94-day sales cycle.
Now 68 days.

The challenge

The manufacturer's Salesforce environment had been configured by three different consulting firms over six years. Each engagement had left its mark — stages that reflected a generic sales methodology rather than how this business actually sold, data models built for one consulting firm's standard playbook, and integrations that were either missing entirely or working around gaps in the configuration. The sales team had largely stopped trusting the system.

The data entry burden told the story clearly. Sales representatives were entering the same opportunity data across six systems: Salesforce, SAP, a dealer portal, a pricing platform, a contracts system, and a warranty database. None of them were connected. Every update to a deal required six separate manual entries. The sales cycle averaged 94 days. Forecast accuracy was 58% — low enough that sales managers had stopped relying on Salesforce forecasting and were maintaining their own spreadsheets in parallel. The system of record had become a data entry obligation rather than a decision-making tool.

The approach

Shelorve spent four weeks with the sales team before touching any configuration — mapping how deals actually progressed from first contact through close, what data was genuinely used at each stage, where decisions were made, and where the manual work was concentrated. The existing Salesforce opportunity stages bore no resemblance to the actual sales motion. They reflected an inherited configuration, not the manufacturer's reality.

Sales Cloud was rebuilt from scratch based on the actual sales process — stages with entry and exit criteria defined by the people who managed the pipeline, fields that captured data the business actually used, and workflows that reflected how the team actually worked. The rebuild was done in close collaboration with sales managers and senior reps, not delivered as a finished product for them to adopt.

Six MuleSoft integrations connected Salesforce to every system in the sales ecosystem: SAP, the dealer portal, the pricing platform, the contracts system, and the warranty database. Data entered once in Salesforce flows automatically to all connected systems — the six-system manual entry burden was eliminated. The SAP integration — which a competing firm had estimated at six months — was delivered in eight weeks. The difference was genuine depth in both Salesforce and SAP architecture, which meant the data model was designed correctly from the start rather than discovered and redesigned mid-build.

Einstein opportunity scoring was trained on four years of the manufacturer's own closed-won and closed-lost opportunities — not a generic model deployed against a new data set. It learned the specific combination of account attributes, engagement signals, deal characteristics, and stage velocity that predicts close for this business. The model was validated against historical data before deployment and monitored against actual outcomes from go-live.

The outcome

The sales cycle reduced from 94 days to 68 days in the first full quarter after go-live — a 28% improvement. Forecast accuracy improved from 58% to 81%. Sales managers moved back to Salesforce as their primary planning tool within the first month — not because they were asked to, but because the forecast had become reliable enough to use.

Manual entry across six systems was eliminated from day one of go-live. The SAP integration was delivered in eight weeks against a competitor estimate of six months, and it has operated without a production incident since deployment. Opportunity data flows automatically across all connected systems the moment it is entered in Salesforce. The system of record is now genuinely that — a single source of truth that the business relies on rather than maintains alongside its own shadow records.