2. Employ predictive analytics to warn off trouble early
Understanding the state of the supply chain is always critical. But it is even more difficult to see which suppliers may be distressed when the supply chain has all but stopped and has not fully restarted. Predictive analytics can warn of trouble, especially at suppliers, while there is still time to fix issues.
The first step is to map the supply chain, identifying to the best of a company’s ability suppliers that are even below tier 2 – in other words, suppliers to suppliers to suppliers. Then prioritize the suppliers that are most critical to the future function of the supply chain and then start monitoring them for distress, a process that can include direct discussions with lower tier suppliers.
Predictive analytics can complement this process and help identify what may not be obvious.
EY has worked with several OEMs and a major supplier in Europe and the US to use analytics to examine the likelihood that a company will be among the survivors in the shift from ICE to electric drive and other pressures on the industry.
In Europe, EY has used an algorithm that includes 32 different statistical measures to help show which companies have potential weaknesses that may not allow them to survive and transform in the long term.
The algorithm considers, among other inputs, product diversity, margins, equity and access to capital markets to be able to get the financial resources to be able to transform.
Other risk assessment options
EY has also worked with a truck manufacturer to develop a series of KPIs to form a risk assessment score for its dozens of suppliers, enabling the company to engage with suppliers and develop strategies to mitigate supply chain disruption.
These types of assessments are also of great use when an OEM is looking to ramp up production. In one case, a client was looking to significantly increase a plant’s volume. It needed to conduct operational audits of critical tier 1 and tier 2 suppliers and provide action items for troubled suppliers. EY helped the client improve is supplier stabilization program tool and conduct assessments of 10 critical suppliers.
Of course, analytic tools are only as good as the available data. In countries such as the US, Germany and parts of Asia, for example, the financial reporting system should provide much of the necessary data to make predictive analytics viable. In parts of Latin America, this might not be the case and other sources of data must be sought. We have seen some examples where OEMs have encouraged suppliers to provide data for the analysis.