The Contribution of a Model to Estimate Activities in Software Projects Based on Lessons Learned

Authors

DOI:

https://doi.org/10.24023/FutureJournal/2175-5825/2021.v13i1.541

Keywords:

Activity estimates, Lessons learned, Project management, Models. Software projects

Abstract

Purpose – The main objective of this article is to propose the use of a model developed by Matturo and Silva (2010) to capture knowledge in software projects based on the lessons learned.

Design/methodology/approach – We carried out a qualitative research from a descriptive perspective through a single case study applied to an Enterprise Information Technology company. The company is a leader in market solutions to support customer experience management. For the data collection process, we used systematic literature review, document analysis and semi-structured interviews.

Findings – The results supported project managers to better understand the storage and use of information from lessons learned in dimensioning the use of human resources and to support the estimation of new project activities. In addition, the results showed the organization's disregard for not giving due importance to the information and knowledge generated during the life cycle of a project.

Research, Practical & Social implications – The model allows companies to obtain new knowledge or consult existing knowledge throughout the life cycle of projects and to support project managers in the process of estimating activities and preparing budgets with greater precision, using the information from lessons learned as a support. acquired in the completed projects.

Originality/value – The lack of information in the initial scope of the project and in the definition of activities in the human resource allocation process hinder the duration of the project's development activities, directly resulting in inaccurate estimates. As a result, this scenario contributes to the increased risk of deviations in terms and / or costs of software projects.

 

Downloads

Download data is not yet available.

Author Biographies

Renato Penha, Universidade Nove de Julho – UNINOVE

      

Wagner Solivan Ferreira, Universidade Nove de Julho – UNINOVE

 Universidade Nove de Julho – UNINOVE, São Paulo, (Brasil).    

Luciano Ferreira da da Silva, Universidade Nove de Julho – UNINOVE

 Universidade Nove de Julho – UNINOVE, São Paulo, (Brasil). 

Flavio Santino Bizarrias, Universidade Nove de Julho – UNINOVE

 Universidade Nove de Julho – UNINOVE, São Paulo, (Brasil). 

Cláudia Terezinha Kniess, Universidade Federal de São Paulo – UNIFESP

 Universidade Federal de São Paulo – UNIFESP, São Paulo, (Brasil). 

References

Abdellatif, TM, Capretz, LF, & Ho, D. (2019). Automatic recall of lessons learned for software project managers software. Information and Software Technology, 115, 44-57.

Andrade, J., Ares, J., Martinez, MA, Pazos, J., Rodriguez, S., Romera, J., & Suarez, S. (2013). An architectural model for testing software lesson learned systems. Information and Software Technology, 55 (1), 18-34.

Birk, A. Dingsoyr, T. & Stalhane, T. (2002). Post-mortem: Never leave a project without it. IEEE Software, 19 (3), 43-45.

Bjorvatn, T., & Wald, A. (2018). Project complexity and team-level absorptive capacity the drivers of project management performance. International Journal of Project Management, 36 (6), 876-888.

Brusamolin, V., & Moresi, E. (2008). Historical narratives: a preliminary study on the management of information technology projects. Information Science, 37 (1), 37-52.

Casey, V., & Richardson, I. (2009). Implementation of Global Software Development: a structured approach. Software Process: Improvement and Practice, 14 (5), 247-262.

Cho, S. (2006). An exploratory project expert system for eliciting correlation coefficient and sequential updating of duration estimation. Expert Systems with Applications, 30 (4), 553-560.

Creswell, JW (2010). Research design: Qualitative, quantitative, and mixed methods approaches. London: Sage.

Da Silva, L. F., & Russo, R. F. S. M. (2019). interviews Application of qualitative research. Journal of Business and Projects. 10(1).

Dey, PK, Kinch, J., & Ogunlana, SO (2007). Managing risk in development projects software: a case study. Industrial Management & Data Systems, 107 (2), 284-303.

Flyvbjerg, B., & Budzier, A. (2011). Why your IT project may be riskier than you think. Harvard Business Review, 89 (9), 601-603.

Friese, S. (2012). Qualitative Data Analysis with Atlas.ti. London: SAGE Publications.

Garcia-Sanchez, E., Garcia-Morales, V., Martin &-Rojas, R. (2018). Influence of technological assets on organizational performance through absorptive capacity, organizational innovation and internal labor flexibility. Sustainability, 10 (3), 770.

Gil, AC (2008). Methods and techniques of social research. 6. ed. Editora Atlas SA.

Godoy, AS (1995). Introduction to qualitative research and its possibilities. Journal of Business Administration, 35 (2), 57-63.

Godoy, AS (1995). Qualitative research: basic types. Journal of Business Administration, 35 (3), 20-29.

Goffin, K., Koners, U., Baxter, D., & Van der Hoven, C. (2010). Managing lessons learned tacit knowledge and in new product development. Research-Technology Management, 53 (4), 39-51.

Guzman, JG, Martin, D., Urban, J. of & Amescua, A. (2013). Practical experiences in modeling software engineering practices: The project approach patterns. Software Quality Journal, 21 (2), 325-354.

Harrison, W. (2002). Software engineering lessons learned repository. In 27th Annual NASA Goddard / IEEE Software Engineering Workshop, 2002. Proceedings. (pp. 139-143). IEEE.

Jugdev, K. (2012). Learning from lessons learned: project management research program. American Journal of Economics and Business Administration, 4 (1), 13.

Kerzner, H. (2009). Project Management: A Systems Approach to planning, scheduling and controlling. (10 d). New York: John Wiley and Sons.

Keys, MS, Araujo, CD, Teixeira, L., Rosa, D., Jr., I., & Nogueira, C. (2016). A new approach to managing Lessons Learned in PMBOK process groups: the Ballistic Model 2.0. International Journal of Information and Systems Project Management, 4 (1), 27-45.

King, WR, & Marks, Jr., PV (2008). Motivating through knowledge sharing the knowledge management system. Omega, 36 (1), 131-146.

Komi-Sirviö, S., Mäntyniemi, A., & Seppanen, V. (2002). Toward a practical solution for capturing knowledge for projects software. IEEE Software, 19 (3), 60-62.

Marconi, MDA, & Lakatos, MS (2003). Fundamentals of scientific methodology. (5th Ed). São Paulo: Atlas.

Martins, GDA & Theóphilo, CR (2009). Methodology of scientific research. São Paulo: Atlas.

Matturro, G., and Silva, A. (2010). A Model for Capturing and Managing Software Engineering Knowledge and Experience. UCS J., 16 (3), 479-505.

McClory, S., Read, M., & Labib, A. (2017). Conceptualising the lessons-learned process in project management: Towards a triple-loop learning framework. International Journal of Project Management, 35 (7), 1322-1335.

Neves, JL (1996). Qualitative research: characteristics, uses and possibilities. research notebook administration, São Paulo, 1 (3), 1-5.

Papatheocharous, E., Bibi, S., Stamelos I., & Andreou, AS (2017). An investigation of effort distribution among development phases: A four-stage progressive software cost estimation model. Journal of Software: Evolution and Process, 29 (10), e1881.

Pizzani, L. da Silva, RC, Bello, SF, & Hayashi, MCPI (2012). The art of literature in search of knowledge. RDBCI: Digital Journal of Library and Information Science, 10 (2), 53-66.

PMI, P., & PMI. (2017). Knowledge A Guide to the Project Management (PMBOK Guide). In Project Management Institute.

Santos, GV (2014). Methods for capturing lessons learned: towards continuous improvement in project management. Magazine and Project Management-GeP, 5 (1), 71-83.

Scott, L., & Stålhane, T. (2003). Experience Repositories and the Postmortem. In Wissensmanagement (pp. 79-82).

Souza, DVD, & Zioni, F. (2003). New analytical prospects in research on environment: the theory of social representations and the qualitative technique of data triangulation. Health and Society, 12, 76-85.

Tahir, T., Rasool, G., Mehmood, W., & Gencel, C. (2018). An Evaluation of Software Measurement Processes in Pakistani Software Industry. IEEE Access, 6, 57868-57896.

Tan, CH, Yap, KS, & Yap, HJ (2012). Application of genetic algorithm optimization for fuzzy rules on expert judgment semi automation using Pittsburg approach. Applied Soft Computing, 12 (8), 2168-2177.

Tastekin, SY Erten, YM, & Bilgen, S. (2016). Accounting for product similarity in project duration estimation software. International Journal of Software Engineering and Knowledge Engineering, 26 (01), 63-86.

Tereso, A., Ribeiro, P. Fernandes, G., Laurel, I., and Ferreira, M. (2019). Project Management Practices in Private Organizations. Project Management Journal,

Thiollent, M. (2009). Action research in organizations. Atlas.

Williams, T. (2008). How do organizations learn lessons from projects-And do they?. IEEE Transactions on Engineering Management, 55 (2), 248-266.

Winter, R., & keys, MS (2017). Innovation in the management of lessons learned in an IT project with the adoption of social media. International Journal of Innovation: IJI Journal, 5 (2), 156-170.

Yin, RK (2015). Case Study: Planning and methods. Bookman publisher.

Yousef, QM, Alshaer, YA, & Alhammad, NK (2017). Dragonfly Estimator: The Hybrid Software Projects' Efforts Estimation Model using Artificial Neural Network Algorithm and Dragonfly. International Journal of Computer Science and Network Security, 17 (9), 108-120.

Downloads

Published

2021-01-01

How to Cite

Penha, R., Ferreira, W. S., da Silva, L. F. da, Bizarrias, F. S., & Kniess, C. T. (2021). The Contribution of a Model to Estimate Activities in Software Projects Based on Lessons Learned. Future Studies Research Journal: Trends and Strategies, 13(1), 73–93. https://doi.org/10.24023/FutureJournal/2175-5825/2021.v13i1.541

Issue

Section

Artigos / Articles

Most read articles by the same author(s)