To achieve operations excellence with Oracle Cloud and best practices in master data management
A US-based locks and security products major with $860 Mn in revenue presence across multiple continents was experiencing operational complexity with growing product sprawl. Under the hood of this complexity was the lack of a master data management system that would govern product taxonomy and supply enterprise systems with consistent and uniform product data in real-time. Moreover, the security products manufacturer wanted to achieve better product classification, especially as it handled 70,000 items with 309 attributes across four websites. As a result, the manufacturer implemented Oracle Product Hub Cloud to bridge the gap between engineering. This would supply ERP systems with sanitary and consistent master data – for which it chose Birlasoft as its transformation partner.
Through our engagement, we helped our customer establish a data stewardship function and rationalized their item classifications with a consolidated data model. We also defined product governance processes and migrated thousands of items from on-premise systems to Oracle Product Hub Cloud. Finally, we closed the loop by implementing Oracle Integration Cloud and reusable error handling processes. Through this engagement, we helped the client achieve a high degree of automation in MDM workflows and saved them $100,000 in annual licensing costs . However, the key benefit for the bottom line was reduced lead time for product commercialization and high-quality product data at the source. See the entire process in detail below.
The Challenge
1. Inability to define and manage attributes across websites causes process inefficiency
Our client manufactures a range of security products that are listed on multiple websites. Managing this extensive product portfolio in a company that has been growing over the last 100 years calls for resilient, flexible, and consistent data models with a minimum set of attributes to define master data across all domains. However, the lack of a central MDM platform meant that the client was unable to manage and define attributes spanning all the sites, which led to process inefficiency and a lack of consistency in reference data within key enterprise systems.
2. Suboptimal data models result in difficulty managing multiple classes of products
One of the critical steps to realizing business value through MDM solutions is to build optimal data models where common attributes can create variants of SKUs. Our client was unable to operate with this simplicity because of suboptimal data models, which had not been rationalized over the years. Their teams wanted to leverage a solution that would help them easily maintain common attributes of SKUs with something analogous to Style Items in the Oracle Product Hub ecosystem.
3. Obsolete taxonomy leads to inefficient classification and increases complexity
In the absence of an optimized taxonomy, our client operated with unnecessary complexity. They wanted to better classify their SKUs into 'Finished Goods,' 'Packaging,' 'Components,' 'Configurator,' 'Raw Materials', and 'Assemblies.' For this, the client needed help architect a stringent taxonomy to load high-quality master data into the implemented solution.
The Solution
1. Rationalizing and sanitizing to achieve high-quality master data
To help our client manage their master data with ease, our teams first identified areas where they could make significant gains. Next, we analyzed 309 attributes of items across four websites and saw the scope of simplifying the data model by 42%. To achieve this, we eliminated duplicate data and consolidated the data model to 132 attributes in total.
Further, we analyzed 70,000+ items across distributed enterprise systems, which were initially classified into 320 categories. Then, we rationalized them to 172 item classes, which helped us establish a consolidated core taxonomy. We achieved by reinstating the parent-SKU inheritance relationship at the SKU level. In addition, we leveraged our RPrIm accelerator templates, which helped us implement mass configuration of setups, ensuring minimal disruption and rapid delivery for our client. Finally, 70k+ items were migrated from distributed on-prem systems to Oracle Product Hub Cloud.
2. Achieving real-time system interfacing with Oracle Integration Cloud
Because our client was still leveraging on-prem technologies like Product Information Management systems, we implemented Oracle Integration Cloud (OIC) to build real-time integration and reverse interface with the Product Hub Cloud. This entailed installing an OIC agent on the client's network to integrate OIC and on-prem databases. OIC implementation brought speed and responsiveness into the core business logic and enabled complete automation of business criteria and processes for various scenarios in a scalable fashion.
3. Closing the loop with a data stewardship function and proactive measures
Maintaining high-quality master data is a continuous process that calls for adequate process guardrails and people practices. To help the client prevent lapses and drift in master data quality, we helped them establish a dedicated and scalable Product Data Stewardship function and recommended optimal processes, defined standards, and policies.
We also defined product governance processes with 100+ business rules underpinning change management workflows. In addition, we implemented a reusable error handling mechanism in OIC to notify the right teams, thereby helping them proactively diagnose core systems in cases of failures. Lastly, we used a completeness score utility to generate a measure for item quality and implemented a criterion to prevent the fall in the quality score of an item below 70%.
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The Impact
A well-architected taxonomy driving an MDM implementation yields significant benefits to business operations. For our client, it brought the following key benefits:
  • In line with the Pareto principle, we eliminated 74,000+ items for our client, which brought $100,000+ annual savings in licensing costs.
  • High-quality, consistent master data at the source, achieved through pin-to-pin data validation in the migration process, ensured a single source of truth for all enterprise systems.
  • Automating most of the processes within MDM product creation and change workflows saved expensive person-hours and delays.
  • Finally, Product Hub Cloud implementation enabled our client to visualize hierarchies and taxonomies across data domains easily.
In sum, this MDM transformation helped our client achieve operational excellence and reduced the lead times for product commercialization. By ensuring scalable practices, solutions, and guardrails, we could ensure that our client continues to operate with these gains over the long term after this engagement.
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