Central Team, Regional Demands
Summit Logistics Software has 600 employees and sells in North America, EMEA, and APAC. A central RevOps team of five owns forecasting, CRM administration, sales compensation analytics, and executive reporting. Each region has one embedded sales operations analyst who reports to the regional sales VP. Regional leaders say central is too slow; central says regions bypass standard processes and build local spreadsheets. The request backlog is 60 days, and the top three requests from each region are different. Headcount is frozen, but the CRO can reallocate two existing analysts. The central team is spending 45% of its time on ad hoc reporting and 20% on CRM tickets. A recent forecast review found that each region uses a different commit definition. The CRO wants a structure that improves speed without losing standards.
1. Diagnose the operating model problem. What is central versus embedded actually for, and what decisions should sit where?
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The problem is not headcount; it is unclear decision rights. Central is best for standards, shared infrastructure, forecasting methodology, compensation analytics, and executive reporting. Embedded is best for regional context, adoption, deal inspection, and local sales leader support. Right now, central is doing ad hoc reporting that should be self-service or embedded, and regions are building local spreadsheets because central is slow and the standards do not fit local go-to-market. The 60-day backlog and different top-three requests confirm a prioritization problem, not just capacity. The different commit definitions are a standards failure: that must be central.
The fix is a split. Central owns the forecast definition, CRM data model, and global dashboards. Embedded owns regional adoption, training, and first-line analysis. Create a single intake with a scoring model: revenue impact, number of regions affected, risk, and effort. Central keeps a 70/20/10 capacity rule: 70% standards and shared services, 20% regional enablement, 10% innovation. Embedded analysts get a dotted line to central for standards and a solid line to the regional VP for execution. This preserves speed without sacrificing a common language.
2. Propose a revised structure and governance model using the two reallocated analysts. Include a request intake and prioritization mechanism.
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Use the two reallocated analysts to create a shared services pod. One focuses on forecasting and reporting standards; the other focuses on CRM, routing, and request triage. Do not distribute them one per region; that recreates fragmentation. Instead, assign each as a domain lead with regional coverage. Regional embedded analysts remain the local face.
Establish a weekly intake council with one representative per region and central. Score requests on strategic alignment, revenue impact, urgency, and effort. Publish the top 10 and the not-now list. Set a service-level agreement for requests: 48-hour triage, 10-day delivery for small changes, and a quarterly roadmap for larger work. Central publishes the forecast commit definition and a single dashboard. Regions can add local views but not local definitions. Give embedded analysts explicit authority to resolve Tier 1 requests without central approval. Escalate only cross-region conflicts. This uses the two analysts to remove bottlenecks, not to add another layer.
3. How would you measure whether the new model is working within two quarters?
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Measure three things: speed, standards, and outcomes. Speed: median request cycle time, backlog age, and percentage of Tier 1 requests resolved by embedded analysts. Standards: forecast commit definition adoption, number of local spreadsheet variants, and CRM data completeness. Outcomes: forecast accuracy, win rate, and sales cycle by region. Run a quarterly operating review with the CRO and regional VPs.
Also track employee experience with a short pulse survey on whether central is responsive and whether regions feel heard. Avoid measuring only ticket volume; that rewards activity. Within two quarters, aim for a 50% reduction in backlog age, one forecast definition used in all regions, and measurable improvement in forecast accuracy. If regions still bypass the model, examine whether the intake scoring is excluding legitimate local needs. Be willing to adjust the split. The goal is a learning operating model, not a perfect org chart.