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exist. The Decision Model, invented by Barbara von Halle and Larry Goldberg in 2011, has been successfully adopted by insurance and banking firms, and continues to spread throughout the financial industry. The Decision Model and Nota- tion standard, published by Object Management Group in 2014, enables organizations to access and share centralized business decisions using a common tabular format. A short list of vendors on the group’s DMN com- mittee includes IBM, Oracle and FICO. Von Halle and Goldberg were also key contributors to the specification. Both models are suitable for gov- ernment, and both exemplify the trend toward standardization of decision management. The benefits of decision modeling Decision modeling extracts complex business logic from software systems and allows internal business experts to manage the logic in a central reposi- tory. Business decision tables are two- dimensional and organized into simple conditional statements that result in a single conclusion. The tables are man- aged in a structured repository and are intuitive to maintain as the underlying policies and regulations change. Most important, the logic in deci- sion models is expressed in business- friendly (not technical) terms that are defined by business people and linked behind-the-scenes by technical people to actual data sources. That approach has proven invaluable. It means deci- sion models are truly a technology- agnostic and business-aware deliv- erable. It means the same decision model can operate against more than one data source without any changes. And it means a data source can be replaced with a new one without mak- ing any changes in existing decision models. In short, decision models are inde- pendent of data sources and indepen- dent of target technology. They are purely business driven and deploy anywhere and to many places, if need be. Rob Lux, Freddie Mac’s executive vice president and CIO, wrote in a 2013 blog post that, by using a deci- sion model, it took Freddie Mac “only 17 days to write, test and deploy the 100-plus rule changes comprising Hur- ricane Sandy disaster relief policies for the systems lenders use to sell and ser- vice Freddie Mac mortgages. This is about 90 percent less time than it took to operationalize policy changes fol- lowing disasters like Hurricane Katrina or the 2012 New England floods.” Among other things, decision modeling: • Allows decision logic to become a managed asset, like other forms of data. • Strengthens stewardship over deci- sions by internal business analysts. • Shortens response to continually changing policies and regulations. • Frees up otherwise fixed program costs. • Shortens software development cycles and yields far fewer errors. • Supplants monolithic systems. • Reduces the complexity and number of IT contracts and the dependence on third-party labor. To realize the potential of decision modeling, the federal government could establish a governmentwide pilot project that would entail model- ing a subset of business decision logic pertaining to a topic area subject to federal regulation, such as telecom- munications, patents, acquisitions, environmental issues or taxes. Then the government could model the chosen set of regulations in simple decision tables, in accordance with the Decision Model or DMN, and load the connected decision tables contain- ing the regulations into a web API tool to make them centrally available and systematically accessible. The Digital Government Strategy encourages the use of web APIs to make “data assets freely available for use within agen- cies, between agencies, in the private sector or by citizens.” Such an architecture would allow internal business analysts to update the regulations in real time as changes occur. Upon successful adoption of the new decision model paradigm, legacy hard-coded systems could be redacted and eventually phased out. n Dawn Levy is a management con- sultant and electrical engineer with more than 20 years of service, pre- dominantly to business and techni- cal leaders in the federal market. She seeks to deliver efficiency and pro- ductivity to her clients and to reduce superfluous spending. 24 October 2015 FCW.COM DrillDown Decision models are independent of data sources and independent of target technology. They are purely business driven and deploy anywhere and to many places, if need be. 1015fcw_022-024.indd 24 10/13/15 9:43 AM
September 30, 2015
November and December 2015