The uploaded interview model uses a $2M net-new services target. The calculator below keeps that as the starting case, but makes the assumptions editable because the real quota, revenue credit and historical win rates belong to Baker Tilly.
Change the assumptions. The point is not to defend one number; it is to show how I would manage the territory mathematically once internal data is available.
Annual signed SOWs at the selected average.
Target divided by selected qualified win rate.
Approximate count if each qualified pursuit carries the selected average value.
Useful pacing metric, not a recommendation to force monthly closes.
The starting model gives more weight to Oracle field relationships and Baker Tilly's internal network, with targeted outbound used for high-conviction forcing events. The mix should be recalibrated from actual historical source conversion.
Territory AEs, Channel Managers, Alliance Managers and joint competitive pursuits. Highest leverage when Baker Tilly helps software velocity.
Audit, tax, transactions, PE and advisory relationships. Warm access with professional-services trust already established.
Only signal-backed accounts with a documented reason now: carve-out, CFO, funding, system sunset, audit/control pain or multi-entity growth.
Baker Tilly explicitly expects AI-driven prospect research, scoring, sequencing and proposal support. I would use the same architecture I have already built for commercial sourcing: APIs and public signals create a better human decision, then CRM captures what actually happened.
Funding, M&A, CFO hires, ERP sunsets, events, webinar activity and internal referral signals.
Company, subsidiary, sponsor, finance leaders, Oracle territory and Baker Tilly relationship context.
Account IQ: fit, trigger, complexity, reachability and confidence.
Why now, business hypothesis, discovery questions, proof asset and knowledge gaps.
Human-approved email / call / referral / Oracle co-sell with a defined next action.
CRM stage, objections, win/loss, cycle time and source economics recalibrate the model.
Used evidence-based re-scoring instead of trusting stale CRM priority.
Cleaned commercial universe after reclassification.
Why now, participants, scope, confidence and next action.
Example of turning external datasets into practical commercial research infrastructure.
This is an initial cadence to test, not a permanent productivity quota.
Target only researched inflection accounts. Goal: roughly three real first conversations, then inspect why the rest did not convert.
Keep shared opportunities current, find reciprocal whitespace and register new partner-sourced motions promptly.
Industry-team education, live client-signal review and fast feedback to the originating partner.
The first quarter should end with more than training completion: it should establish working internal and Oracle relationships, qualified pursuits, and a repeatable operating cadence.
The goal is not to look busy. It is to create opportunities the practice wants to pursue, make internal and Oracle partners want to work with me again, and maintain CRM evidence strong enough that leadership can make staffing decisions from the forecast.