Jim Powell just published a Q&A with me on Using Decision Management to Maximize Analytics. We covered a bunch of things:
- What, exactly,is decision management and what does it have to do with advanced analytics?
- What’s the history of decision management – where did it come from and does it work?
- What kind of decisions are we talking about here?
- These are not the decisions people usually focus on with analytics so how can you identify suitable decisions?
- Why do you need a new way to describe the analytic requirements of these decisions?
When it comes to analytics, many organizations focus on using analytic insight to improve executive decision making. Yet there is often an even greater opportunity when using analytics to improve operational decision making. Operational decisions about a single customer or transaction are made by call centers, local staff, and automated systems. These decisions affect everything from fraud to customer satisfaction, from risk management to resource utilization. Although each decision has a localized impact, enterprises make so many of these decisions that the cumulative impact is enormous.
I am giving a class at the TDWI World Conference “Evolving Your Requirements Approach to Advanced Analytics with Decision Management” in Boston, July 20-25. This is a new class for TDWI that builds on my successful class at the University of California Irvine Extension program.
Big data makes it hard to scale human interpretation, forces faster and more precise decision making, and puts a premium on advanced analytics. Applying big data analytics requires a clear and direct focus on managing decision making, especially in operations. But most organizations lack an approach that lets them specify their requirements, and their ability to find opportunities for, and successfully use, advanced analytics is limited. This course lays out a framework to identify the op
I am speaking on Moving to Real-Time Analytic Decision Making with Decision Management at the TDWI Executive Summit in Boston, July 21-23
The right time to make decisions for organizations is increasingly real time. Customers want responses in real time; supply chains must adapt to disruption in real time; fraud must be caught before it gets into the system while self-service and Web applications can’t wait for human intervention. At the same time, organizations have discovered the value of analytic, data-driven decisions. The challenge is to reconcile these demands—to provide real-time, analytic decision making.
In this sess
I am co-chair, with Fern Halper,of the TDWI Solution Summit: Beyond BI to Advanced Analytics for Business Advantage in San Diego, June 1-3.
Business analytics has become an important new trend for companies that want to be competitive—and stay that way. While certain kinds of advanced analytics have been on the market for decades, adoption is finally increasing for a number of reasons, including the economic climate, the availability of computing power, the growth in the amount and variety of data, and a greater appreciation for the power of analytics. Forward-looking companies are moving beyond BI—the slicing and dicing of data to produce reports and dashboards—to more advanced forms of analytics. These companies want to become more proactive to drive top- and bottom-line benefits. Among many use cases, they are using advan
I am speaking with Dean Abbott at the TDWI Executive Summit in San Diego, August 20th at 4:15pm on Ten Best Practices in Operational Analytics One of the most powerful ways to apply advanced analytics is by putting it to work in operational systems. Using analytics to improve the way every transaction, every customer, and every website visitor […]
I am speaking at the TDWI Executive Summit in San Diego, August19th at 11:15am on Moving to Real-Time Analytic Decision Making with Decision Management For organizations today, the right time to make a decision is increasingly in real time. Customers want responses in real time, supply chains must adapt to disruption in real time, and fraud must […]