SAP TM – BRING YOUR TRANSPORTATION FORECASTING CAPABILITES TO ...

The estimation of future transportation demand and adjustment to changed needs can be solved via an optimized forecasting process. Optimized forecasting in this sense can be separated into two different areas:

• Transportation forecasting to support logistical planning cycles (long-term, mid-term, short-term)
• Transportation simulation across modes to determine capacity demand in combination with potential freight spend

Transportation Forecasting linked to logistical planning cycles

Each company operates differently when it comes to allocating transportation demands and subcontracting carriers from a timing perspective. Therefore, these timing constraints have to be managed and taken into consideration individually.

But all the companies have one thing in common: The fact that logistical planning cycles can be differentiated into long-term, mid-term and short-term cycles (independent of their individual timeframe). Looking a bit deeper into theses cycles, each of them serves a different purpose.

Normally long-term planning covers a horizon of one year. This timeframe will be used to analyze the transportation demands based on the forecasting for inbound and outbound material volumes, current contracts or already known replenishment requisitions to derive the required transport capacity. The demand planning will be done based on monthly buckets and these results will be used as input for the freight sourcing process. The aim here is to detect any potential capacity requirement, which needs to be covered from a contracting perspective.

Mid-term planning in contrast will consider a horizon of three to four months in rolling cycles while planning in weekly buckets. Input for comparison is here as well the forecasting for inbound and outbound material volumes combined with updated contracts and replenishment requisition demands. The objective is to detect deviations between contracted and actual required transportation capacities. This allows a mitigation as soon as the deviation is recognized and create capacity requests based on current companies needs.

Finally, a timeframe of 14 to 40 days in rolling cycles while planning in weekly buckets will be covered by the short-term planning. Based on Sales Orders, Replenishment Orders and Purchase Orders the most efficient transportation plan for execution based on limited capacities will be created as shown in the figure below.

The use of SAP Transportation Management’s tools utilizing the SAP Transportation Management planning and scheduling framework allows to model these planning cycles within the system. As described earlier based on the various inputs within SAP TM the output will be different.

Long-term planning can be translated with strategic planning. For this activity the entire transportation network and linked activities within the past year will be analyzed to determine preferred routing options. Once the relevant options are identified these results will serve as foundation for carrier contracting utilized in the Freight & Capacity Procurement Process within SAP TM. Outputs in SAP TM can be Requests for Quotation or Freight Agreements negotiated with the logistics service providers, which will be described later on in detail.

Also, this information will serve as the input for tactical planning where additional transportation demands need to be allocated at an early point in time. The goal is to plan and create optimized capacity bookings for ocean, air and rail transportation especially on routes with tight capacity. Typically, the horizon for these capacities will cover more than 4 months into the future up to one year and can be covered in SAP TM with Freight Bookings or Freight Orders.

The operational planning will reflect the short-term planning. Within SAP Transportation Management this addresses multiple transportation planning activities such as multi modal transportation optimization or carrier & cost optimization. Here the optimal number of Freight Orders based on the current order situation will be created and linked to the most cost optimal carrier considering business shares and other criteria’s which can differ from company to company. Additionally improved asset utilization and the consumption of pre-booked reservations will fall under this umbrella. Here already created Freight Bookings and their allocated capacity with regards to ocean and rail transportation services will be consumed. Results displayed in SAP TM will be updated Freight Bookings or Freight Orders. From a horizon perspective these activities will take place until 4 weeks from today’s planning date.

As mentioned earlier the forecasting process is only one part of the strategic planning. The other part is the determination of capacity demand combined with the optimal freight spend. A closer look into the transportation network is important in order to determine a companies preferred routing options for certain lanes, a combination of different lanes within the same mode or even a more complex combination of different modes of transports and needs to be evaluated as well.

Transportation simulation across modes of transports to determine capacity demand and potential freight spend

The comparison of costs based on the same lanes within one mode of transportation operated by different logistics service providers is easy. Here mainly the demand for existing lanes will be analyzed. Then the next step is to compare and identify the capacity requirements for these lanes and publish the demand across the different logistics service providers within the own network to receive their quotes for these particular lanes. Afterwards the responses of the logistics service providers need to be evaluated and balanced with regards to the freight spend. Here the balancing need to consider a low freight spend as well as diversification with regards to the number service providers in order to minimize the risk of disruption or shortages. This process can be supported and automated via SAP Strategic Freight Procurement and various versions can be simulated and evaluated to identify the optimal combination of business shares and acceptable freight costing per carrier. Here various parameters such as historical carrier performance can be considered as well.

Once a company has identified its optimal combination the contracts for the carriers can be created in the system directly.

More challenging but also more and more important within this process of freight sourcing is to archive a comprehensive picture aggregating a combination of different lanes within the same mode or even more complex the combination of different modes of transports. As already within the same mode there can be various combinations of lanes to move goods to a certain destination as shown in the picture below.

Transports within the same transportation mode already can be linked to different price. The mentioned pricing deviations will increase even more when we have a closer look into different modes of transports. Here countless combinations and a huge number of logistics service providers can be combined to obtain optimal freight rates while ensuring capacity confirmation with identified partners. Due to this ever-growing overload of complex data and a time-consuming carrier selection process it is difficult to get a detailed and comprehensive view of all possible combinations for a solid decision making.

Therefore, this decision-making process needs to be support by the identification and evaluation of the ideal routes for certain combinations, such as rail, road and ocean. But there is a lot more than that. Possible transshipment locations such as container freight stations or rail yards and their linked processing times as well as the associated costs need to be considered for a precise view and transparency regarding lead times and overall costs.

Therefore, the possibility to facilitate a broad variety of capabilities for simulation purposes is a must. This way it is feasible to take into account the whole diversity of results possible by changing a various set of parameters of parameters. For example, the freight price might differ when parameters such as equipment type, transit time or guaranteed capacity of the carrier will change.

State of the Art digital platforms such as SAP’s S/4HANA and SAP TM are supporting the overall process for forecasting the transportation demand and address to the core challenges described above. Just consider using this as an opportunity to become more efficient and gain visibility across your forecasting and freight sourcing process.

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