‘Predictive simulation is just for manufacturing, right?’ Wrong!

Use case 1: Validating expansion projects

Expansion projects can involve substantial capital expenditure, affect multiple processes and involve complex stakeholder dynamics. Predictive simulation lets you model all aspects of the proposed expansion to see the impact of different design, process and technology choices.

For example, you can use it to:

• Conduct risk assessments
• Identify potential impacts on supply chains and staffing levels
• Pre-empt bottlenecks
• Understand the impact on productivity

Importantly, you can also use predictive simulation to validate the business case for expansion and secure stakeholder buy-in for proposals.

One example is BJC HealthCare. Using Twinn Witness predictive simulation software, they modelled plans to expand hospital facilities, using the simulation to reach a consensus on collaborative working processes across the new spaces. The modelling provided a ‘single version of the truth’ that informed decision-making. As a result, BJC enhanced patient care while reducing the number of required beds.

Use case 2: Optimising contact centre operations

Predictive simulation lets you test different strategies based on call volumes, scheduling, routing, agent skillsets, shift patterns and KPIs like CSAT and NPS.
3 Italia is an excellent example of this. They were designing a new customer service delivery model and needed to find the most efficient way to implement it at their contact centre. They simulated daily operations to define new ways of working, validate targets and inform contingency planning. As a result, they delivered a more customer-centric service with clarity on what was needed to meet targets.

Similarly, staff scheduling is crucial for ensuring efficiency and employee satisfaction. Barclays Merchant Services handles up to 80,000 support calls a month and more than 20 million authorisation calls a year. It needed to find the best way to use staff and structure shifts while still delivering outstanding service.

By simulating call centre operations, Barclays was able to optimise staff numbers and shift length and quantity. Overtime costs were then reduced by up to £100,000 a year – and they still hit customer service targets.

Use case 3: Improving customer experiences

Predictive simulation can help optimise customer experiences in settings as diverse as museums, shops, restaurants and events. You can evaluate a range of scenarios to understand the impact of myriad variables, from visitor flow to health and safety and staff allocation.

Let’s take renowned London attraction Madame Tussauds. With 2 million guests annually, visitor enjoyment and health and safety are high priorities. Using Witness, Madame Tussauds better understood the processes behind guest flows and queuing systems – and had clarity on capacity considerations for various times of day. This helped them optimise their approach to staffing and guest care.

And there was a significant financial benefit, too. Madame Tussauds had been planning a £2 million investment to improve the guest experience, but the predictive simulation showed that the proposed changes wouldn’t deliver the desired results. 

Use case 4: Supporting R&D

Predictive simulation can help R&D by modelling the supply chains for and use of new technologies.

The Liverpool School of Tropical Medicine (LSTM) set a standard here. In their work on tuberculosis (TB) in developing countries, they used Witness to model the patient pathways involved in diagnosis. This knowledge helped them understand the potential outcomes of introducing new diagnostic technologies.

The model helped the LSTM team identify the most effective strategies for reducing TB transmission and improving patient outcomes . It also ensures that policy-makers and funders are confident that extra investment into these diagnostics technologies is justified. This is now contributing to the decline of tuberculosis around the word while ensuring the best use of resources and funds.