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Build Your Big Data Analytics Capability with Decision Management


The old way:

Big data is a hot topic. Big Data was coined as a term by Gartner to mean data that has Volume (more data), Variety (of many types) and Velocity (that arrives more rapidly). Value is extracted from big data using advanced analytics such as data mining and predictive analytics. This data can be turned into insight about risk, fraud, customer opportunity, demand and more. This insight is valuable because it can improve decision-making by complementing or even replacing judgmental rules.

It is an organization’s day to day operations that drives this data – more systems are producing more digital exhaust, more cloud-based third party data sources can be integrated into operations, more data about customers’ activities is gathered at the front line of an organization. The value of big data analytics comes from reapplying this insight to operations, improving the way an organization acts day to day. This means focusing on applying this insight to operational decision.

Many operational decisions are increasingly made in real-time yet today too many predictive analytic models are applied in batch. Still others fail to match the reality of the operational systems they need to influence, sitting on the shelf because they cannot be effectively applied. Some could be used but must wait months, sometimes many months, in the IT queue to be implemented. These delays degrade the accuracy of the analytic and consume value that would otherwise have been created.

The new way:

Analytics teams are increasingly focusing on decisions and on business rules. Understanding the decisions to be improved means that analytics that are developed will be consumable. Matching the analytic to the business decision to be improved at the start, rather than at the end of the project means that business results become the focus not statistical measures. Focusing on the decision engages the business quickly and effectively.

Automating these decisions using a business rules management system provides an effective platform for applying these analytics in real-time. Not only can rules be written to use the analytic, to act on it, the use of PMML and in-database analytic technologies allow the business rules management system to calculate the value of the analytic right when it is needed. This means that the most up to date data is used, improving accuracy. The use of a business rules management system also helps bridge what would otherwise be a three way gap. Business, IT and analytics professionals must all work together effectively to apply analytics in operations. Managing decisions using a business rules management system allows you to do this.

Tip #3: Focus advanced analytics on improving operational decisions and use business rules as a way to integrate business, IT and analytics teams.

Don’t forget that Decision Management Solutions is exhibiting at Building Business Capability 2013. We provide a complete set of consulting, training and software support for Decision Management to position you for short- and long-term success with business rules and big data analytics. Come by our booth (P8) and meet me and our VP Consulting Gagan Saxena. For more on decision management:

  • Don Perkins and Doris Kimball have a presentation on A Practical Approach Using Decision Management and Decision Modeling at The Principal Financial Group (Wednesday)
  • I am speaking on lessons learned and best practices modeling decisions in aerospace, banking, insurance and healthcare (Thursday)
  • There’s a panel discussion on decisions from the business perspective (Thursday)
  • My book “Decision Management Systems: A Practical Guide to Using Business Rules and Predictive Analytics” will be at the bookstore and I will be signing books and answering your questions (4:20pm on Thursday)
  • Learn how the new  Decision Model and Notation Standard will make it easier to model decisions and share the results at the panel (Friday)

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