Note: This blog post is co-authored with my colleague Laurent Colombant
Crisis situations often bring out the best in humanity, as we've seen repeatedly since the onset of the coronavirus. Unfortunately, crisis situations also reveal those among us with bad intent.
During the COVID-19 pandemic, our global supply chain was flooded with suspect offers by uncertain middlemen. This created an atmosphere of confusion and distrust. Take the investigation by the FBI in coordination with a California union and Kaiser Permanente to track down a presumably fake company that had agreed to deliver 39 million N95 masks. Six million of those were to be delivered to Kaiser.
In this case, Kaiser had checks in place for onboarding new suppliers. Those checks raised a red flag – the supplier failed to provide information about how the buyer could verify and inspect its shipment of masks. This is a good news story. Funds were never exchanged, and Kaiser helped save many other government agencies from losses. Not every situation turns out so well.
Challenges of supply chain disruption
The disruptions COVID-19 brought to our global supply chain were unprecedented. Many organizations faced two acute challenges:
- Suppliers in affected regions or countries reduced or altogether stopped producing some items that were essential to the production of finished goods. For example, some medications couldn't be produced, and aircraft production lines for certain models stopped. This left many companies scrambling for alternatives.
- The climate was – and still is – ripe for fraudsters to take advantage of breakdowns and disruptions in these processes. But identifying bad players is a challenge.
With a limited production of supplies, companies around the world worked quickly to find alternative suppliers of critical goods similar to what they normally purchase. But they sometimes over-paid for those supplies. And they were exposed to risk from bad players who were abusing the situation.
Today, it's apparent that many supply chains were over-dependent on certain suppliers or were not well-balanced. Some companies even discovered that they had overlooked instances where they were fully dependent on sole suppliers for certain goods.
Making matters worse, many organizations still confront routine data management challenges. Much of this stems from poor data quality and diverse data that’s spread across internal and external environments. Being able to effectively cleanse and combine this structured and unstructured data – such as text-based information – is essential to getting a clear picture of suppliers. If companies can manage supplier data well, they’re better prepared to:
- Conduct due diligence around critical suppliers.
- Comply with contractual conditions.
- Accurately analyze procurement spend.
- Optimize supplier choices in situations that demand fast, continual supplier onboarding.
Onboarding and other steps to ensure supplier integrity
Legal and compliance requirements call for strict supplier onboarding processes, even in normal times. This is routinely done to check for any associations a supplier may have with known sanctioned companies or individuals. This effort is still very important. But the evolving, unpredictable landscape of COVID-19 put many critical supplies in high demand and short supply. Having trustworthy suppliers to deliver personal protection equipment (PPE), medications – and even basics like food and clothing – is more important than ever before.
In addition to following strict onboarding processes, organizations can take other steps to ensure they have appropriate controls and measures in place. This will ensure supplier integrity and help to predict supply chain risks. With this foundation in place, any issues that surface can be addressed in a timely fashion.
With sound data management in place, you can rely on advanced analytics like machine learning to automate processes and deliver fast insights that inform decisions about who to do business with. This starts with onboarding and continues to ongoing analysis of suppliers and procurement spend.
For example, you can use automated processes to continuously monitor suppliers for compliance, fraud and money laundering – and get notified of any red flags. These methods can check continuously for financial risks – identifying ultimate beneficial owners, looking for politically exposed persons, checking for dual usage goods, and more. With these analytic insights, you'll be prepared to take rapid corrective actions that prevent supply chain disruptions and avoid delays in deliveries of medical supplies and other goods.
Continuous monitoring and propagation models
Being able to continuously monitor internal data on suppliers, spend and procurement is always essential. Continuous monitoring uses analytics to rapidly identify risks and errors in data. This technique combines predefined fraud scenarios with data management, proven models and rules. As a result, continuous monitoring uncovers unusual supplier behavior, duplicate invoices, contract discrepancies and more.
It’s just as important to be able to access relevant data from the public domain and incorporate it into decision-making processes. One method for doing this involves using propagation models to help you proactively mitigate issues. Whether it’s a natural disaster or a pandemic, a propagation model provides an indicator of where a catastrophe will strike next.
If you know where your suppliers are located, you’ll be able to quickly spot those at risk. It’s especially important to know this for “just in time” production environments that operate with little inventory. Through continuous monitoring and supplier validation, you can determine if there are other reliable suppliers of the same (or similar) goods in a geography that's not currently affected by the catastrophe. And if the at-risk supplier is not a sole supplier, you may be able to switch suppliers. You can run simulations with machine learning techniques to calculate how the change will affect your costs.
Data visualization lets you view data in a variety of ways to get a clearer picture of actions you could take. For example, you can examine heat maps of suppliers to see multiple dimensions of risk that pertain to compliance, fraud and auditing departments. You can also visualize anomalies and the results of sensibility analysis. Then you can document that the decisions you make are based on facts.
After incorporating external text data from public domains, you can use sentiment analysis to understand key people associated with suppliers that may present risk. Combining results of procurement and supplier integrity analytics shows an overall supplier risk score. Data visualization can help you spot ghost suppliers, networks of dishonest suppliers and bid rigging – all of which tend to be more frequent during a crisis.
The pandemic altered virtually every facet of our lives. But supply chain issues could be viewed as one of our biggest wake-up calls. It’s clear that organizations must work together to improve their supply chains, catch fraudsters and strengthen economies. Data analytics can help by enabling you to continuously evaluate suppliers and related processes. Embracing this approach can help you avoid reputation and supply chain risks – ranging from supplier management and procurement to payment cycles.Learn how SAS can help you move forward with resilience