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SmartData Collective > Uncategorized > Understanding Value
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Understanding Value

TeradataAusNZ
TeradataAusNZ
4 Min Read
Understanding Value
Illustration generated with FLUX.1 [schnell] via Cloudflare Workers AI.
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It is interesting when we talk about the value of a customer (sometimes referred to as profitability). There are a number of different rules of thumb presented as the best way to derive value; the approach tends to be determined by the use of the outcome. Marketing wants to understand value to be able to differentiate services and offers, while finance wants to reconcile to the GL, and so on. Some approaches have flexibility to be a little wrong and others strive for perfection. So there is no wonder that the conversation of customer value causes so much excitement in organisations.

The challenge that becomes evident very quickly is that there is no such thing as the perfect model or a right way to build a model, there is only a wrong way in the eyes of the end users. Users will never use a model once it has been deemed incorrect for purpose, hence the proliferation of profitability models in organisations. In my experience organisations have at a minimum three different profitability based models, there is no wonder that a profitability conversation is so passionate! How do you move towards accepting a single model?

The adoption of any model takes time, people need to understand the rules and assumptions that have been used when building the model, for all users to agree to its make up. Education needs to evolve with the capabilities of the organisation and model to ensure that people stay onboard. The complexity of the model needs to provide the end users of the model with the information required to perform their jobs.

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The only gotcha is that the model needs to have the ability to become more complex over time, using more detailed information and more detailed rules as the organisation matures. On day one, no user is going to be interested in drilling down five levels to understand the why’s. But in time they will, consequently the model needs to be able to support detailed investigation not just a score without any context.

 

Daniel Tehan

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