Revenue Intelligence & Analytics

When everyone thinks the same,

nobody's thinking very much.

Walter Lippman

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Sales intelligence and revenue intelligence needn't be oxymoronic.  More often than not though, they are.

Companies don't generally make very good decisions based upon data or evidence - particularly when they pertain to sales and revenue.

Even today, they still make most of their decisions by looking very casually at what other companies have done or are doing.  Or they make decisions based on what they've done in the past, or what one or more of their senior exec's did or saw at another company.  Either way, they observe or hear about things they think have worked, with no forensic analysis, systematic evaluation or follow up.  When sales results go up, down or sideways, senior executives only very rarely ask why a particular result did or did not happen.

They base their decisions on what they believe to be true or what they think ought to work, often in the face of overwhelming evidence that something isn't in fact true or isn't working or can't ever work.

As opposed to understanding what works - and why it works, and then rationally deciding to do it again or do it more often.

Imagine going to a doctor and asking them what they're going to do and they tell you they're going to take out your appendix.  You ask why they're going to do that, and they say, "Well, that's what I did for the last patient and it seemed to work pretty well for him." 

And yet that is exactly the logic we often see applied inside companies particularly to questions concerning the generation or protection of revenues.  We did this five years ago or we did this somewhere else and it worked.  A competitor is doing this and it's working for them.  I applied this practice in my old company and it went really well.  Surely the chosen treatment ought to fit the specific diagnosis of this patient and their circumstances, rather than some hazy guesstimate based on someone else somewhere else?  And surely what we do inside companies ought to be based upon the facts.  What are the problems?  What are the causes of the problems?  And what can we do to make the problems better?  Or at least, to not make them worse?


Professor Jeffrey Pfeffer from Stanford University talks about the corporate aversion to fact-based analytics and evidence-based decision making, and how persistent cognitive biases among senior executives cripples decisions inside companies.

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We've developed Telemetry RT3 to change all that, and bring some intelligence - artificial and otherwise, to revenue intelligence.  And in doing so to help sales leaders deal with the enormous complexity of the sales challenges they face, particularly now in the perennial age of COVID19.

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