About the Customer
The customer is a subsidiary of an Osaka-based chemical company and one of the largest industrial paint companies in India. It develops and supplies decorative, automotive and industrial coatings.
Business Scenario
Before partnering with Maventic, the client had an SAP and a production forecast application (third-party system), wherein the latter was incapable of exposing REST APIs.
Challenges
Operating with disconnected systems and manual forecasting processes, the company struggled with inefficient data exchange and delayed decision-making.
- Lack of REST API Functionality – Required direct engagement due to the forecast application’s inability to access SAP system information.
- Manual Demand Forecasting – The process was entirely manual, relying on standalone applications.
- Delayed Decision-Making – Inefficient forecasting led to slower decision-making.
Solution
The customer decided to integrate their SAP system with the forecast application using Cloud Integration to address challenges related to file storage and accessibility. After evaluating SAP Cloud Integration partners, they selected Maventic to enable the forecast application to consume flat files from SAP via an Amazon S3 bucket. Maventic utilized SAP BTP (CPI, S3 Adapter, REST Services) and SAP ERP (ABAP) for this integration.
- SAP BTP Usage – SAP BTP provided flexibility for hybrid environments, with SAP Cloud Integration and the S3 Adapter enabling seamless flat file transfers to Amazon S3.
- REST Services – REST services were employed to interact with the forecast application, enabling simple, scalable, and stateless communication between systems.
- Integration Flow – The flow involved storing flat files in the S3 bucket, which could then be accessed by the forecast application. SAP Cloud Integration facilitated the transfer of data from SAP ERP, while the S3 Adapter enabled interaction with Amazon S3.
Business Impact
The SAP-Amazon S3 integration transformed production planning, delivering automated forecasting and improved inventory management.
Improved Forecasting
Automated data exchange enabled accurate demand forecasting, optimizing production planning and resource allocation.
On-Time Delivery to Dealers
Better forecasting ensured timely production and distribution, meeting dealer demand consistently.
Reduced Shortage of Stock & Dead Stock
Accurate demand prediction minimized both stockouts and excess inventory, optimizing working capital.
Increased Longevity of Products
Improved inventory turnover and reduced storage time enhanced product quality and freshness for customers.
