How Premier Pet went from one week to 3 minutes per scenario simulation and scaled operations without growing the planning team
Premier Pet grew fast: new plants, more lines, more products, more complexity. It moved from a controllable context to an operation with over 500 SKUs, hundreds of raw materials and multiple plants and DCs. The problem was no longer production: it was planning.
Highlight results
Indicators observed after integrating planning, scheduling and distribution into a single model connected to the ERP and factory systems.
"During the pandemic, demand grew exponentially and that was one of the reasons we accelerated the opening of the new plant in Paraná. With new plants, new lines and new products, Excel has a certain limitation. We needed a complete solution: planning, scheduling and DC replenishment, all together."
The challenge
The planning model was not keeping up with growth. There was heavy reliance on Excel, manual processes, low simulation capacity and slow decisions. Generating a single scenario could consume an entire week of work, which fully constrained decision-making and kept the team busy operating the plan instead of deciding the plan.
What drove the change
The need was not only to improve. It was to enable growth. The team itself recognized the limits of the previous model, and two objectives guided the decision: eliminate manual work and make the team more analytical, removing spreadsheets from the center of operations.
The solution
Premier Pet structured planning across three connected layers: master planning with NPLAN, scheduling with APS and distribution with DRP. All integrated with the ERP and factory systems.
The flow became unified: demand → scenario → decision → orders → scheduling → execution → feedback. No rework and no parallel spreadsheets.
What changed in practice
Simulation stopped being a bottleneck
Before, it was one scenario per week with heavy manual effort. Today, multiple scenarios are generated in minutes, enabling alternative comparison and raising decision quality.
Planning became automatic
Before, the master plan was built in Excel and orders were entered manually. Now, the plan is generated automatically and orders are created in seconds.
Purchasing stopped depending on intuition
Before, purchasing decisions were based on history and perception. Today, they are driven by the real plan, with exact visibility of what needs to be bought and in which horizon.
Structured inventory policy
Before, the policy was undefined and operations could even stop due to excess stock. Today, the policy is structured by ABC curve and capacity, preventing stoppages and tuning coverage to each item profile.
Scheduling stopped creating bottlenecks
Before, the flow was decided by shop-floor operations and bottlenecks appeared almost every day, with stoppages due to silo or capacity shortages. Today, the flow is automatically optimized by the APS, ensuring continuity.
"Before APS, operations decided the flow between silos and bagging machines on the shop floor. Almost every day we had some kind of bottleneck. Sometimes the line stopped because there was no silo available to receive the product. Today the system ensures upfront that the flow will be followed in the most optimized way possible."
Replanning stopped being manual
Before, any stop required rebuilding the plan in Excel. Today, replanning is fast and structured, keeping coherence between demand, materials, capacity and distribution.
Scale without growing the team
Operations grew significantly: more plants, more lines, more SKUs and more raw materials. The planning team, however, did not have to grow at the same pace, because the nature of the work changed.
"With new plants, new lines and new products, Excel reached its limit. We had to keep up with growth and could not fail to deliver. The work is the same, but today we are much more analytical than operational."
Real visibility to decide
Before, decisions were made without seeing the full impact. Today, the team tracks inventory behavior over time, identifies excess and shortage, evaluates line idleness and anticipates problems.
This visibility is used in practice, including aligning maintenance at the best moment, identifying windows with the lowest impact on the production plan.
"Today I can see that the week of March 26th has an idle window on the line. Then I go to maintenance and say: this is the ideal week for you to act. Before, this visibility simply did not exist."
Before vs after
- Excel as the planning base
- 1 scenario at a time
- 1 week to simulate
- Purchasing by history
- Undefined inventory policy
- Frequent bottlenecks
- Manual replanning
- Three-layer integrated planning
- Multiple scenarios compared
- 3 minutes per simulation
- Plan-driven purchasing
- Policy structured by curve and capacity
- Flow optimized by APS
- Fast and structured replanning
The key takeaway
Premier Pet did not just gain efficiency. It gained decision capability. It moved from an effort-based model to a simulation-based model, which allows growing with complexity without losing control.
Want to scale operations without growing the planning team?
Talk to the NPLAN team about integrating planning, scheduling and distribution into a single model connected to your ERP.