Consulting
Complexity Assessment
For executive teams and project teams facing a difficult decision.
- Scope
- 1–2 workshops
- Result
- Causal map of the problem, HNFR analysis of the planned measure and prioritised options.
System Dynamics · Simulation · Digital Twins
Test your decision in a model before you make it in the real world.
Complexity Engineering applies System Dynamics and simulation to strategic decisions under uncertainty. We make feedback, delays and side effects visible and run scenarios with your data, together with your team.
That is why our address is systemdynamics.ch.
Approach
Complex problems behave differently than expected.
Measures that work in the short term often backfire months later. The cause is rarely a single mistake. It lies in the structure of the system, and that structure is what we model.
- Feedback
- Success reinforces itself until a limit takes hold. Knowing the loops tells you where a lever works.
- Delays
- Investment, hiring and behavioural change take months to show effect. The model shows when the effect arrives.
- Side effects
- With the HNFR analysis we examine the main, side, distant and feedback effects of a measure before it is implemented.
HNFR analysis by example
Measure20 % discount for new customers in the first year
- Main effectMore new contracts, the customer base grows faster.
- Side effectMargins fall. Existing customers feel disadvantaged and ask for a discount too.
- Distant effectCompetitors follow suit and price levels drop across the market.
- Feedback effectCustomers get used to discounts and leave when they end. Churn rises and forces new discounts.
A conventional risk analysis asks what can go wrong. The HNFR analysis traces how a measure acts through other actors and over time back on your own goal.
Offers
Four ways to start working with us.
Each offer has a clear scope and a tangible result. The complexity assessment is a good starting point when the question is still open.
Consulting
Strategic Simulation Study
For investment, growth and transformation decisions under high uncertainty.
- Scope
- 4–8 weeks
- Result
- Calibrated simulation model, scenario comparison and a basis for decisions by the executive or supervisory board.
Software
Decision Simulator
For teams that want to run scenarios themselves on a regular basis.
- Scope
- depends on project
- Result
- Interactive browser simulator with your data, including handover and introduction.
Training
System Dynamics Training
For specialists and managers who want to structure complex problems themselves.
- Scope
- 1–3 days, in-house
- Result
- Systems thinking, causal loop diagrams, modelling with Vensim or Stella and HNFR analysis, with practice models.
Fields of application
- Business models and growth
- Energy and infrastructure
- Circular economy and resources
- Cities and urban systems
- Health and public sector
- Capacity and supply chains
Examples
How a model supports a concrete decision.
Three typical questions from our fields of application. They show the path from the question through the model to the result.
Integrated energy systems
- Question
- Is a battery storage system worthwhile for our existing PV plant, and from when?
- Model
- Energy flows, storage capacity, tariffs, investment and operating costs over 20 years.
- Result
- Comparison of investment options with payback period and sensitivity to electricity prices.
Circular business models
- Question
- Does a take-back and refurbishment model pay off for our products?
- Model
- Product stock in the market, return rates, refurbishment capacity, cost and material flows.
- Result
- Break-even point, critical return rate and required capacity.
Strategic decision simulators
- Question
- How fast can we grow without putting delivery and quality at risk?
- Model
- Demand, capacity build-up with delays, staff, quality and customer satisfaction.
- Result
- A simulator the leadership team uses to play through and compare growth paths.
Simulator
What happens if churn falls but advertising is cut?
A small model of the kind we build for clients, greatly simplified: a new offering penetrates a market of 10,000 potential customers. Pick a scenario or move the sliders and compare with the base scenario.
Scenarios
Share of non-customers who buy each month because of advertising
Strength of word of mouth per month
Share of customers who leave each month
Customers after 5 years9'317
Peak monthMonth 24
New customers in peak month400
Your scenarioBase scenario
Adoption = (p + q · K / N) · (N − K) Churn = c · K
Would you like to test scenarios like these with your own company data?
Discuss a decision simulator →Model assumptions and limits
- The time unit is one month, the horizon is 60 months.
- The customer base K is integrated with the Euler method and a step size of 0.25 months: K(t+dt) = K(t) + dt · (adoption − churn).
- Adoption follows the Bass diffusion model: advertising reaches the share p of non-customers, word of mouth acts in proportion to the customer share K/N.
- The market potential N = 10,000 is fixed. Customers who leave rejoin the market potential.
- Prices, competition, capacity limits and seasonality are not included. The parameters are example values and not calibrated.
Example model (Bass diffusion with churn). In client projects, models are calibrated with real data.
Process
From problem to tool in five steps.
Frame the problem
Capture goals, time horizon and the observed behaviour over time.
Map the structure
Develop the cause-and-effect relationships as a diagram together with your team.
Build and test the model
Set up a quantitative simulation model, calibrate it with data and validate it.
Test scenarios
Play through strategies and measures, compare risks and levers.
Hand over
Simulator, report and training, so your team can use the model on its own.
About
Research and practice combined.
Prof. Dr. Stefan N. Groesser
Founder, Complexity Engineering
Stefan N. Groesser has researched, taught and consulted on system dynamics and simulation for many years. He is a professor at Bern University of Applied Sciences, where he leads the Digital Twins and Decision Analytics area.
Complexity Engineering brings these methods to companies and public administrations: with models that reflect current research and solutions that work in daily practice.
Publications and research ↗Contact
Tell us about your question.
A first conversation is free of obligation. Briefly describe your situation and we will get back to you within two working days.
- Complexity Engineering ↗
Publications & resources
Books from our imprint.
Erfolgskompetenzen aufbauen · Volume 1
Sich selbst führen
Dein Arbeitsbuch für Ausbildung und Studium
A workbook on self-leadership: sleep and exercise, values and meaning, motivation, habits, dealing with emotions and initiative. A personal development project with a measurable target runs through the whole book. (In German.)
Volume 2 “Arbeiten und lernen” (working and learning) appears in 2026, volume 3 “Mit anderen wirken” (working with others) is in progress.