Question

Ability to differentiate overall health scores created by the use of exceptions from those that are not in reports on Scorecards 2.0

  • 18 September 2017
  • 2 replies
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We would like to be able to create reports that can distinguish whether the value of an overall health score is due to the use of an exception or just due to the calculated score based on the weights of the measures.



At this time, all of our measures are automated via the rules engine, but our CSM's use exceptions to flag at-risk accounts they are alerted to via person-to-person interactions regardless of whether or not the account looks healthy 'on paper' based on the score calculated from the automated measures. We would handle an exception risk differently than a calculated risk, and we would like to be able to report on these differences as well as fire CTA's to managers based on exception risks.



Since the C360 view of the scorecard 2.0 denotes when an exception is being used or not, I was hoping this would be a reportable field, but sadly, it is not. Would love to see this make the roadmap!

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Hi Brittany,



It's great to see that you're using the exception logic available in Scorecards 2.0! Are you able to share what your exception logic looks like? Is it just driven off of a single measure that CSMs use to capture their subjective sentiment? 



One thought on a possible way to report on this would be to build an at-risk report that included in the filter to exclude/include any exception driven risks where you'd use the criteria that drives the exception in the scorecard (for example: CSM Sentiment <50) in the filter for that report. 



Alternatively you could create an at risk report that showed only the overall score and the CSM sentiment score so you could visually see examples where the CSM sentiment was below your exception threshold. 



Would any of these work for your use case?

I would love to see this as an option in reporting as well. We use a similar exception for a CSM to overwrite the overall score if they flag an account because of information we learn directly from the customer.

While the exception makes sense for measuring risk in most cases, if I want to analyze the effectiveness/predictiveness of our scorecard, it’s challenging to do because by the time a customer has churned, in almost all cases the score is already red because our CSMs have flagged the account. So it gives a false sense of how predictive the rest of our score actually is.

Additionally, if I want to analyze the health of the customers who we are considering at risk, the score is a self-fulfilling prophesy because we’ve already manually dictated that the score is red, but in a case like this, I’d like to see how their score stacks up if I ignored the exception.  For instance, I’d like to be able to look at all our at-risk renewals for the year, at a glance, and see it by score, but because we’ve already designated these as at-risk, they are by definition red because of the exception.

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