Business Modelling with Simulation
Computer-based simulation provides a powerful way to do “what-if” analysis to forecast how a complex system (for example, a factory, hospital, airline network, major project or supply chain) will perform if there is a change in operating policy or organisation. It can also be used to understand the impact of disruptive events, such as natural disasters, pandemics or breakdowns in communication or transportation infrastructure, and how these impacts can best be mitigated.
Scenario thinking contains key components to promote the effective exchange of opinions and beliefs within a management team. The construction of multiple futures holds open airtime for differing opinions about the nature of the future, and provides a forum for the debate, questioning, and synthesis of complementary, contrasting, and conflicting viewpoints. Essentially, scenario interventions within organisations construct multiple frames of future states of the external world, only some of which may be well-aligned with current strategy. Scenario thinking can facilitate “vigilance” in strategic thinking – in that alternative futures are thought through and strategic options can subsequently be evaluated against these futures. The process of scenario thinking enhances the evaluation and integration of information, and promotes contingency planning for the unfolding of both favourable and unfavourable futures.
Operations management provides a range of analytical tools to help managers create competitive advantage. Over a number of years by combining academic research with industrial application the operations management team have developed robust techniques for; developing operations strategy, building performance management systems and designing operational business models that can be used within any industrial sector.
Strategy Mapping and Performance Management
The development of a robust operations strategy to guide your business is critical to success. Accurate flow-down of corporate objectives to all parts of the business is the key to this. The Strategy Mapping methodology does two things. First it ensures the correct decisions are made in building your operations strategy by linking corporate goals with day-to-day activity, and second, it creates a robust baseline for the construction of a practical performance management and measurement system.
Understanding all aspects of an organisation’s activity is crucial to developing your operational model and the capabilities that support it. Combining Product Lifecycle Management Techniques and Value Chain Analysis provides a useful set of tools that will allow a deep analysis of your operation, the output of which will inform decision-making at all levels from the strategic to the detail. This decision-making will help to ensure you build and deploy the optimum operational model and cultivate the correct capabilities to support it. This operational foundation will optimise efficiency and productivity
Business Modelling with Optimisation
It allows urban delivery companies to develop their routing strategies, doctors to create most effective treatment plans for individual cancer patients, manufacturers to schedule their operations to meet their orders on time, governments to evacuate disaster areas quickly, and much more.
Risk and Uncertainty
Making decisions in an uncertain world is inevitable for all organisations. In IDeA, we develop and utilise both qualitative and quantitative modelling approaches to get to the heart of challenging problems. Utilising a mixture of data and judgement, we structure problems to understand the uncertainties that are impacting on decisions and what the consequences are of certain actions. Our approach forces decision makers to articulate their underlying challenges and focus our modelling on the decision-making challenge – not the underlying technology.
We have experience of working with a range of organisations including Scottish Power, SSE, Rolls Royce, dstl, etc. Examples of projects we have worked on include modelling the reliability growth of complex assets, assessing the risk on major projects, fusing engineering knowledge and data surrounding maintenance operations, modelling the risk of different supply networks, and prognostics modelling for complex assets.