Value-driven design

Value-driven design (VDD) is a systems engineering strategy based on microeconomics which enables multidisciplinary design optimization. Value-driven design is being developed by the American Institute of Aeronautics and Astronautics, through a program committee of government, industry and academic representatives. In parallel, the US Defense Advanced Research Projects Agency has promulgated an identical strategy, calling it Value centric design, on the F6 Program. At this point, the terms value-driven design and value centric design are interchangeable. The essence of these strategies is that design choices are made to maximize system value rather than to meet performance requirements. Value-driven design (VDD) is a systems engineering strategy based on microeconomics which enables multidisciplinary design optimization. Value-driven design is being developed by the American Institute of Aeronautics and Astronautics, through a program committee of government, industry and academic representatives. In parallel, the US Defense Advanced Research Projects Agency has promulgated an identical strategy, calling it Value centric design, on the F6 Program. At this point, the terms value-driven design and value centric design are interchangeable. The essence of these strategies is that design choices are made to maximize system value rather than to meet performance requirements. This is also similar to the value-driven approach of agile software development where a project's stakeholders prioritise their high-level needs (or system features) based on the perceived business value each would deliver. Value-driven design is controversial because performance requirements are a central element of systems engineering. However, value-driven design supporters claim that it can improve the development of large aerospace systems by reducing or eliminating cost overruns which are a major problem, according to independent auditors. Value-driven design creates an environment that enables and encourages design optimization by providing designers with an objective function and eliminating those constraints which have been expressed as performance requirements. The objective function inputs all the important attributes of the system being designed, and outputs a score. The higher the score, the better the design. Describing an early version of what is now called value-driven design, George Hazelrigg said, 'The purpose of this framework is to enable the assessment of a value for every design option so that options can be rationally compared and a choice taken.' At the whole system level, the objective function which performs this assessment of value is called a 'value model.' The value model distinguishes value-driven design from Multi-Attribute Utility Theory applied to design. Whereas in Multi-Attribute Utility Theory, an objective function is constructed from stakeholder assessments, value-driven design employs economic analysis to build a value model. The basis for the value model is often an expression of profit for a business, but economic value models have also been developed for other organizations, such as government. To design a system, engineers first take system attributes that would traditionally be assigned performance requirements, like the range and fuel consumption of an aircraft, and build a system value model that uses all these attributes as inputs. Next, the conceptual design is optimized to maximize the output of the value model. Then, when the system is decomposed into components, an objective function for each component is derived from the system value model through a sensitivity analysis. A workshop exercise implementing value-driven design for a global positioning satellite was conducted in 2006, and may serve as an example of the process. The dichotomy between designing to performance requirements versus objective functions was raised by Herbert Simon in his essay, 'The Science of Design' in 1969. Simon played both sides, saying that, ideally, engineered systems should be optimized according to an objective function, but realistically this is often too hard, so that attributes would need to be satisficed, which amounted to setting performance requirements. But he included optimization techniques in his recommended curriculum for engineers, and endorsed 'Utility theory and statistical decision theory as a logical framework for rational choice among given alternatives.' Utility theory was given most of its current mathematical formulation by von Neumann and Morgenstern, but it was the economist Kenneth Arrow who proved the Expected Utility Theorem most broadly, which says in essence that, given a choice among a set of alternatives, one should choose the alternative that provides the greatest probabilistic expectation of utility, where utility is value adjusted for risk aversion. Ralph Keeney and Howard Raiffa extended utility theory in support of decision making, and Keeney developed the idea of a value model to encapsulate the calculation of utility. Keeney and Raiffa also used 'attributes' to describe the inputs to an evaluation process or value model.