The client, a two-wheeler manufacturer based in India, wanted to deep dive into the motorcycle market in India and understand the supply chain process for the top players in India. The goal was to identify the supply side gaps created by the current offerings in the industry and the customer demands.
The approach looked at every aspect of the supply chain for two-wheeler manufacturing with the top-selling brands as examples. We used data collected from different stakeholders along the supply chain; logistics partners, original equipment manufacturers and vendor tie-ups.
The first step was to define and estimate the market size of the budget two-wheeler industry, followed by key player benchmarking and financial analysis and analyzing corporate structures and vendor tie-ups in India. We identified the key top-selling players in the budget motorcycle industry and deep dived into their supply chain process and logistics partners to observe best practices and industry trends.
We backtracked the supply chain to the previous stage of production; original equipment manufacturers. We identified the several original equipment manufacturers (OEMs) in the industry and compared their working with the OEMs providing auto parts to the top players. We also looked at production capabilities across vendors to identify potential partner OEMs. The bill-of-materials for each of the shortlisted OEMs were also analyzed to look for any supply issues faced by these companies.
We then looked at corporate structures and tie-ups from other two-wheeler manufacturers and other firms down the supply chain in India to look at the success stories and possible best practices. We also looked at past financial statements to determine the financial requirements and performance of other players in the industry along the supply chain, setting organizational benchmarks for the client.
Following the analysis, the findings and recommendations were shared with the client, wherein we suggested the strategic choices for vendor tie-ups with the client to improve their production numbers efficiently.