Estimating the value of decisions relating to managing and developing software-intensive products and projects

Emilia Mendes; Burak Turhan; Pilar Rodríguez; Vitor Freitas

doi:10.1145/2810146.2810154

Estimating the value of decisions relating to managing and developing software-intensive products and projects

Emilia Mendes, Burak Turhan, Pilar Rodríguez, Vitor Freitas

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

7 Citations (Scopus)

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.

Original language	English
Title of host publication	11th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2015)
Subtitle of host publication	October 21st, 2015, Beijing, China
Editors	Leandro Minku
Place of Publication	New York NY USA
Publisher	Association for Computing Machinery (ACM)
Number of pages	4
ISBN (Electronic)	9781450337151
DOIs	https://doi.org/10.1145/2810146.2810154
Publication status	Published - 2015
Externally published	Yes
Event	International Conference on Predictive Models and Data Analytics in Software Engineering 2015 - Beijing, China Duration: 21 Oct 2015 → 21 Oct 2015 Conference number: 11th http://promisedata.org/2015/

Conference

Conference	International Conference on Predictive Models and Data Analytics in Software Engineering 2015
Abbreviated title	PROMISE 2015
Country	China
City	Beijing
Period	21/10/15 → 21/10/15
Internet address	http://promisedata.org/2015/

Keywords

Bayesian network
Software product and project management
Value-based decision making
Value-based software engineering

Cite this

Mendes, E., Turhan, B., Rodríguez, P., & Freitas, V. (2015). Estimating the value of decisions relating to managing and developing software-intensive products and projects. In L. Minku (Ed.), 11th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2015): October 21st, 2015, Beijing, China [7] Association for Computing Machinery (ACM). https://doi.org/10.1145/2810146.2810154

Mendes, Emilia ; Turhan, Burak ; Rodríguez, Pilar ; Freitas, Vitor. / Estimating the value of decisions relating to managing and developing software-intensive products and projects. 11th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2015): October 21st, 2015, Beijing, China. editor / Leandro Minku. New York NY USA : Association for Computing Machinery (ACM), 2015.

@inproceedings{d7886dd3c7fd432291b9b1473e0ec758,

title = "Estimating the value of decisions relating to managing and developing software-intensive products and projects",

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.",

keywords = "Bayesian network, Software product and project management, Value-based decision making, Value-based software engineering",

author = "Emilia Mendes and Burak Turhan and Pilar Rodr{\'i}guez and Vitor Freitas",

year = "2015",

doi = "10.1145/2810146.2810154",

language = "English",

editor = "Minku, {Leandro }",

booktitle = "11th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2015)",

publisher = "Association for Computing Machinery (ACM)",

address = "United States of America",

note = "International Conference on Predictive Models and Data Analytics in Software Engineering 2015, PROMISE 2015 ; Conference date: 21-10-2015 Through 21-10-2015",

url = "http://promisedata.org/2015/",

}

Mendes, E, Turhan, B, Rodríguez, P & Freitas, V 2015, Estimating the value of decisions relating to managing and developing software-intensive products and projects. in L Minku (ed.), 11th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2015): October 21st, 2015, Beijing, China., 7, Association for Computing Machinery (ACM), New York NY USA , International Conference on Predictive Models and Data Analytics in Software Engineering 2015, Beijing, China, 21/10/15. https://doi.org/10.1145/2810146.2810154

Estimating the value of decisions relating to managing and developing software-intensive products and projects. / Mendes, Emilia; Turhan, Burak; Rodríguez, Pilar; Freitas, Vitor.

11th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2015): October 21st, 2015, Beijing, China. ed. / Leandro Minku. New York NY USA : Association for Computing Machinery (ACM), 2015. 7.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Other › peer-review

TY - GEN

T1 - Estimating the value of decisions relating to managing and developing software-intensive products and projects

AU - Mendes, Emilia

AU - Turhan, Burak

AU - Rodríguez, Pilar

AU - Freitas, Vitor

N1 - Conference code: 11th

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - Bayesian network

KW - Software product and project management

KW - Value-based decision making

KW - Value-based software engineering

UR - http://www.scopus.com/inward/record.url?scp=84947546011&partnerID=8YFLogxK

U2 - 10.1145/2810146.2810154

DO - 10.1145/2810146.2810154

M3 - Conference Paper

AN - SCOPUS:84947546011

BT - 11th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2015)

A2 - Minku, Leandro

PB - Association for Computing Machinery (ACM)

CY - New York NY USA

T2 - International Conference on Predictive Models and Data Analytics in Software Engineering 2015

Y2 - 21 October 2015 through 21 October 2015

ER -

Mendes E, Turhan B, Rodríguez P, Freitas V. Estimating the value of decisions relating to managing and developing software-intensive products and projects. In Minku L, editor, 11th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2015): October 21st, 2015, Beijing, China. New York NY USA : Association for Computing Machinery (ACM). 2015. 7 https://doi.org/10.1145/2810146.2810154

Access to Document

10.1145/2810146.2810154

Link to publication in Scopus