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In SAC Smart Discovery simulation how is the base value calculated?

What prompted me to ask is that I have a negative which doesn't appear to reflect the data. The target column is 'Number of Non-Conformances' (measure) which can only have a positive or zero value.

All other measures are excluded, so only analysing dimension influencers.

Thanks

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is this because there are characteristics which lower the likelihood and which raise the likelihood. If greater weighting of lowering characteristics is selected it is possible to predict below zero?

Henry_Banks
Product and Topic Expert
Product and Topic Expert
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Hi Angus, please could you add a screenshot or two so that we can picture the use-case and anomaly here?

Kind regards, H

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hi Henry thanks hopefully these explain.

negative base value:

then change Booking Status dimension and the expected value is also negative:

also unsure how the change in booking status influence value equates to the change in the overall expected value

thanks

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Answers (3)

Answers (3)

former_member357026
Discoverer

Hi Angus,

The Simulation within Smart Discovery is based on regression models and shows how a combination of contributors (values of our influencers) impact a target (the measure we are interested in).

So, for each value (that we can change independently or all together), we know how it positively/negatively/neutrally contributes to the overall target.

Now, if we looking at the chart, which helps visualizing the whole configuration, Base Value is a "retro calculation" made for assessing whether the combination of contributing values we are looking at brings an increase or a decrease on the target overall.

flavia.moser, please feel free to chime in and complete my answer.

Kind regards,

Jérôme.

achab
Product and Topic Expert
Product and Topic Expert

Hi henry.banks I would agree on your suggestion on a general standpoint. I am not directly in charge of this experience though, so I'll leave the final word on the next steps to flavia.moser. I think Flavia is out of office for the time being, so hopefully she can get back to us next week at best.

Kind regards,

Antoine

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Thanks for the input guys. flavia.moser if it helps explain / investigate, the JF Tech demo also returns negative base values. Although as i say this isn't really the question, it is understandable that a combination of influencers could have a negative result. The question is more how the base value is calculated - ie is it an averaged weighting for all influencers not shown in the simulation - and why does it change when you change simulation values

Henry_Banks
Product and Topic Expert
Product and Topic Expert

Hi Angus,

I don't know much about your key influencers here, so difficult to say in context.. what you are seeing here are the various 'contributions by variable' as identified by the automated classification/regression models used in Smart Discovery.

Under the covers, this is the same approach as SAP's Automated Analytics - built using Cloud Platform's "Predictive Business Services " REST APIs. it is moreless this statistical approach: https://help.sap.com/viewer/c36bc49d7cce4d35a2099aecdea81e2c/3.2/en-US/c1fcbb766d764665ba0b67c420da8...

.. And implemented using this cloud service: https://help.sap.com/viewer/20cd1b0396db4826a9b76b4ce869f00a/Cloud/en-US/e8bda9b653ff4b48a702124e277...

Maybe we can do more to enhance our own documentation, have help tips to guide the user, or at least link out to deeper existing resources? bentonli flavia.moser antoine.chabert what do you guys think?

.. but yes, SAC doesn't know that the target 'Base Value' can't be negative in your case. Alas, there's no way or setting in SAC to say 'force this continuous variable to show positives-only, or specify a lower limit' before running the algorithm.

A similar problem can be seen when using Time Series Forecast, where negative values are projected. Infact, we're implementing a checkbox 'force positive forecast' to help users only chart positive values, so I'll bring some attention to your requirement.

Infact we're expecting big gains soon with new predictive capabilities (in a number of different directions), so perhaps we can revisit these topics during the UK Partner event in mid-May?

Kind regards,
H