Cora Data Foundation

Genpact's Cora Data Foundation is a low-code, ready-to-deploy solution that helps organizations source, curate, and enrich their data. When data is accessible in multiple formats for analysis and reporting, teams can rapidly uncover actionable insights and drive competitive advantage.

Cora Data Foundation is a platform agnostic solution and leverages Genpact's deep industry expertise within a pre-built library of configurable assets. These assets are based on Genpact's experience managing business processes for many industries and business functions – including finance and accounting, supply chain, insurance, high-tech, manufacturing, banking, and capital markets.

The solution can collate and process data at varying levels of granularity – from raw form to denormalized and aggregated – for use in artificial intelligence and machine learning applications to support analytical models and insight generation across various systems of engagement.

Common data challenges in the enterprise

• Cost control and operational inefficiencies
  Disconnected, fragmented systems create visibility and control issues – when poor quality data goes in, transactions and processes come out filled with errors.
• Lack of actionable insights
  Disparate sources of data and outdated business information result in inaccurate forecasts and inefficient decision-making.
• Poor user experience and low ROI
  A lack of standardization creates a poor user experience, and outdated metrics limit usability and ROI.
• High risk and low compliance
  A lack of proactive measures to control operational risks compromises data compliance and integrity.
• Limited or no governance model
  Many organizations lack centralized data governance and ownership of master data, which slows business operations.

Overcoming these challenges with Cora Data Foundation

• Reduced cost and faster time to market
  Scalable, ready-to-deploy components like industry-specific data models and data pipelines lead to a cost efficiency improvement of 25–40% and a faster time to market of 10–12 weeks.
• Predictive and prescriptive insights
  Integration of semi-structured and unstructured data enables enterprises to turn data into analytical insights – illustrating what's likely to happen and what actions to take to effectively address a situation.
• Enhanced user experience
  A standardized and intuitive user experience provides personalized dashboards and analytics with built-in natural language generation.
• Highly secure and compliant
  High levels of data security – including data encryption, decryption, and personally identifiable information masking – help protect individuals and the enterprise.
• A robust governance model
  A metadata management capability with machine learning capabilities improves data quality, backed by self-healing features for issue remediation.

Case Studies

Transforming source to pay

A global power-generation-equipment manufacturer was grappling with a variety of issues across its source-to-pay data and analytics function. Vendor dissatisfaction, high and variable sourcing costs, contract leakages, and inconsistent payment terms all played a part. Using a Cora Data Foundation solution, the manufacturer sourced, structured, curated, and loaded data from multiple businesses, ERPs, and other applications into an integrated data repository. Using this integrated data, the manufacturer was able to monitor key and cross-functional metrics in real time, generate business insights, and support predictive analytics. As a result, the manufacturer was able to create a business impact of $117 million in just one year and increase spend visibility to $21 billion.

Taking control in finance
A leading financial organization wanted to digitally transform to reduce costs, democratize data, and increase innovation. Using Cora Data Foundation, the organization was able to rationalize financial reports, optimize its financial close, improve overhead allocations, and strengthen financial controls. Combined, this led to benefits of around $74 million, including $15 million in savings on financial audits against an annual audit expense of $68 million. In terms of productivity and accuracy, the organization has reduced the time spent gathering and validating data by 30% and has achieved an earnings forecast accuracy of 90%+ year over year.