Client: A leading multinational company
Products / Services: Industrial machinery, electronics
Areas of operations: Worldwide
The client, which manufactures multiple products in different business segments and markets them globally, were facing difficulties in achieving faster quote turnaround time for pricing negotiations with its customers. The client’s existing technology had limited capabilities to capture and measure market pricing, assess the impact of pricing actions and decisions, and support transactional negotiations across all products. They were not able to identify the pricing levers that were affecting their profitability. Therefore, pricing and sales tactics were not meeting market trends and requirements, resulting in inconsistency in pricing execution, significant margin drop and lost revenue.
Wipro implemented a pricing transformation initiative that assessed the client’s pricing and sales effectiveness as well as transformed key elements of strategy, price setting, and transaction and performance management. The solution included data integration, transformation, building of a data lake, automation using the open source business intelligence tool Pentaho, and data storage in Amazon Redshift.
- Designed a data mart to integrate data from salesforce and other source systems to provide a unified view of pricing data
- Integrated real time, batch and external data to AWS Redshift
- Implemented a metadata-based data integration approach to integrate multiple sources to data lake
- Automated the transactional negotiations process using Pentaho
- Leveraged Pentaho ETL tool to transform and load data into pricing data mart by following the Kimball approach and Pricing Dimensional Data Model. The files were processed using AWS Redshift spectrum
- Enabled storage of the data from the price optimization platform and transformed data in Redshift which could be consumed through API
The client enabled best-in-class pricing capability as a core competency and competitive differentiator. The pricing transformation enabled the client to measure the impact and effectiveness of pricing decisions throughout the pricing lifecycle. It enabled automated, intelligent, and data-driven negotiation governed by policies and pricing guidelines.
- Power of Redshift and parallelism helped reduce 20% of loading time and increased performance of data integration
- Data-driven decisions instead of rule-based decisions helped improve pricing strategy effectiveness
- New and improved user interface with dashboards of customers’ KPIs helped identify customers with higher profit margin, which led to savings of 10 - 15% in terms of operational costs
- Saved effort while onboarding new customers through metadata approach and providing transactional and profits data to business on time to take necessary decisions
This was a complicated data integration implementation in terms of scale and size. The pricing data mart enabled business users to identify poor pricing practices, make data-driven decisions, identify high and low performing customers and products, and measure impact on revenue. -Raman Awal Global Practice Head - Information Management, Data Analytics and AI, Wipro Limited.