AI Helps Mitigate These 5 Major Supplier Risks

A growing number of suppliers are turning to AI technology to better manage their risks.

9 Min Read
Shutterstock Photo License - Blue Planet Studio

Artificial intelligence is driving a lot of changes in modern business. Companies are using AI to better understand their customers, recognize ways to manage finances more efficiently and tackle other issues. Since AI has proven to be so valuable, an estimated 37% of companies report using it. The actual number could be higher, since some companies don’t realize the different forms of AI they might be using.

AI is particularly helpful with managing risks. Many suppliers are finding ways to use AI and data analytics more effectively.

How AI Can Help Suppliers Manage Risks Better

AI technology has been helpful for businesses in different industries for years. It is becoming even more valuable for companies as ongoing economic issues create new challenges.

The benefits of AI stem from the need to manage close relationships with business stakeholders, which is a difficult task. Businesses do not exist on islands. All companies require complex relationships with various suppliers and service providers to develop the products and services they offer to clients and customers — but those relationships always carry some risk. Since the War in Ukraine, Covid-19 crisis and other problems have worsened these risks, AI is becoming more important for companies that want to mitigate them.

Here are some of the risks that organizations face in dealing with suppliers, and what they can do to mitigate those risks with artificial intelligence.

Failure or Delay Risk

Failure to deliver goods is one of the most common risks businesses have suffered over the past two years. This risk is best defined as a complete supply or service failure, which can be permanent or temporary.

There can be many localized or widespread reasons for a supplier to fail to provide goods or services. For example, poor management might cause their business to collapse, eliminating their products from the supply chain. The availability of materials can cause failures, as suppliers cannot manufacture products when they lack the resources to do so. Finally, unexpected or unavoidable events, like the blockage of a major trade route or unprecedented and severe storms, can cause catastrophic delays that shut down manufacturing or prevent trade from coming or going to a region.

This is one area that can be partially resolved with AI. You can use predictive analytics tools to anticipate different events that could occur. Cloud-based applications can also help.

Google Cloud author Matt A.V. Chaban addressed this in a recent article. Hans Thalbauer, Google Cloud’s managing director for supply chain and logistics stated that companies are using end-to-end data to better manage risks at different junctions in the supply chain to avoid breakdowns.

Brand Reputation Risk

Suppliers have to be true to their mission and think about their reputation. Fortunately, AI technology can make this easier.

There are a few ways that a company’s brand can be negatively impacted by a member of its supply chain. If a supplier maintains poor practices that result in frequent product recalls, the business selling those products might be viewed by consumers as equally negligent and untrustworthy. Likewise, if a supplier publishes messaging that contradicts a brand’s marketing messages, consumers might become confused or disheartened by the inconsistency of the partnership. Because the internet reveals more about supplier relationships and social media provides consumers with louder voices, businesses need to be especially careful about the brand reputation risks they face in their supply chains.

How can AI help with brand reputation management? You can leverage machine learning to drive automation and data mining tools to continue researching members of your supply chain and statements your own customers are making. This will help you identify issues that have to be rectified.

Competitive Advantage Risk

Businesses that rely on the uniqueness of their intellectual property face risks in working with suppliers, who might sell that IP, counterfeit goods or otherwise dilute the market with similar products.

Saturated markets require companies to develop some kind of unique selling proposition to provide them with a competitive advantage. Unfortunately, the power of that competitive advantage can wane if a business opts to work with an untrustworthy supplier. In other countries, rules about intellectual property are less rigid, and suppliers might be interested in generating additional revenue by working with a business’s competitors, offering information about secret or special IP. Though the supply chain itself might be unharmed by this risk, this supplier behavior could undermine a business’s strategy and cause it to fail.

AI technology can help suppliers improve their competitive risk in numerous ways. They can save money through automation, identify more cost-effective ways to transport goods and improve value in other ways with artificial intelligence.

Price and Cost Risk

This risk involves unexpectedly high prices for suppliers or services. In some cases, business leaders do not adequately budget for the goods and services they expect from their suppliers; in other cases, suppliers take advantage of a lack of contract or “non-firm” prices to raise their costs and earn more income from business clients. This is one of the easiest risks to avoid, as business leaders can and should perform due diligence to understand reasonable rates amongst suppliers in their market.

AI technology can also help in this regard. Machine learning tools have made it a lot easier to conduct cost-benefit analyses to recognize opportunities and risks.

Quality Risk

Cutting corners can cut costs but doing so can also result in poor product or service quality that is unattractive to consumers. Businesses need to find a balance between affordability and quality when considering which suppliers to partner with.

Some suppliers maintain a consistent level of high or low quality, but with other suppliers, quality can rise and fall over time. Some factors that can influence quality include material and labor cost in the supplier’s region, shipping times and costs and the complexity of the product or service required. Business leaders who recognize a dip in quality might try to address the issue with their current supplier before looking for a new supplier relationship.

Fortunately, AI can help identify any of these issues.

The Best Risk Mitigation Strategy Requires AI Technology

AI technology has made it a lot easier for suppliers to manage their risks. Undoubtedly, the best way to mitigate the risks associated with suppliers is with a robust supplier risk management system. The right AI tools and procedures help business leaders perform more diligent research and assess supplier options more accurately to develop a supply chain that is less likely to suffer from delays, failures, low quality, undue costs and other threats. Risk management software developed for the supply chain help business leaders build and maintain strong relationships with top-tier suppliers, which should result in a stable and lucrative supply chain into the future.

Share This Article
Exit mobile version