Beyond resilience: 5 ways to gain competitive advantage in supply chain management

Most teams and organizations deliver their best results when they’re working in perfect harmony. Just as an orchestra has five important components—woodwinds, brass, percussion, strings and an experienced conductor—supply chain leaders need to develop five key capabilities to move beyond resilience and capitalize on disruption. To enable an anti-fragile supply chain, leaders should cultivate sensing, prediction, simulation, mitigation and orchestration. 

Today supply chain leaders are seeking a more sophisticated approach to risk management. Uncertainty is inevitable. Leaders who develop these five capabilities can anticipate and react more quickly than competitors to a disruption—offering them an opportunity to provide a superior customer experience and gain market share.

In a supply chain, every flutter matters. Sensing is the ability to gather real-time data and insights from each link of the supply chain to anticipate potential disruptions. Many industry leaders are building early warning systems that continuously track and assess risk indicators. Lenovo, for example, has developed an AI-powered solution, Lenovo Supply Chain Intelligence (SCI). It monitors hundreds of data sources to assess demand drivers, supplier service levels, weather patterns and port congestion to detect the faintest tremors of risk before they become earthquakes.

During the early days of the COVID-19 pandemic, SCI detected a potential disruption in the supply of components from Wuhan, China. Lenovo was able to take proactive measures to mitigate the impact of the city’s eventual lockdown.

While we can't control the future, we can anticipate it. Prediction leverages advanced analytics and AI to forecast potential disruptions, as well as assess their likelihood and potential impact. By analyzing historical data, market trends and even social media sentiment, predictive models enable supply chain managers to foresee disruptions earlier and plan for corrective actions. For example, leading retailers use predictive analytics to anticipate surges in demand for certain products during a holiday season, enabling them to adjust inventory levels and avoid stockouts.

Simulation enables supply chain teams to run “dress rehearsals” to prepare for and test their responses to potential disruptions. Simulation engines enable the analysis of "what-if" scenarios to test different responses to potential disruptions and assess their impact. By simulating the effects of a port closure or a supplier bankruptcy, companies can identify vulnerabilities and develop contingency plans. Industry leaders are also developing digital twins of their supply chains to simulate the impact of potential events—such as a key supplier going out of business—so they can evaluate alternative sourcing options and ensure supply chain continuity.

Mitigation is the art of minimizing a disruption’s impact by taking the best corrective action. Tactics may include diversifying supply sources, building buffer stock or establishing alternative transportation routes. For instance, during a natural disaster, a company with a robust mitigation strategy might quickly shift production to a different facility or leverage its network of suppliers to source critical components from unaffected regions.
 

AI can help. Today, industry leaders are using AI to develop tools that consider a range of variables before recommending the best available mitigation actions.

In times of disruption, effective supply chain management requires not only the coordination of preventive and mitigation actions across the enterprise, but also across the entire supply chain. Streamlined and even automated orchestration can ensure suppliers, partners and internal teams are aligned and can respond effectively to disruptions.
 

When a natural disaster strikes, effective orchestration is necessary so that all teams are working toward a common goal and minimizing the impact on customers and the business. This might involve reallocating inventory, adjusting production schedules and communicating proactively with customers to manage expectations.

These capabilities can’t be developed overnight. They require investments in technology, process redesign and strategic partnerships, as well as a relentless pursuit of excellence. Three technologies can help teams develop the muscles required to accelerate supply chain risk management decisions:

• Optimization: Optimization uses mathematical models to improve decision-making so that resources are allocated efficiently and effectively. Whether it’s inventory allocation, transportation routing or production scheduling, optimization enables supply chain leaders to make the best possible choices, even in the face of uncertainty. For example, a logistics company might use optimization to choose the best delivery routes so they can reduce transportation costs and improve delivery times.
• Machine learning (ML): ML algorithms analyze vast data sets to identify patterns and trends that humans might miss, helping to deliver more accurate predictions, proactive risk identification and smarter decision-making. A retailer, for instance, might use ML to analyze customer purchase history and predict future demand, which helps them tailor their inventory and marketing strategies.
• Generative AI: While still in its early stages of adoption, generative AI has the potential to revolutionize supply chain management. It can be used for scenario planning, creating synthetic data to improve models and generating creative solutions to complex problems. It’s not difficult to imagine a generative AI system that can create realistic simulations of various supply chain disruptions, allowing companies to test their response strategies in a safe and controlled environment. As generative AI capabilities mature, they will become a powerful tool in a supply chain leader’s arsenal.

In the unpredictable world of supply chain management, companies that prepare today—including by developing the five critical capabilities of sensing, prediction, simulation, mitigation and orchestration—will thrive tomorrow. These capabilities, powered by technologies such as optimization, machine learning and generative AI, will help supply chain leaders anticipate disruptions, respond quickly and effectively and emerge stronger than ever.