5 steps to getting started with predictive simulation

The first challenge faced by many businesses new to predictive simulation is how to leveragejohn beadsmoore small the maximum value from a predictive-simulation model. Then comes choosing how best to implement the comprehensive suite of technology and techniques that are part of the most effective simulation solutions. While I suggest seeking advice from internal resources and experienced external simulation specialists, here see five broad tips that should help you at the onset of any predictive-simulation initiative.

1. Know what you want

While predictive simulation is a powerful tool, to optimize results you need to know which business issues you’re trying to address. Simulation definitely isn’t a panacea for all business ills, but it does provide a means of demonstrating both the immediate and long-term impacts of decisions, replicating dynamically how certain operations, processes, spaces, equipment and resources are going to behave. It gives everyone the opportunity to see how potential changes might pan out, not just for them as individuals or departments, but for the organization as a whole. As such, the scope of a simulation model is potentially huge, which is why having a clear objective based on business priorities is essential.

901 VR Wall ffffff2. Engage your stakeholders as soon as possible

Stakeholders should be involved in the setting of model objectives and scope before any model building starts. If  key stakeholders are fully involved in this phase, they are forced to fully understand their operations, question assumptions and interact in a way that deepens knowledge on the way to clearer insight. Doing this earlier rather than later helps develop human thinking and provide access to the best information in enough time to ensure that the resulting model is the best it can possibly be.

Early stakeholder engagement also provides all those involved with the opportunity to understand and appreciate how potential benefits outweigh the pain of change. This not only offers reassurance that decisions have been investigated thoroughly and objectively, but instills all stakeholders with the confidence that a project is on the right track. By removing emotion and subjectivity at an early stage, you’re more likely to reach timely decisions by reducing extensive debate, which in turn expedites timescales and potentially saves large sums of money.

3. Start with something important but achievable

For first-time predictive simulators, the best way to start is to pick one specific business problem to solve and develop a model to achieve this. For example, a particular cell within a manufacturing production line that is causing you problems. Any budgetary and time constraints will be best met through this targeted approach and the resulting model will not only serve to address this specific business issue, but will also establish the simulation foundations which will underpin any future predictive simulation activity. 

4. Move fast and maintain momentum

Models aren’t set in stone and can always be tuned to solve other business issues as understanding, needs and perspective change, meaning that a phased, iterative approach to simulation is often the most beneficial. The dynamic nature of models means that they can be re-used to support the evolving demands of the business, with new opportunities or challenges evaluated to accurately predict the impact of proposed changes to ensure the very best decisions are made.

Also, the latest dynamic-simulation solutions grow with your business (in terms of complexity and size), providing the opportunity to analyze new opportunities and threats as soon as they appear on the business horizon.

5. Think big

It’s important to look beyond your initial model. By taking problems from the real world into the virtual world, dynamically visualizing the various potential outcomes and selecting the best course of action, simulation affords businesses the luxury of exhaustive testing without the associated risks and costs of testing in a live environment. But, to fully optimize results, simulation must ultimately take its rightful place as an integral business process, underpinning all decisions from the board-level down.

This should be the ultimate simulation goal, as it’s only when simulation is embedded into day-to-day operations that organizations can hope to fully understand the dynamic and interconnected nature of their business, providing new insights into how the organization is run, highlighting room for improvement and ensuring optimum efficiency, productivity and (perhaps most importantly) profitability.

John Beadsmoore is head of projects & delivery at Lanner