Q1. Could you start by giving us a brief overview of your professional background, particularly focusing on your expertise in the industry? 

In 2026, I will complete 23 years in the fashion and Omnichannel Retail domain. Having worked across Export houses, International Brands, Domestic Retail Chains, Digital Retail Chains, and Omnichannel new-age brands, I have been building and scaling businesses for 18 years. 

Starting with Reliance Industries Ltd, where in 2008 I built, launched, and scaled the concept of Popup stores for its Brand Only Vimal, growing businesses to 2500 Cr in Gross revenue. I was lucky to have the opportunity to lead these initiatives across various organisations. 

My key expertise lies in building up businesses from 0 up and scaling them up in a much more sustainable manner, considering customer experiences as the prime.

 

Q2. What is the one 'hidden friction point' in the Indian fashion supply chain that could cause a systemic margin collapse in the next 24 months? 

The biggest challenge or hidden friction point in the Indian fashion supply chain is ensuring uniform merchandise across regions, cultures, and geographies with diverse customer preferences. This leads to certain regions having higher sell-through and stockouts, while other regions have no or lower sell-through for merchandise that is not suitable for the consumer in those regions. This further leads to two situations: 

Stock Transfers

Efficient retail brands do stock transfers across different states, zones, or regions to optimize inventory. However, the downside of this is that it results in loss of sales for the days the inventory is in transit, plus by the time it reaches the new region, the impulse demand might have faded away, or the trend might have died down, resulting in inventory pileup, which results in discounting, which eats away at your margin earnings.

Deep Discounts 

The other situation is due to the complexities of processes, bigger formats or brands look at not moving inter-store stocks in different regions but run deep discounts to liquidate the inventories, eating away the earned margins. 

 

Q3. With 3 out of 5 new shoppers in 2026 coming from Tier 2 & 3 cities, how did your experience with Reliance Smart / Trends Small Town inform a distribution strategy that accounts for lower basket sizes but higher loyalty? 

Region- or demographic-centric assortment, with a key focus on local fashion trends amplified by regional movie stars or influencers, is key for tier 2 and 3 cities and towns. This helps in higher conversions and a better customer connect. Consumers generally ape the trends that are adorned by their favorite celebrity or influencer, thus the micro trends of a region or emerging from these tier 2 or 3 cities need to contribute significantly to the data points driving assortment plan and range creation for these cities and towns accordingly.

 

Q4. 2026 sees a rise in discretionary spending by India's aging 'Silver Economy.' How are companies adapting the Category Management for a demographic that values 'Comfort and Quality' over 'Pop Culture Trends'?

It is interesting to observe that even the value based fashion retailers as well as the mid economy brands and formats are quickly adapting to global trends driven by brands like Zara, Uniqlo, M&S wherein instead of the pop culture trends, the value based Indian retailers are picking up trends of Affordable Fashionable Comfort from the International brands while not compromising on adaption of the latest trends relevant to the Silver Economy age group from these brands. Thus, it creates an inclusive product range that appeals to the aging silver economy as well 

 

Q5. With Gen Z driving the 2026 demand for gender-neutral and circular fashion, how do you quantify the ROI of a 'sustainable' category versus its higher sourcing cost? 

Sustainability on the sourcing front can be broadly classified into 3 segments: 

• Sustainable raw material 
• Recycled Raw Material 
• Thrifting

For sustainable raw materials like organic cotton, for natural dyes sourcing costs are high, for sure. However, for say, recycled polyester or cotton material, the sourcing cost is slightly lower. However, we are missing out on a major trend that is picking up with Gen Z: Thrifting. This is something brands need to engage with to ensure we can stop the problem of resource-intensive manufacturing of new clothes and reduce their environmental and carbon footprint.

Like how you have outlet stores of Brands, it needs to pick up on Thrift Stores of Brands to enable a better ROI on the sustainability front, as this kind of sustainability initiative would have lower sourcing cost impacts.

 

Q6. How are companies moving from 'Historical Procurement' to 'Predictive Sourcing' using AI to anticipate 2026 cotton price volatility? 

Companies are leveraging AI to analyze real-time data, simulate "what-if" scenarios, and automate procurement decisions. To anticipate 2026 cotton price volatility, this transition involves some of the following ways, which are being adopted

AI-Powered Price Forecasting Platforms: Companies are deploying specialized AI tools like cotcast.ai (built on Microsoft Azure) to analyze global production, demand, stock levels, and weather data. These tools offer substantial accuracy in cotton price forecasting, enabling companies to make 1-cent-accurate decisions on raw material pricing to secure margins.

Predictive 'Should-Cost' Models: Instead of relying on supplier quotes, AI models now calculate the "should-cost" of cotton by analyzing factors like weather patterns, freight rates, and geopolitical risks. This allows procurement teams to negotiate based on facts rather than market noise.

Agentic AI for Automated Decision-Making: By 2026, AI agents will sit within core business processes, moving beyond just providing dashboards. These agents can automatically identify risks, suggest alternatives, and even trigger purchasing actions (e.g., hedging against cotton price spikes) within predefined guardrails.

Integrating Diverse Data Streams: Predictive systems analyze unstructured, real-time data, including social media, satellite imagery, and localized weather data (temperature, humidity), to correlate environmental changes with yield, anticipating shortages well in advance. 

Regionalized Sourcing: AI enables companies to regionalize supply chains to reduce reliance on highly volatile global markets by using predictive analytics to identify the best, lower-risk suppliers.

 

Q7. If you were an investor looking at companies within the space, what critical question would you pose to their senior management? 

First and foremost, questions to be asked:

How are we planning assortment at a regional state zone level, considering tastes and preferences like language and food habits change every hundred kilometers in the country, to ensure better sell-throughs and lesser inventory pileup

What is the key differentiator in the product and service offering vs the farthest competition? Even if we are not able to differentiate from the farthest competition, I think we should not stand a chance of succeeding

Whom are we benchmarking our product and brand to, and what do we aspire to be as a brand?

What are the unit economics working of each product they are launching? 

What are the alternate revenue models they are considering apart from Omni Channel Retail (Offline and Online) and quick commerce platforms?

What are they planning on product, tech, and customer experience to be ahead of the competition curve?