Customer master data management is a key focus area for any manufacturing giant and this case study discusses how NeosAlpha produced a solution by leveraging the Boomi IFS integration features to achieve the same.
Our client is a renowned manufacturer of plastic piping systems in the UK. Their piping systems are used for various applications, including drainage, plumbing, water supply, water management, cable management, heating and ventilation. They are listed on the London Stock Exchange and a constituent of the FTSE 250 Index.
After several successful acquisitions, their parent company consists of more than 15 subsidiaries operating independently.
Each of these subsidiaries has its suppliers and customers. They maintain the details of the suppliers, customers and prospects in their ERP system. Some of the suppliers and customers were related to more than one subsidiary.
To improve efficiency in managing their customer and supplier relationships, the parent company wanted to produce a data estate that would contain quality data without duplicates. In the long term, they aim to run Business Intelligence and Data Analytics on reliable, trustworthy data.
All subsidiary companies of the parent manufacturing company were using IFS as their ERP platform. Each subsidiary company had its instance of IFS and stored the details of all customers, suppliers and prospects.
More than one way in which these data were captured, updated and maintained in the IFS system. Sales teams manually updated the customer and prospect data as CSV files.
Customer servicing agents could create, update and delete records in IFS via a custom-built legacy application. Each data source had minimal and inconsistent validation rules for the data fields.
The quality of data stored in IFS was poor. It contained duplicate records for the same customer or supplier. For example, Sony Limited and Sony Ltd were held as two records even though both shared the same address and postcode.
Many records contained polluted data like the phone number field containing the postcode and address line 1 containing the phone number.
Some records did not have any value for many fields. In addition to data quality issues, missing data was also an issue because many records contained no value for required fields.
When data across all the IFS instances were reviewed as a single unit of data, the data issues increased exponentially because of one-to-many relationships between a subsidiary company and customers and suppliers.
How NeosAlpha Helped
Our first order of business was to meet with the client’s sales and customer management teams to fully understand their key concerns, data issues, and impact.
After carefully listening to the team and understanding their goals, our NeosAlpha’s MDH experts presented a clearly defined roadmap and timeline.
Our priority was to produce an IAL view that would consolidate data from all the IFS instances used by various subsidiary companies. After performing, a detailed data analysis, our consultants worked closely with the client to understand the genuine reasons for a duplicate record.
For example, as per the client’s business process, they wanted to treat a customer having different payment terms with more than one subsidiary company to be treated as another customer.
We performed several dry runs in Boomi’s MDH staging environment to fine-tune the matching rules so that no duplicate gets created as a golden record.
We did not stop with a successful MDH process for supplier and customer data. The team continues to present strategic, forward-thinking ideas that help our client to move further on its data transformation journey.
For example, building data pipelines to push the golden records into a data warehouse for analytics and to generate business intelligence reporting to support informed decision making.
More than 12,000 supplier and 75,000+ customer records have been processed successfully as part of the initial data load into the 2 MDH processes.
- 78% of supplier records have been identified as golden records
- 5% of records have been marked as data quality errors.
- 22% of customer records were found to be a genuine duplicate
- The business was able to resolve the issues themselves using the Boomi’s Quarantine dashboard without having any dependency on IT teams
- Improved customer communication, relationship, and sales teams were able to run customized, targeted up-sell and cross-sell campaigns
The solution is automated as a scheduled integration process to validate the new and modified records.