Guide to Reviewing Sales Forecasts

Guide to Reviewing Sales Forecasts

Please consider coming up with a best case, worst case, and most probable sales forecast.  

• ASSUMPTIONS:  In deciding what the three scenarios are, what assumptions have you made to come up with these forecasts?  (Note: assumptions need to be made explicit for transparency and assessment and eventually, for comparison of actual vs. plan during implementation reviews.  It has been said that assumptions can kill and so these need to be explicitly documented and reviewed.)
• TRENDS:  Are these three forecasts data-based?  If so, what data did you look at?  How far back did you look at?
• PROJECTIONS:  Looking at the sales trends for the past three years, how would your sales forecasts compare with projections?  Projections are extrapolations or extensions of the past three-year sales trend to the next three years (2018, 2019 & 2020).  Targets are normally greater than projections because the latter is what you would expect to get if nothing changes internally or externally.
• LEVELS OF ACHIEVEMENT:  Again, looking at the past three-year sales data, what was the level of achievement of previously forecasted sales?  How accurate have they been?  Are stores hitting their quotas? What is the percentage forecast error? Has this been the trend in the past three years? Have variances been reviewed and causes identified?  Have these variances been considered in coming up with the sales forecasts?
• SEGMENTATION:  Are sales data segmented per type of location (leading malls, community malls, transport stations, outside malls, etc.), location within (ground floor, second floor, food court, activity center, etc.), and other relevant groupings or segments?  How does a consideration of the segmented sales results of the past three years affected your sales forecast?
• DATA PROCESSING:  How are sales data processed?  Are they immediately averaged?  Have outliers (extremes) been carefully accounted for?  How do you treat these outliers? How dispersed are the data (if range of data is more than 20%, it may not be appropriate to simply average the data)?
• COMPARISONS:  Have you looked at the sales data of direct and indirect competitors? (Ways of getting these include published sources, suppliers, informal conversations of sales ambassadors with sales people of competitors, etc.).  Have you looked at industry averages for similar operations? (These may be available from industry associations, publications, etc.).  Internal benchmarking may be the next best thing if competitor data are not available.
• PROPOSED INITIATIVES:  Have initiatives been proposed to support achievement of the proposed forecasts?  Have these initiatives been quantified in terms of the sales they would generate?  If yes, are these initiatives more than enough to hit the proposed sales targets?  If not, are there other sales initiatives that you can propose for you to hit your targets?
• RISK MANAGEMENT:  What are the risks involved in proposed initiatives? Have you identified potential problems for each one?  What contingency actions have you prepared in case these problems become manifest?  In other words, do you have a Plan B or even a Plan C?  How do you mitigate the risks to minimize their effect?

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