Spend analytics services outsourcing & consulting services
Procurement has always been one of the oldest and yet critical business functions in an enterprise. It has witnessed numerous technological investments in terms of digital enhancement and transformation. However, there are still some relevant challenges that the procurement function has been facing for a few years, making it essential to use advanced spend analysis in procurement to generate better insights and decisions. AI-powered spend analytics outsourcing and consulting from Infosys BPM help procurement leaders unlock hidden value, improve compliance, and support strategic decision-making with trusted data and insights. To address these challenges,- Infosys BPM has introduced TradeEdge, an enterprise-grade, AI-powered procurement spend analysis service that leverages spend data to help enterprises in their journey towards a holistic digital transformation.
Built for CPOs and procurement leaders, our procurement spend analysis services also support finance teams tracking AP visibility and compliance and ESG functions monitoring supplier risk giving every stakeholder a shared, trusted view of spend.
AI-powered spend intelligence offering
The Infosys BPM spend analysis service delivers spend management solutions designed to augment an enterprise’s procurement ecosystem with AI-enabled spend data management, spend analysis, and opportunity identification, as well as various leading domain services, to overcome business challenges.
Based on Infosys BPM's TradeEdge spend analytics engagements across global enterprise clients.
$200+ billion
Spend analysed
3,000+
Categories
125+
Insights
10+
Global enterprise clients
Strategic spend analytics outsourcing scenarios we support
Organizations typically engage Infosys BPM's procurement spend analysis services in high-impact scenarios such as:
- Consolidating spend visibility across multiple ERPs, business units, or regions to create a single source of truth for procurement decisions.
- Identifying and prioritizing savings and value opportunities through tail spend management solutions in indirect categories where leakage and non-compliance are hard to detect.
- Supporting sourcing waves and category strategies with robust, AI-generated insights on supplier performance, pricing, and risk.
- Monitoring ESG, risk, and sustainability indicators across suppliers and categories to inform responsible sourcing decisions.
- Enabling M&A integration or shared services set-ups by rapidly normalizing and analyzing spend from acquired entities.
In each case, the goal is to turn raw spend data into actionable intelligence that directly supports procurement strategy, supplier negotiations, and executive reporting.
Features of spend analysis
- Enable automated data ingestion with pre-built connectors and adaptors facilitating seamless integration without any alteration to the internal systems
- Leverage AI for automating supplier and product harmonisation and further enrich by leveraging multiple external data sources
- Leverage Infosys domain expertise for AI model training to enhance the effectiveness of procurement analytics
- Implement AI-enabled data cleansing, quality checks, transformation, and de-duplication using a spend analysis solution
- Utilize AI-enabled spend analysis and taxonomy to enhance the effectiveness of your spend analytics system
- Leverage rule-based engine, industry-specific knowledge base, and ML models to achieve accurate classification of spend data
- Multilingual and extensible classification (n-level taxonomy supported)
- S&P experts for spend data validation and governance of the United Nations Standard Products and Services Code (UNSPSC) or custom taxonomy
- Switch from descriptive to predictive analytics with extensive dashboards and predictive analytics capabilities of spend analysis.
- Use Dynamic Guided Opportunity Analysis for continuous identification and validation of improvement opportunities in procurement.
- Monitor procurement health in near-real-time through a KPI scorecard and leverage root-cause analysis to identify areas of improvement in spend data trends.
- Leverage more than 100 pre-built dashboards and analysis to gain granular visibility to spend data patterns and trends
- KPI scorecard: A contextual dashboard to track business metrics and associated targets for procurement managers with pre-built drilldowns for each KPI to enable detailed tracking of spend analysis outcomes
- Root-cause analysis: A general purpose tool that allows root-cause analysis on specific procurement business measures as well as enhanced spend data visibility across categories, business units, products, etc., and integrates seamlessly with spend analysis tools
- Mix-and-trend dashboard: An integrated dashboard comprising of multiple linked analysis that help enterprises to identify the contribution of categories, groups, products, countries, business units, and suppliers to spot associated trends in spend analysis.
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Success stories
Bringing values to businesses through our products and services
Case Study
Case Study
Insights
Challenges and solutions - spend analytics outsourcing
The following challenges and solutions reflect typical issues CPOs and procurement leaders face when scaling spend analytics outsourcing and consulting:
The core issue is fragmented, inconsistent data. An effective spend analytics program centralizes data from all source systems, applies ongoing cleansing and normalization, and maintains a governed “single source of truth” for suppliers, categories, and transactions. This allows procurement and finance to work from the same numbers and avoid manual reconciliation.
This usually happens when analytics stops at dashboards. Mature spend analytics turns patterns into prioritized opportunity pipelines such as consolidation, specification standardization, off-contract spend reduction, or risk signals and links them to sourcing events and category strategies. Stakeholders see not just what is happening, but what should be done next and in what order.
Manual rules and ad hoc taxonomies don’t scale. A more resilient approach combines machine learning-based classification with expert review of edge cases, using feedback loops to improve over time. This keeps classification accuracy high as the business changes, without needing to constantly grow internal analytics headcount.
Many programs focus only on value and miss non-financial dimensions. By integrating ESG attributes, risk scores, and policy rules into the spend model, analytics can highlight suppliers, categories, or regions that are misaligned with ESG or compliance requirements. Procurement can then use this insight to inform sourcing decisions, supplier development, and contract clauses.
The solution is to define KPIs and value tracking that link analytics-driven actions to outcomes such as savings, cost avoidance, compliance uplift, risk reduction, and working capital benefits. Regular reporting that connects specific initiatives to these metrics makes it clear how spend analytics is supporting strategic procurement and enterprise performance.
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