Enterprise-wide visibility and spend analysis are critical to achieving long term sourcing savings. Unfortunately, many sourcing executives are constrained by data across too many disparate systems to recognise this untapped potential.
Companies must be able to
effectively analyse and track spend to drive bottom line
Internally, a tremendous amount of time is spent preparing the data to perform the analysis, which reduces resources dedicated to actually sourcing goods and services.
Scanmarket's Spend Analysis Module can help gather all data extracted from various company systems into an application, and be able to identify and aggregate at item and category level, which transactions should be mapped with matching items or categories.
The module provides access for you to a reporting application able to slice and dice spend and thereby assist buyers with their strategic procurement decisions.
Scanmarket Spend Analysis Key Features
- Reliable technology: IBM Cognos based
- Spend data extraction
- Data profiling and validation
- Data cleansing and enrichment
- Supplier and item harmonization
- Auto classification of SKU commodities to custom or industry standards using AI aboratories & IBM Cognos technology
- Fully customisable, multidimensional, browser based analytic environment
- Step by step analytics to help users prioritise and select commodities for sourcing
- Ability to search/sort/aggregate items by keywords
- Possibility to estimate savings opportunities
- Optimize supply base
- Attain leverage for the category you buy
- Aggregate demand across OpCo's/Countries
- Opportunity to negotiate lower cost contracts (particularly useful for indirect spend analysis and collaborative negotiations preparation)
- Monitor compliance
- Monitor performance
- Modular approach (per department, location, category, supplier)
- Possibility to handle dissimilar databases, different languages
- Transversal spend visibility throughout all OpCo's
- Significant savings
- Very competitive market price (low entry level - remains competitive as the data/locations grow)