SAP MDM 7.1
Time is one of the aspect that impact Product in term of its physical characteristics or in terms of perceived effectiveness of its qualities. This has a direct implication on expected revenue for Retailers or Manufacturers and also impact on the operational cost to invest in logistics and inventory management.
Therefore it is critical to model this business scenario while defining the Master Data Management solution for enterprise.
This paper talks about as how time variant product scenarios can be modeled using SAP MDM.
Tata Consultancy Services
09 October 2015
Ajay has been associated with Tata Consultancy Services (world-leading information technology consulting, services organization). He is handling the responsibility of Head of Item MDM Practice in TCS.
It is well known that each product has shelf life. After the prescribed shelf life product is ceased to fit for purpose. Retail organization always aspire to manage product launching and supply chain effective to get maximum remaining shelf life of the Product in store rather than in inventory, warehouse or in transit.
There is one more key dimension that affects the shelf life. Some products change their physical characteristics as time passes away. Some product like season specific or event specific drastically drop their useful value as soon as the season or event is over.
Retailers should manage such products effectively to maximize return value.
Time variant products that change their physical characteristics are tricky to manage in itself. Organization information management systems should be able to model such products accordingly to reflect its time variant nature. Many organizations know the importance of these aspects but fail to manage appropriately in Information Management.
This paper talks about as how effective management of such time variant products starts from the Master Data Management using SAP MDM.
Time Variant Products
Time Variant products are the one that change key aspects, either physical characteristics or its useful life span.
- Products value drops drastically after specific time frame though its physical characteristics are intact and fit for use. Such products are typically season use products. For example, rainy products have high demand and value during monsoon season or educational high end products have high demand during back to school season. After the specific time frame, return revenue of those products drops significantly.
- Products that change physical characteristics and still continue to be fit for purpose. Such products are typically fresh food products like fruits. For instance, banana could take different physical characteristics and can be sold to be used in that specific physical characteristics. Green bananas product become yellow banana product with complete change in its salable view. Logistics, storage, price and purpose are completely different for green and yellow bananas.
Category 2 product are tricky to handle. For instance, green bananas become yellow bananas if kept in inventory for certain time period. Thus the inventory of green banana becomes zero whereas inventory stock for yellow bananas increases all of a sudden without any manual intervention. Effective supply chain and inventory management are key to ensure adequate supply of items in stores. However if such time variant products are not tracked properly with respect to time span, it could lead to non-availability of stock for some products and excess stock for other products.
Retail operations should take cognizant of this critical aspect and ensure that at any given point in time product identity is accurately mapped. Retail operating systems should have ability to identify this product identity transition. However it is practically difficult for every operational system to track the identity change.
Master Data Management Solution
Product Master Data Management (PIM) solution comes to rescue to handle the situation. PIM acts as single source which is reliable, integrated and trusted Product information. PIM should take the responsibility to define as how Product identity changes over the period of time.
There are two aspects of the solution:
- Tracking the time change for time variant products: This is a responsibility of Retail operations and operational systems to track the inventory and shelf time span of the specific product lot.
- Publishing Product identity at any specific time: This is the responsibility of PIM solution. PIM solution defines the multiple product identities and also defines as how those product identities are related to each other. For instance, PIM would define both Green Banana and Yellow Banana products. It also defines a time based rule that reveals the identity of specific product instance / lot provided that time change is tracked by the operational systems.
In non time variant products, typically operational system like inventory management system would refer to PIM system to discover detailed physical characteristics and other product details. For instance, PIM system would provide information as how specific product should be stored in inventory, at what temperature it should be stored, what size of packaging hierarchy it would have etc.
The same principle is followed for time variant products as well. The only difference is that the operational system like inventory management system keeps a track of time as when specific lot of Product is stocked in inventory. While referring to PIM system, the inventory management system would also provide the elapsed time since specific product is stocked along with the current product identity details (current product type). In return of this query, PIM system provides details not only about the product characteristics, but it also can provide details about change in product identity (type). For instance, as per the business rule defined in PIM system, if specific time span is already over for Green Banana to become Yellow Banana, the PIM system would provide the new product identity of Yellow banana to the original green banana identity product lot.
In this way the responsibility to accurately identifying the product identity is split between PIM system and operational systems. Operational systems track the elapsed time span, whereas the PIM system will hold the business rule and reveal accurate product identity at given point in time.
SAP MDM Solution Components
For sake of simplicity and to illustrate the subject that is being discussed in this paper, other complexities are removed and avoided.
Primary Product Catalog (Food Product) holds various products. For simplicity this is considered for only food retailer purpose. Typically such catalog would have multiple types of products including food, non food, grocery, toys etc for a typical retailer. Food Product holds the details of various physical characteristics and as well as additional details of the products.
The Food Product is organized by Primary Product Hierarchy (Food Hierarchy). This organizes food products into various hierarchical characteristics.
Transformation Catalog holds the transformations to be applied on to time variant products. Transformations are associated with starting product at the beginning of transformation, target product which is a product resulting after the transformation and associated transformation rule.
Transformation Rule defines the rules associated with various transformations. These rules could be time variant or time independent. Natural progression is one of the type of time variant transformation rule.
Transformation Rule Type defines the taxonomy and associated category specific attributes that further defines the characteristics of specific transformation rule. Natural Progression types of rules are defined by the elapsed days after which the rule is set to trigger specific action. This action could be simply to change the “Product Type” of specific banana product lot from green to yellow bananas.
SAP MDM Configuration
For sake of simplicity, only specific components are illustrated with dummy data elements. Food Product is a catalog to maintain Food products details for ABC Organization. It holds various types of products and their associated attributes. Only limited set of attributes are defined as example.
Food Hierarchy is defined to illustrate various types of products. Third level in hierarchy is illustrated to describe various products like “Apple and Pear”, “C Vitamin Fruits”, “Organic Fruits” and “Bananas” etc. Bananas are further split into “Green Bananas” and “Yellow Bananas”.
Transformation catalog holds various transactions to be applied on Food product in ABC organization. It holds reference to “Start Product” which is the product at the beginning of the transformation. Whereas “Target Product” is the product that resulted after the transformation. It also hold the reference to transformation rule which is maintained in other catalog. Other vital details are also maintained as part of the “Transformation” that includes but not limited to name of the transformation and transformation identify etc.
Transformation Rules are the rules that define actual transformation. Transformation Rules are referenced by Transformations. Transformation Rule hold key basic information like Transformation Rule name and Transformation Rule ID. Transformation Rules are classified in hierarchy that defines attributes associated with specific Transformation Rules.
Transformation Rule Type taxonomy defines various types of rules and attributes definition associate with specific type of rules.
Transformation Rules are classified in various possible ways the food products can be transformed. Broadly it could be time based transformation where transformations are bound to happen after specific time span. It could be further split into natural progression of transformation or manually introduced transformations. Change in bananas from green bananas to yellow bananas are natural progression transformations. Whereas seasonal variance of price of the product is manually introduced time based transformation. Time independent transformation are one time transformations that are driven by changing business environment. It could include change of the sales geographical location of the specific product to address to certain uptick in product demand in those specific geographical locations.
As illustrated, “Days Life” attribute is associated with Natural Progression type. Banana rules illustrated further are mapped to this taxonomy and hence characterized by the numbers of days after that this rule is set to trigger specific action.
For example, “Banana 6” rule is type of “Natural Progression” and is defined to trigger action after 6 days of elapsed time.
To illustrate the example, let us consider that Brand A, Brand B and Brand C bananas are defined across their green and yellow types. ABC Organization sells both green and yellow bananas for Brand A and Brand C.
Two transformations are defined for Brand A and for Brand C to transform respective green bananas into respective brand yellow bananas. Each of these transformations are mapped to specific transformation rules. For example Brand A transformation is mapped to “Banana 6” rule. It also specifies that this transformation will transform the product from Brand A green banana to Brand A yellow banana.
Similarly Brand C is associated with transformation which is further mapped to “banana 8” rule.
Defining the service is out of scope for this paper. However it would be straight forward to define a service that would reference to Food Products catalog and Transformation Rules to identify the current point in time Product type for any time variant product inventory.
Product information is split across Product Master Data Management and with various operational systems. This creates a challenge to effectively handle the time variant products that change physical characteristic of product over the period of time and results into a new salable product. It is the responsibility of both Product Master Systems and as well operational systems in the landscape to handle time variant products. With perfect information synchronization between these two types of systems, the time variant product scenario can be effectively handled.