Demand & orders
Customer Orders
- Queue
- Utilisation
- customer-orders:primary Idle
Trend
- Planning
Business Process Optimization · Dynamic Modeling
Better business decisions through Dynamic Modeling.
We help organizations understand how complex business systems behave before investments or operational changes are implemented. Compare scenarios, quantify business impact and identify the strongest decision instead of relying on isolated assumptions.
16
anonymised applications
Documented decision questions from manufacturing, supply chains and service operations.
End-to-end
rather than isolated optimisation
Dependencies, queues, resources and trade-offs are considered together.
Scenarios
compared before implementation
Alternatives are tested in the model before time and capital are committed.
Anonymised application portfolio
Dynamic Modeling in Practice
Dynamic Modeling is a business decision platform—not a modeling tool. These examples show the range of documented decision questions and model outputs, not promised or verified client results.
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16 anonymised applications
- Areas
Production-site capacity and performance
- Business challenge
- How do capacity alternatives affect production volume, margin, unit cost and lead time across the whole system?
- Business outcome tested
- The model compared capacity scenarios and made the interactions between volume, process flow, cost and performance visible.
Typical KPIs
- Areas
Production routing and capacity decisions
- Business challenge
- Which combination of process route, speed, availability, skills and investment supports the most robust production flow?
- Business outcome tested
- The scenarios set routing and capacity levers against their effects on responsiveness, resource use and financial performance.
Typical KPIs
- Areas
Inventory and investment decisions with constrained storage
- Business challenge
- How should inventory, push/pull rules and the timing of additional capacity interact when storage is constrained?
- Business outcome tested
- The model compared replenishment, inventory and investment scenarios and showed their effects on stock, utilisation and delivery flow.
Typical KPIs
- Areas
Assembly bottleneck and routing analysis
- Business challenge
- Where do resources constrain assembly flow, and in which sequence should process or capacity alternatives be tested?
- Business outcome tested
- The model located constraints, compared solution sequences and made the associated resource loading transparent.
Typical KPIs
- Areas
Constraint-removal sequence
- Business challenge
- Which constraint should be addressed first so that a local change actually supports system flow?
- Business outcome tested
- The simulation made the constraint sequence visible and provided a shared decision basis for prioritising interventions.
Typical KPIs
- Areas
Warehouse and supply-concept selection
- Business challenge
- Which push/pull and supply concept fits the process dependencies, system support and required response time?
- Business outcome tested
- The model compared logistics concepts, exposed dependencies and structured the decision about further implementation.
Typical KPIs
- Areas
Operating model for port and fuel logistics
- Business challenge
- How do unloading, stockpiles, equipment, ordering rules and staffing respond to fluctuating demand and disruption?
- Business outcome tested
- The model quantified operational drivers, located a constraint and compared availability, ordering, staffing and outsourcing scenarios.
Typical KPIs
- Areas
Production and supply-chain responsiveness
- Business challenge
- Which production and inventory rules support short response times across different demand and product structures?
- Business outcome tested
- The scenarios compared network, production and inventory rules and prepared a qualitative steering recommendation.
Typical KPIs
- Areas
From trouble ticket to resolution
- Business challenge
- How do demand, support skills, handoffs and priority rules affect response time and service-target performance?
- Business outcome tested
- The model connected customer requests, skills and handoffs into an end-to-end service flow and compared alternative operating modes.
Typical KPIs
- Areas
Staffing for technical incidents
- Business challenge
- Which staffing and process configuration supports service targets under a variable load of technical incidents?
- Business outcome tested
- The simulation compared staffing and incident flow using consistent service, time and cost indicators.
Typical KPIs
- Areas
Central or local data-centre service model
- Business challenge
- How do central and local service configurations compare across cost, utilisation, response time and service quality?
- Business outcome tested
- The model made cross-organisational trade-offs measurable and compared alternative service and responsibility mixes.
Typical KPIs
- Areas
Workplace-device lifecycle
- Business challenge
- Which procurement, replacement and support rules balance availability, capital requirements, cost and lead time?
- Business outcome tested
- The scenarios compared lifecycle policies from a shared cost, availability and process perspective.
Typical KPIs
- Areas
Record-to-report productivity
- Business challenge
- How do automation, work allocation and staffing change the flow of recurring HR reporting?
- Business outcome tested
- The model tested automation and staffing scenarios and made their relationship with time, utilisation and service targets visible.
Typical KPIs
- Areas
Customer flow and staffing in retail
- Business challenge
- How do customer arrivals, waiting, staffing and issue resolution affect walkouts and service performance?
- Business outcome tested
- The simulation connected customer flow with staffing and compared operational changes through consistent service indicators.
Typical KPIs
- Areas
Fibre rollout within a fixed budget
- Business challenge
- Which sequence, skills, contracts and resources support a predictable rollout within the budget envelope?
- Business outcome tested
- The model compared rollout sequences and resource decisions together with budget, speed and quality cost.
Typical KPIs
- Areas
Bottleneck and sequence analysis in network rollout
- Business challenge
- Where do process, skills or contracts constrain rollout, and which intervention sequence supports the overall plan?
- Business outcome tested
- The simulation located rollout constraints and compared sequencing, skills and contract alternatives.
Typical KPIs
Interactive process simulation
See how one decision moves through the entire system.
This simplified digital twin of a chemical production process makes demand, capacity, queues and trade-offs visible. Change an assumption and watch performance and the bottleneck move before investing in the real operation.
Educational model with illustrative values—not a forecast and not client data.
Compare scenarios
Test decision alternatives side by side.
The current state and two alternatives use the same logic. Adjust the alternatives and compare the consequences, not only one metric.
Change the business assumptions
Every control changes the same connected model draft. Changes are marked and recalculated only when you choose “Simulate scenario”.
Fixed comparison baseline
Simulation run
Ready- Active
- 0
- Completed
- 0
- Blocked
- 0
- Discarded
- 0
End-to-end system map
Orders, material, resources, buffers and deliveries from the same calculated simulation run.
Current bottleneck
- Idle
- Idle
Planning
Production Planning
- Queue
- Utilisation
- Planning gate Idle
Trend
- Material
- Idle
Procurement & raw material
Raw Material
- Queue
- Utilisation
- Level
- Raw-material feed A Idle
- Raw-material feed B Idle
Trend
- Reactor
- Idle
Parallel production
Mixing Reactor
- Queue
- Utilisation
- MP reactor Idle
Trend
- Tanks
- Idle
Buffers & tanks
Storage Tanks
- Queue
- Utilisation
- Level
- Tank V1 Idle
Trend
- Packaging
- Idle
Packaging
Packaging
- Queue
- Utilisation
- Packaging LTC2 Idle
- Packaging LTC4 Idle
Trend
- Warehouse
- Idle
Finished-goods warehouse
Warehouse
- Queue
- Utilisation
- Level
- Warehouse handling Idle
Trend
- Shipping
- Idle
Shipping & customer
Shipping
- Queue
- Utilisation
- Shipping dock A Idle
- Shipping dock B Idle
Trend
- Customer
- Idle
Shipping & customer
Customer
- Queue
- Utilisation
- customer:primary Idle
Trend
- Customer Orders. Idle. Queue: 0 / 48. Utilisation: 0%.
- customer-orders:primary. Idle.
- Production Planning. Idle. Queue: 0 / 48. Utilisation: 0%.
- Planning gate. Idle.
- Raw Material. Idle. Queue: 0 / 72. Level: 0 / 72. Utilisation: 0%.
- Raw-material feed A. Idle.
- Raw-material feed B. Idle.
- Mixing Reactor. Idle. Queue: 0 / 40. Utilisation: 0%.
- MP reactor. Idle.
- Storage Tanks. Idle. Queue: 0 / 60. Level: 0 / 60. Utilisation: 0%.
- Tank V1. Idle.
- Packaging. Idle. Queue: 0 / 40. Utilisation: 0%.
- Packaging LTC2. Idle.
- Packaging LTC4. Idle.
- Warehouse. Idle. Queue: 0 / 84. Level: 0 / 84. Utilisation: 0%.
- Warehouse handling. Idle.
- Shipping. Idle. Queue: 0 / 40. Utilisation: 0%.
- Shipping dock A. Idle.
- Shipping dock B. Idle.
- Customer. Idle. Queue: 0 / 48. Utilisation: 0%.
- customer:primary. Idle.
One change, multiple consequences.
Every KPI is calculated from the same simplified model, revealing impact and trade-offs together.
- Throughput
- 0.0 batches/day
- Lead Time
- —
- Work In Progress
- 0 batches
- Machine Utilization
- 0 %
- Service Level
- —
- Variable cost per unit
- —
- EBIT
- 0 k€/month
- Bottleneck Location
- —
- We do not guess.
- We simulate before you invest.
- Test alternative decisions before implementing them.
- Identify bottlenecks before they become expensive.
- Understand system behaviour instead of optimizing isolated activities.
From modelling into engineering
Validate automation potential across the entire system
Dynamic Modeling shows how automation affects throughput, lead time, WIP, cost and bottlenecks before engineering and investment decisions are made.
- 01
- 02
- 03
- 04
- 05
Methodology
Six steps from business question to recommendation.
The method keeps objectives, assumptions and alternatives traceable. Each step sharpens the decision that has to be made before implementation.
Step 01
Preparation
Collect available process knowledge and data, involve the right contributors and define the operating context.
Step 02
Define Objectives
Name the management decision, the intended outcome and the criteria used to compare scenarios.
Step 03
Build Baseline Model
Represent the current process and its assumptions so the starting point can be reviewed together.
Step 04
Create Target Scenarios
Describe credible changes to process, demand, capacity or investment for comparison.
Step 05
Simulate Alternatives
Run the scenarios through the model and examine bottlenecks, waiting times, performance and trade-offs.
Step 06
Recommend Best Solution
Compare the evidence against the agreed objectives and recommend the strongest route forward.
Decision gate
The recommendation creates a clear handoff into implementation.
A selected target scenario becomes the basis for project, process and product management, Digital Delivery and subsequent operations. If the evidence is not yet sufficient, the scenario can be revised before implementation cost is committed.
Engagement stages
Start at the level your question needs.
Problem Check, Model Blueprint and Modeling Sprint build on one another. The right entry point depends on how clearly the problem, objective and available data are already described.
Problem Check
- Purpose
- Clarify the operational problem, the decision at stake and whether Dynamic Modeling is the right next step.
- Result
- A focused problem statement and a recommendation for the next engagement stage.
Model Blueprint
- Purpose
- Define objectives, model boundaries, available inputs and the scenarios that need to be compared.
- Result
- An agreed blueprint for the baseline model, target scenarios and simulation work.
Modeling Sprint
- Purpose
- Build the baseline, create target scenarios, simulate alternatives and prepare the management recommendation.
- Result
- A comparison of alternatives and a recommendation for the implementation decision.
From idea to delivery
Validate before implementation begins.
Ideation shapes the concept. Business Process Optimization tests its behaviour. Project, Process & Product Management governs the decision into execution, and Digital Delivery builds the chosen target state.
Four connected stages: Ideation & Concept Development, Business Process Optimization using Dynamic Modeling, Project, Process & Product Management and Digital Delivery.
Ideation & Innovation
Business Process Optimization
Project, Process & Product Management
Digital Delivery
One partner across the lifecycle
The model ends with a decision delivery can use.
Documented objectives, assumptions and target scenarios become the decision basis for governance and delivery. The complete Somos-Co lifecycle then continues through operations, hosting and continuous improvement.
Choose your starting point
Bring us the business question—not a software specification.
Together, we will determine whether a Problem Check, Model Blueprint or Modeling Sprint is the right next move.