Industry

How automating decision management helps organizations compete

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Automating decision managementUsing sophisticated automation to support innovative business models and drive competitive advantage is nothing new for forward-thinking operations executives.

Automation is also being applied to the decision-making process. After all, if it takes forever to respond to a customer request, or if the response is incorrect or unsatisfactory, it can be hard to keep up.

A key automation capability is automating decisions with business rules, especially decisions that are key to exceptional experiences. This particular automation capability intrigues me, even more than automating tasks with bots, because when I think of making decisions, I think of a distinctly human activity.

I asked Harley Davis, vice president of decision management and France Lab at IBM, to describe the evolution of decision management and the drivers for companies to automate decisions with business rules. You can listen to the full interview here, but here are a few highlights.

The evolution of decision management

“Decision management has a long history in the enterprise,” explains Davis. “It has roots starting back in the 1980s with the first wave of artificial intelligence and expert systems. From there, decision management came into its own in the ’90s when companies like Fannie Mae and Freddie Mac proposed loan automation systems designed to help banks decide whether or not to grant a loan approval. It took the time required to process and make that decision from weeks down to a matter of days or even minutes.”

This kind of digital automation is at the heart of what Davis considers to be a revolution in operational decision management: “If you can make important decisions hundreds of times faster than your competitor, that results in a huge competitive advantage. As a result, companies are starting to adopt decision management and automation techniques for all sorts of different activities and strategies, and this is making a big difference to their competitive positioning and their ability to deal with their customers.”

The future of decision management

I asked Davis to describe the future of automating decisions and where things are headed in the next decade or so. He says:

“It’s already quite mainstream for companies to automate their decisions using technologies like business rules and content management, but the advent of modern artificial intelligence and machine learning technology will provide a way to take data that’s already generated by all of those systems and make that an instrument of the automation … using analytics tools and machine learning to process that information and decide what’s likely to happen. For example, in sales, determining what product a customer is likely to buy in their particular context, given their purchase history, and given their interaction with you.”

Start small and grow

With all of the different approaches to business process automation, it can be difficult to know which steps to take today that will make a difference and set the stage for future innovation.

Davis points to some of the potential pitfalls to avoid for companies just starting to frame their approaches and strategies.:

“The first one is trying to solve too much. What you really want to do is start small and then grow big. But don’t start so small that the problem you’re trying to solve is not meaningful. And don’t begin with a problem that is too complicated to get started with. Find a problem that is both meaningful and achievable, that actually solves a real business problem that you can associate a real business metric to. Also, by focusing on a problem that’s small enough that you can take on, it’s more likely that in a matter of weeks or a month or two, you’ll be working with a solution that you can test in the context of your business applications. Plan on growing from that initial meaningful, bite-sized application.”

For C-suite executives and technologists today, the challenge is to move beyond the hype of digital transformation to use data and automation in ways that make a real difference in the performance of the organization.

Learn more about automation in my previous blog post, “The future of automating all types of work,” and explore the IBM decision automation solutions that can help organizations optimize decision making.

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