In today’s business landscape, making decisions based on data is not just an advantage but a necessity, especially in the logistics and supply chain industry. The movement of goods and materials across vast networks requires precision, adaptability, and resilience. The sheer volume and diversity of data generated at every stage of the supply chain demand a shift from intuition-based decisions to insights derived from a data-centric approach. In this month’s cover story, we delve into the pivotal role of data-driven decision[1]making in supply chain management, exploring its benefits, challenges, and much more.
In today’s fast-paced business environment, particularly in the global supply chain and logistics sector, data-driven decision-making is absolutely critical. Since the 1960’s, the concept made real progress, flowing to the 80’s and 90’s when computers became more powerful and affordable. Now, as data is being generated everywhere in a multitude of flavors, formats, and functions, making sense of this data and harnessing it has become vital to not only survive, but also grow and stay efficient.
In a data-driven world, relying on a guesswork to operate global supply chain and logistics operations is no longer feasible. As a business owner you want to use a data-driven approach to manage the supply chain and stay ahead of the competition.
But what is data-driven decision making in supply chain operations?
It refers to utilizing insights derived from intelligent data that is gathered from diverse sources to make strategic decisions aligned with the organization’s objectives, rather than relying on intuition or simple observations. This data-centric decision making model positions integrated data as the focal point of the business, breaking down silos and seamlessly connecting various systems.
The primary aim of the business is to leverage real-time data, regardless of its origin, to foster innovation in its products and services, which is also the need of the hour.
Sandeep Chatterjee, Supply Chain and Sustainability Leader, IBM says, “With the kind of data being generated in the last few years, it is imperative to use this data to draw meaningful insights and make decisions based on that.” He emphasized that data is the new oil and the advent of Generative Artificial Intelligence has made it a possibility of robust decision making leveraging data.”
The complexity and scale of supply chain operations demand real-time insights for efficient management. Rapid changes in market conditions, coupled with customer expectations for swift and accurate deliveries, necessitate data analysis for adaptation and optimization.
“Business volatility is extremely high, given the nature of external events i.e. macro and micro. Business competition has gone up with the advent of D2C and Ecommerce. This has led to the leadership team taking quick decisions to counter and protect interest. This decision making sometime may or may not be with data. Given these scenarios, data visibility and availability is crucial to taking right decisions in agile way, said Abhishek Agrawal, Senior Vice President – Supply Chain and Sourcing, Bombay Shaving Company
Chandan Shirbhayye, Associate Vice President & Head of Supply Chain, Aragen Life Sciences said, “Companies that are more process[1]oriented are in a better position to utilize data analytics to improve their performance. Data analytics systems must be process-oriented to link across functions/break the functional perspective at both the strategic and tactical levels. The business process redesign and inclusion of inter-organizational business processes is needed to exploit the advantages of data driven systems.”
“By tracking data and sharing information openly, businesses can create a more efficient and cost-effective supply chain working. Improved supply chain transparency benefits everyone involved and renewed power to scale and perform in a world where consumers are becoming more and more aware of the origins of the products they purchase, supply chain transparency with collaboration is the new mantra which has become increasingly important for businesses, Meheriar Patel, Group CIO, Jeena & Company
S Swaminathan, CEO, GS1, “Data-driven decision-making in real[1]time reduces the risks involved and facilitates better communication and collaboration across parties, ensuring an agile supply chain. Indeed, a smooth flow of communication keeps manufacturers, suppliers, and national and international retailers on the same page, which allows them to modify their plans as per the movement of the supply chain and handle issues related to delays and fleet status accordingly.”
Sanket Seth, Founder & MD, Elixia Tech Solutions Ltd. said, “Data-driven decision making establishes clear performance metrics and KPIs, enables objective supplier performance evaluation, identifies cost-saving opportunities, enhances risk mitigation and contingency planning, and ensures compliance and sustainability.”
Deepesh Kuruppath, CEO, CargoFL says that “Technologies like IoT, blockchain, and advanced analytics can enhance data visibility and reliability in supply chain operations. At CargoFL, we have an AI Data Hub that processes data from multiple sources and provides actionable insights.”
Data-driven supply chain management, significantly enhances supply chain visibility, responsiveness, and efficiency. With better visibility, companies can respond rapidly to disruptions, optimize routes, and allocate resources efficiently. This not only reduces operational costs but also leads to improved customer service, Parvinder Singh, Managing Director, Hans Infomatic
This is an abridged version of the Cover Story published in the November edition of the Logistics Insider Magazine. To read the complete story, click here.
