Category Strategy & Market Analytics

Detailed insights for direct and indirect spend optimization

Our Category Management Software uses category-specific transactional data to determine the most impactful actions you can take to optimize your expenditure.

Our savings analysis covers commercial, demand, and process levers. The Spendscape platform runs in-depth analytics on millions of transactions and applies a set of proven levers to identify and size savings.

How we support you

Aggregate, visualize, and analyze category spend

We provide detailed insights for both direct and indirect spend optimization with our Category Management Tool. Data is aggregated from multiple sources and uploaded to a cloud-based platform for analysis. We then compare it with external indices, clean sheet cost models, and third-party benchmarks.

Create insights at scale

Compare prices against internal and external benchmarks with Linear Performance Pricing.

Stay ahead of volatility

Import index data and create cost archetypes to compare price fluctuations with Input Cost Monitoring.

Derive tangible spend benchmarks

Compare spend with external indices, clean sheet cost models, and third-party benchmarks.

Get deep category analytics

Perform in-depth analyses and use proven levers for several indirect categories.

AUTOMATE CATEGORY INSIGHTS TO HIGHLIGHT SAVINGS OPPORTUNITIES

We provide category management solutions for multiple indirect spend categories including Contingent Labor, Maintenance, Repair and Operations (MRO), Air Travel, and Facilities Management, and for direct spend categories including Linear Performance Pricing (LPP), Similar Parts Analysis (SPA), and Input Cost Management (ICM).

Step 1

Extract data, categorize, and validate; align on savings lever parameters

Step 2

Review output to generate insights and discuss recommendations

Step 3

Define actions and resources to capture savings

Our capabilities

Drive competitive advantage by using best-in-class McKinsey knowledge and deep category management and optimization experience. Perform in-depth analyses using proven category levers for several indirect categories and uncover granular insights to determine the best course of action with the greatest impact potential.

Case study

We identified a 6% savings potential in two weeks for the global maintenance, repair, and operations (MRO) spend of a Fortune 500 high-tech company. We used machine learning and a standard six-step McKinsey taxonomy to classify MRO spend. We applied four advanced analytics to the company’s global MRO spend in the platform and eliminated pricing variances, consolidated supplier base, replaced OEM parts, and rationalized SKUs.