Most auto original equipment manufacturers (OEMs), even though they follow JIT (Just-in-Time), still have substantial component inventories and yet cannot make full kits as per plan. This outcome was quite eloquently summarised by the operations head of one of the largest OEMs in the country:  “My stores carry nearly 10-15 days of component inventory at any time, yet if I were to lock the front gate today and not allow any materials to come in, the assembly line would  stop after the next shift.”   This statement is very telling of the situation at any auto OEM.    This article explores the paradox in component management. All OEMs are trying to minimise inventory by timing component arrivals (JIT), yet inventories remain high (in terms of days of consumption). Even with high inventory levels, full-kit availability for assembly remains a daily struggle.   To set the context, let’s look at the commercial vehicle (CV) industry.  <h2>A few salient features of a CV OEM environment </h2><h3>Sales and customer conditions</h3><ul><li>Highly skewed sales: Most OEMs suffer from highly skewed sales (nearly 80%) towards every month-end. This is due to the interaction of a few factors, such as sales targets, bank loan disbursement targets, and dealer cash cycle. Very low sales during most of the month allow OEMs to plan day-wise production based on monthly sales forecasts and level-loading considerations of the assembly line. A production plan, when broken down into components, can provide a clear forecast of future requirements in terms of quantity and timing over a four-week horizon. </li><li>Low tolerance time: Customers generally have a low tolerance time and want the vehicle as soon as the purchase decision is made. The only time an OEM can reasonably expect is the time it takes for financials (loans, paperwork, etc.) to get cleared, which is usually 3-4 weeks. This usually translates into monthly buckets, as sales are skewed towards the month-end. </li><li>High model range with a long tail: The product offering is vast for any OEM, typically ranging from 1,000 to 1,500 different SKUs. Factors such as utility, price points (including premiumisation with added features), competition, and regional preferences drive this variety. The fight for market share in the CV industry is fierce, and leaving out even niche customer requirements is not an option. This leads to a long tail forming in the product portfolio, about 15% of SKUs contribute to around 80% of sales, while the remaining 85% of SKUs contribute to nearly 20%. </li><li>Higher the ageing, lower the chance of sales: A vehicle is a depreciating asset due to deterioration of its parts. Customers generally do not prefer buying vehicles that are already aged while standing in company or dealer yards. As ageing increases, OEMs have to offer sizable discounts to sell such inventory and also bear refurbishing expenses to counteract the impact of weather. This has led to an industry-wide aversion to ageing vehicle inventory. </li></ul> With such a long tail of infrequently selling variants, short tolerance-time requirements, and month-end spikes in offtake, it is not possible for OEMs to maintain perpetual stocks of all vehicle options. Hence, this forces OEMs to forecast month-end sales based on pending customer enquiries. <h2>Supply and parts conditions</h2><ul><li>High variety of parts: Typically, an auto OEM with such a wide product range on offer will have between 10,000 and 15,000 parts that are regularly used, along with another 5,000 that are infrequently used. Each vehicle is made up of nearly 2,000 different parts. Around 80% of these parts are common across at least two variants due to the modular design philosophy. Yet some variation is necessary to meet functionality and fitment requirements. Ensuring the availability of all these parts poses two major challenges:<ul><li>How much to make available</li><li>When to make available  </li></ul></li><li>High frequency of engineering changes: Product quality and reliability are two major factors in the auto industry that set the competition apart. Each OEM strives to provide highly reliable products. Continuous design corrections in parts, based on market feedback, are the norm. Hence, the longer a part remains in stock, the higher the chances of obsolescence. Any system for managing parts availability must account for future requirements, both in terms of quantity and timing.  </li></ul>Most OEMs try to manage the above complexity in parts inventory using a ‘fixed’ monthly production plan. With such planning, OEMs have an opportunity to time the arrival of parts.    This approach ensures minimal inventory and reduces the risk of obsolescence. MRP modules in ERPs help manage this complexity through accurate calculations across such a wide variety of parts. Coupled with vendor schedule management portals, OEMs generate, communicate, and track schedules to ensure components arrive just in time for the production plan. (Although MRP is used for planning and scheduling parts, many people refer to the system as ‘JIT’, which is a misnomer in the true sense. They use the term more to refer to the control of part offtake from vendors. Even if parts are scheduled using monthly MRP, actual arrivals are  mostly further throttled daily, depending on the visibility of the latest assembly schedules). Given the above understanding of the environment, any OEM should be able to manage full kits (all parts required to start and complete assembly) as per plan while ensuring lower inventories. Yet, as mentioned at the beginning, for most OEMs, the situation is quite the opposite. Inventories remain high, and full-kit availability is a perpetual struggle. The impact of this on a precisely timed supply chain system is immense. So, the question is: Why are OEMs unable to ensure full kits of parts? The variability of supply and demandNo matter how precisely a plan is laid out, both lead times and demand can change. Even after accounting for plan changes, no OEM experiences an OTIF (On-Time In-Full) of part supply higher than 90% at the schedule level. The 10% of schedules that do not arrive on time have a huge impact on production plans, as parts are shared across multiple models. The demand side is also not immune to ‘change’. Even though most sales are skewed towards the month-end, unforeseen demands sometimes emerge, prompting plan changes. The MRP-based timing system cannot account for such ‘Murphy’s law’ situations. The lack of buffers in a precisely timed system  (JIT) exposes the production plan to all possible demand and supply variability. <h2>Resultant effects       </h2><ul><li>Constantly changing plans: When certain parts are missing, a vehicle cannot be assembled, and the production plan must be changed. As soon as the plan changes, whatever the next sequence is pulled ahead to fill the gap, but it may have its own set of missing parts. This immediately turns into a ‘rush’ for parts. This rush leads to wastage in the form of unplanned set-ups, overtime, or premium freight at the vendor’s end. Also, longer lead-time parts that had already arrived for the cancelled production plan now remain in stores (in such cases, vendors cannot be informed beforehand), while the supply chain pushes out the arrival of other parts from nearby vendors. This leads to a build-up of broken full kits in stores. For infrequently consumed parts, this may lead to obsolescence and loss of vendor warranties. Firefighting stress spreads across the value chain, and the focus of SCM team shifts from ensuring future full-kit availability to expediting and pushing out parts now. As this focus shifts, future full-kit unavailability becomes inevitable, and the cycle repeats itself. The MRP planning system becomes meaningless for vendors and SCM teams, as the dates and quantities of system-generated schedules no longer reflect reality. Most organisations see changes in roughly 40% of schedules every month. </li><li>Bullwhip effect in forecasts (demand padding): For sales teams, the most important requirement is the availability of vehicles for billing at month-end. Without this, retaining potential customers becomes next to impossible. Due to the vicious loop of firefighting described above, vehicle unavailability becomes inevitable from time to time. This triggers a ‘safeguard mindset’ in the sales organisation, leading to inflated forecasts. Even though this action is intended to protect sales, it causes further harm. By inflating forecasts, material and capacity from both OEMs and vendors are stolen and parked into inventories that may not sell, while depriving other variants where true demand remains unfulfilled.  </li></ul>Clearly, the practice of MRP-based scheduling, combined with last-minute throttling of parts, is not a practical method to ensure the availability of a complete kit of parts.  How to ensure full kits of parts despite changing schedules and supply issues?One can solve problem of variability is by using stock buffers. However, most MRP systems are configured with the ‘ideology’ of JIT (the principle that any form of inventory is waste). As a result, other than demand, no additional safety stocks are planned.   <h3>Clearly, this planning ideology leads to much greater wastage of inventory and capacity during execution across the ecosystem.</h3><h3> </h3>Therefore, instead of avoiding inventory completely, using ‘logical safety buffers’ (small, planned extra stock) can:<ul><li>Protect against delays and uncertainty</li><li>Help ensure all parts are available when needed</li><li>Reduce chaos and inefficiency  </li></ul><h2> How to operationalise safety buffers</h2>MRP systems have a provision to add safety stock at the part level. The MRP logic fills safety stock first and then adds future demand to release vendor schedules. These buffers can be operationalised by adding the same as ‘safety stock’ to manage scheduling across parts. Since not all parts are regularly consumed, maintaining static buffers across all parts may still lead to inventory ageing, albeit at a lower level. There is a need to design the buffers intelligently and change them dynamically to prevent excess inventory build-up. <h2>How to design safety buffers </h2>Buffers should ideally account for demand during lead time. However, once forecasts are already considered, there is no need to build buffers for the entire lead time again.    Instead, the focus should be on the ‘minimum lead time’. <h2>Understanding the minimum lead time</h2>Every lead time can be divided into two categories: expedite-able time and touch time. Expedite-able components of lead time are usually batching-related and, from time to time, can be reduced by foregoing batching considerations. However, touch time cannot be expedited. No matter how urgent the demand, trying to reduce touch time may turn out to be prohibitively expensive or, sometimes, downright impossible.Touch time typically includes:<figure class="image"><img style="aspect-ratio:1275/362;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//presentation2_1776073908.png" width="1275" height="362"></figure> <h2>How to identify which parts to chase </h2>The MRP system calculates component-level demand by: Exploding the BOM (Bill of Materials) based on production plan (date  and quantity)<ul><li>Adding safety stock to this demand</li><li>Netting off stock on hand and pending schedules to generate a new ‘schedule’</li><li>Aggregating schedules based on the vendor’s delivery frequency. For example,  <ul><li>For a vendor delivering once a month, schedules will be aggregated at beginning of the month</li><li>For a vendor delivering every three days, schedules will be aggregated biweekly</li></ul></li></ul> By this logic, every schedule inherently contains three key pieces of information:<figure class="image"><img style="aspect-ratio:1635/391;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//presentation3_1776074033.png" width="1635" height="391"></figure>Since OEMs follow fixed monthly planning, vendors typically have visibility of four weeks of demand from the beginning of the month. However, not all schedules are equally urgent.    ‘Immediate requirements’ are those within the vendor lead time.    This group of schedules, at the vendor-part level, is defined as the ‘norm’. <h2>How to decide priority</h2>Priority should be based on the risk of stockout, not on schedule dates (see Figure 1).Figure 1<figure class="image"><img style="aspect-ratio:1381/913;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//picture-2_1776074095.png" width="1381" height="913"></figure> Which component schedule is the priority?<figure class="image"><img style="aspect-ratio:1336/213;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//presentation4_1776074341.jpg" width="1336" height="213"></figure> Further<ul><li>Later schedules of Component A (Schedule 2, Schedule 3) may have the same priority as earlier schedules of Component B</li><li>This is because they provide a similar level of protection relative to their lead times </li></ul>The goal is to prioritise based on how close a part is to running out.  Prioritising schedules based on stockout risk creates a singular priority system that subordinates to ensuring the availability of stocks.The priority signal can be further simplified (as illustrated in Figure 2). Figure <figure class="image"><img style="aspect-ratio:150/463;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//picture-1_1776074759.png" width="150" height="463"></figure>Norm is divided into three equal zones and a stockout state. The following colours are assigned to each zone:<ul><li>Black – Stocked out: Immediate action required</li><li>Red – Highest risk of stockout: Expediting action required</li><li>Yellow – Medium risk of stockout: Monitor closely</li><li>Green – Lowest risk of stockout: No immediate action required  </li></ul>Each schedule is assigned a priority colour based on its placement within the norm zone. This is represented by the schedule colour in Diagram 1.   This creates a clear visual system for easy alignment between buyers and vendors. <h2>How this solution ends the paradox </h2>By removing the root causes for ‘plan changes’ and ‘padded forecasting’, i.e., by guaranteeing full-kit availability, the triggers for waste in inventory and capacity are eliminated.     <h4>How does the solution improve full-kit availability?</h4>The ‘safety buffer’ system counters inevitable variations in demand and supply. The simple priority system ensures focus on preventing stockouts.    <h4>How does the solution reduce inventories?</h4>Counterintuitively, this system reduces overall inventory, despite building safety buffers. The inventories that build up in a ‘JIT’ system are broken full kits from cancelled plans. Such inventories are effectively a waste, as they cannot be utilised for production. By introducing safety buffers, the availability of all required parts is ensured. This eliminates ‘idle time’, the time parts spend waiting to form a full kit. This reduction in idle time brings down overall parts inventory levels in the system.   Full-kit availability as per plan also has substantial impact on finished goods (FG) availability at month-end and potentially removes the need for sales team to pad up forecasts. This behavioural change can dramatically reduce the build-up of FG and raw material (RM) inventories that arise from unrealistic (paranoid) demand projections.     <h4>How does the solution reduce firefighting?</h4>Subordinating to a single (non-switching) priority system reduces firefighting fatigue by focusing on what to chase and, equally importantly, what not to invest bandwidth in.    This safety-buffer-based scheduling priority system resolves the paradox highlighted at the beginning of the article. <h2>Expected results </h2>Based on implementations in large OEMs, the following benefits have been observed:<figure class="image"><img style="aspect-ratio:1262/706;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//results-taming-complexity_1776076430.jpg" width="1262" height="706"></figure>

Key Takeaways

Auto OEMs often face a paradox: high inventories yet frequent assembly line stoppages due to missing parts. This article explores why the current practices often fail under supply variability and how shifting to dynamic safety buffers and risk-based prioritisation can ensure full-kit availability, reduce firefighting, and improve inventory turns by 50%.

Taming complexity: Managing supply chains of commercial vehicle OEMs

Most auto original equipment manufacturers <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/industries/auto-and-auto-components/">(OEMs)</a>, even though they follow JIT (Just-in-Time), still have substantial component inventories and yet cannot make full kits as per plan. This outcome was quite eloquently summarised by the operations head of one of the largest OEMs in the country:  “My stores carry nearly 10-15 days of component inventory at any time, yet if I were to lock the front gate today and not allow any materials to come in, the assembly line would  stop after the next shift.”   This statement is very telling of the situation at any auto OEM.    This article explores the paradox in component management. All OEMs are trying to minimise inventory by timing component arrivals (JIT), yet inventories remain high (in terms of days of consumption). Even with high inventory levels, full-kit availability for assembly remains a daily struggle.   To set the context, let’s look at the commercial vehicle (CV) industry.  <h2>A few salient features of a CV OEM environment </h2><h3>Sales and customer conditions</h3><ul><li>Highly skewed sales: Most OEMs suffer from highly skewed sales (nearly 80%) towards every month-end. This is due to the interaction of a few factors, such as sales targets, bank loan disbursement targets, and dealer cash cycle. Very low sales during most of the month allow OEMs to plan day-wise production based on monthly sales forecasts and level-loading considerations of the assembly line. A production plan, when broken down into components, can provide a clear forecast of future requirements in terms of quantity and timing over a four-week horizon. </li><li>Low tolerance time: Customers generally have a low tolerance time and want the vehicle as soon as the purchase decision is made. The only time an OEM can reasonably expect is the time it takes for financials (loans, paperwork, etc.) to get cleared, which is usually 3-4 weeks. This usually translates into monthly buckets, as sales are skewed towards the month-end. </li><li>High model range with a long tail: The product offering is vast for any OEM, typically ranging from 1,000 to 1,500 different SKUs. Factors such as utility, price points (including premiumisation with added features), competition, and regional preferences drive this variety. The fight for market share in the CV industry is fierce, and leaving out even niche customer requirements is not an option. This leads to a long tail forming in the product portfolio, about 15% of SKUs contribute to around 80% of sales, while the remaining 85% of SKUs contribute to nearly 20%. </li><li>Higher the ageing, lower the chance of sales: A vehicle is a depreciating asset due to deterioration of its parts. Customers generally do not prefer buying vehicles that are already aged while standing in company or dealer yards. As ageing increases, OEMs have to offer sizable discounts to sell such inventory and also bear refurbishing expenses to counteract the impact of weather. This has led to an industry-wide aversion to ageing vehicle inventory. </li></ul> With such a long tail of infrequently selling variants, short tolerance-time requirements, and month-end spikes in offtake, it is not possible for OEMs to maintain perpetual stocks of all vehicle options. Hence, this forces OEMs to forecast month-end sales based on pending customer enquiries. <h2>Supply and parts conditions</h2><ul><li>High variety of parts: Typically, an auto OEM with such a wide product range on offer will have between 10,000 and 15,000 parts that are regularly used, along with another 5,000 that are infrequently used. Each vehicle is made up of nearly 2,000 different parts. Around 80% of these parts are common across at least two variants due to the modular design philosophy. Yet some variation is necessary to meet functionality and fitment requirements. Ensuring the availability of all these parts poses two major challenges:<ul><li>How much to make available</li><li>When to make available  </li></ul></li><li>High frequency of engineering changes: Product quality and reliability are two major factors in the auto industry that set the competition apart. Each OEM strives to provide highly reliable products. Continuous design corrections in parts, based on market feedback, are the norm. Hence, the longer a part remains in stock, the higher the chances of obsolescence. Any system for managing parts availability must account for future requirements, both in terms of quantity and timing.  </li></ul>Most OEMs try to manage the above complexity in parts inventory using a ‘fixed’ monthly production plan. With such planning, OEMs have an opportunity to time the arrival of parts.    This approach ensures minimal inventory and reduces the risk of obsolescence. MRP modules in ERPs help manage this complexity through accurate calculations across such a wide variety of parts. Coupled with vendor schedule management portals, OEMs generate, communicate, and track schedules to ensure components arrive just in time for the production plan. (Although MRP is used for planning and scheduling parts, many people refer to the system as ‘JIT’, which is a misnomer in the true sense. They use the term more to refer to the control of part offtake from vendors. Even if parts are scheduled using monthly MRP, actual arrivals are  mostly further throttled daily, depending on the visibility of the latest assembly schedules). Given the above understanding of the environment, any OEM should be able to manage full kits (all parts required to start and complete assembly) as per plan while ensuring lower inventories. Yet, as mentioned at the beginning, for most OEMs, the situation is quite the opposite. Inventories remain high, and full-kit availability is a perpetual struggle. The impact of this on a precisely timed supply chain system is immense. So, the question is: Why are OEMs unable to ensure full kits of parts? The variability of supply and demandNo matter how precisely a plan is laid out, both lead times and demand can change. Even after accounting for plan changes, no OEM experiences an OTIF (On-Time In-Full) of part supply higher than 90% at the schedule level. The 10% of schedules that do not arrive on time have a huge impact on production plans, as parts are shared across multiple models. The demand side is also not immune to ‘change’. Even though most sales are skewed towards the month-end, unforeseen demands sometimes emerge, prompting plan changes. The MRP-based timing system cannot account for such ‘Murphy’s law’ situations. The lack of buffers in a precisely timed system  (JIT) exposes the production plan to all possible demand and supply variability. <h2>Resultant effects       </h2><ul><li>Constantly changing plans: When certain parts are missing, a vehicle cannot be assembled, and the production plan must be changed. As soon as the plan changes, whatever the next sequence is pulled ahead to fill the gap, but it may have its own set of missing parts. This immediately turns into a ‘rush’ for parts. This rush leads to wastage in the form of unplanned set-ups, overtime, or premium freight at the vendor’s end. Also, longer lead-time parts that had already arrived for the cancelled production plan now remain in stores (in such cases, vendors cannot be informed beforehand), while the supply chain pushes out the arrival of other parts from nearby vendors. This leads to a build-up of broken full kits in stores. For infrequently consumed parts, this may lead to obsolescence and loss of vendor warranties. Firefighting stress spreads across the value chain, and the focus of SCM team shifts from ensuring future full-kit availability to expediting and pushing out parts now. As this focus shifts, future full-kit unavailability becomes inevitable, and the cycle repeats itself. The MRP planning system becomes meaningless for vendors and SCM teams, as the dates and quantities of system-generated schedules no longer reflect reality. Most organisations see changes in roughly 40% of schedules every month. </li><li>Bullwhip effect in forecasts (demand padding): For sales teams, the most important requirement is the availability of vehicles for billing at month-end. Without this, retaining potential customers becomes next to impossible. Due to the vicious loop of firefighting described above, vehicle unavailability becomes inevitable from time to time. This triggers a ‘safeguard mindset’ in the sales organisation, leading to inflated forecasts. Even though this action is intended to protect sales, it causes further harm. By inflating forecasts, material and capacity from both OEMs and vendors are stolen and parked into inventories that may not sell, while depriving other variants where true demand remains unfulfilled.  </li></ul>Clearly, the practice of MRP-based scheduling, combined with last-minute throttling of parts, is not a practical method to ensure the availability of a complete kit of parts.  How to ensure full kits of parts despite changing schedules and supply issues?One can solve problem of variability is by using stock buffers. However, most MRP systems are configured with the ‘ideology’ of JIT (the principle that any form of inventory is waste). As a result, other than demand, no additional safety stocks are planned.   <h3>Clearly, this planning ideology leads to much greater wastage of inventory and capacity during execution across the ecosystem.</h3><h3> </h3>Therefore, instead of avoiding inventory completely, using ‘logical safety buffers’ (small, planned extra stock) can:<ul><li>Protect against delays and uncertainty</li><li>Help ensure all parts are available when needed</li><li>Reduce chaos and inefficiency  </li></ul><h2> How to operationalise safety buffers</h2>MRP systems have a provision to add safety stock at the part level. The MRP logic fills safety stock first and then adds future demand to release vendor schedules. These buffers can be operationalised by adding the same as ‘safety stock’ to manage scheduling across parts. Since not all parts are regularly consumed, maintaining static buffers across all parts may still lead to inventory ageing, albeit at a lower level. There is a need to design the buffers intelligently and change them dynamically to prevent excess inventory build-up. <h2>How to design safety buffers </h2>Buffers should ideally account for demand during lead time. However, once forecasts are already considered, there is no need to build buffers for the entire lead time again.    Instead, the focus should be on the ‘minimum lead time’. <h2>Understanding the minimum lead time</h2>Every lead time can be divided into two categories: expedite-able time and touch time. Expedite-able components of lead time are usually batching-related and, from time to time, can be reduced by foregoing batching considerations. However, touch time cannot be expedited. No matter how urgent the demand, trying to reduce touch time may turn out to be prohibitively expensive or, sometimes, downright impossible.Touch time typically includes:<figure class="image"><img style="aspect-ratio:1275/362;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//presentation2_1776073908.png" width="1275" height="362"></figure> <h2>How to identify which parts to chase </h2>The MRP system calculates component-level demand by: Exploding the BOM (Bill of Materials) based on production plan (date  and quantity)<ul><li>Adding safety stock to this demand</li><li>Netting off stock on hand and pending schedules to generate a new ‘schedule’</li><li>Aggregating schedules based on the vendor’s delivery frequency. For example,  <ul><li>For a vendor delivering once a month, schedules will be aggregated at beginning of the month</li><li>For a vendor delivering every three days, schedules will be aggregated biweekly</li></ul></li></ul> By this logic, every schedule inherently contains three key pieces of information:<figure class="image"><img style="aspect-ratio:1635/391;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//presentation3_1776074033.png" width="1635" height="391"></figure>Since OEMs follow fixed monthly planning, vendors typically have visibility of four weeks of demand from the beginning of the month. However, not all schedules are equally urgent.    ‘Immediate requirements’ are those within the vendor lead time.    This group of schedules, at the vendor-part level, is defined as the ‘norm’. <h2>How to decide priority</h2>Priority should be based on the risk of stockout, not on schedule dates (see Figure 1).Figure 1<figure class="image"><img style="aspect-ratio:1381/913;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//picture-2_1776074095.png" width="1381" height="913"></figure> Which component schedule is the priority?<figure class="image"><img style="aspect-ratio:1336/213;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//presentation4_1776074341.jpg" width="1336" height="213"></figure> Further<ul><li>Later schedules of Component A (Schedule 2, Schedule 3) may have the same priority as earlier schedules of Component B</li><li>This is because they provide a similar level of protection relative to their lead times </li></ul>The goal is to prioritise based on how close a part is to running out.  Prioritising schedules based on stockout risk creates a singular priority system that subordinates to ensuring the availability of stocks.The priority signal can be further simplified (as illustrated in Figure 2). Figure <figure class="image"><img style="aspect-ratio:150/463;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//picture-1_1776074759.png" width="150" height="463"></figure>Norm is divided into three equal zones and a stockout state. The following colours are assigned to each zone:<ul><li>Black – Stocked out: Immediate action required</li><li>Red – Highest risk of stockout: Expediting action required</li><li>Yellow – Medium risk of stockout: Monitor closely</li><li>Green – Lowest risk of stockout: No immediate action required  </li></ul>Each schedule is assigned a priority colour based on its placement within the norm zone. This is represented by the schedule colour in Diagram 1.   This creates a clear visual system for easy alignment between buyers and vendors. <h2>How this solution ends the paradox </h2>By removing the root causes for ‘plan changes’ and ‘padded forecasting’, i.e., by guaranteeing full-kit availability, the triggers for waste in inventory and capacity are eliminated.     <h4>How does the solution improve full-kit availability?</h4>The ‘safety buffer’ system counters inevitable variations in demand and supply. The simple priority system ensures focus on preventing stockouts.    <h4>How does the solution reduce inventories?</h4>Counterintuitively, this system reduces overall inventory, despite building safety buffers. The inventories that build up in a ‘JIT’ system are broken full kits from cancelled plans. Such inventories are effectively a waste, as they cannot be utilised for production. By introducing safety buffers, the availability of all required parts is ensured. This eliminates ‘idle time’, the time parts spend waiting to form a full kit. This reduction in idle time brings down overall parts inventory levels in the system.   Full-kit availability as per plan also has substantial impact on finished goods (FG) availability at month-end and potentially removes the need for sales team to pad up forecasts. This behavioural change can dramatically reduce the build-up of FG and raw material (RM) inventories that arise from unrealistic (paranoid) demand projections.     <h4>How does the solution reduce firefighting?</h4>Subordinating to a single (non-switching) priority system reduces firefighting fatigue by focusing on what to chase and, equally importantly, what not to invest bandwidth in.    This safety-buffer-based scheduling priority system resolves the paradox highlighted at the beginning of the article. <h2>Expected results </h2>Based on implementations in large OEMs, the following benefits have been observed:<figure class="image"><img style="aspect-ratio:1262/706;" src="https://web-assets.vectorconsulting.in/storage/editor_uploads//results-taming-complexity_1776076430.jpg" width="1262" height="706"></figure>

Taming Supply Chain Complexity: Managing Inventory in Auto OEMs

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Stop the paradox of high inventory and line stoppages. Learn how CV OEMs use dynamic safety buffers and risk-based priority to ensure full-kit availability and improve inventory turns by 50%.

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