From Data to Decisions – The Shift To Decision Management
Organizations have faced a constant technology arms race to achieve basic levels of decision management. From data warehousing, to data marts, to reporting tools to BI, and now Big Data, organizations and leaders have been inundated with technology fads. While the the latest buzz in technology may come and go, Constellation Research believes organizations seek a path from data to information to insight to action. This path from Data to Decisions drives the science and discipline behind decision management.
Consequently, decision management in the data to decisions world examines the necessary tools, steps and methods for deriving insight from data and acting on it. These tools are useful creating informed people and processes, but the continuation and follow-through to decisions and actions demands a robust set of performance monitoring and management practices. Those are the table stakes. In many cases, application of decision automation, semantic technology and collaborative tools are also needed. Data 2 decisions is about moving from insight to action and moving to fact based decisions making at all levels of the organization.
I sat down with James Taylor, a thought leader in this space to hear his insights on the latest trends.
The Inside View With James Taylor – One of The Leaders In Decision Management Systems
R “Ray” Wang (RW): James is the CEO and a Principal Consultant of Decision Management Solutions. He is the leading expert in how to use business rules and analytic technology to build Decision Management Systems. James is passionate about using Decision Management Systems to help companies improve decision making and develop an agile, analytic and adaptive business. He provides strategic consulting to companies of all sizes, working with clients in all sectors to adopt decision making technology. James has spent the last 20 years developing approaches, tools, and platforms that others can use to build more effective information systems. He has led Decision Management efforts for leading companies in insurance, banking, health management and telecommunications.
James is the author of “Decision Management Systems: A practical guide to using business rules and predictive analytics” (IBM Press, 2011). He previously wrote Smart (Enough) Systems: How to Deliver Competitive Advantage by Automating Hidden Decisions (Prentice Hall) with Neil Raden, and has contributed chapters on Decision Management to multiple books including “Applying Real-World BPM in an SAP Environment”, “The Decision Model”, “The Business Rules Revolution: Doing Business The Right Way” and “Business Intelligence Implementation: Issues and Perspectives” as well as many articles to magazines.
In addition to strategy and implementation consulting, James delivers webinars, workshops and training. He is a regular keynote speaker at conferences around the world such as the Decision Management Summit, Business Rules Forum, Predictive Analytics World and IBM’s Business Analytics Forum.
James was previously a Vice President at Fair Isaac Corporation where he developed and refined the concept of decision management. The best known proponent of the approach, James helped create the emerging Decision Management market and is a passionate advocate of decision management. He understands how companies buy and use these technologies and he has helped companies successfully adopt these technologies and apply them in the context of Business Process Management and Business Intelligence initiatives.
1. I noticed that you are tying Decision Management to the Customer Relationships? What are some basic principles that someone knew to this space should know about?
James Taylor (JT): Historically Decision Management got applied primarily in risk and fraud but the energy recently has shifted to customer decisions. Decision Management works best on high volume, repeatable decisions. For most organizations, decisions about customers are the ones they take most often. Focusing on how to manage these decisions offers companies tremendous value in becoming more customer-centric and improving their customer engagement and relationships. At the end of the day your customer relationships are driven by their reaction to the decisions you make about them. Developing systems to manage these decisions that are agile enough to change when that is necessary, that embed analytics to improve these decisions, and that are adaptive so they can improve over time is a critical need for better customer relationships. Managing customer decisions is not the only thing you can do with Decision Management, just a great place to start to unlock customer value and drive the customer journey.
2. What’s been the big shift in the journey from Data to Decisions?
(JT): I think there have been three big shifts. The first is an increase in the use of more advanced analytics. Where reporting and perhaps dashboards used to be the primary way to use data, now more organizations are using data mining, predictive analytics and advanced visualization techniques. We see a tremendous growth in these more advanced analytics. Second we also see a focus on operations and operational decisions, with more organizations trying to improve decision-making at the front-line of their organization – where they interact with customers and their supply chain – not just in their back office. Finally we are beginning to see organizations becoming explicit about the decisions involved. Instead of just putting data out there, summarizing it and perhaps visualizing it and hoping that someone will be able to make better decisions, organizations are explicitly identifying the decisions that they need to improve. Then they are building the right kind of decision support or decision management system to ensure that decision gets done right. This last topic is a personal interest and one of the most exciting sessions for me is the hands-on session where folks will actually get to do some decision modeling.
3. Where are we with this fad and hype around #bigdata? Is this just the beginning or will we morph?