CASE STUDY
Data Analytics
Improving operational efficiency and optimizing costs with machine learning.
PROBLEM
India’s largest energy utility power supply corporation wanted to utilize machine learning and deep analytics capabilities to improve their operational efficiency while optimizing costs and revenue.
OVERVIEW
The corporation believed in the capabilities of machine learning but needed to identify the correct area to begin implementing deep analytics and ensure organization-wide buy-in and adoption.
They also wanted the project execution partner to identify the data availability parameters for their needs from the Systems Applications and Products (SAP) that had been integrated across their different locations. Ultimately, these identifications would help to ensure the success of implementation and sensible outcomes.
PRAKAT SOLUTION
- Identified the organizational need that could be addressed with the right data analytics profiling – in the form of vendor assessment and rating.
- Studied the SAP systems in place for data analysis, tool-based data profiling, and extracting and correlating data.
- Built a data analytics dashboard and a machine learning platform that captured, extracted, and presented data from multiple systems.
- Successfully implemented a vendor rating model that takes SAP applications data to provide supplier performance measurements on responsiveness, quality, delivery, and post-delivery performances.
Data analytics and automation
KEY WINS
Organization-wide adoption of the newly-implemented Vendor Rating System.
Identified and quantified process efficiencies and cost savings from automation and decision support systems.
Continuous improvement of procurement outcomes across current vendor performance parameters including: pre-award, post-award, quality, delivery, post-delivery, response time, completeness, deviations, and overall timeliness to accept the purchase order.
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