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Leveraging technology to build resilient and sustainable supply chains
By Rishi Trivedi
Published On December 19, 2023
Leveraging technology to build resilient and sustainable supply chains
In this article we will articulate how organizations can leverage technology and analytics to drive resilience in Supply chain management. Traditionally, evaluation of supply chain function has been driven largely by vanilla metrics such as reliability, timely delivery and financial efficiency. In the recent past, owing to globalization of businesses leading to a highly competitive environment, sustainability and resiliency are fast becoming twin goals for evaluating supply chains in the context of risk management and business continuity plans.
Sustainability versus resilience
Sustainability refers to factoring ecological effect and societal impact arising out of all activities of the supply chain through the entire journey. It includes sustainable initiatives such as zero carbon emissions from operations and transport, efficient use of scarce water resources and the concept of circular economy in order to achieve zero waste through recycle and reuse. The concept is fast gaining momentum in the backdrop of the UN2030 Agenda for sustainable development. Resilience in supply chain is all about the ability of supply chain function to weather uncertainties and risk factors adequately in order to ensure global availability at the right time and this includes environmental sustainability as well.
Common challenges faced by organizations in supply chain management
Supply chain refers to the complete value chain encompassing demand forecasting, supplier network planning, procurement and production, inventory management and transportation up to last mile delivery. There is a myriad of challenges that organizations face when it comes to achieving resiliency in supply chain functions.
1. Supply chain function is a vast expanse and encompasses a network of firms that are going to work in tandem in order to deliver the product or service to the end consumer. The number of players involved across the value chain in itself poses a big challenge. While some of the players may be Tier 1 suppliers, there are several Tier II and Tier III players that are not even visible to the organizations.
2. Most supply chains are still controlled by legacy systems that are neither digitized nor connected, rendering it impossible to provide even basic data for informed decision making. That makes implementing both resiliency and sustainability initiatives a far cry.
3. Finally, sustainability initiatives cannot be managed if there is no way to measure the impact of the efforts due to scattered and disintegrated touch points and information flow.
Role of technology supply chain analytics in addressing the challenges
Industry 4.0 has empowered businesses with new age tools that can create interconnected information systems and empower players with access to real time data to make informed decisions. Leveraging technology enhances productivity, helps mitigate risks and builds resilience. According to statistics from Gartner, eighty-two percent of CEOs in supply-chain-intensive industries plan to increase investments in digital capabilities across their enterprise. Let us articulate how this can be achieved and how it can impact businesses positively.
· Automation of repeat operations
Manual and repetitive tasks can be automated to bring about efficiency in operations, resulting in faster throughput and productivity, shorter delivery times and cost efficiency. Employee health and safety are added benefits from automating manual processes involving physical activity and reducing manual labor involvement. Let us take an E-commerce store as an example. Flipkart significantly improved delivery time by introducing automated sorting and packing in their operations which instantly translated to improved customer service and loyalty and helped them stay ahead at a time when Amazon were on a market consolidation drive. Gartner predicts that “75% of large enterprises will have adopted some form of intralogistics smart robots in their warehouse operations by 2026.”. The automation is also aimed to address lack of labor availability constraints and cost optimization.
· Digitization of processes
Supply chain digitization refers to leveraging technology to transform data from analog processes to digital formats across the value chain. Supply chain processes when digitized will help to integrate the entire supply chain ecosystem, making it visible to all the players. Data that is integral to decision making will transition from back end to a dashboard in the form of business intelligence. This will enable tracking. analyzing and planning activities in a dynamic and agile way. For example, there could be a customer order cancellation or a machinery breakdown that has impacted production planning. These are information that should be available in real time to all stakeholders so that they can respond to consequences as needed in their respective areas and take quick and informed decisions based on real time data.
· AI and ML for supply chain analytics
Demand forecasting is by far the most important and the very first step in building resilient supply chains. When we increase accuracy in demand forecasting, it has a ripple effect in stock holding, increased purchase efficiency and improved working capital efficiencies. Advanced technologies such as data analytics AI and ML will help to optimize decision making and bring about agility in operations. Supply chain analytics can help with three dimensions to analytics.
Predictive analytics -The how
Augmenting supply chains with predictive analytics will provide answers to questions about what could happen in the future and thereby improve the quality of demand forecasting and ensure optimization of inventory levels. Predictive analytics will forecast future trends based on past data analytics and will use AI models to factor in new situations that could create variation in demand. Excess inventory could lead to blockage of working capital and even wastage in case of perishable goods while shortage of inventory could lead to loss of customer trust due to non-availability when in demand. Hence, predictive analytics for demand forecasting is pivotal to resilient supply chains.
Diagnostic analytics – The why
Once supply chain functions are digitized, diagnostic analytics is a powerful tool that will help to analyze vast amounts of data from the past and provide answers to questions on why certain things went wrong and happened the way it turned out. For example, an unexpected fluctuation in demand or a faulty distribution system or a plant breakdown or a campaign that did not align with forecast. The diagnostic tools will analyze the root cause and present situation to the prescriptive team to take over.
Prescriptive analytics -The what
Finally, predictive analytics will prescribe the action that needs to be taken to factor in findings from predictive and diagnostic analytics. This will cover all touch points across value chain and optimize production and purchase planning, warehouse optimization, optimizing logistics efficiency , such that last mile delivery happens in a most efficient and cost-effective manner while ensuring customer expectations are satisfactorily fulfilled.
At Anamind, we build robust supply chain solutions for planning and forecasting which has helped businesses across sectors and revenue sizes to build accuracy and agility. This has resulted in significant increase in customer satisfaction levels besides significant operational efficiencies and cost savings.
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