Photo by wloven/iStock / Getty Images

Cultivating Greater Market Agility With System Dynamics Simulation

Several years ago, with the solar energy sector booming, a major supplier asked us to help them evaluate next moves. We used the system dynamics approach to model their rapidly evolving competitive landscape, and conduct what-if analysis of multiple scenarios. Result: better understanding of financial risks and new insights into alternative strategies.


  • Fast-growing markets, like the solar energy sector, present a multitude of challenges. Our client, a materials supplier in this rapidly evolving and complex industry, was faced with the advent of new technologies and new competitors at multiple points along the supply chain.
  • With solar module prices approaching grid parity in some markets, leading industry analysts were predicting continued growth in demand and prices for raw materials. That would present a golden opportunity – but what if the boom went bust?
  • The company needed to quickly explore a range of strategic options, including vertical integration, capital investments, and partnerships. How could it leverage its strengths and capture shifting profit opportunities?
  • Given the uncertainties, where should the company choose to play? And how would the answer be affected by changing dynamics in the solar supply chain?
Photo by wakila/iStock / Getty Images
There’s no one better at deeply and clearly understanding a system and how it produces value than Matt Mayberry. A few low key conversations - a few days invested - and Matt has unassumingly and quietly created a systems model that executives or front line teams can use in so many ways: testing new strategies, challenging old ones, or solving a wide range of business problems. Over the years, Matt’s models have helped change a lot of minds. He has redefined perceptions and challenged business realities — helping numerous clients overcome prevailing, long held “theories”, embrace facts, and commit to the REAL levers that drive the success for their businesses.
— Frank Mellon, President, Mellon Solutions

Project Goal

Use system dynamics simulation to assess strategic growth options in a high-potential, fast-changing market sector.

Our Approach

  • The situation faced by our client was an excellent match for a system dynamics approach to modeling. This methodology has been used since the 1950s to simulate complex, non-linear systems; its stocks-and-flows structure makes it easy to experiment with scenarios and outcomes, while keeping the overall model fairly simple.
  • Working closely with the client and our partner the McLean Group, WholeWorks built a unique model of the solar industry supply chain, from raw material to end product.
  • The model helped us focus on cause-and-effect structures that would drive future industry cycles. These included delays in capacity decisions and plant construction, which often led to overbuilding and excess capacity. (The figure at right is a representative model for a different business.)
  • We quickly explored a range of scenarios for a two-decade period, incorporating widely varying assumptions about future solar demand, raw material supply, possible new entrants, and the possibility of low-grade substitute materials affecting the market.
  • The model enabled WholeWorks and the client to project, in an iterative process, likely ranges for the Return on Investment of the strategic options under consideration. It also prompted fresh thinking about new alternative strategies.

A Portion of a Supply Chain Model Using a System Dynamics Approach

control Panel Used to Experiment With the Supply Chain Model Above


  • The simulation indicated that a boom-and-bust cycle was likely within 2-3 years. Record material prices were spurring a capacity-building race among new suppliers in Asia, with overcapacity and price collapse likely. This prompted critical thinking about avoiding risky investments.
  • The real-life scenario played out much as predicted: demand softened, new capacity came on line, and prices collapsed within two years. The client was better prepared to respond than they would have been, had they based their decision on analysts' predictions. 
  • The supply chain model helped the client better understand supply chain interdependencies - how competitive investment upstream can have ripple effects downstream, and vice versa. Better understanding of the system prompted deeper strategic thinking, and greater client confidence about its options in the face of uncertainty.
  • Our analysis also helped the client make a more informed decision about a new manufacturing facility by providing them with an expected range for the Return on Investment.