Capability-level duplication inside the surviving stack — where the same job is done in two or three tools, what the duplication is costing, and which consolidation move to make.
Inside even a rationalized stack, the same capability often exists in two or three places. Contract storage lives in the CLM, in ERP attachments, and in a shared drive. Supplier records sit in vendor master, in the CLM, and in spend analytics. Each duplication seemed reasonable when set up. Together they create the real cost: data drift, integration overhead, training burden, and audit confusion when two systems answer the same question differently.
Where the Tool Footprint Optimizer asks “which tools to keep,” this asks “within the tools we keep, where is the same capability duplicated — and what is that duplication costing us?” Capability-level overlap surfaced, scored, and consolidated.
AI reads schemas, configurations, and feature mappings to list what each tool can do — at the capability level, not the product-name level.
Where the same capability — contract storage, supplier records, approvals, categorization, document signing — exists in two or more tools.
Drift incidents, sync integrations, duplicate training, audit reconciliation hours, and operator confusion quantified per overlap.
Pick one home for each duplicated capability, retire the rest, or define a clean split — with the migration path and workflow impact named.
“Inside the stack we have decided to keep, where is the same job being done twice — and what is that costing us.”
A capability-overlap inventory, a cost score per duplication, and a consolidation recommendation per capability — consolidate, split cleanly, read-only mirror, retire, or accept and govern.
A 20-minute working session. We’ll walk through what the optimizer produces from real schema and integration data.