Estimating the Value of Decisions Relating to Managing and Developing Software-intensive Products and Projects. Mendes, E.; Turhan, B.; Rodríguez, P.; and Freitas, V. In Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering, of PROMISE '15, pages 7:1--7:4, New York, NY, USA, 2015. ACM.
Paper doi abstract bibtex The software industry's current decision-making relating to product/project management and development is largely done in a value neutral setting, in which cost is the primary driver for every decision taken. However, numerous studies have shown that the primary critical success factor that differentiates successful products/projects from failed ones lie in the value domain. Therefore, to remain competitive, innovative and to grow, companies must change from cost-based decision-making to value-based decision-making where the decisions taken are the best for that company's overall value creation. Our vision to tackle this problem and to provide a solution for value estimation is to employ a combination of qualitative and machine learning solutions where a probabilistic model encompassing the knowledge from different stakeholders will be used to predict the overall value of a given decision relating to product management and development. This vision drives the goal of a 3-year research project funded by the Finnish Funding Agency for Technology and Innovation (Tekes), with the participation of several industry partners.
@inproceedings{Mendes:2015:EVD:2810146.2810154,
abstract = {The software industry's current decision-making relating to product/project management and development is largely done in a value neutral setting, in which cost is the primary driver for every decision taken. However, numerous studies have shown that the primary critical success factor that differentiates successful products/projects from failed ones lie in the value domain. Therefore, to remain competitive, innovative and to grow, companies must change from cost-based decision-making to value-based decision-making where the decisions taken are the best for that company's overall value creation. Our vision to tackle this problem and to provide a solution for value estimation is to employ a combination of qualitative and machine learning solutions where a probabilistic model encompassing the knowledge from different stakeholders will be used to predict the overall value of a given decision relating to product management and development. This vision drives the goal of a 3-year research project funded by the Finnish Funding Agency for Technology and Innovation (Tekes), with the participation of several industry partners.},
acmid = {2810154},
added-at = {2015-09-17T22:38:59.000+0200},
address = {New York, NY, USA},
articleno = {7},
author = {Mendes, Emilia and Turhan, Burak and Rodr\'{\i}guez, Pilar and Freitas, Vitor},
biburl = {http://www.bibsonomy.org/bibtex/2d66dd61b59eaace273c4e32f07a43a96/burak.turhan},
booktitle = {Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering},
description = {Estimating the Value of Decisions Relating to Managing and Developing Software-intensive Products and Projects},
doi = {10.1145/2810146.2810154},
interhash = {2669a4ba9b6904a2cdc0806b522192e4},
intrahash = {d66dd61b59eaace273c4e32f07a43a96},
isbn = {978-1-4503-3715-1},
keywords = {myown},
location = {Beijing, China},
numpages = {4},
pages = {7:1--7:4},
publisher = {ACM},
series = {PROMISE '15},
timestamp = {2015-09-17T22:38:59.000+0200},
title = {Estimating the Value of Decisions Relating to Managing and Developing Software-intensive Products and Projects},
url = {http://doi.acm.org/10.1145/2810146.2810154},
year = 2015
}