Dana Hamerschlag is a Harvard Business grad and leader in the sales technology industry who leads product innovation at sales consulting firm Miller Heiman Group. Dana explains, despite the hype, most organizations aren’t doing much with AI, but rather analytics.
Why that is?
People haven’t invested in the right data sets to use AI engines or predictive models in the right way.
Dana states that for AI to work, businesses have to understand both the outcomes and the inputs. Right now, most people only have the outcomes figured out. Take CRM data like what’s extracted from Salesforce for example. Because the data from these platforms isn’t initially labeled based on existing sales methodology/blue sheet insights when entered into the system, salespeople can’t know how to turn a potentially dead deal into a closed deal.
Bottom line: If you can’t talk about how to change the outcome with actions, then you can’t leverage AI to its full potential. You need to be able to recommend an action from the input side to get an outcome of predictive analytics with any value.
And so here we are... struggling to bring AI to its full potential in the enterprise. Dana and her team are working to produce a solution to this input-outcomes dilemma, available for interview or for comment on this perspective briefed above.
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