<h2>A hidden trade-off</h2>In theory, the pharmaceutical industry, like other industries, seeks to balance availability, inventory, and freshness in its distribution. In practice, however, Indian pharmaceutical companies have overwhelmingly prioritised availability over the other two. Operating in a highly profitable, product-led industry, with gross margins on many formulations exceeding 50%-60%,(1) even a small loss of sales due to non-availability is often seen as unacceptable.  <h2>The cost of ‘zero stockout’ thinking</h2>The default response to what is essentially a ‘zero stockout’ mandate is predictable: carry more inventory. As a result, many Indian pharmaceutical companies typically report 3-6 months of finished-goods inventory at an aggregate level.(2) However, SKU-level data within large firms reveals that a significant number of products carry 6-9 months of stock,(3) even though physical replenishment lead times (RLTs) from plant warehouses to depots are usually under 15 days.(4)   Even with relatively optimised production campaign cycles of 3-6 months, these inventory levels remain disproportionately high. This over-reliance on inventory as a safeguard for availability often comes at a cost, adversely impacting another critical lever in the pharmaceutical industry: the freshness of stock.<ol><li>Ageing inventory: With an average shelf life of 24-36 months,(5) SKUs that hold 6-9 months of inventory at the company or C&F level and take another 2-3 months to move through the stockist-retailer channel take roughly 8-12 months before reaching the chemist. This means approximately 33% of the total shelf life is already used up by the time it reaches the chemist. As a result, chemists may struggle to sell the products in time, or consumers may receive medicines nearing expiry, increasing the risk of customer dissatisfaction. </li><li>Increased returns and incineration: Ageing inventory in the supply chain creates an additional challenge. As per trade practice, pharmaceutical distributors and retailers often withdraw stock six months before expiry.(6) Unsold stock is then returned to centralised locations for incineration. Research shows that 78% of surveyed stockists send more than 4%-10% of inventory back to companies, primarily due to products nearing expiry.(7) This imposes a financial burden on pharmaceutical companies. </li></ol><figure class="image"><img style="aspect-ratio:4000/2189;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//image_1775046258.png" width="4000" height="2189"></figure>When products are recalled, the costs already incurred for manufacturing medicines, materials, and logistics to depots are effectively wasted. On top of this, companies must bear additional costs for reverse logistics back to incineration facilities as well as for incineration and disposal processes themselves. Across the industry, these combined losses and incremental expenses run into thousands of crores annually. The fundamental conflict  In short, the industry is stuck in a conundrum wherein: <ul><li>Improving availability requires increasing inventory, which can compromise freshness</li><li>Improving freshness requires reducing inventory, which can compromise availability </li></ul>Unable to deliver both high availability and high freshness at the same time, the industry has largely chosen to live with this dysfunction of high inventory, accepting high returns and write-offs as the cost of trying to ensure availability.    <h2>Why availability is really an illusion </h2>Paradoxically, despite all the inventory that pharmaceutical companies maintain, the availability this strategy seeks to protect often proves illusory.  The root cause lies upstream. Most pharmaceutical companies operate on a campaign-based production model because product changeovers can take anywhere from 4 to 48 hours.(8) A 48-hour changeover alone can result in nearly a 7% loss of monthly capacity. To avoid frequent set-ups, companies cluster production batches into campaigns. These plans are then ‘frozen’ for the month to maximise campaign sizes and minimise changeover losses. Once production is completed, inventory is pushed downstream in bulk, based on forecasted demand, into a highly fragmented distribution network comprising company depots or  C&F agents.<figure class="image"><img style="aspect-ratio:4000/2306;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//image_1775042871.png" width="4000" height="2306"></figure>In most pharmaceutical firms, a large portion of dispatches, often 50%-60%, occurs in the final week of the month. This spike in billing is driven by company-led target pushes and by stockists placing orders to fill visible inventory gaps before month-end. The resulting surge in dispatches can quickly deplete C&FA inventories for certain SKUs. Given long RLTs, restoring these stocks in time becomes difficult, creating pockets of low availability or stockouts. These stockouts typically last until the next dispatch arrives but often remain invisible in month-end availability reports.    Further, at this level of SKU-location complexity, demand rarely unfolds exactly as forecasted. Variability across regions, therapies, and trade channels means that many SKUs do not move as expected in specific geographies. As a result, batches produced earlier may remain unsold in some locations and begin to age, with an increasing portion drifting towards near-expiry status. To avoid regulatory and commercial risks, firms are often forced to pull back ageing stock for destruction or heavy discounting. This can sometimes create stockouts in certain markets for specific SKUs for a few days, even though the same SKU (produced in later campaigns) may still be available elsewhere in the network.  In addition, unpredictable local demand shocks, such as water- or food-borne illnesses, seasonal flu spikes, or regional outbreaks, can abruptly increase consumption at specific SKU-locations, further threatening availability.   The result is a paradox: high inventory coexists with low availability for certain SKUs at certain times.   To address unavailability, planning and sales teams are pushed into reactive firefighting, escalating urgent production requests to plants. So, the ‘fixed’ monthly plan rarely remains fixed. Urgent production requests are raised, forcing plants to accommodate them within the same cycle. This leads to a 30%-40% increase in time spent on unplanned changeovers, many of which are time-intensive molecule-to-molecule switches. <h2>The way out</h2>The real issue lies in a monthly forecast-based production system combined with push-based distribution, which leads to the above problems. Addressing this requires a fundamental shift towards producing and moving inventory in line with real consumption rather than planned volumes. This shift involves the following steps:<ol><li><h6>Producing every campaign to the latest real demand rather than a ‘monthly’ plan</h6>Instead of producing large quantities against forecasts and pushing them downstream, campaigns should be used to replenish what has actually been consumed in the market. This can be achieved by maintaining a target inventory level (buffer) for each SKU at a central location, set based on maximum demand during the production lead time (assuming raw materials are always available). Production planning should then focus only on replenishing this target. This approach reduces the risk of overproduction and inventory ageing while ensuring that SKUs, which are actually selling, are replenished reliably.  When shifting from a fixed monthly production schedule to replenishment-driven campaigns, planned changeovers may increase as production responds more frequently to actual consumption signals. However, as plants begin responding to the latest demand signals, the likelihood of stockouts at the central location, designed to hold finished goods instead of pushing them immediately downstream, becomes very low. As a result, total changeovers across the month are likely to decline or stay the same as unplanned, reactive changeovers typical of a forecast- and push-driven approach are significantly reduced. In a fixed schedule, unplanned changeovers tend to rise as the month progresses, especially towards the month-end, and often involve more disruptive and time-consuming molecule-to-molecule switches. In contrast, a replenishment-driven system enables better sequencing, resulting in larger batches, more stable campaigns, fewer molecule-to-molecule changeovers, and minimal or no unplanned interventions. Overall, changeovers become more predictable and equal to or lower in total. To further improve responsiveness, opportunities to reduce campaign sizes, through faster changeovers or equipment upgrades, can be explored to improve reaction time. Cutting changeover time by 20%-30% and trimming cycle time enable the plant to recover lost productivity from downtime while boosting overall output. </li><li><h6>Preventing the distribution push</h6>The central stocking model, which is critical for ensuring stable plant campaigns, will not materialise if the stocks are pushed to downstream locations as per monthly targets. Only by aggregating demand across multiple markets can variability be reduced, as fluctuations across locations tend to offset one another, making the overall demand signal more stable and predictable for the plant. However, inventory can be effectively pooled at a central warehouse (CWH) only if downstream dispatches are restricted to meeting consumption during transportation lead time. This enables pooled stock to be dynamically reallocated across depots as demand patterns evolve.  In practice, this means inventory should be released from the CWH only when downstream consumption creates a gap at stocking points, referred to as planned buffers. Each upstream node then prioritises replenishment based on the degree of buffer depletion and the risk of stockout at the immediate downstream node. This creates a single priority system across the supply chain, where consumption signals propagate upstream and trigger replenishment. Preventing excess inventory in the system is equally important. Shipments beyond the defined buffer limits at each node must therefore be automatically curtailed. At the same time, buffer levels must remain responsive to demand changes. As demand patterns evolve, buffers should adjust dynamically, shrinking when demand declines and expanding when demand rises.   Together, these mechanisms ensure that inventory remains concentrated at the CWH, while downstream locations hold only what is needed to replenish actual consumption. This preserves the buffering role of the CWH, keeps the system aligned with real demand, and prevents unnecessary inventory build-up. </li><li><h6>Shortening replenishment lead times: Introducing RWH</h6>However, buffer-based replenishment is only as responsive as the RLT. If the RLT from the CWH to depots across India is as long as 15 days, the system becomes inherently slow to react. During sudden demand surges, such as month-end dispatch spikes at C&FAs, which persist as long as incentives and performance reviews remain tied to monthly billing targets, or abrupt disease-driven demand, such long lead times cannot adequately protect availability. As a result, depots and stockists are forced to carry higher precautionary inventory.    To enable downstream nodes to operate with smaller buffers while still protecting availability, RLTs must therefore be reduced. Introducing regional warehouses, or RWHs (North, South, East, and West), can help achieve this. Currently, in most firms, shipments move directly from plants to individual C&F locations, requiring trucks to be formed separately for each destination. This often leads to longer and less reliable dispatch times. With an RWH serving an entire zone, shipments from the CWH can be consolidated more easily, reducing dispatch delays and overall transportation lead time. Depots can then be replenished more frequently from the RWH based on actual consumption.   Because buffer size is determined by RLT and its reliability, shorter and more predictable lead times enabled by RWHs allow C&FAs to operate with significantly smaller buffers while still protecting availability during intermittent demand spikes. As a result, a larger share of the system’s inventory naturally remains concentrated at aggregated upstream locations, such as the CWH and RWHs, enabling faster responses to localised demand changes.  At the same time, products spend less time idling in downstream nodes, leading to a significant improvement in freshness.  </li><li><h6>Ensuring system discipline</h6>For this model to sustain, certain operational practices and the way decisions are made across the network must be fully aligned with the new logic:</li></ol> <ol style="list-style-type:upper-latin;"><li>Controlled planning for large demand spikes: The system buffer can be designed to accommodate random demand spikes and even month-end sales skew. However, other extraordinary and large demand surges, such as local promotions or schemes, must be explicitly planned for as needed. If these events deplete buffers beyond what RLTs can recover, availability will be at risk.  Therefore, all such activities must be planned separately. Buffers may be temporarily adjusted, or replenishment may be triggered in advance based on the expected uplift and available lead time. The key is to absorb these events within the buffer framework, without distorting the underlying replenishment logic. Uncoordinated pushes distort consumption signals, disrupt replenishment priorities, and can destabilise the system. </li><li>Strict handling of supply disruptions: Prolonged supply constraints can trigger hoarding behaviour across the network, as downstream nodes attempt to secure inventory ahead of others. This undermines the replenishment logic and creates parallel planning systems. Such situations must be centrally managed with clear allocation, rationing, and prioritisation rules to preserve system integrity. </li><li>Automated execution and control: Managing buffers, replenishment triggers, and priority rules is a daily, high-frequency process across thousands of SKU-location combinations, making manual execution difficult. These decisions are therefore ideally placed on autopilot through systems that automatically track consumption, trigger replenishment, update buffers, and enforce priorities. This ensures speed, consistency, and discipline, preventing local overrides from gradually taking over </li><li>Continuous improvement: Despite these precautions and enablers, occasional stockout situations or excess inventory issues may still occur. These should be systematically tracked and analysed at the SKU-location level to identify root causes, whether due to parameter gaps, execution failures or changing demand patterns. Insights must then be fed back into buffer design and replenishment rules.</li></ol> <h2>The outcome</h2>The structural shift in where inventory is held, and how it moves through the system, fundamentally improves the performance of the distribution system. When RLTs are short and driven by actual consumption:<ul><li>Availability at C&F exceeds 99%, as stock is replenished before shortages materialise.</li><li>Total inventory reduces significantly by 20%-25%, as stock is adjusted to replenishment speed and reliability, rather than long forecast horizons and worst-case assumptions.</li><li>Freshness improves across the network as inventory turns faster, dwell time at C&F depots falls, and excess stock is prevented from ageing at low-consumption locations.</li><li>Incineration and returns fall sharply, as inventory is rebalanced across regions based on consumption and sales.</li><li>Margin erosion is reduced, as write-offs and emergency shipments are no longer treated as a ‘cost of doing business’.</li></ul>

Key Takeaways

Indian pharma industry’s ‘zero stockout’ trap leads to a 9-month inventory pile-up, yet local shortages persist. By shifting from a ‘push’ based methodology to a ‘pull’ based methodology, firms can reduce inventory by 25%, while ensuring 99% availability, and eliminate wastage.

The Indian pharma inventory paradox

The Indian pharma inventory paradox

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Solve the pharma inventory paradox by shifting from push based model to pull-based replenishment to reduce inventory by 25% and achieve 99%+ availability.

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