This is the key question facing business leaders, supply chain managers and plant managers. Because resilience is mission-critical when you have aggressive performance targets against the backdrop of inflation, rising energy prices, labour market constraints and logistics disruptions.
To hit those targets, business problem owners need to be confident their operations and processes are robust and sufficiently insulated against volatility outside their direct control. Predictive digital twins, powered by business process simulation technology, are an increasingly utilised tool for providing that confidence – helping you thrive (and not just survive) in an uncertain landscape.
Let's explore why.
In times of economic and business stability, planning isn’t as challenging. You can make reasonable forecasts about demands and can implement systems that enable you to respond. However, in this uncertain economic and geopolitical environment, businesses need to account for:
In this context, there are so many variables and complex correlations to consider – and the path to success is harder to navigate. It can feel like a minefield to evaluate these challenges and understand how potentially radically different scenarios affect the company’s ability to deliver to plan.
So what’s out there for people looking to make critical decisions around future business footprint; re-shoring; recruitment and skills requirements; automation, innovation and technology investments; or new supply chain configurations?
That’s where predictive digital twins come in.
Gartner defines a digital twin as “a digital representation of a real-world entity or system. The implementation of a digital twin is an encapsulated software object or model that mirrors a unique physical object, process, organisation, person or other abstraction.”
Predictive digital twins make sense of complexities. They provide a virtual business to help you answer strategic and tactical questions that affect the organisation’s ability to hit its KPIs. With a digital model of your business, you can ask ‘what-if’ questions, such as:
An individual engineer, analyst or manager can’t answer these questions using a simple spreadsheet or ‘current state’ BI dashboard. These questions involve a myriad of dynamic variables, complex processes, multiple disruptions and near-infinite potential interventions or resulting actions. In other words, they need the capabilities you get with predictive digital twins.
We’re seeing lots of businesses draw up best-, medium- and worst-case scenarios as part of their resilience planning. But that approach only works if assumptions are correct.
By applying ‘what if?’ scenarios to dynamic predictive digital twin models of your processes, you can stress test resilience against multiple internal and external variables. Therefore, you’re not working based on assumptions, you’re working with invaluable foresight based on comprehensive, KPI-based analytics.
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