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FCW : October 2015
Tradition is good, but efficiency is bet- ter. In an annual report released in April, the Government Accountabil- ity Office examined fragmentation, overlap and duplication among gov- ernment programs and identified 440 actions that agencies and Congress could take to improve operational efficiency and effectiveness. Similarly, the Office of Man- agement and Budget’s Digital Government Strategy strives to improve IT efficiency and effectiveness for the Ameri- can people. A key tenet of the strategy is ensuring that data and content are accurate, avail- able and secure. The strategy further emphasizes the need to treat all content as data. Experience shows that a major cause of IT inefficiency is the continual rebuilding of hard-coded, decision-based systems. Business decision logic is a type of data, but unlike tra- ditional data elements that are stored and managed in databases, it is typi- cally hard-coded into software. Modifying software to reflect chang- es in business decision logic is cost- ly, cumbersome and slow. Yet hard- coded software systems dominate government IT. Those systems are largely devel- oped by third parties under large, complex and risky contracts with lengthy software development life cycles. And until recently, hard-coding decision logic was the only option. Moreover, compartmentalized agen- cies have traditionally lacked the incentive to coordinate system invest- ments enterprisewide. As a result, gov- ernment systems are often overlap- ping, fragmented or duplicative. The trend toward standardization A contrasting approach exists that would reduce operating costs, increase response times and improve accuracy while empowering internal analysts and experts. Government agencies would rely on those internal decision-makers to centrally govern decision logic, with minimal technol- ogy labor. The need to continually rebuild hard-coded, decision-based systems would diminish. This pre- vailing alternative is known as decision modeling. An interim step on the way to true decision modeling implementation might be rules engines, which could resolve some technical challenges by doing away with the hard-cod- ing paradigm. However, rules engines without decision mod- els would do little to overcome the superfluous developer costs associated with continual software rebuilds. Moreover, decision models would not replace rules engines because the two are complementary. In fact, decision models are easy to automate in today’s rules engines, so those models increase the value of rules engines. (This is because a new, agile life cycle exists from a busi- ness analyst-created decision model directly to rules engine code, with minimal IT intervention.) Two decision modeling frameworks BY DAWN LEVY Business decision logic is a type of data, and it’s time agencies started treating it that way Decision modeling: A key to better government 22 October 2015 FCW.COM DrillDown Modifying software to reflect changes in business decision logic is costly, cumbersome and slow. Yet hard- coded software systems dominate government IT. 1015fcw_022-024.indd 22 10/13/15 9:43 AM
September 30, 2015
November and December 2015