"It was the best of times, it was the worst of times, it was the age of wisdom, it was the age of foolishness, it was the epoch of belief, it was the epoch of incredulity, it was the season of Light, it was the season of Darkness"
If someone, having no idea of “A Tale of Two Cities”, thinks Charles Dickens is a Chief Supply Chain officer in the Post Covid era, he might as well be forgiven because this timeless quote feels as relevant as ever in the ever-complex background of Supply Chain today.
It is indeed probably both the best time and the worst time to be a Supply Chain professional. On one hand, the unprecedented macro socio-economic complexities of the Post Covid world (think unemployment, inflation, war, climate change – to name a few) make it increasingly difficult to keep the fine balance between supply chain cost and efficiency, Cost Per Pieces is increasing by every passing day, courtesy increased labor cost, inventory storage cost and handling fees, driven by an ever demanding customer base pampered by a multitude of options at their fingertips. However, on the other hand, unparalleled technological advancements are making it easier to add more efficiency to the overall supply chain process. One thing for sure – Supply Chain Digital Transformation is not ‘Nice to Have’ anymore. It is imperative for survival in a highly competitive environment.
The Rise& Rise of Advanced Analytics:
Advanced analytics has emerged as a cornerstone in reshaping the dynamics of supply chain decision making. The ability to harness massive amounts of data (Big Data), coupled with sophisticated analytical tools, empowers organizations to gain unprecedented insights into their supply chain. While traditionally supply chains have always been using descriptive analytics to gain insights from historical data, the evolution from descriptive analytics to more predictive and prescriptive analytics is becoming the hallmark of modern digital supply chain analytics.
Predictive analytics leverages historical data and statistical algorithms to forecast future trends, demand, and potential disruptions. By analyzing patterns and trends, organizations can anticipate market shifts, optimize inventory levels, and enhance overall operational efficiency.
Prescriptive analytics takes decision-making a step further by providing actionable insights and recommendations. By considering various scenarios and potential outcomes, organizations can optimize their supply chain processes in real-time. This proactive approach enables faster response to disruptions, reduces lead times, and ultimately enhances customer satisfaction.
In my current role as a Director of Inbound Supply Chain for one of the world’s leading foodservice distributors, I experience firsthand every day the transformational power of advanced analytics. Whether it is diagnostic analytics to find out root causes for service level or supplier fill rate problems, or predictive analytics to come up with potential future service level issues or demand forecasting exceptions, advanced analytics is adding value and efficiency to the “Day in Life” of the supply chain business organization, and how.
AI/ML & its role in revolutionizing digital supply chain:
The integration of AI/ML has been a game changer in Supply Chain analytics. By harnessing the massive amount of supply chain data like demand signals, purchase history, inventory movement, route information & logistics data, enterprises are using AI/ML to bring innovation at scale to help supply chain decision making.
In my current experience and capacity to lead a large-scale supply chain digital transformation, here are some of the key areas where AI/ML (and as a natural extension, Generative AI) is driving significant innovation in Supply Chain.
Advanced Demand Forecasting: One of the key contributions of AI/ML to supply chain decision making is the ability to enhance demand forecasting accuracy. Machine learning algorithms analyze historical sales data, market trends, and external factors to generate more precise demand forecasts. This not only reduces the likelihood of stockouts or excess inventory but also allows for better allocation of resources.
Network Inventory Optimization: Inventory Optimization is another area where AI/ML is creating a lot of value. Leveraging network analysis, we can dynamically adjust inventory levels based on real-time demand fluctuations, supplier performance, and external factors such as weather and geopolitical events. By automating inventory replenishment decisions, organizations can achieve optimal stock levels, minimizing carrying costs while ensuring product availability.
Route Optimization: AI-driven route optimization is transforming logistics and transportation management. Machine learning algorithms consider various parameters, including traffic conditions, fuel prices, and delivery schedules, to identify the most efficient routes. This not only reduces transportation costs but also minimizes carbon footprint, aligning supply chain operations with sustainability goals.
Collaborative Planning and Supply Chain Visibility:The integration of advanced analytics and AI/ML is a foundation for collaborative planning. By providing stakeholders with real-time, actionable insights, we can break down silos and enable cross-functional collaboration. Supply chain visibility using control towers is key in terms of gaining near real time visibility to supply chain operations. This becomes particularly crucial in addressing supply chain risk and disruption. When equipped with accurate and timely information, supply chain professionals can collectively formulate adaptive strategies to mitigate risks, respond to changes, and ensure the resilience of the supply chain.
Epilogue:
Well, can we really say the last words on this topic? The short answer is a resounding NO. Advanced analytics & AI/ML is evolving at such breakneck speed, it is getting tough to stay ahead of the game. However, one thing for sure –AI/ML and advanced analytics are surely shaping the future of a digital and connected supply chain. And a digitally connected supply chain is the way forward to handle the disruptions and volatility that modern supply chain is presenting to enterprises. In this current world when macro and micro socio-economicconditions continue to throw curveballs, being well connected and leveraging the digital innovations via advanced analytics and AI/ML is the winning formula. Well – for now at least!