Unified intelligence in supply chain
Recent global supply chain events have exposed a lack of capabilities and structure in legacy consumer packaged goods (CPG) and retail operating systems. As these deficiencies persist, many organizations have experienced significant disruptions. Inventory shortages, delayed deliveries, and increased operating costs, triggered by supplier insolvencies, transportation delays, natural disasters, and geopolitical tensions, continue.
Still, some companies have learned to meet customer demand, maintain profitability, and enhance customer experience despite the adversity. What distinguishes them from other firms is their ability to harness vast amounts of data generated from online and offline channels.
Leveraging data is critical, not only for addressing traditional demand forecasting challenges, but also for managing customer expectations and mitigating supply chain disruptions. To succeed, CPG and retail leaders must acknowledge where their supply chain systems are fragmented and focus on data integration, to prevent disruption and capitalize on emerging opportunities.
Fluctuating demand, economic uncertainties, natural calamities, and labor shortages will always be with us. That’s why leading firms are cultivating resilient and sustainable supply chains by investing in data and digital platforms.
Paths of disruption
“In 2021 and 2022, disruption in supply chains is estimated to have cost businesses $1.6 trillion in missed revenue opportunities per year.”
– Forbes
Here are six strategies industry leaders are implementing to achieve unified intelligence and an interconnected system for robust supply chain operations.
1. Expand visibility with a virtual control tower
The core of a virtual control tower revolves around centralizing and integrating data from various sources to provide real-time visibility and control over the entire supply chain. It acts as a “digital nerve center,” allowing organizations to proactively monitor, analyze, and manage supply chain activities. By integrating data from ships, containers, ports, warehouses, distribution centers, and other sources, real-time tracking, realistic delivery timelines, optimized inventory management, route efficiency, and scalable operations combine to support customer satisfaction.
Control towers also enable predictive analytics, necessary to anticipate and mitigate potential disruptions, such as adverse weather or port congestion. Armed with this information, decision makers can apply corrective actions ahead of disruption and optimize emerging opportunities.
In the future, integrating generative AI (genAI) into control towers holds immense promise. Its success depends on robust data quality and integration across supply chain dynamics, covering demand fluctuations, production schedules, and logistics. Modernizing technology stacks to handle the intensive computational demands of AI model training is essential. Moreover, ensuring data privacy compliance under regulations, such as General Data Protection Regulation (GDPR), adds another layer of complexity to implementation efforts.
2. Optimize operations with ‘digital twin’ technology
CPG and retail companies can deploy a partner ecosystem to leverage advanced data analytics and digital twin technology. At its core, digital twins represent a digital, virtual replica of a company’s global supply chain operation, encompassing manufacturing facilities, freight and cargo operations, third-party contractors, and distribution centers. This technology allows companies to stress-test multiple scenarios daily, examining potential outcomes without real-life disruptions.
Digital twins are ideal for setting up contingency plans, identifying alternate transportation routes, and making sure that upstream and downstream activities work according to the company’s business strategy. Their ability to leverage deep reinforcement learning, cloud technology, and near real-time data sets help enhance operations, increase machine uptime, and reduce waste.
Digital twins make a difference
“One leading retail company used digital twins to achieve a 7% reduction in carbon emissions and a 5% improvement in customer orders received on time.”
3. Stay one step ahead with predictive modeling
A coherent data management system is crucial for CPG and retail companies, allowing data extraction at every phase of the product journey, from factory to consumer. Implementing predictive modeling at each stage of the journey unlocks insights that enhance efficiency, improve customer experience, and provide a competitive edge.
By analyzing vast datasets of historical sales, promotions, and external factors, such as weather and social media trends, companies can accurately forecast demand. Accurate models ensure reduced inventory overstock and understock, ensuring that products are on shelves when consumers order. Predictive analytics can also help build resilience in supply chains by developing risk control capabilities in the face of disruptions.
4. Achieve autonomous planning through AI and ML
AI has traditionally been used to optimize logistics by improving delivery routes, managing inventory, and streamlining warehouse operations. It has also been employed to automate repetitive tasks, optimize transport route planning, and perform quality control.
By embedding AI and machine learning (ML) automation into decision-making processes, companies are better able to make real-time adjustments to shifting supply and demand. One retail company recently started utilizing unstructured data on shipments, suppliers, and external sources to analyze trends, identify anomalies, and extract actionable insights.
Benefits of autonomous planning
“According to McKinsey, autonomous supply chain planning can increase revenue by up to 4%, reduce inventory by up to 20%, and lower supply chain costs by up to 10%.”
5. Manage consumer data
Consumer behaviors are rapidly shifting. Across the board, there is a diminishing customer loyalty, a shift to direct-to-consumer channels, shrinking delivery times, increasing demand volatility, and the rise of subscription models. These changes, driven by digitalization and evolving customer expectations, require companies to adopt a new mindset to remain competitive.
Companies must adopt a customer-centric, data-driven mindset, integrating diverse data sources, including unstructured data, with traditional data in a near real-time, cloud-based ecosystem. This unified approach is essential for leveraging insights and remaining competitive. During and after COVID-19, firms that had cloud infrastructure and predictive analytics capabilities in place were better able to respond to supply chain challenges. Real-time data analytics provide deeper insights into consumer preferences, enabling companies to adjust their supply chains accordingly. Leveraging AI and cloud-based data ecosystems will continue to be crucial for anticipating and proactively responding to changes.
6. Embrace new modes of transport
Emerging transport technologies, such as autonomous vehicles, drones, and hyperloop, promise to revolutionize logistics. These innovations offer faster, more reliable, and cost-effective transportation options that deliver goods efficiently, minimize reliance on fossil fuels, and enhance sustainability. And while regulatory hurdles, technological maturity, and infrastructure development are key challenges that need to be addressed, the future will not be denied.
Pilot projects, such as Tesla’s autonomous trucks and hyperloop initiatives, are already receiving a lot of attention. As these technologies mature and become more widely adopted, they will profoundly impact global supply chains, enhancing efficiency and resilience. Very soon, they may also address the shortfall of commercial drivers, save on fuel costs, and reduce driving costs associated with human drivers by as much as 70%.
What’s next for CPG and retail supply chains?
Recognizing the pivotal role of data, many CPG and retail firms have already begun to invest in advanced platforms, technology, cloud infrastructure, and integrated analytics. This impetus underscores a strategic shift from reactive to proactive supply chain management. It acknowledges that transformation unfolds incrementally, addressing diverse challenges and constraints across the value chain.
At the forefront are leading companies leveraging innovative tools, such as control towers, digital twin intelligence, predictive modeling, and AI/ML. These technologies support robust data intelligence and facilitate seamless integration across historically siloed systems. By fostering resilience, agility, and efficiency, these firms not only navigate disruptions more effectively, but also unearth substantial growth opportunities in an increasingly dynamic marketplace.
Looking forward, the integration of GenAI into supply chain control towers represents a significant frontier. This advancement promises to elevate predictive capabilities, optimize resource allocation, and enhance decision-making. However, achieving these milestones necessitates a comprehensive approach, encompassing stringent data privacy measures under regulations, such as GDPR, and the continuous evolution of technology stacks to meet the demanding computational requirements of AI model training.
Learn more now!
To learn more about transforming your supply chain for greater visibility, control, and customer satisfaction, or to consult with one of our industry experts, please contact EXLservice.com.