization. There is no doubt that each type of logistics problem has its own characteristics, and relevant computer algorithms must be developed for each different problem to provide the best optimization solution. However, it is worth noting that: (1) the algorithm structure must be recognized and understood by each logistics optimization system; (2) the optimized algorithm should be flexible and can be coordinated with other systems during use. There are many possible options for logistics optimization problems, such as the reduction of cargo transportation capacity, sometimes with thousands of possible solutions. The use of an inappropriate algorithmic structure means that the computer-selected solution may be based on unreliable data that violates the optimization principle, or the entire solution may take too long to compute.
Seven, the operation - the computing platform must calculate the optimization plan within the effective time
Since every practical logistics problem has thousands of optimization solutions, a powerful computer is needed to support the calculation, which can guarantee the best logistics optimization solution in a reasonable time. Obviously, since the optimization technology is to be quickly realized in the actual operating environment, it is necessary to obtain an optimal solution in a short time. Compared to a single computer operation, a powerful computer network platform can provide a better and faster solution.
Eight, talent - professional talent must dominate
Optimization technology is developing rapidly, but without some professional technical personnel to master it, it will not achieve the desired results. These technicians can ensure the correctness of the data and model, and the technology can be put into practice to run according to the design. It is unrealistic to hope that through some data collection, using models and software analysis without the support of technical talents, they dominate knowledge and experience.
Nine, the process - the operation of the business process must support optimization and ensure the space for improvement
Logistics optimization is a process of continuous accumulation of changes, because the objectives, rules and processes of logistics are not static. When changes come, not only do data, models, and algorithms need to change, but potential business processes also need to consider how to change to support new optimizations. Business processes that do not support optimization or ensure the optimization of logistics optimization will result in optimization techniques that cannot be effectively utilized or even useless.
X. Return on investment – ​​investment returns must consider the entire technology, talent and implementation
There is no free lunch in the world. Logistics optimization requires a lot of capital, technology and talent. The return on investment needs to consider two points:
(1) Evaluation of the overall optimization value;
(2) Comparison of optimization schemes and selection of optimization techniques.
In terms of cost value estimation, when a company has a ready-made network platform and application software, it generally underestimates the cost of using logistics optimization technology, and these need to be completed by professionals. Few cases have successfully used logistics optimization techniques at a lower cost than the initial estimate of the cost of technology. If the total cost of logistics optimization is initially controlled, the cost of the overall solution will generally decrease.
In the return on budget investment, there must be a good way to determine a baseline, measure the value of technology and the role of talent, measure the effect of the improvement, and then consider further optimization. Because the data is time-sensitive, the implementation process needs constant attention, and no company can accurately predict how their logistics optimization solutions can actually achieve results.
Ten principles for optimizing logistics operations
For most companies, optimizing logistics operations is an effective means for companies to reduce costs. In the past, many companies in the United States have focused on business process automation and related logistics information collection. These measures have already achieved results and helped the company. Reduced costs, but also laid the foundation for computer hardware and software for logistics optimization. In this context, Dr. Ratliff, the director of the Institute of Logistics at Georgia Tech, and the US logistics expert, recently wrote a white paper proposing ten principles for logistics optimization.