Solution
AI for Data
Solution
AI for Data
Industry
CPG
Region
US
Context
Enterprises thrive on data-driven decisions, yet the integrity of this data often gets compromised by fragmented systems, inconsistent rules, and manual interventions. In HR and related functions, this challenge becomes acute, as errors in employee records, benefits, or headcount metrics translate into tangible business risks and inefficiencies. AI for Data addresses this by embedding automation, advanced rule validation, and scalable monitoring directly at source. The result is a trusted data foundation that ensures accuracy, improves governance, and empowers leaders to act with confidence, unlocking enterprise-wide efficiency and measurable business value.
Problem Statement
Our client, a global CPG leader with operations across North America, struggled to manage critical HR datasets due to siloed processes and lack of a unified data quality framework. Stakeholders lacked visibility into ongoing improvements and found it challenging to quantify the impact of poor-quality data on business outcomes. Inconsistent rules further weakened insights, resulting in inefficiencies across HR operations. We designed and deployed an AI-powered Data Quality Engine with automated rule checks, granular validations, and real-time insights, enabling stakeholders to measure improvements, reduce costs, and reinforce trust in enterprise data.
Impact
- $600K+ annual savings through resolution of data-related inefficiencies.
- ~25% increase in data accuracy for HR metrics like headcount, turnover, and benefits tracking.
- Clear financial attribution framework quantifying the impact of bad vs. good data.
- Improved trust in enterprise data driving strategic workforce decisions