"Finally," Leo said, "multiply that 'average season' by each Seasonal Index."
One rainy Tuesday in March, her cousin Leo, a data analyst visiting from the city, saw her frantically scribbling inventory notes on a napkin.
Her profit margin increased by 18% not because she sold more ice cream, but because she stopped buying for summer in winter. how to calculate seasonal variation
He drew four boxes on the napkin. "First," Leo said, "write down your total sales for each season for the last two years."
Elena calculated: Last year's total = $70k + $25k + $12k + $35k = $142,000. Plus 10% growth = $142,000 × 1.10 = total for next year. "Finally," Leo said, "multiply that 'average season' by
"Yes," Leo smiled. "An index of 1.0 means 'exactly average.' Below 1.0 is low season. Above 1.0 is high season." "Now you can predict next year," Leo said. "First, forecast your total sales for next year using a simple trend—say, you expect 10% growth because you're adding outdoor seating."
"Exactly. That's the 'flat line'—what you'd sell per season if there were no seasons at all." "Now for the magic," Leo said. "For each season, divide its average by the overall average. That gives you the Seasonal Index ." "First," Leo said, "write down your total sales
And every year, she recalculated the indices using the latest three years of data, because seasons shift. A new boardwalk hotel opened, boosting spring sales. Her Spring Index crept up from 0.99 to 1.10.