Our Purpose

We live in a complex world where the old rules of strategy are no longer sufficient on their own.  To set a course for an enterprise (project, partnership or enterprise that is expected to last 3+ years without adjustment is to engage in a dangerous journey through an ever changing world.  To ensure that your enterprise can stand the test of time and achieve its purpose you must be able to understand your world.  The reason that these long-term strategies struggle is that they have been developed under the assumption that the world is linear and complicated, they rarely acknowledge complexity.

To test different strategies in the real world is incredibly costly, not only financially but also in reputation, energy and focus etc.  We have found the solution to be modelling and simulation.  By developing models and simulations of your physical assets, process, people, systems or devices, you are able to explore multiple strategies and futures before ever committing resources.  You can quickly identify what works, what doesn't and the most effective plans for practically any possible scenario, expected or unexpected.

You can collect and analyse real-time data from your people, systems and stakeholders, your decisions and compare the results against how your strategy was designed to perform.  This builds a knowledge base of unexpected impacts and feedback loops created by the actions made, enabling you to continuously improve your decision making process.

We equip organisations with the ability to understand their world through complex systems theory disciplines and tools. Utilising these the insights from complexity to design, execute and visualise strategies using technology and science, enterprises are able to navigate their complex world, achieve their purpose and make history. 

ThinkAxia is a complex systems consulting firm based in New Zealand which partners with universities and organisations to solve complex problems through innovative research, design, simulation and execution.

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Our Services

Our clients represent industries that range from defence to agriculture and everything in between. They call on us when they need support in understanding the complex world they are in and assistance in designing the systems that will enable them to execute their strategy. 

Our Services:

  • Enterprise systems engineering (ESE) - “… is defined as the application of SE principles, concepts, and methods to the planning, design, improvement, and operation of an enterprise. To enable more efficient and effective enterprise transformation, the enterprise needs to be looked at “as a system,” rather than merely as a collection of functions connected solely by information systems and shared facilities.“

    ( SEBOK: https://www.sebokwiki.org/wiki/Enterprise_Systems_Engineering )

    Russel Ackoff has characterised an enterprise as a 'purposeful system' composed of agents who choose both their goals and the means for accomplishing those goals. The variety of people, organisations, and their strategies is what creates the inherent complexity and non-determinism in an enterprise. ESE must account for the concerns, interests and objectives of these agents. (SEBOK)

    While a systems perspective is required for dealing with an enterprise, it is rarely achieved by those found in the middle of it. This is where ThinkAxia, and our partners are able to provide unique consultancy as advisors with a systems point of view to navigate their complexity.

  • System of Systems Engineering (SOSE) - “There are several definitions of system(s) of systems (SoS), some of which are dependent on the particularity of an application area. Maier (1998) postulated five key characteristics (not criteria) of SoS:

    • operational independence of component systems,

    • managerial independence of component systems,

    • geographical distribution,

    • emergent behavior,

    • and evolutionary development processes,

    and identified operational independence and managerial independence as the two principal distinguishing characteristics for applying the term 'systems-of-systems.' A system that does not exhibit these two characteristics is not considered a system-of-systems regardless of the complexity or geographic distribution of its components.

    In the Maier characterisation, emergence is noted as a common characteristic of SoS particularly in SoS composed of multiple large existing systems, based on the challenge (in time and resources) of subjecting all possible logical threads across the myriad functions, capabilities, and data of the systems in an SoS. There are risks associated with unexpected or unintended behavior resulting from combining systems that have individually complex behavior. These become serious in cases which safety, for example, is threatened through unintended interactions among the functions provided by multiple constituent systems in a SoS.“

    ( SEBOK: https://www.sebokwiki.org/wiki/Systems_of_Systems_(SoS) )


  • Model Based Systems Engineering (MBSE) and Software - We have partnered with the world leader in simulation and modelling, Anylogic to ensure you have the tools you need to design, model and simulate your system of systems enabling you to navigate your complex world and continually improve your decision making capabilities. These tools enable you to monitor and control your organisations, projects or any systems, anywhere, anytime.

    Why use modeling and simulation?


      Simulation modeling provides a safe way to test and explore different “what-if” scenarios. Make the right decision before making real-world changes.


      Virtual experiments with simulation models are less expensive and take less time than experiments with real assets.


      Simulation models can be animated in 2D/3D, allowing concepts and ideas to be more easily verified, communicated, and understood.


      Unlike spreadsheet- or solver-based analytics, simulation modeling allows observation of system behavior over time at any level of detail. E.g., you can check warehouse storage space utilisation at any given date.


      A simulation model can capture much more details than an analytical model, which provides for increased accuracy and more precise forecast.


      Uncertainty in operations’ time and outcome can be easily represented in simulation models, which allows you to measure risk and find more robust solutions.