What is a trend you see in an industry of interest? Take rooftop solar for small factories: size the yearly install market as adoption climbs an S-curve, find when it peaks, and say what share Suryavik Energy would need for Rs 500 crore of revenue.

The yearly install market crosses Rs 5,000 crore in year 2, peaks at Rs 8,000 crore in years 3 and 4, then shrinks as adoption saturates. It is the change in adoption, not its level, that sets each year's market. Suryavik would need 6.25% of the peak market for Rs 500 crore, but 16.7% by year 7 and half the market by year 8, so the trend favours installers who build a recurring business on the installed base.

Think of mobile phones in a village. The year most families buy their first phone is the busiest year for the phone shop; once most families own one, sales fall back to replacements, even though phone ownership is at its highest ever. The yearly market for installs is the change in adoption, so it peaks where the S-curve is steepest and falls as adoption flattens, even while the number of factories with solar keeps rising. That distinction is the insight an interviewer wants from a trend question: a trend is a curve, and where you are on it decides what kind of business wins.

Each point of adoption is 5,000 factories, and each factory is a Rs 40 lakh install, so each point is Rs 2,000 crore of installs. Adoption rises 2 points in year one, Rs 4,000 crore; 3 points in year two, Rs 6,000 crore, crossing Rs 5,000 crore; and 4 points in each of years three and four, the Rs 8,000 crore peak. Then the steps shrink: 3, 2, 1.5 and 0.5 points, taking the yearly market down to Rs 1,000 crore by year eight. Across the eight years the market installs Rs 40,000 crore in total.

At the peak, Rs 500 crore is 6.25% of an Rs 8,000 crore market, about 1,250 installs a year. Holding Rs 500 crore after the peak means taking share every year, from about 6% to 17% by year seven, in a fragmented market where installers compete mostly on price. That is the hidden risk in a pure installer: its revenue tracks the slope of the S-curve, and the slope turns down just as the company scales. A thesis built on this trend would favour the installer that keeps a relationship with each factory after the install.

Revenue that grows with the installed base rather than with new installs. If maintenance, monitoring and financing earn, for illustration, Rs 400 per kW a year, the 23% of factories with solar in year eight would generate about Rs 460 crore a year, growing while installs shrink. Then ask how sensitive the forecast is: a fall in panel prices would cut the rupee value per install even as it speeds adoption, and a change in the rules for selling surplus power to the grid could move the whole curve. Say that the adoption path is your forecast, and that the peak's timing, not its existence, is the uncertain part. The limitation: this sizing ignores factories adding capacity later and replacing panels after their life, both of which add a tail to the market.