Public funding moved before the tender process.
A global lighting company's business-development team saw a major US stimulus programme create a short window of opportunity. It needed to know which states and cities would receive funding, which infrastructure projects were taking shape and who would influence the spending decisions.
Manual searches and industry websites did not provide that view early enough. Official tender portals showed opportunities after the market had already begun to form.
Signals became potential opportunities.
TSC configured Genie around federal, state and city funding announcements, infrastructure developments and project signals. The system linked relevant announcements to places, projects and decision-makers. Machine learning helped identify potential opportunities from new source material.
When a signal met the agreed criteria, it was routed into Salesforce. Account managers could qualify it using the source evidence and the stakeholder context rather than starting with a tender notice alone.
For shortlisted projects, stakeholder mapping identified the public bodies, city stakeholders and other decision-makers around the opportunity. The map and signal record stayed connected to the lead as it moved into the commercial workflow.
A reusable opportunity model remained.
The workflow surfaced more than US$50 million in potential opportunities during its first two weeks. It identified more than 70 potential opportunities over six months. These figures describe pipeline identified by the project. They do not represent realised revenue.
The working model connected public funding, emerging projects, stakeholder context and the company’s CRM. It could continue to detect and route opportunities as new programmes and markets entered scope.
