Key Note Emilia Mendes

Improving and Estimating the Value of Decisions

In his call to arms paper, which gave origin to Value-based Software Engineering (VBSE), Boehm (back in 2003) very clearly put forward that much of the current software engineering practice and re-search is carried out in a value neutral setting, where: Every require-ment, use case, object, test case, and defect is treated as equally im-portant; “Earned value” systems track project cost and schedule, not stakeholder or business value; A “separation of concerns” is practiced, in which the responsibility of software engineers is confined to turning software requirements into verified code. As part of three-year research project (2015-2017) funded by the Finnish Funding Agency for Tech-nology and Innovation, we are collaborating with four ICT companies to help them improve their decision-making relating to software or software-intensive products, and to be able to predict the overall value of their decisions. All companies already employ a value-based ap-proach to decision making; however decisions are based on tacit knowledge, in the sense that decision makers’ mental models have not been explicitated, and alternatively combined and used with the help of data visualization tools/’what-if’ scenarios in support of their deci-sion-making processes. The goal and main contribution of this keynote is to detail our proposed framework towards value estimation, in addi-tion to some preliminary empirical results, in order to support those companies who wish to improve their value-based decision making, and to predict the value of their decisions. As will be detailed later, the proposed framework also includes the theory of organizational knowledge creation and the Expert-based Knowledge Engineering of Bayesian Networks process.