4 pressing business resilience challenges

From engineering and production to operations and supply chain management, everyone is now juggling new risks.

With fluctuating capacity and customer demand, rapid capacity and resilience planning is like feeling your way through a dense fog. In this blog, we’ll look at four overarching planning challenges – and how predictive digital twins can provide fast, evidence-based clarity.

Challenge 1: Getting fast answers to complex questions

“How should we redesign the line to maintain social distancing and manage with reduced staff? Should we automate processes as part of this?”

“Will we benefit from deploying AGVs? If so, what type and in what configuration?”

“What’s our capacity to supply if we experience another extreme event outside of our control?”

These are difficult questions usually involving complex, variable and interconnected business processes. In addition, there can be hundreds, if not thousands of “what-if” scenarios you could probe as you try to answer them.

Predictive digital twins help you cut through that complexity. They give you a risk-free way to analyse manufacturing, assembly and supply chain logistics processes.

And they can help identify the technology, personnel, operational, and procedural requirements needed to ensure your business is resilient enough to ride out any unexpected operating conditions.

Importantly, you get those answers within your required decision time. To give you an idea of speed, it used to take Washington River Protection Solutions (WRPS) 20-25 working days to answer highly complex questions involving hundreds of “what-if?” scenarios being evaluated over many simulated decades of process activity.

WRPS manages a challenging nuclear waste clean-up project with major cost and safety considerations, so the stakes are as high as it gets.

Now, thanks to Lanner’s cloud-based WITNESS.io simulation solution, it takes just a couple of days from posing complex business questions, to comparing consolidated strategic answers and making mission critical, million-dollar decisions.

Challenge 2: Challenging assumptions with evidence

“More throughput means we’ll need more pallets, right? Reach a certain threshold of demand, and we’ll need to expand, no?”

At face value, these are logical assumptions. And you could validate them using static or experience-led estimations. But underneath those assumptions lie a myriad of variables across complex connected production and distribution processes.

When you’re talking about making significant investments in both time and money, you need the power to challenge those assumptions.

Predictive digital twins give you that power. In using them, you’re not relying on intuition. Instead, you’re understanding true business implications based on causes and effects, and can confidently make evidence-based decisions.

Nissan is a prime example. The company use Lanner’s WITNESS Horizon Predictive Simulation software to look at both major strategic, and smaller tactical, challenges.

In one ‘quick win’ use case, they instantly saved £22,000 on pallet procurement – because predictive simulation showed that operating with a reduced number wouldn’t negatively affect throughput rates.

In another rapid virtual piloting case, Nissan avoided a £25,000 investment in a new station, because the predictive digital twin showed they could cope with rising demand using existing equipment.

At the opposite end of the problem-solving spectrum, the same simulation capability is used by Nissan to ‘virtually pilot’ new facilities and processes prior to commitment.

Challenge 3: Getting management buy-in for plans and investments

Whether it’s securing funding for innovation or demonstrating the value of relaying lines, Predictive Simulation provides the business case justification for your strategic, resilience-driven process changes and improvements.

Here’s a quick illustration. A Royal HaskoningDHV Digital manufacturing client was building a new battery production facility for electric vehicles. It was an innovative new product stream for the company, and assembly involved more than 10,000 individual components.

The team had three weeks to present an investment case to the board, instilling confidence they could achieve the required throughput.

In just 10 business days, a predictive digital twin was deployed showing ROI on different levels and types of spend. It revealed that the current factory designs wouldn’t deliver the necessary throughput and highlighted bottlenecks they hadn’t yet considered.

The team then secured board buy-in for necessary automation, supporting the business case with the insights from the simulation asset.

Challenge 4: Building skills to support ongoing resilience planning

Having access to Predictive Digital Twins is an important step in solving many business resilience challenges. But beyond the technology, you also need the right people and process skills to derive value.

This is a fast-moving area, with Industry 4.0 increasing data volumes and artificial intelligence and machine learning expanding analysis capabilities.

Even for experienced modellers, continuing professional development is essential in understanding how a Digital Twin ecosystem could, and should evolve, what data should be fed in and what questions should be asked.

In addition to training and mentoring, our customers say one of the most valuable ways to elevate skills is by understanding best practices and problem-solving techniques from other industries. By keeping up with peers across sectors, modellers discover new techniques and use cases they can apply internally.

Increased maturity in deploying predictive analytics solutions better positions analysts to manage resilience questions across the business. It equips them to uncover and mitigate otherwise unknown issues that could create risk over the short and medium term.

What should you do next?

If you’re like most businesses, you face a combination of all four of these challenges, and you’ve now had a quick taste of how predictive digital twins can help overcome them.

Your next step is to understand the optimum deployment approach, by watching the recording of our webinar 'Strategically Planning for the Future: Developing Resilient, Agile Processes Using Predictive Digital Twins'.

During this webinar, we discuss how predictive digital twins can help you overcome key business challenges to build a more resilient and adaptable future.