Name: Introducing the Sourcing, Allocation & ATP Calculation of Order Management Services Module in SAP Commerce Cloud
Uploaded: 2024-9-2
Duration: 484 s
Description: Learn about sourcing strategies, fitness evaluation, and allocation in SAP Commerce Cloud. Discover how to optimize consignment configurations and ATP calculation for efficient order management.# This description was auto-generated #

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<div><div><div><div><div><div>Learn about sourcing strategies, fitness evaluation, and allocation in SAP Commerce Cloud. Discover how to optimize consignment configurations and ATP calculation for efficient order management.<br><br># This description was auto-generated #</div></div></div></div></div></div>

Introducing the Sourcing, Allocation & ATP Calculation of Order Management Services Module in SAP Commerce Cloud

Sourcing service comes with sourcing strategies for splitting orders into different consignments  depending on some factors  like stock availability and shipping distance. SAP Commerce Cloud provides a list of sourcing strategies out-of-the-box. No splitting strategy: This strategy evaluates  which locations can fulfill  the order as a single consignment. Pickup strategy: This strategy evaluates  if the specified pickup location  can fulfill the order as a single consignment. No restrictions strategy: This strategy evaluates  which locations can fulfill the order  by splitting the order entries  into many consignments  and sourcing them at different locations. As we know, once the sourcing results  are returned by the sourcing service,  the allocation service will create  the corresponding consignments.  It also allows you to reallocate items  from a consignment to another warehouse.  The sourcing strategy results  depend on the relative weight assigned to four predefined sourcing factors,  according to a built-in algorithm  called Fitness Evaluation.   These factors include: Distance from the sourcing location  to the delivery address Allocation, The number of products available from a sourcing location The priority level assigned to a sourcing location	 by backend users. Score is similar to priority,  but calculated for each situation.  The weight distribution can be adjusted  in the administration perspective  in the Backoffice.  Now, let’s talk about the sourcing  and allocation in more details. In SAP Commerce Cloud,  the process of finding the best sourcing location  or the best consignment configuration  is called fitness evaluation,  which involves several concepts. Fitness represents the relative suitability  of a sourcing location or consignment allocation. Fitness Factors are the possible factors  which will impact the sourcing result,  such as warehouse priority, distance to shipping address or stock amount.  Weighting refers to the percentage importance  of a factor in comparison to other factors. Fitness evaluation contains two steps: Calculate the Fitness value for each potential location. Decide the optimal sourcing locations  or consignment allocations. Let’s explore the fitness evaluation process  with a practical example next.  First, let’s define all factors, each assigned a corresponding weight.  Please note, the weights must add up to 100. In this example, three factors are used:	 Distance with the weight value of 50. Allocation with the weight value of 30. And priority with the weight value of 20.  Next, we’ll use the current settings  to perform a fitness evaluation  for a certain order.  The process starts with calculating  corresponding fitness values for each factor.  In this example, let’s calculate the fitness value for the distance factor.  Suppose we have three sourcing locations, L1, L2 and L3, regarding the distances  to the current order delivery address. L1 is 50km away, L2 is 200km away,	 L3 is 10km away. Then, We sum up all the distance values,  which in this case total to 260km. And we calculate the weight percentage  of each location by using its distance value  in relation to the total distance value.  E.g. for L1, (50 / 260) *100 = 19.23% The sourcing location will be better if the distance is shorter.  Hence, we will invert the percentage values  to get the factor fitness value.  E.g., for L1: it is (100 - percentage value) = 80.77% Likewise, we determine the distance  fitness values for L2 and L3,  as depicted in the table.  Using the same principle,  we can calculate the fitness value of all factors  for each sourcing location. Next, we need to calculate the weighted factor fitness for each sourcing location  by multiplying each factor fitness by its corresponding weight percentage.  Take for example location L1, its factor fitness is 80.77.  By multiplying it by 50%,  we get its weighted distance fitness,  which equals 40.39.  After calculating the weighted factor fitness  for each sourcing location,  add them together.  Thus, the final fitness value  for L1 will be the sum of 40.39, 5, and 11.25,  amounting to 56.64.  Once we have determined the fitness values for L1, L2, and L3, we're equipped to identify the optimal sourcing locations.  There are varied methods to generate the consignments.  One such feasible method  is the greedy algorithm,  where we make local optimal decisions  in a bid to achieve a globally optimal outcome.  In our context, the greedy algorithm  performs the following tasks. It arranges the sourcing locations  in descending order based on their weighted fitness. It attempts to fulfil as much  of the order as possible  using the first sourcing location. The algorithm then continues to meet as much  of the remaining order as it can,  utilizing the next sourcing location in line. It repeats step 3 until  either the entire order is satisfied,  or we exhaust all sourcing locations.  Assume one user has placed an order containing two items. Product ABC with a quantity of 5, Product XYZ with a quantity of 10. The table below displays the current stock level  for each combination of product and location.  For instance, location L1 houses 3 units  of product ABC and 9 units of product XYZ. Using the greedy algorithm approach,  we need to rank sourcing locations  based on their weighted fitness.  Therefore, L3 should be the first,  followed by L1, and then L2.  We then source the maximum quantity  of items from the fittest location first  into a single consignment.  The final result of the fitness evaluation  is demonstrated in the table below. The order is split into two shipments,C1 and C2. The first shipment, C1,  contains 3 units of ABC and 2 units of XYZ,  both from location L3. The second shipment, C2, comprises 2 units of ABC and 8 units of XYZ,  all sourced from location L1.  In order management, availability to promise (or ATP)  means the quantity of a product  that can be promised to a potential buyer  from a particular base store or point of service. ATP calculation can happen at the base store (global) level,  or at the point of service (local) level.  This process involves calculating the quantity  of a product at a collection of warehouses,  and taking into account the events  that can increase or reduce the quantity of  that product at those warehouses.  The ATP value is calculated according to an ATP formula that defines  which data to consider for this calculation and how each value should be interpreted.   You can select only one ATP formula  to be used as the default for a base store.  In the Backoffice Administration Cockpit, under the ATP Formulas screen,  you can configure ATP formulas by adding or subtracting variables.  Let’s open the backoffice,  navigate to order management, ATP formulas,   choose the default_formula for electronics store,  You will see a list of events that can increase  or reduce the product quantity in those warehouses. For each event, you have the option to enable  or disable it.  For more content and details about the order management service module  you can refer to these resources.  In this session, we’ve learned basic concepts,  functionalities, services and processes  in the order management service module,  which plays an important role  in order processing for SAP Commerce Cloud.  Thank you for watching!