This is our story of leveraging supply chain management analytics, Artificial Intelligence (AI)-driven market sensing, and robust visibility and reporting frameworks to optimize inventory and the supplier network for a leading frozen foods company.
As we know…
Consumer Packaged Goods (CPG) companies encounter significant challenges in managing demand variability, presenting a landscape of complexities unparalleled in other industries. Organizations require accurate assessments to evaluate demand / supply risks, balance inventory levels and navigate the pitfalls associated with the proliferation of costly ingredients.
For sustainable revenue and a competitive edge, CPG companies must invest in supply chain analytics solutions to elevate forecasting accuracy, mitigate risks and future-proof operations.
The client grappled with a vicious cycle of challenges …
To break this cycle of challenges, WNS stepped in as a strategic advisor and co-creation partner…
Collaborating with internal teams (R&D, procurement) and external stakeholders (suppliers, third-party providers). We leveraged our supply chain data analytics capabilities to develop a tailored, ecosystem-enabled solution.
Our approach involved co-creating a framework for supply chain inventory optimization and laying out a charter for forecast accuracy improvement by infusing supply market intelligence. We deployed our AI-enabled 360-degree risk intelligence platform, which included a reporting and visibility layer comprising a front-end data visualization tool for scorecards and dashboards.
Critical aspects of the comprehensive solution included :
Demand Forecasting
- Predicted accurate future customer demand for Stock-keeping Units (SKU) using an effective combination of qualitative and quantitative data
- Developed next-generation demand-supply and inventory dashboards to monitor Key Performance Indicators (KPI) at a monthly level, such as forecast accuracy percentage, production volumes and parts availability, among others
Risk Monitoring & Early Warning
- Leveraged an AI-driven continuous risk monitoring platform, tracking financial, operational, legal / ethical, human and environmental risks
- Provided quarterly risk briefings to senior category managers and the Chief Procurement Officer to apprise them of the evolving risk landscape
SKU Ingredient Rationalization
- Identified opportunities for cash savings, reducing / harmonizing ingredient specifications and streamlining the supplier count using AI-driven SKU and Bill of Materials (BOM) rationalization
Inventory Optimization
- Determined the optimal stock levels for multiple nodes in a multi-echelon network (considering cost and service level constraints) through a dynamic inventory optimization algorithm. This algorithm is capable of adapting to changing demand patterns and lead times
Manufacturing Scorecards
- Provided visibility into manufacturing site performance across various KPIs with manufacturing scorecards – encompassing safety, quality, production, customer service, finance and sustainability
The end-to-end supply chain optimization enabled the client to…
Streamline suppliers, identify potential risks and respond to market demands promptly and cost-effectively. Establishing KPIs and scorecards empowered leaders to take informed actions for improved operations.
Tangible outcomes included:
USD
K
+
in annual savings through a
percent
reduction in ingredients and supplier base consolidation (to less than 10 suppliers)
-
percent
enhancement in material availability, attributed to consistent deliveries of required raw materials
USD
Million+
worth of inactive inventory identified through inventory analysis
-
percent
improvement in capacity across plants, driven by enhanced performance visibility from manufacturing scorecards
FAQs
1 What is AI-led supply chain risk management?
AI led supply chain risk management uses artificial intelligence, predictive analytics, and real-time monitoring to identify, assess, and mitigate supply chain disruptions. It helps businesses improve supplier visibility, forecast demand accurately, manage inventory risks, and make proactive decisions that enhance operational resilience and supply chain efficiency.
2. How does AI improve supply chain risk management?
AI in supply chain risk management improves visibility across suppliers, inventory, and operations through predictive analytics and automated monitoring. It helps businesses detect potential disruptions early, optimize inventory levels, reduce forecasting errors, and respond faster to changing market conditions while improving decision-making and operational efficiency.
3. What is AI supply chain analytics transformation?
AI supply chain analytics transformation refers to the use of AI, machine learning, and advanced analytics to modernize supply chain operations. It enables businesses to improve demand forecasting, inventory optimization, supplier management, and manufacturing visibility while driving faster insights, cost savings, and data-driven decision-making.
4. How does AI optimize frozen food supply chains?
Frozen food supply chain optimization with AI helps companies improve demand forecasting, manage inventory efficiently, reduce inactive stock, and monitor supplier risks in real time. AI-driven analytics also enhance manufacturing visibility, streamline procurement, and ensure better product availability while reducing operational costs.
5. What are the benefits of AI in supply chain analytics?
AI supply chain analytics transformation helps businesses gain real-time visibility, improve forecast accuracy, optimize inventory, and reduce supply chain risks. It also supports supplier consolidation, enhances manufacturing performance tracking, lowers operational costs, and enables faster, data-driven decisions for improved supply chain efficiency.