In today’s fast-evolving business landscape, customer expectations for speed, reliability, and personalization are at an all-time high. Yet, many supply chains continue to struggle with outdated processes, fragmentation, and inefficiencies that undermine their ability to keep pace. This article by Ramesh Akella, Senior General Manager – Operations & SCM, Wipro Enterprises Ltd., dives deep into the underlying reasons why traditional supply chains are falling short and lays out a bold Six-Step transformation framework. The goal? To reimagine supply chains as highly agile, tech-driven ecosystems that make the ambitious vision of 8-minute fulfillment – where orders are seamlessly processed and delivered with unmatched speed and precision – a REALITY!
In a landscape of escalating customer expectations and volatile markets, traditional supply chain management systems and their associated technologies are unable to fulfill critical SCM objectives. With forecast accuracy stagnating at about 60% across DC – channel- SKUs level, businesses are trapped in a costly cycle of excess inventory, frequent stockouts, and lost sales—leading to wasted resources, dissatisfied customers, missed opportunities, and significant profit erosion.
Ramesh Akella
CURRENT PROBLEM: LIMITATIONS IN EXISTING DEMAND AND SUPPLY PLANNING TOOL BASED PROCESS
A 2023 Deloitte survey estimates many businesses are contemplating or transitioning to advanced tools to improve prediction accuracy for Demand planning, Master Production Scheduling (MPS), and Supply planning. Despite this shift, dependency on right tools is the key link to navigate uncertain nature of the environment. Are the demand and supply planning tools really help the business to tide over the uncertainty, the response in overwhelming cases is otherwise.
According to a 2024 Gartner report, poor forecast accuracy costs businesses $1.8 trillion annually in lost sales and operational inefficiencies, leading to tangible consequences: excess inventory ties up crores in capital, while stockouts drive customers to competitors, eroding trust and revenue.
With the existing tools giving about 60% accuracy at the distribution centers the gap between current capabilities and modern expectations is stark. Customers now expect near-instant fulfillment—Amazon’s same-day delivery and local grocery apps delivering in under 30 minutes have set a new standard. Rapidly shifting consumer preferences, agile competitors, technological disruptions, and geopolitical supply chain shocks amplify this challenge.
Meanwhile, ESG mandates demand sustainable operations, adding complexity to supply chain planning. Legacy systems struggle to keep pace with real-time data, dynamic demand, or sustainability goals. Addressing these critical shortcomings is essential for building resilient, adaptive supply chains.
WHY FORECAST ACCURACY TANKS
Fixated with historical data: Relying on historical data to predict future demand is like navigating a storm with an outdated map. Multiple factors come into play like cultural trends, seasonality demography, innovations in process and products, technological breakthroughs etc render past patterns obsolete.
Supply chain professionals frequently face scenarios where distribution centers meet forecast demand, only to be later blindsided by black swan events, competitive disruptions, or sudden market shifts. For instance, viral marketing campaigns or innovative product launches, price and offer events can make demand planning awry, skew sales estimates, leaving business unprepared.
These pressures expose the limitations of relying on past data which expect the future will also pan out as in the past coupled with existing algorithm-based planning tools which are unable to keep pace with real-time data & dynamic demand render the planning process ineffective
Understanding these critical failures is the first step toward building resilient, adaptive supply chains.
Models Built for Sales: Not Stock: Current processes focus on predicting finished goods sales on historical data and algorithms manage finished goods inventory based on predicted sales. If the forecast misses, which is a common occurrence, then the inventories planned will lead to overstocking or missed sales. So are we solving the wrong problem?? Are we missing controlling controllable?
Traditional SCM processes prioritize sales. forecasting for finished goods, often sidelining inventory optimization across the supply chain as per POS data. The sales demand will go up or down based on multiple factors playing in the market. Effective SCM must prioritize resilience, ensuring the right SKU at the right inventory level to absorb market variability and meet customer expectations – so stakes on inventory management is unprecedented.
Outmoded Algorithms & Data Chaos: Current SCM tools struggle with rapid demand fluctuations, fragmented data streams, and poor data quality and besides the burden of maintaining ERP masters. Issues like inaccurate sales data, delayed reporting, and interdependent variables (e.g., weather impacting offtakes) create gaps in forecasting. Current SCM systems rely on rigid algorithms that are inadequate to adapt to real-time market led events. A 2023 McKinsey study found that 45% of supply chain effectiveness stem from data gaps, inaccuracy, or integration failures.
The S&Op Mirage: Sales and Operations Planning (SnOp) is often hailed as the backbone of SCM, but it’s become a ritual of exaggerated commitments than the market potential. SnOp meetings aim to align sales forecasts with operational plans, yet they frequently produce overly optimistic projections tied to business targets rather than market realities. The process relies on subjective judgment calls, historical data, and manual interventions, leading to forecasts that miss the mark.
For example, a 2024 Aberdeen Group study revealed that 70% of companies using advanced Sn Op tools still report forecast errors exceeding 30%. The issue?? SnOp prioritizes consensus over accuracy, resulting in plans that look good on paper but fail in execution. Optimism does not translate into results. Despite AI/ML enhancements and collaborative platforms, S&OP continues to fall short raising a critical question: does it truly drive better planning and fulfillment?"
Last-Mile Logistics Lag: In the age of instant gratification, last-mile transportation is the make-or-break moment for customer satisfaction. Consumers demand fast, affordable, and transparent deliveries-tracking updates every minute and delivery window as short as an hour. Yet current logistics systems are plagued by inefficiencies: poor route optimization, lack of real-time visibility, and reliance on outdated communication channels. Social media and platform reviews have abundant posts expressing customer frustration over delayed deliveries—highlighting the stark gap between expectations and reality. In effect, even well-executed upstream operations are undermined by inefficient last mile logistics. To bridge this gap, express logistics must evolve—leveraging smarter technology to meet rising demands while reducing costs and minimizing environmental impact.
SIX-STEP SCM OVERHAUL
To realize the vision of 8-minute fulfillment future where planning and execution harmonize like a Beethoven score, enabling orders to be processed and delivered at lightning speed, businesses must reimagine supply chain management from “Ground Up”. The following six-step strategy blends real-time data, lean principles, and ESG imperatives to build agile, sustainable, and customer-centric supply chains.
1. Replace Long-Term Sales Guesses with Short-Term Inventory Optimization
Shift from long-term sales forecasting to short-term finished goods inventory predictions. Focus on what’s needed now by leveraging real-time demand signals from POS systems, social media trends, and IoT devices. For example, Zara uses real-time sales data to adjust inventory weekly, reducing overstock by 15% (Forbes, 2024). This approach minimizes waste and aligns with universal business of reducing excess production.
2. Bet on Inventory optimization tools
Replace complex planning suites with Multi-Echelon Inventory Optimization (MEIO) tools for streamlined supply chain efficiency. Start small by implementing a basic inventory management tool to test its fit for your business, then gradually transition to advanced optimization solutions. Prioritize a phased approach to ensure effective change management and stakeholder buy-in, which are as critical as achieving high fill rates.
Integrate MEIO with locally developed production planning tools that capture real-time demand signals from consumption points to optimize scheduling across production lines. These inventory tools should enhance efficiency across all supply chain layer factories, warehouses, and stores. Leading companies using lean-focused MEIO tools have reduced inventory costs by up to 10%, driving cost efficiency and supporting sustainability goals.
3. Schedule Smarter with Real Data
Base production schedules on consumption, inventory depletion and signals from insights from secondary sales (e.g., retailer sell-through data) rather than gut feelings or outdated projections. This data-driven approach ensures production aligns with actual demand, reducing waste and supporting ESG waste reduction targets.
4. Pull, Don’t Push
Adopt a pull-based manufacturing system with lean inventory buffers to handle short-term demand and supply fluctuations. Unlike push systems, which flood the supply chain with goods based on forecasts, pull systems produce only what’s needed based on real-time demand. Toyota’s Just-In-Time (JIT) model is a prime example, reducing inventory holding costs by 30% (Harvard Business Review, 2023). Lean buffers also minimize overproduction, aligning with ESG environmental goals.
5. Leverage Tech for Last-Mile Excellence
Invest in AI-driven logistics platforms to optimize last-mile delivery. Tools like route optimization algorithms, real-time tracking, and predictive analytics shall be helpful For example, Amazon’s AI-powered logistics reduced last-mile costs by 20% in 2024 (Bloomberg). Drones and autonomous vehicles, already in use by companies like UPS, can further accelerate deliveries while reducing carbon emissions, supporting ESG Scope 3 goals.
6. Embed ESG Across the Supply Chain
Integrate ESG principles into every step of the SCM overhaul to ensure sustainability and stakeholder trust. These goals vary by industry and company size but align with broader sustainability and ethical standards. Few ESG SCM priorities…
Environmental: Use renewable energy in warehouses and electric vehicles for logistics to reduce all categories of emission. Decrease water consumption, eliminate single use plastic, reforestation etc
Social: Ensure fair labor practices in the supply chain, such as auditing suppliers for ethical standards, diversity and so on...
Governance: Maintain transparent reporting of supply chain metrics, verified by third-party audits, anti-corruption, etc.
AGILE FULFILLMENT VISION
The 8-minute fulfillment future is not a pipe dream—it’s a tangible goal enabled by technology and strategy. Imagine a customer ordering a product online and receiving it within minutes via a hyper-optimized supply chain: real-time demand signals trigger instant production adjustments, Inventory ensures stock is perfectly positioned, and AI enabled logistics services deliver the order. The result is a win-win: delighted customers and a sustainable business.
CHALLENGES TO OVERCOME
Data Integration: Unifying real-time data from diverse sources (e.g., POS, IoT, social media) requires robust IT infrastructure.
Cost of Transformation: Adopting inventory models (not complex demand prediction tools) , AI, and green logistics , demands upfront investment, though long-term savings offset costs.
Supplier Alignment: Convincing suppliers to adopt real-time data sharing and sustainable practices can be slow.
Regulatory Hurdles: ESG compliance, such as Scope 3 emissions reporting, adds complexity but is non-negotiable.
The agile fulfillment future demands a radical rethinking of supply chain management. By abandoning outdated forecasting, embracing real-time data, and leveraging inventory prediction models and AI, businesses can achieve unprecedented speed, efficiency, and sustainability. Integrating ESG principles ensures these changes benefit not just the bottom line but also the planet and society. The time to act is now—those who adapt will lead the charge in the next era of supply chain excellence.
Categories
