Systems thinking is a disciplined way of understanding interdependencies within systems.

At io we use systems thinking to ensure all elements of projects work together to achieve the objectives of the whole. This mindset underpins everything io does; whether it is creating dynamic models and simulations of projects to optimise decisions; protecting value throughout the project lifecycle; or starting projects with the end in mind.

This systems approach is aligned with io's Decision Quality (DQ) framework, where the content of the model is just detailed enough to yield insight appropriate relative to the phase of the project and no more than that. We refer to this as precise simplicity. As a project transitions through the lifecycle more detail is required, and the model is evolved accordingly. This is best done through io's Agile approach, where a base model is established and additional functionality is explored in parallel side studies called sprints; as these sprints yield valuable insight, they are layered into the model such that it evolves as the team's system understanding enhances. This allows continual testing of decisions and ensures value created is protected through the life of the project.

By applying Systems Thinking io establishes a holistic understanding of the interdependent sub-systems and equipment that create a system, and through creation of a dynamic model of this system we can run simulations. Through these simulations, we can analyse the behaviour of the system under different scenarios, allowing the leverage points for system optimisation to be rapidly identified and the negative or unexpected impacts of these optimisations to be understood; allowing trade off decisions to be taken with greater understanding and certainty. The systems models that io develops incorporate technical, economic and regulatory factors, meaning the model is not only used for technical optimisation but can be used as a decision support tool, testing different economic strategies and strategic policies for a project, ensuring that it is as effective as possible in the context of a client's full suite of value drivers.

The values around which the system model optimises the design are critical to ensure the correct decisions are made, as it is against these values that the trade-offs are assessed. io will conduct a framing workshop to identify the value drivers as part of the mobilisation, kick off and framing phase of the project. This will be done by using the Analytic Hierarchy Process (AHP). AHP is a structured decision support technique developed by Thomas Saaty in the 1970s and is particularly useful for group decision making. AHP measurement is through pairwise comparisons, where the project is decomposed into a hierarchy of value drivers that are then evaluated against one another, and relies on the derivation of priority scales which measure intangibles in relative terms. The judgements may be inconsistent, and how to measure inconsistency and improve the judgements, wherever possible to obtain better consistency is a concern of AHP. Accordingly, the AHP technique is used to facilitate reaching agreement on a project’s value drivers through decision dialogue.

How io applies systems modelling

By working with a systems mindset, we capture the project's value drivers, translate those drivers into requirements and model the entire project system. This can be purely a technical model; however, the real value lies in the breadth of experience and diverse backgrounds of the team, who develop a techno-economic model encompassing the holistic variables, which can affect the performance of a project in the context of value drivers. This approach allows io to create a dynamic model of a project, which is resilient to macro changes, such as commodity price fluctuations and reservoir uncertainties, and micro changes, such as component performance or specification changes. The advantage of this model is that a vast array of options can be simulated, facilitating rapid decision making. Our systems dynamics model provides a holistic and integrated view of a project from a single dashboard.

The tool helps decision makers to:

• understand the interdependencies of a project and the impact on value through sensitivity analysis

• indicate the likely optimum solution to a development problem

• protect the value of this solution through the project lifecycle

By interpolating between data points, the tool can quickly help decision makers understand the implications of multiple different combinations of assumptions.