Accommodating SCAM

• Much of the data is affected by SCAM, so values of ‘1’ are not seen

• We can identify general ‘small’ flows by looking at those with a revised total of 3

• We can estimate the proportion of these that had originally had a value of ‘1’

• By applying flow frequencies observed in un-modified Scottish data
• By generating a mean value across multiple affected tables