James Taylor's Decision Management

James Taylor

Delivering point of sale revenue with decision automation

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One of the tactical gains often seen when decisions are automated is revenue gain at point of sale not from the targeting but from the simple fact of pushing decisions to the point of contact. This increased revenue comes because many people are not ruthless comparison shoppers and because pushing decisions to the point of contact can means closing the business at once. Take the example of insurance underwriting. Pushing this decision to the point of contact means eliminating the need for an underwriter to review the application so that the person actually interacting with the customer, typically not an underwriter, can make the decision. What about cross-sell offers for customers who only use your ATMs? Pushing decisions to the point of contact means making the ATM make the cross-sell. What about correctly identifying the spare part a customer needs? Pushing the decision to the point of contact means helping them identify the part for themselves on your website not making them send an email or make a phone call to someone who understands how the product is put together. All this comes down to using the automation of a decision to enable anyone, or any system, to make the decision. Manual decision-making, in contrast, often requires customers to wait or return later, risking that they will find someone else to offer them what they want. Pushing to close this gap can result in serious risk exposure if you rely on less well trained staff, or simply less experienced ones, to make complex decisions. Automating the decision enables those with expertise, and historical data, to ensure that the decision is appropriate and yet allowing it to be delivered at point of contact with customers.

Now one of the great things about computers is their speed. Not only can they do things fast, but the speed at which they do things keeps improving and the cost keeps declining. Automation of a decision can therefore cut the decision time to zero or close enough to zero for a human. Take a loan example. If I can decide on a loan in 3 days when my competitors take 5 that might give me a slight edge. But customers will still need to wait so the advantage is not great. Even if I can cut my time to a few hours I still don't have a huge edge. But if I can get my decision time to almost zero then I can give a customer an answer in the branch, on the phone, at the website. Customers like instant gratification - if the price seems OK they might well just take it. Cut the decision time to zero and you can capture more business.

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A blog about the use of decision management technologies like predictive analytics and business rules to deliver agility, improve business processes and bring intelligent automation to SOA.

James Taylor

James Taylor blogs on decision management for ebizQ, and is an independent consultant on decision management, predictive analytics, business rules, and related topics.

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