Decision Support for Supply Chain Management

The modern world can be a funny place. For every scientific discovery or innovation, we are also humbled by the fragility of our systems. In one industry in particular, this has never felt more pertinent.

Ralf Paschen November 15, 2021

The modern world can be a funny place. For every scientific discovery or innovation, we are also humbled by the fragility of our systems. In one industry in particular, this has never felt more pertinent. Supply chain management has not been exempt from technological and geographical development, but when unpredictable circumstances unfold, their sensitivity becomes abundantly clear. Just look at last year. In the same moments, we discovered stunning solutions in Machine Learning while also having to queue for several hours to fill our cars with petrol. New forms of robotics were invented just as we scrambled to ensure we have sufficient toilet paper in our homes.

Newfound interconnectivity and globalisation have transformed our supply chains into webs, where a myriad of factors are constantly at play. Observing and understanding all these moving parts is difficult. Additionally, shock events like Covid-19 also throw planning into disarray, with the various knock on effects causing further disruptions.

In times of economic hardship, financial resources are squeezed resulting in limited financial flexibility and risks of negative financial outcomes. The sheer volume of data available is helpful but also difficult to decipher, leading to risks in information usage where it has the potential to greatly help predict outcomes and provide decisions support. Decisions end up being ill informed and made with little confidence, generating strategic risks. All these different perils culminate in the potential to miss KPIs, proving a serious problem for the function of a business.

To adequately navigate these uncertainties there are key metrics to fulfill: making sure customer demand is satisfied, ensuring quality and punctuality of delivery and all the while building a strong supplier relationship. These challenges have led to key objectives for those managing these supply chains.

It involves minimising working capital and reducing its cost, for example, by automating more processes where possible. Understanding supply chain risks is also pivotal – predicting the lack of HGV drivers in the UK recently for example could have helped avoid a number of issues. Finally supply chain managers need thorough top-down analysis of their processes. It ensures they have full visibility and can sufficiently action crucial things like prioritising high-value investments.

At its core, the solution to these problems is one of analysis. Only by observing and inspecting every potential scenario that may occur in supply chains, can someone provide confident predictions for decision making and exhibit a better understanding of risks. But as we know, our multifaceted supply chains contain a great number of variables, with a number of them being time sensitive demanding rapid decision making. Computationally this is a challenge, as it requires a high volume of processing as well as consolidation of a number of different data types being channeled from disparate locations. Perfecting how we interact with this computation through a dashboard and rapid feedback is also essential. While the computer can provide the various outcomes for decision support, ultimately it has to still be the human making conclusions based on the results.

Though some platforms attempt to answer these concerns, often they prove limited. Current supply chain simulations are often restricted to using a subset of data/historical data which doesn’t give the full picture. Solutions that provide complete Monte Carlo style simulations involving all data sources will prove far more useful. Of course, situations are not always so complex and often may not require such deep analysis. But it is the unpredictability of supply chains that means it’s difficult to know exactly when you will suddenly be faced with tricky decisions. Only by being continuously primed for this moment can you best navigate it.

Ultimately, with an all in one solution for global supply chain management simulation, the challenges of modern supply chains can be faced head-on. It would help understand the risks, reduce them and move the focus on investing in more impactful areas. Decisions can be made with higher confidence due to accurate forecasting, with time-sensitive variables seeing rapid responses. The surprises of our funny world can be eliminated and KPIs can be securely fulfilled.