If I understand well, your requirement is to compare sold quantity in month t with the sum of quantity sold in months t-1 and t-2. If so, I can suggest using dplyr package that offer the nice feature of grouping rows and mutating columns in your data frame.
resultData <- group_by(data, KId) %>%
arrange(sales_month) %>%
mutate(monthMinus1Qty = lag(quantity_sold,1), monthMinus2Qty = lag(quantity_sold, 2)) %>%
group_by(KId, sales_month) %>%
mutate(previous2MonthsQty = sum(monthMinus1Qty, monthMinus2Qty, na.rm = TRUE)) %>%
mutate(result = ifelse(quantity_sold/previous2MonthsQty >= 0.6,0,1)) %>%
select(KId,sales_month, quantity_sold, result)
Adding
select(KId,sales_month, quantity_sold, result)
at the end let us display only columns we care about (and not all these intermediate steps).
I believe this should satisfy your requirement. NA is the result column are due to 0/0 division or no data at all for the previous months.
Should you need to expand your calculation beyond one calendar year, you can add year column and adjust group_by() arguments appropriately.
For more information on dplyr package, follow this link
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