Forecasting of Logistics and Operations

 

What is Logistics Forecasting? 

Logistics demand forecasting is the process of accurately anticipating the demand for products, services, and shipments throughout the supply chain.This considers even the most uncontrollable conditions or circumstances. To accomplish this, it would be ideal for manufacturers to implement a forecasting model to predict capacity demand, relying on a combination of their own historical data and multiple external variables. The best model is one that allows for the automatic adjustment of forecasts in order to include new customers or other changes in business and increase accuracy.

Why is Logistics Forecasting a Complex Process? 

Of all the stages of the supply chain, logistics often gets the rougher deal as it appears to be a combination of the mostly unpredictable unknowns such as varying weather patterns, erratic fuel costs and the skyrocketing costs associated with last-mile delivery in recent years. This makes it even more complicated and therefore is also quite often overlooked when it comes to applying learnings from demand forecasting. 

Demand forecasting at the basic level looks at historical customer demand data, applying it to certain predictions for future buying patterns, and generating a forecast of how much product you need to have available at a given time and place. When applied to logistics, demand forecasting can help plan for the seemingly unexpected scenarios, cut costs, and streamline existing and future manufacturing logistics planning efforts including load distribution, flexibility in case of disruptions, seasonality, inventory costs, and inbound logistics planning.

 

 

Benefits of Logistics Forecasting:

Reduced Operations Costs

In the absence of strong forecasting models, logistics companies can end up with reduced profit margins due to unnecessary costs. Logistics fleets which operate at half or lower capacity, coupled with inefficient operations and maintenance can end up costing logistics companies more than they realize. With a robust logistics demand forecasting model that induces actions   based on data-driven analytics, can help optimize operations and slash down costs across the board. These solutions help with the reduction of fleet sizes, leasing costs, maintenance costs, storage costs, parking and driver costs.

Dynamic Pricing
A good dynamic pricing can help with stable ROI based on the current supply, demand and market status. Thus, logistics companies who have control of their own data can successfully understand trends such as seasonality, weekly and monthly fluctuations and reflect them in price changes almost daily. This can result in benefits for the carrier who fills his trucks with freight, and good for the shipper who saves money. Finally, logistics companies can effectively sell their goods and services for the right price at the right time. A sound demand forecasting, combined with a solid understanding of capacity and inventory, allows companies to better scope prices and where they should be set. 

 

INCREASED EMPLOYEE EFFICIENCY
With the right use of data analytics, employees can perform better, more accurately and timely than before. If logistics planners have all insights and timely data on hand, they can dedicate their productive hours on critical operations rather than wasting efforts on calculating and predicting where they need to locate their assets and check how full they are. A higher reliance on advanced technologies to make data-driven decisions can make employment much more efficient.  
IMPROVED RESOURCE PLANNING AND SCALABILITY

By having accurate demand forecasting techniques in place, scalability can be achieved with sufficient flexibility to scale up or down without wasting time and effort. Operations resources can be adequately planned to meet demand and supply gaps when required. Optimal forecasting efficiency improves customer satisfaction and eliminates bottlenecks in the operations cycle.

 

What s forecasting in supply chain management
In supply chain management, forecasting is the act of predicting demand, supply, and pricing within an industry. Forecasting involves investigating the competition, collecting supplier data, and analysing past patterns in order to predict the future of an industry. Forecasting is an important skill for a supply chain manager to have, and it encompasses multiple skills that one should acquire as they grow in their career.

1.     Planning Processes
The scheduling and planning process is vastly improved through forecasting. Paying attention to the past and present demand for products allows a supply chain to stay on top of the game.

2.      Seasonal Variations in Demand
Among the many reasons that forecasting is needed in supply chain management is being able to predict and plan for seasonal variations in demand. In a similar vein, planning for promotional activity and product launches are just as important and benefit greatly from demand forecasting. With data to back up predictions, there is less guesswork to fret over.

3.      Predict Product Demand
In a broader sense of the term, demand forecasting allows for the prediction of product demand in even the most specific of situations. While no company can predict the future with complete accuracy, relying on patterns and making informed decisions based on past and present data will get a company as close as possible.

 

4.      Customer Satisfaction
Understanding customer needs is essential in product-focused industries. Being able to predict customer demand will result in fulfilling orders with short lead times on time. This will also have the effect of increasing trust between customer and supplier. 

 

5.      Reduce Safety Stock
By definition, safety stock is the excess stock that is kept around as a safety net in case demand for a product increases. With forecasting, however, this extra measure is not needed. This frees up storage space and saves time and worry.

6.     Reduce Inventory Stockouts
When it comes to JIT (Just In Time) systems and buying from long lead time suppliers, forecasting demand is essential. When it comes to JIT systems, demand forecasting allows for products to sit in storage for less time, thus less money is wasted than if items were to take up space in the warehouse for an extended period of time. For long lead time suppliers, forecasting demand is needed in order for suppliers to get your products to you in a timely manner. 

7.      Improve Shipping
Supply and demand affect every aspect of the supply chain process. For example, being able to predict the demand for a certain product will allow supply chain managers time to ensure that enough workers are present to ship a certain amount of product. Not having enough workers results in orders not getting to customers on time. Likewise, having too many workers on the clock results in high labor costs.

8.     Improve Pricing
Price forecasting puts the power back into the hands of a company. The impact price changes have on a particular area of a supply chain can be predicted and handled accordingly. 

 

 Conclusion:

logistics forecasting and demand forecasting in supply chain management play crucial roles in optimizing operations, reducing costs, and improving overall efficiency. Logistics forecasting helps anticipate product demand, plan for unexpected scenarios, and streamline logistics planning efforts. It enables logistics companies to reduce operational costs, implement dynamic pricing strategies, increase employee efficiency, and improve resource planning and scalability. On the other hand, demand forecasting in supply chain management aids in planning processes, predicting seasonal variations in demand, understanding customer needs, reducing safety stock and inventory stockouts, and improving shipping and pricing decisions. By utilizing accurate forecasting techniques and data-driven analytics, organizations can enhance customer satisfaction, eliminate bottlenecks, and make informed decisions to stay competitive in the dynamic business environment.

 

Reference: https://houston.ascm.org/blog/id/3

 

ISME Student Doing internship with Hunnarvi Technologies Pvt Ltd under guidance of Nanobi data and analytics. Views are personal.

 

#LogisticsForecasting #SupplyChainManagement #DemandForecasting #OperationsOptimization #CostReduction #EfficiencyImprovement #ResourcePlanning #Scalability #DynamicPricing #InventoryManagement #DataAnalytics #CustomerSatisfaction #ShippingEfficiency #PriceForecasting #SupplyChainPlanning #InternationalSchoolofManagementExcellence #NanobiDataandAnalytics #hunnarvi

 

 

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