Structural Shifts in Spare Parts Ecosystems
Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry?
I worked with Maruti Suzuki for 38 years & got superannuated in 2023 as a senior advisor for Vehicle logistics & Spare Parts operations at the Gujarat plant. Before that, I was General Manager- Spare Parts & Logistics & was handling Spare Parts- Planning, Inventory control, Pricing & Warehouse operations (including regional warehouses across India).
Have also worked in Sales & Marketing and Production verticals at various positions. At present, I do consultations both online & at the site.
Q2. How has the spare parts and logistics ecosystem evolved over the past decade, and which shifts do you believe are truly structural rather than cyclical?
In India, all OEMs are looking for ways to reach customers faster; in this endeavor, they are building warehouses in each Indian zone.
Q3. Where have digital tools or analytics genuinely improved demand forecasting and fill rates, and where have they failed to deliver practical impact?
With the increasing no of SKUs they deal with, it is practically impossible to work without a forecasting tool & improve the service ratio. These tools fail to generate accurate forecasts for parts used in new models & models that are going to be discontinued.
Q4. Where do you see OEMs underestimating opportunity while independent or digital players are quietly gaining ground?
It is not independent players gaining ground; it is the suppliers (vendors) to OEMs capturing the market.
Q5. Where do sustainability initiatives in spare parts logistics most often break down when they meet real cost and service-level pressures?
The milk run system & truck fill ratio are important factors for logistics efficiency.
Q6. Which tiers of the automotive supplier ecosystem are most vulnerable to geopolitical shocks today?
Suppliers dependent on overseas companies for raw materials or inner parts are most vulnerable to geopolitical uncertainty.
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