A. System Context Assessment Business Model B2B SaaS with annual subscription contracts. Operational Structure Sales Customer Success Implementation Engineering Support Value Flow Signed customer → Configure platform → Integrate systems → Train users → Customer goes live → Subscription revenue begins Current Performance 20 customers onboarded/month Average onboarding time: 30 days Customer satisfaction: 7.8/10 Engineering utilization: 98% Strategic Objective Increase onboarding throughput without increasing headcount. System Boundaries Starts when contract is signed and ends when the customer is fully live. Critical Assumptions Engineering performs every integration. Every customer follows the same onboarding path. All integrations require custom work. Performance Constraints Limited engineering capacity Large integration queue Sequential approval process System Performance Summary The onboarding system is constrained by engineering availability, creating delays that slow revenue recognition and reduce customer satisfaction. B. System Flow Analysis Step Capacity Waiting Time Resource Usage Customer Impact Contract Signed High 0 days Sales Positive Account Setup High 1 day Implementation Low Data Migration Medium 3 days Implementation Moderate Integration Low 10 days Engineering Very High User Training High 2 days Customer Success Medium Go-Live Medium 1 day Customer Success High Handoff High 0 days Support Low System Flow Map Sales ↓ Account Setup ↓ Data Migration ↓ Engineering Integration ← PRIMARY BOTTLENECK ↓ Training ↓ Go Live ↓ Customer Success C. Constraint Identification Primary Constraint Engineering Integration Team Constraint Type Capacity Constraint Why It Is the Constraint Highest queue length Longest processing time All projects wait here Nearly full utilization Every onboarding depends on this step Impact Revenue delayed Customer frustration Lower onboarding capacity Slower company growth D. Throughput Analysis Current Throughput: 20 customers/month Potential Capacity: 35 customers/month Lost Throughput: 15 customers/month Constraint Utilization: 98% Average Queue Before Constraint: 10 days Estimated Improvement After Optimization: Throughput increases to 32–35 customers/month Onboarding time reduced from 30 to 18 days E. Constraint Optimization Plan Step 1 – Identify Engineering integrations are limiting throughput. Step 2 – Exploit Prioritize highest-value integrations. Eliminate unnecessary customization. Standardize common integration templates. Reduce context switching. Step 3 – Subordinate Schedule implementation work around engineering capacity. Prevent projects from reaching engineering before prerequisites are complete. Pause low-priority customization requests. Step 4 – Elevate Hire one integration engineer. Introduce low-code integration tools. Automate repetitive configuration tasks. Create reusable integration libraries. Step 5 – Repeat Once engineering is no longer the constraint, identify the next limiting factor, such as customer training or implementation. F. Capacity Buffer & Flow Design Capacity Buffer Maintain approximately 20% spare engineering capacity for urgent requests. Time Buffer Reserve a 2-day buffer before go-live to handle unexpected issues. Inventory Buffer Keep a backlog of validated onboarding projects ready for engineering. Resource Balancing Shift administrative tasks from engineers to implementation specialists. Work Sequencing Prioritize: High-value enterprise customers Quick integrations Standard onboarding packages Complex custom implementations G. Throughput Performance Dashboard KPI Target Throughput Rate 35 customers/month Constraint Utilization 85–90% Lead Time Under 20 days Queue Time Under 3 days Flow Efficiency Above 75% Work in Progress Maximum 12 projects Review Cadence Daily: Engineering queue review Weekly: Throughput and bottleneck review Monthly: Constraint reassessment Quarterly: Capacity planning H. Constraint Health Scorecard Constraint Visibility: 9/10 Throughput: 6/10 Flow Stability: 7/10 Capacity Management: 5/10 Operational Agility: 7/10 Scalability: 6/10 Continuous Improvement: 8/10 Overall System Health Score 68/100 I. 90-Day Throughput Improvement Roadmap Phase 1 (Days 1–30): Constraint Identification Objective: Understand the bottleneck. Key Actions: Measure queue times. Track engineering workload. Map onboarding process. KPIs: Constraint utilization Queue length Risk: Incomplete operational data. Phase 2 (Days 31–60): Constraint Optimization Objective: Increase engineering throughput. Key Actions: Standardize integrations. Automate repetitive tasks. Prioritize high-impact work. KPIs: Integrations completed/week Average integration time Risk: Resistance to process changes. Phase 3 (Days 61–75): System Alignment Objective: Align upstream and downstream teams. Key Actions: Adjust onboarding schedules. Improve cross-functional communication. Reduce unnecessary work-in-progress. KPIs: Lead time Handoff delays Risk: Poor coordination between departments. Phase 4 (Days 76–90): Continuous Improvement Objective: Sustain gains and identify the next constraint. Key Actions: Review performance metrics. Reassess system bottlenecks. Launch ongoing improvement cycles. KPIs: Monthly throughput Customer satisfaction Revenue realization time Risk: Focusing on local optimization instead of system-wide flow. J. Executive Throughput Report System Performance Summary The primary limitation is engineering integration capacity. By focusing improvement efforts on this constraint, onboarding throughput can increase significantly without major increases in staffing. Top 10 Operational Insights Engineering is the system bottleneck. High utilization creates long queues. Standardization offers the biggest immediate gain. Custom work delays all customers. Flow is more important than resource utilization. Queue time exceeds processing time. Automation can reduce engineering effort. Work-in-progress should be limited. Faster onboarding accelerates revenue recognition. Continuous constraint management supports sustainable growth. Top 5 Constraints Engineering integration capacity Custom integration requests Sequential approvals Limited automation Engineering context switching Top 5 Throughput Improvements Standardize integrations Automate repetitive tasks Prioritize high-value work Balance workloads across teams Add engineering capacity where justified Top 5 Quick Wins Remove unnecessary customization. Introduce reusable integration templates. Limit work-in-progress. Improve engineering scheduling. Review the constraint daily. System Health Score 68/100 Most Important Constraint to Address First Engineering integration capacity, as it governs the throughput of the entire onboarding system. One Rule for All Future Operational Improvement Decisions Always improve the system's current constraint before optimizing any non-constrained activity, because increasing the efficiency of non-bottlenecks does not increase overall throughput.