<h2>An inspiring history</h2>The operational practices of almost every player in the <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/industries/auto-and-auto-components/">automobile and auto component</a> industry are greatly influenced by the pioneering innovations of Henry Ford and Taichi Ohno. Henry Ford used space as a 'forced' limitation in the shop floor layout to ensure a rapid flow of inventory. Piled-up inventory in the allotted space forced a cascading stoppage of the entire line, and this simple mechanism ensured that everyone focused on flow rather than just producing to utilise the capacity of individual workstations. The 'assembly line' concept, a simple mechanism, helped Ford create a benchmark in making the Model T car – the total lead time to produce a Model T was 81 hours (from raw material mining to loading a car for dispatch). Ford was hugely successful with the Model T and became the most dominant car manufacturer during the 19th century.  Later, Taichi Ohno, inspired by the working of supermarkets in the US, developed the concept of Kanban cards, which did the same magic as Ford’s innovation of space limitation in an environment of a large variety of SKUs. The card or a physical bin (dedicated to an SKU) indicated the quantity of a specific SKU’s inventory. As per the process, the card or the bin is released only when the succeeding work centre consumes the quantity in the card or the bin. No one is allowed to manufacture or move inventory without triggering a Kanban card or without the bin being available. This ensured a focus on flow (as opposed to just work centre utilisation) in an environment with a wide variety of SKUs.  The physical bins or cards could then be used to set up an ongoing improvement process. The plant can keep reducing the number of Kanban cards, which will, in turn, expose the various flow problems. Other tools and techniques were invented to ensure plants could remove the obstacles to flow, such as setting up of reduction techniques, standardisation, 5S, etc. The entire manufacturing system is now famous as the Toyota Production System (TPS). It is also known as JIT (Just-in-Time) manufacturing. The operational practices of TPS helped Toyota produce highly reliable yet affordable cars for the masses. By the late 20th century, Toyota had built a decisive competitive edge in the market. It was able to make strong inroads into the US market, previously dominated by the big three of the US auto market.  <h2>Learning from history</h2>Most auto plants in India use some form of Kanban system or restricted bins (or restricted carriages to hold SKUs). Some plants deliberately limit space to force the flow of inventory. For example, the purchase material store in many OEM (Original Equipment Manufacturer) and Tier-1 auto component organisations have space limitations to carry enough inventory to cover a few shifts of production. With minimal inventory on the production floor and in incoming stores, and the implementation of other TPS (JIT manufacturing) tools like 5S and cellular layout, most plants look clean and organised. Visually, these clean plants give the impression that years of effort have gone into implementing the best flow system and that the auto OEMs’ supply chains are very stable.  <h2>Is that really the case?</h2>The stability of a <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/research-and-publication/blogs/transforming-demand-into-sales-how-supply-chain-completes-the-missing-link/">supply chain</a> can be gauged by two parameters: the level of expediting and the stability of the inventory profile in the chain. To understand the level of instability, one needs to first appreciate the complexity of an auto supply chain. Auto plants, whether automobile or Tier-1 component plants, are mostly assembly-oriented. Each end SKU requires multiple parts to arrive together for assembly. Non-availability of a single feeding part can delay assembly of the SKU. The level of stability of a plant is directly indicated by the availability of complete kits for the planned assembly schedule. The higher the kit coverage (number of days of planned production for which kits are complete), the more stable the plant is. Our research and experience in the Indian <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/industries/auto-and-auto-components/">auto industry</a> show that most auto OEMs and component manufacturing plants suffer greatly from poor kit coverage. It is not uncommon to have many incomplete kits of SKUs at the day level, particularly for those being demanded immediately by the customer. Purchase managers struggle to get kits for a day. Frequent rescheduling due to incomplete kits further aggravates the kit availability problem. The purchase manager of the OEM or even the purchase manager of a component vendor is in expediting mode throughout the day, trying to somehow get adequate kits to meet the production plan of the day. The production schedules are not stable for even a day, and at times not even for a shift.  Most auto supply chains in India lack the stability of schedules. At the same time, the inventory of the entire supply chain goes haywire from time to time. For example, during every economic downturn, the OEM dealer inventory balloons many times, and the OEMs’ reaction to production corrections usually has a significant lag (about 6-7 months). This leads to a 'bullwhip' effect, and the inventory goes haywire for many players in the chain. At the same time, every month-end, the auto OEM’s inventory level drops, with a huge spike in dispatches in the last week. A similar inventory problem exists with the component vendor, whose warehouses usually hold a month’s inventory even though they are a few hours away from the assembly plants of the auto OEM’s assembly plants. Despite having a month’s inventory, the OEMs do not seem to have the component SKU they need for the day. Theoretically speaking, instability indicators (high expediting and varying inventory levels) should not be seen in a supply chain, which is supposed to move inventory based on ‘just in time’, only on a pull trigger, like availability of space or a bin.   We need to analyse if the auto supply chains have really implemented JIT manufacturing principles or is it the case of a few visible 'props' on the shop floor.  Limitation of space or bins makes the supply chain extremely sensitive to flow issues when demand is widely fluctuating. Toyota has been able to deal with the challenge of deliberate bin limitations through standardisation process and the deliberate smoothening of demand (at the SKU level) for customers.  But most Indian auto OEMs have not been able to impose the smoothening of SKU demands across time horizons and are therefore severely exposed to wide fluctuations at the SKU level. At the same time, changing Euro norms have increased the rate of new product introduction at a component level. When new components are replacing old ones frequently, the number of bins must be re-defined frequently, which in turn makes it impossible to be in a process of ongoing improvement (the baseline of the number of bins is not fixed to bring about a continuous process of reduction of bins to expose the flow problems). In this environment, strictly following bin-availability-based production across the entire chain is nearly impossible. So, they have made a compromise: used the bins to move inventory between the component vendor and the OEM, but not to trigger production with the Tier-1 vendor. If the bin is not used to trigger production, then one has to bear the brunt of high inventory. So, the 'solution' that most auto OEMs have devised to force the weaker partner in the chain to provide the required protection. The auto OEMs maintain enough inventory to cover a few shifts of production at their incoming stores and insist that their Tier-1 vendors keep adequate stock at warehouses near their assembly lines. The stocks are produced not based on a pull trigger (of a bin or a card), but on a 'push' as per the OEM’s forecasted schedules.  The same is true for dealers – they receive inventory based on OEMs’ sales targets. It is not aligned with the actual rate of secondary sales. Most auto OEMs in India do not have a Kanban system for inventory movement between the dealer and the OEM, as the demand fluctuations across time horizons for an SKU are high, and they have not been able to enforce smoothening of SKU demand on the market.   <h2>An ineffective connotation of push and pull</h2>As a result, most auto supply chains become botched-up combinations of a push system with few 'visible' elements of pull system mechanisms in restricted locations of the supply chain. Tier-1 and Tier-2 vendors operate on forecasted schedules provided by the OEM every month. Due to plant scheduling and material planning based on the OEM’s monthly or weekly forecast, the vendors’ ability to respond quickly to the OEMs’ daily production plan changes is restricted. Therefore, they fail to meet changing requirements at a daily level. Many <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/industries/auto-and-auto-components/">auto component</a> vendors analyse their performance against the OEM’s initial monthly plans and give themselves high marks. At the same time, issues such as rescheduling, searching for missing components and daily expediting requests remain on the problem lists of both the OEM and the Tier vendor.  <h2>The way forward</h2>How does one improve the auto supply chain? Most OEMs and auto component vendors have an ineffective supply chain where the level of finished goods inventory is many times higher than the level of incoming component inventory level. This is despite the fact that the component level holds the highest form of aggregation (the same component can be used across many end SKUs). It is not uncommon to find components required to complete an SKU missing, while the same components have already been used up in an SKU that is unlikely to be dispatched in the near future. One can argue that the same component could have been used to produce what is required rather than produce what is not required. If one can reverse the inventory pattern at OEM, an OEM stands to gain a lot without changing the way all Tier vendors work.  We know that an auto component vendor has already invested in space to maintain buffers for OEM. So, if we are able to have the right inventory profile at a daily level, then an OEM can still enjoy a low inventory of components while having good availability of the feeding components.  If one wants to move an entire auto supply chain from a push to a pull system and implement JIT manufacturing in its true sense, the best place to start is the demand side of the auto OEM. We can reduce dealer-level demand spikes by moving inventory from the OEM to the dealer only based on consumption, not on a sales target. The consumption-based movement also requires holding higher aggregated inventory at the central warehouse than at the dealers’ end. Production at the OEM can also be based on warehouse consumption rather than the sales forecast. Pull-based planning, along with a periodic process to change the inventory norm based on changes in the observed sale rate (as compared to the supply rate), can help auto OEMs to practically implement pull systems without having to resort to forced smoothening of demand at the SKU level for the customer. When one OEM switches to pull-based inventory movement at the dealer level, the immediate impact would be better smoothening of load on the plant and, subsequently, on the multiple-tiered component vendors (This article does not get into details of how a pull-based system can be implemented at the OEMs; this is a subject for a separate article. The focus of this article is on component vendors). In the current paradigm of push-based functioning, most auto component vendors are expecting improved forecast accuracy from OEMs as the answer to the puzzle. The OEMs, however, believe that component vendors need adequate capacity buffers to absorb any kind of variation. Is there a way out of this conflict?  Forecasts can never be accurate at a component level – the OEM’s component requirements are dependent not just on vehicle offtake forecasts but also on the impact of changing production schedules due to incomplete kits. It is nearly impossible to mathematically model the vicious loop of rescheduling decisions to forecast component requirements with any reasonable accuracy. So, the only way out for component vendors is to shift from push-based production to pull-based production, even though they have a monthly offtake schedule from the auto OEM. So, instead of trying to adhere to the OEM’s monthly schedule, they need to produce the actual offtake from the warehouse. To reduce disruptions in the plant at a daily level, they need a buffer level that protects them from maximum consumption during the supply lead time. Consumption from the buffer level (or the norm level) can be the trigger for daily production. The norm level is the artificial lock – no one is allowed to move inventory or produce above the norm (e.g., in terms of the use of space or in response to Kanban cards). However, if the supply lead time is long, the level of demand spikes imposed on the plant is high. To minimise the impact of spikes, it is important to reduce the supply lead time. Most auto component vendors actually have short production lead times, but the supply lead time goes up due to the unavailability of various feeding components (procured from Tier-2 vendors). The problem is aggravated by the lack of adequate space at the purchase stores. There is a need for adequate space to ensure good supply of feeding components. The feeding component inventory (of Tier-2 vendors) should be enough to accommodate demand during the feeding component’s supply lead time. Procurement triggers should not be based on forecasts but on daily consumption. Once adequate inventory buffers are available for the feeding component (incoming components from Tier-2 vendors), the supply lead time for components fromTier-1 vendors comes down.  The level of inventory for incoming feeding inventory can go up in the short term. Still, the finished goods inventory can come down dramatically – there should be a net reduction in total supply chain inventory for the Tier-1 vendor. Once all sub-components are available on a daily basis, the ability of plant to respond to changing requirements is greatly enhanced, as the spike gets smoothened too. Since the offtake at the component level will vary, the level of available inventory at the finished component warehouse of the vendor will differ from the buffer level. For example, on a daily basis, some SKUs will have low stock levels compared to the norm, while others will have high stock levels. The level of stocks, as compared to the norm, can be used as a priority system for production and dispatch. An SKU with actual stock closer to the norm (between 2/3rd of the norm and the full level of norm) can be tagged as green, while those between 1/3rd and 2/3rd of the norm can be marked as yellow, and those below 1/3rd of the norm can be tagged as red. SKUs that are at red level of inventory need to be prioritised over yellows and greens. The priority system is important, as reacting to consumption of even small quantities might be difficult due to setup and other production considerations. The colour system gives the plant the flexibility to make production decisions. The same colour system can be used to determine whether the sales rate is higher than the supply rate and to trigger changes in the norms (Ideally, in a stable system, most SKUs should stay in the yellow zone). The same colour-based priority system can be implemented for feeding components to the incoming side. One can work on a process of ongoing improvement by helping suppliers (Tier-2 vendors) reduce their supply lead times, which in turn will reduce the level of inventory at the Tier-1 vendor. Our experience of implementing the above system over a one-year period has shown that total inventory turns can be improved from an average of six per year to about 18 per year. But this requires sustained effort with a partnership-based approach to help each Tier-2 vendor improve their lead time. It is important to build win-win partnerships with vendors and let go of promiscuous relationships based solely on price reductions.  As they say, win-win and lose-lose are the only practical possibilities in every relationship. Win-lose is just a temporary phase that deteriorates into lose-lose within no time. So, the only way to ensure a win for us is to ensure a win for the other party in the relationship.

Key Takeaways

The Indian auto industry grapples with inherent challenges while attempting to implement JIT, resulting in a supply chain that combines both push-based systems and JIT. The article advocates a shift towards a buffered pull-based inventory movement system that can provide the envisioned advantages of JIT to all partners in the end-to-end supply chain.

Auto supply chain in India – A mishmash of 'Push' and 'Pull' methods

<h2>An inspiring history</h2>The operational practices of almost every player in the <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/industries/auto-and-auto-components/">automobile and auto component</a> industry are greatly influenced by the pioneering innovations of Henry Ford and Taichi Ohno. Henry Ford used space as a 'forced' limitation in the shop floor layout to ensure a rapid flow of inventory. Piled-up inventory in the allotted space forced a cascading stoppage of the entire line, and this simple mechanism ensured that everyone focused on flow rather than just producing to utilise the capacity of individual workstations. The 'assembly line' concept, a simple mechanism, helped Ford create a benchmark in making the Model T car – the total lead time to produce a Model T was 81 hours (from raw material mining to loading a car for dispatch). Ford was hugely successful with the Model T and became the most dominant car manufacturer during the 19th century.  Later, Taichi Ohno, inspired by the working of supermarkets in the US, developed the concept of Kanban cards, which did the same magic as Ford’s innovation of space limitation in an environment of a large variety of SKUs. The card or a physical bin (dedicated to an SKU) indicated the quantity of a specific SKU’s inventory. As per the process, the card or the bin is released only when the succeeding work centre consumes the quantity in the card or the bin. No one is allowed to manufacture or move inventory without triggering a Kanban card or without the bin being available. This ensured a focus on flow (as opposed to just work centre utilisation) in an environment with a wide variety of SKUs.  The physical bins or cards could then be used to set up an ongoing improvement process. The plant can keep reducing the number of Kanban cards, which will, in turn, expose the various flow problems. Other tools and techniques were invented to ensure plants could remove the obstacles to flow, such as setting up of reduction techniques, standardisation, 5S, etc. The entire manufacturing system is now famous as the Toyota Production System (TPS). It is also known as JIT (Just-in-Time) manufacturing. The operational practices of TPS helped Toyota produce highly reliable yet affordable cars for the masses. By the late 20th century, Toyota had built a decisive competitive edge in the market. It was able to make strong inroads into the US market, previously dominated by the big three of the US auto market.   <h2>Learning from history</h2>Most auto plants in India use some form of Kanban system or restricted bins (or restricted carriages to hold SKUs). Some plants deliberately limit space to force the flow of inventory. For example, the purchase material store in many OEM (Original Equipment Manufacturer) and Tier-1 auto component organisations have space limitations to carry enough inventory to cover a few shifts of production. With minimal inventory on the production floor and in incoming stores, and the implementation of other TPS (JIT manufacturing) tools like 5S and cellular layout, most plants look clean and organised. Visually, these clean plants give the impression that years of effort have gone into implementing the best flow system and that the auto OEMs’ supply chains are very stable.  <h2>Is that really the case?</h2>The stability of a <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/research-and-publication/blogs/transforming-demand-into-sales-how-supply-chain-completes-the-missing-link/">supply chain</a> can be gauged by two parameters: the level of expediting and the stability of the inventory profile in the chain. To understand the level of instability, one needs to first appreciate the complexity of an auto supply chain. Auto plants, whether automobile or Tier-1 component plants, are mostly assembly-oriented. Each end SKU requires multiple parts to arrive together for assembly. Non-availability of a single feeding part can delay assembly of the SKU. The level of stability of a plant is directly indicated by the availability of complete kits for the planned assembly schedule. The higher the kit coverage (number of days of planned production for which kits are complete), the more stable the plant is. Our research and experience in the Indian <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/industries/auto-and-auto-components/">auto industry</a> show that most auto OEMs and component manufacturing plants suffer greatly from poor kit coverage. It is not uncommon to have many incomplete kits of SKUs at the day level, particularly for those being demanded immediately by the customer. Purchase managers struggle to get kits for a day. Frequent rescheduling due to incomplete kits further aggravates the kit availability problem. The purchase manager of the OEM or even the purchase manager of a component vendor is in expediting mode throughout the day, trying to somehow get adequate kits to meet the production plan of the day. The production schedules are not stable for even a day, and at times not even for a shift.  Most auto supply chains in India lack the stability of schedules. At the same time, the inventory of the entire supply chain goes haywire from time to time. For example, during every economic downturn, the OEM dealer inventory balloons many times, and the OEMs’ reaction to production corrections usually has a significant lag (about 6-7 months). This leads to a 'bullwhip' effect, and the inventory goes haywire for many players in the chain. At the same time, every month-end, the auto OEM’s inventory level drops, with a huge spike in dispatches in the last week. A similar inventory problem exists with the component vendor, whose warehouses usually hold a month’s inventory even though they are a few hours away from the assembly plants of the auto OEM’s assembly plants. Despite having a month’s inventory, the OEMs do not seem to have the component SKU they need for the day. Theoretically speaking, instability indicators (high expediting and varying inventory levels) should not be seen in a supply chain, which is supposed to move inventory based on ‘just in time’, only on a pull trigger, like availability of space or a bin.   We need to analyse if the auto supply chains have really implemented JIT manufacturing principles or is it the case of a few visible 'props' on the shop floor.  Limitation of space or bins makes the supply chain extremely sensitive to flow issues when demand is widely fluctuating. Toyota has been able to deal with the challenge of deliberate bin limitations through standardisation process and the deliberate smoothening of demand (at the SKU level) for customers.  But most Indian auto OEMs have not been able to impose the smoothening of SKU demands across time horizons and are therefore severely exposed to wide fluctuations at the SKU level. At the same time, changing Euro norms have increased the rate of new product introduction at a component level.   When new components are replacing old ones frequently, the number of bins must be re-defined frequently, which in turn makes it impossible to be in a process of ongoing improvement (the baseline of the number of bins is not fixed to bring about a continuous process of reduction of bins to expose the flow problems). In this environment, strictly following bin-availability-based production across the entire chain is nearly impossible. So, they have made a compromise: used the bins to move inventory between the component vendor and the OEM, but not to trigger production with the Tier-1 vendor. If the bin is not used to trigger production, then one has to bear the brunt of high inventory. So, the 'solution' that most auto OEMs have devised to force the weaker partner in the chain to provide the required protection. The auto OEMs maintain enough inventory to cover a few shifts of production at their incoming stores and insist that their Tier-1 vendors keep adequate stock at warehouses near their assembly lines. The stocks are produced not based on a pull trigger (of a bin or a card), but on a 'push' as per the OEM’s forecasted schedules.  The same is true for dealers – they receive inventory based on OEMs’ sales targets. It is not aligned with the actual rate of secondary sales. Most auto OEMs in India do not have a Kanban system for inventory movement between the dealer and the OEM, as the demand fluctuations across time horizons for an SKU are high, and they have not been able to enforce smoothening of SKU demand on the market.   <h2>An ineffective connotation of push and pull</h2>As a result, most auto supply chains become botched-up combinations of a push system with few 'visible' elements of pull system mechanisms in restricted locations of the supply chain. Tier-1 and Tier-2 vendors operate on forecasted schedules provided by the OEM every month. Due to plant scheduling and material planning based on the OEM’s monthly or weekly forecast, the vendors’ ability to respond quickly to the OEMs’ daily production plan changes is restricted. Therefore, they fail to meet changing requirements at a daily level. Many <a target="_blank" rel="noopener noreferrer" href="https://www.vectorconsulting.in/en/industries/auto-and-auto-components/">auto component</a> vendors analyse their performance against the OEM’s initial monthly plans and give themselves high marks. At the same time, issues such as rescheduling, searching for missing components and daily expediting requests remain on the problem lists of both the OEM and the Tier vendor.  <h2>The way forward</h2>How does one improve the auto supply chain? Most OEMs and auto component vendors have an ineffective supply chain where the level of finished goods inventory is many times higher than the level of incoming component inventory level. This is despite the fact that the component level holds the highest form of aggregation (the same component can be used across many end SKUs). It is not uncommon to find components required to complete an SKU missing, while the same components have already been used up in an SKU that is unlikely to be dispatched in the near future. One can argue that the same component could have been used to produce what is required rather than produce what is not required. If one can reverse the inventory pattern at OEM, an OEM stands to gain a lot without changing the way all Tier vendors work.  We know that an auto component vendor has already invested in space to maintain buffers for OEM. So, if we are able to have the right inventory profile at a daily level, then an OEM can still enjoy a low inventory of components while having good availability of the feeding components.  If one wants to move an entire auto supply chain from a push to a pull system and implement JIT manufacturing in its true sense, the best place to start is the demand side of the auto OEM. We can reduce dealer-level demand spikes by moving inventory from the OEM to the dealer only based on consumption, not on a sales target. The consumption-based movement also requires holding higher aggregated inventory at the central warehouse than at the dealers’ end. Production at the OEM can also be based on warehouse consumption rather than the sales forecast. Pull-based planning, along with a periodic process to change the inventory norm based on changes in the observed sale rate (as compared to the supply rate), can help auto OEMs to practically implement pull systems without having to resort to forced smoothening of demand at the SKU level for the customer.  When one OEM switches to pull-based inventory movement at the dealer level, the immediate impact would be better smoothening of load on the plant and, subsequently, on the multiple-tiered component vendors (This article does not get into details of how a pull-based system can be implemented at the OEMs; this is a subject for a separate article. The focus of this article is on component vendors).   In the current paradigm of push-based functioning, most auto component vendors are expecting improved forecast accuracy from OEMs as the answer to the puzzle. The OEMs, however, believe that component vendors need adequate capacity buffers to absorb any kind of variation. Is there a way out of this conflict?  Forecasts can never be accurate at a component level – the OEM’s component requirements are dependent not just on vehicle offtake forecasts but also on the impact of changing production schedules due to incomplete kits. It is nearly impossible to mathematically model the vicious loop of rescheduling decisions to forecast component requirements with any reasonable accuracy. So, the only way out for component vendors is to shift from push-based production to pull-based production, even though they have a monthly offtake schedule from the auto OEM.  So, instead of trying to adhere to the OEM’s monthly schedule, they need to produce the actual offtake from the warehouse. To reduce disruptions in the plant at a daily level, they need a buffer level that protects them from maximum consumption during the supply lead time. Consumption from the buffer level (or the norm level) can be the trigger for daily production. The norm level is the artificial lock – no one is allowed to move inventory or produce above the norm (e.g., in terms of the use of space or in response to Kanban cards).   However, if the supply lead time is long, the level of demand spikes imposed on the plant is high. To minimise the impact of spikes, it is important to reduce the supply lead time. Most auto component vendors actually have short production lead times, but the supply lead time goes up due to the unavailability of various feeding components (procured from Tier-2 vendors). The problem is aggravated by the lack of adequate space at the purchase stores. There is a need for adequate space to ensure good supply of feeding components. The feeding component inventory (of Tier-2 vendors) should be enough to accommodate demand during the feeding component’s supply lead time. Procurement triggers should not be based on forecasts but on daily consumption. Once adequate inventory buffers are available for the feeding component (incoming components from Tier-2 vendors), the supply lead time for components fromTier-1 vendors comes down.  The level of inventory for incoming feeding inventory can go up in the short term. Still, the finished goods inventory can come down dramatically – there should be a net reduction in total supply chain inventory for the Tier-1 vendor. Once all sub-components are available on a daily basis, the ability of plant to respond to changing requirements is greatly enhanced, as the spike gets smoothened too.  Since the offtake at the component level will vary, the level of available inventory at the finished component warehouse of the vendor will differ from the buffer level. For example, on a daily basis, some SKUs will have low stock levels compared to the norm, while others will have high stock levels. The level of stocks, as compared to the norm, can be used as a priority system for production and dispatch. An SKU with actual stock closer to the norm (between 2/3rd of the norm and the full level of norm) can be tagged as green, while those between 1/3rd and 2/3rd of the norm can be marked as yellow, and those below 1/3rd of the norm can be tagged as red. SKUs that are at red level of inventory need to be prioritised over yellows and greens. The priority system is important, as reacting to consumption of even small quantities might be difficult due to setup and other production considerations. The colour system gives the plant the flexibility to make production decisions. The same colour system can be used to determine whether the sales rate is higher than the supply rate and to trigger changes in the norms (Ideally, in a stable system, most SKUs should stay in the yellow zone).   The same colour-based priority system can be implemented for feeding components to the incoming side. One can work on a process of ongoing improvement by helping suppliers (Tier-2 vendors) reduce their supply lead times, which in turn will reduce the level of inventory at the Tier-1 vendor. Our experience of implementing the above system over a one-year period has shown that total inventory turns can be improved from an average of six per year to about 18 per year. But this requires sustained effort with a partnership-based approach to help each Tier-2 vendor improve their lead time. It is important to build win-win partnerships with vendors and let go of promiscuous relationships based solely on price reductions.  As they say, win-win and lose-lose are the only practical possibilities in every relationship. Win-lose is just a temporary phase that deteriorates into lose-lose within no time. So, the only way to ensure a Win for us is to ensure a Win for the other party in the relationship.

<h4>Auto supply chain in India – A mishmash of 'Push' and 'Pull' methods</h4>

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<h4>Auto supply chain in India – A mishmash of 'Push' and 'Pull' methods </h4>

Read more about creating fully pull-based supply chain systems based on Theory of Constraints in Indian auto companies.