New Delhi: Vector Consulting Group, a leading management consulting company, has unveiled a research-based report on the Indian auto manufacturing industry’s implementation of Just-In-Time (JIT), an inventory management practice.
Renowned for challenging conventional wisdom across various sectors and employing a system-oriented approach to solving chronic industry problems, the consulting firm, in this report, is questioning JIT.
JIT is a pull-based inventory movement method known for significantly reducing inventory costs, enhancing efficiency, lowering waste, and improving responsiveness. Without a pull system for inventory which is in sync with the market, smaller players (tier 2/3) in the auto supply chain often face the bullwhip effect — sudden shifts in orders and bloated inventory — leading to potential disruptions in operations and financial strain.
After Toyota pioneered JIT in the 1970s, the company’s resounding success inspired widespread adoption and adaptation of JIT among other automakers worldwide. The India Auto industry too created auto hubs to bring suppliers closer, streamline logistics, and foster collaboration. Therefore, this industry (compared to others) is best geared to fully implement JIT (including Kanban and Heijunka) in the end to end supply chain.
However, contrary to expectations, the report based on the survey and interviews conducted by Vector Consulting Group uncovers that, even after half a century, NO Indian OEM seems to have successfully implemented JIT in their end-to-end supply chain (spanning from suppliers to dealerships). While most OEMs (75%) have implemented JIT practices in their production processes, their supply chain and distribution partners have not been fully roped in. (One exception seen is of an MNC OEM who has done a zero inventory model at dealer level, with real demand from end consumer demand triggering inventory movement. Some have also done a demand-pull replenishment for only spare parts from their OEM warehouse to dealers.)
Most follow a mixed push-pull system – i.e. of monthly/weekly forecast-based ordering from dealers, scheduling monthly production requirements from suppliers with daily inventory movement to OEM plants as per demand. Further, while many suppliers (tier 1) are engaged in ‘JIT partnerships’ by some OEMs, there are clear signs that the inventory benefits are skewed only towards the OEMs.
The study drew these conclusions after examining the inventory practices of major Indian OEMs, Tier 1/2 suppliers.
Achal Saran Pande at Vector Consulting said, “Indian auto manufacturing industry is growing rapidly, and to become the world’s automobile manufacturing hub, it is essential to streamline our supply chain practices. The market has evolved, and hence, systems such as JIT, which delivered success earlier, will not necessarily thrive in today’s volatile environment. At the same time, going to the other end and deploying a non-pull-based approach leads to stock pileups, increased costs and low capital turnover. Hence, we need a ‘pull’ based approach which protects the supply chain from high and varied lead times and dampens variability in the market while also ensuring high end-to-end supply chain agility.”
Recognizing the limitations of JIT in the way it’s currently implemented in India and pointing to the conceptual lacuna that limits the methodology’s implementation in an environment of high demand variability (with the proliferation of models and variants with each OEM), as well as high and highly lead times for supplies (global supply chains), Vector proposes a more effective end to end pull system that can ensure the benefits usually expected from JIT to OEMs while offering a practical win for all their partners.
The proposed solution involves:
·Completely abandoning forecast or sales /targets for every-day decisions on inventory creation in production and its movement to warehouse locations
·Dampening demand variability with the help of strategically placed buffers and implementing a system of ‘buffers replenishing buffers’ based on consumption triggers from lower nodes in the supply chain.
·Implementing an execution-based priority to deal with variability in demand and capacity so that the system gets clear signals on what to focus upon, when total demand across products exceeds capacity
·Putting in place a method for periodically changing buffer levels by intelligent sensing of any change in demand patterns both in the recent past and that expected in near future.
