We already know that since logistics deals with a multiple of functions having to do with the company’s discipline of planning, managing and controlling the way goods, personnel and services are distributed, then it only makes sense that any type of tool that can help enhance the effectiveness of this process must be considered and included in the arsenal of solutions an organization must have at its disposal.
Logistics include all steps and processes that create these resources and ultimately deliver them to the customer, something that can be greatly enhanced by bringing logistics statistics into the mix in order to aid in the achievement of said goals.
Statistics is defined as the area of mathematics that deals with the collection analysis, interpretation, presentation, and organization of data that gets collected from many sources with the goal of achieving pertinent conclusions. When it comes to business statistics, then we are dealing with the utilization of all of this data to make decisions that positively impact the organization when faced with uncertainty, and it can be applied to many areas of the business from production and operations to financial analysis and customer service. The importance of business statistics is paramount on the ability an organization has to make decisions that will ultimately guide their growth and redirect their resources towards their future developmental needs.
Planning in Logistics is one of the most important areas that ensure success, since they are in charge of ensuring their systems run in accordance with the business goals of the organizations and that is why a logistic manager must seriously consider the advantages received from the inclusion of statistics into their data analysis and thus ensure effective planning.
Planning can include in most cases the definition of the best transportation routes as well as the volumes being transported. As you can see, deciding on both of those fronts can be greatly enhanced if you consider previous data collected from former trips and other routes utilized. That is one of the many ways statistics can and should be used to ensure better logistic operations.
Purchasing is another important area that managers and organizational executives must carefully watch in order to ensure that purchased items and services are delivered in accordance with the needs of the company, the decisions made by management and the local laws and regulations. The role of statistics in this area in invaluable, since it can help prevent errors and also to anticipate the needs of the market so the proper decisions can be made in advance and possible disruptions due to the volatility of supply and demand can be avoided in a timely manner.
Maintenance & Transportation is another aspect that sometimes gets overlooked, but that it has a very great and specific importance when it comes to the smooth operation of the organization and everything that has to do with logistics and the supply chain specifically. Maintenance refers to all of the equipment, the means of transporting products, goods, and personnel internally and externally. These managers are responsible for negotiating with local vendors and freight companies in order to ensure that goods are being delivered in a timely manner and that they are being tracked using systems that guarantee proper control and oversight over shipments before, during and after transit.
The importance of statistics in these areas cannot be overstated, as the proper tracking, recycling and analysis of this information can constantly ensure improvement in operations and information that will facilitate the proper planning and evolution of methods being currently utilized.
Analytics in logistics can be divided into three main categories and they are: descriptive, predictive and prescriptive.
Descriptive analytics uses data in order to improve the way information is being reported to the supply chain. This means that just because you are gathering a large amount of data, it doesn’t necessarily mean that you are being effective in the way that data is being gathered and more importantly, analyzed. Descriptive analytics look for ways to drill-down on data and find what is meaningful and separate it from the background noise.
Predictive analytics, just as its name indicates, tries to predict what the future holds for your supply chain. This includes anything having to do with forecasting at different levels and the use of data to estimate how patterns can be used to predict future movements, purchasing orders, stock management and more. It goes without saying that predictive analytics allows managers to make smart decisions and develop effective strategies to better deal with things to come.
Prescriptive analytics use available information to recommend the best course of action in order to optimize resources and personnel. One of the best examples is using data to plot the best routes for transporting goods or to manage warehouse operations like line picking and stocking.
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