Decision Logic is geared to simulate complex, process-based problems in sufficient detail to produce evidence-based findings and recommendations that once implemented will add significant value to our clients.  One of our core capabilities in this regard is analytical simulation applied within a proven process.  The term analytical simulation is more generally the use of a simulation technology for the purposes of analysis (vice using simulation for training or other purposes).  In our case we employ a simulation development environment that lets us closely represent the complexities associated with a range of underlying systems, like training systems, fleet management processes, maintenance facilities, supply chains etc.

Our analytical simulation capabilities include important simulation methodologies like Monte Carlo simulation (the use of definable random variables) to ensure we account for risk and uncertainty in values, particularly as they propagate over time.  Our environment lets us represent items or "things" moving through complex systems, flow or "stuff" moving through pipelines or grids or dynamic values changing over time through the use of continuous event methods.  What all this means is that we can very quickly create solid representations of your problems.  But just having the tools isn't enough.  We also need an effective process in which to apply those tools to produce a useful result. 

Our Basic Process

This is a very basic look at our underlying analytical simulation process.  There are many additional options within this process, but we have listed here to demonstrate the rigour of our basic approach.

Analytical Simulations to Produce More Robust Business Cases

It is our belief that business cases should be created and made with similar traits and rigour to legal cases.  They should be based on evidence, with contentions and claims made in the case backed up with solid data.  Importantly, we feel that a new approach to business case modelling using analytical simulation techniques as opposed to simpler spreadsheet approaches will become the new norm in the future.  Whilst we use spreadsheets where needed, the more complicated an underlying system, the more likely it is that building a business case in analytical simulation framework is a better option.  These will still include include Monte Carlo simulation, and produce a discounted cash-flow type output.  They still let us run many hundreds or even thousands of "possible futures" inside the business case cost model and lets us examine outputs like Net Present Value (NPV) of the opportunity as a probability distribution, rather than a single result based on point assumptions.  We crystallise the risk and show you its potential range of impacts, good and bad.  Putting multiple cases into a portfolio, our background in simulation, statistics and OR can help your organisation choose the optimal portfolio of future opportunities to invest in, and how much money you should consider allocating to each to maximise your total return and minimise risk.

Our analytical simulation approach to business case modelling offers a new paradigm, and provides more effective estimations when the complexity and detail over time leave behind what a spreadsheet can usefully produce.