Enhancing Predictive Capabilities for Agile Supply Chains

TVS Supply Chain Solutions has entered into a long-term agreement with Daimler Truck South East Asia Pte Ltd to provide integrated chain supply solutions (ISCS) services in Singapore. The partnership's main focus is to accomplish a robust logistics solution for distributing spare parts while streamlining supply chain activities across the Asia-Pacific landscape. As a key logic center based in Singapore, they aim to deliver impeccable service and manage 8,000 stock-keeping units and 65,000 order lines per year.

Taking global predictive analytics market into account, it was estimated at USD 10.2 billion in 2022, and it is anticipated to reach USD 67.86 billion by 2032 with a registered compound annual growth rate (CAGR) of 21.4% during the forecast period 2023 to 2032. Several research studies have shown that 66% of global firms have to bolster their supply chains to cater to the demands of the post-COVID world. As a result, 57% of companies are in the process of building supply chain resilience by investing in stringent measures that boost agility. Let us dwell on key factors that can positively boost the ordinary supply chain activities to be agile.

Collaborative Forecasting

Predictive capabilities can be improved through collaborative forecasting by gathering insights from potential investors, who can be manufacturers, suppliers, and even customers. The collective information helps the organization maintain accuracy in line with supplying market requirements. More importantly, by providing real-time data insights, stakeholders can swiftly respond to unexpected changes in demand or supply and further minimize lead times and inventory costs. Besides, this collective approach can help the firm handle disruptions and utilize resources wisely. As a result of this, agile supply chain can perform well in the market and satisfy customer needs. 

To share sales data and insight, Nike collaborates with its retailers, such as Dick's Sporting Goods and Foot Locker. They also integrate sales data with their demand forecasts, which helped firms precisely forecast demand across stores and regions. 

Matthew Monaghan, Head of DSJ Global, APAC says "Given the intricate interdependencies among various functions within the supply chain, seamless collaboration is essential for aligning objectives, optimizing processes, and driving continuous improvement"

Real-time Data Integration

Real-time Data Integration plays a crucial role by allowing agile supply chains to have access to the latest and critical data information on market trends, stock levels and production processes. It is imperative that organizations ponder about real-time visibility into supply chain activities which can be accomplished with the integration of data streams from social media platforms, IoT sensors and RFID tags. In the present challenging business landscape, firms have to access the data timely in order for precise demand forecasting, manage risk and agile decision-making process.   Hence, with real-time data, the firms can find major changes early, utilize resources wisely and adapt to the changing demands of customers.  

Procter & Gamble incorporates real-time data from its manufacturing activities to improve production planning. Real-time data enable the firm to change production schedules quickly, improving efficiency and lowering downtime.

Sanjiv Chatterjee, Head of Supply Chain- Africa, Middle East, and Turkey( AMET)- LIPTON Teas and Infusions says "In today's rapidly evolving landscape, agility is paramount for organizations, needing a comprehensive, multifaceted, and agile approach to manufacturing processes"

Scenario Analysis                

Through the process of scenario analysis, it enables agile supply chains to model every possible business context, examine high risks and analyze the strategies to figure the best one that works for the organization. Besides, since most scenarios are well looked in advance, the firms can be in a suitable position to adapt to the immediate change occurring in the market for instance delays from supplier end and behavior changes of consumers and can frame suitable strategies to deal with. Hence, by putting scenario analysis into practice, the firm can make adequate changes with ease, bolstering its competitive edge and no complication in the decision making process.

As part of risk management, Unilever performs scenario analysis to find huge risks and disruptions in the supply chain process. The firm can develop contingency plans and risk strategies to ensure supply chain resilience by modeling all possible scenarios.  

Vickram Srivastava, Head Of Planning - Global Supply Chain, Sun Pharma says "Customer satisfaction and delight is a key driver of business success, and the supply chain plays a very important role in ensuring that"

Data-driven Forecasting

By effectively utilizing Data-driven Forecasting, the organization can make use of past data related to sales, present trends of the market and valuable insights from customers through which accurate forecasts can be developed for future demands.   Moreover, they can examine big datasets with the help of the latest analytics methods in the form of machine learning and time series analysis to find trends and patterns, allowing more precise forecasting. More importantly, there can be instances wherein firms should be in a situation to react quickly to market changes and choice of customers by incorporating data streams from several mediums, which can improve predictive capabilities.

For instance, Walmart makes use of sophisticated algorithms and machine learning models to examine huge amounts of sales data and local events. This allows them to forecast demands for their products with accuracy, making sure the appropriate products are available in the right quantities and at the right time.

Vinay Sheel Bansal, Head of Supply Chain and Procurement, Gharda Chemicals Limited says "Machine learning plays a pivotal role in categorizing inventories, enhancing truck loading efficiency, and redesigning packaging for reuse and reduced waste"

In a nutshell, the business environment is highly competitive, and there is a huge need for predictive capabilities to improve the agility and resilience of supply chains. With the effective utilization of predictive capabilities and by making use of data-driven insights, advanced technologies, the firm can seamlessly deal with abrupt changes affecting supply chain operations and move forward. As businesses continue to stay proactive in this complex landscape, embracing predictive analytics can be smart choice for a core competency enabling them to drive competitive advantage and progress.