Engagement Snapshot

  • Client: Braydon Farms (floral operation)
  • Duration: Multi-week distribution planning engagement with ongoing optimization
  • Team: Dr. Duan, Mrs. Amy Hu, and distribution planning specialists

Challenge

A new floral operation needed to develop an efficient distribution plan for delivering products to the Marvin Stores chain. Without an optimized approach, travel time and expenses threatened profitability and operational sustainability.

Our Approach

  1. Distribution Network Analysis – Assessed current delivery routes, product volumes, and Marvin Stores locations to identify optimization opportunities.
  2. Route Optimization Model – Developed a distribution plan that significantly reduced travel time and expenses while maintaining delivery reliability.
  3. Implementation Support – Incorporated the distribution plan into operational workflows with documentation and training.
  4. Ongoing Optimization – Established framework for tweaking and adjusting the system based on business growth recommendations.

Outcomes

  • Significantly reduced travel time and distribution expenses to the Marvin Stores chain.
  • Successfully incorporated distribution plan into daily operations.
  • Established foundation for scalable distribution as business grows.
  • Ongoing study framework enables continuous improvement based on operational data.

Client Testimonial

“On behalf of my wife and I, we would like to sincerely thank Dr. Duan, Mrs. Amy Hu, and you for the time you spent developing a distribution plan for our new floral operation. We have incorporated it into our operation and it appears to have significantly reduced our travel time and expenses in distribution our products to the Marvin Stores chain. Hopefully this will be an on-going study and we will be able to ‘tweak’ or alter the system based on your recommendations as our business grows. Again, thank you for your help. It is very much appreciated.”

— Stephen (Brad) Bradshaw Garrott, Owner, Braydon Farms

Ready to optimize your distribution operations? Schedule a consultation.

Engagement Snapshot

  • Client: Enterprise SaaS platform (Series E)
  • Duration: 12-week modernization sprint + quarterly advisory
  • Team: Engagement lead, analytics engineer, revenue operations specialist, design researcher

Challenge

The executive team ran three overlapping forecast processes—finance, product usage, and marketing attribution—leading to inconsistent board updates, stalled investments, and eroding stakeholder confidence.

Our Approach

  1. Diagnostic Assessment – Mapped data lineage across CRM, billing, telemetry, and campaign tooling; quantified accuracy gaps and cycle time.
  2. Unified Data Model – Built a semantic layer aligning ARR, NRR, pipeline, and adoption metrics; automated QA and reconciliation tasks.
  3. Scenario Planning Workbench – Delivered Bayesian forecast models with narrative outputs tailored for finance, product, and GTM leaders.
  4. Change Enablement – Facilitated cadence redesign, executive dashboards, and training to embed the new forecast process.

Outcomes

  • Forecast accuracy improved 18% in two quarters while reducing manual spreadsheet work by 70%.
  • Board reporting shifted from defensive to proactive scenario planning.
  • Finance, product, and marketing adopted a shared prioritization framework anchored in the new data model.

Ready to modernize your forecasting discipline? Book a working session.