Wednesday, December 17, 2008

How to analyze sales data

Do you need to analyze your data?

Just as the analogy of not needing a map when you know where you are going, in a world where you only have one sales person and one customer, there is little need to track sales MI. Just as you want to segment your customer base such that you know each of their needs, so you want to segment your sales force such that you have perfect insight into their activities, successes and areas for improvement.

With a national sales force you thus needs to consider breaking them into segments, whether that be by geography or type. Customers purchase products, they rarely purchase or see the sales person or company as a region or as a product only. As such, your data needs to get to product specific as soon as is feasible. For example, you may create a dashboard with sales by region by product. To provide context a target is required. The sales may need to be weighted where for example one product delivers significantly more GP than another, or where the wider organization has set targets for specific product lines. So, put simply, you need data. Without it you are flying blind.


Targets themselves can be used as buffers. For example, if you take a monthly target and divide it by the number of working days, then round up to the nearest integer, the integer multipled by the number of working days will be higher than the original total. To arrive at an accurate daily target simply multiply the monthly target by the % of the days gone to date. The difference will thus trickle through each day. If you chose the first approach, then towards the end of the month the month to date target will be some 6% higher than the actual; in the event the target is not being hit the target can thus be moved. Whether you do this is a moot point, the very optionality is valuable.


Once you have this data, you have to explicitly recognize the impact of constrained time, that is you need to be clear that all your actions in the sales space will drive activity either now or in the future. Given the time constraint, the ideal action will not only impact the chosen team/ region, but will have a knock-on effect to other regions. Given this, the below represent the classic steps that maximise time vs. likely value whilst flushing out the key insights:

* Compare the ranking of the top three regions by YTD against target
o Insight - consistently top ranked performer will only continue to deliver to the extent that they risk losing their top spot. So, initially in the year, make them famous, to the extent that they have something to lose if they drop below. Mid way, provide insights and focus action on second and third placers to drive their performance.
* Compare product performance across each region vs. target
o Insight - if one region is performing very well with a particular product, then highlight to low performing regions as example of what can be achieved.
* Compare performance over last three weeks against performance
o Insight - you need to be able to assess whether you actions are having the desired effect; three weeks is enough time to see a reaction; if there is none then ask whether it is a lost cause or if there is still scope for improvement.

The key driver of the decision is the quality, or not, of the people in the team, in particular the leader, quickly followed by whether there are enough people in the team in the first place. The leader needs to be taking the situation seriously and conveying that the target is achievable.

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