ERP Effort Estimation Based on Expert Judgments

I.P. Erasmus, Maia Daneva

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

5 Citations (Scopus)
365 Downloads (Pure)

Abstract

A new technology shift brings to the ERP domain a change in the industry and a new platform build on in-memory optimized databases, introduced and known as SAP HANA [1]. This technology shift in the ERP domain led to SAP's ERP on HANA, the solution where the ERP suite is offered on the same platform as ERP Services such as Business Analytics. The integration of ERP Services and the ERP suite brings to the industry new opportunities to "fine tune" customer and industry specific business processes. This radical shift in innovation brings with it new challenges in terms of ERP effort estimation. No longer can we rely on a single method such as functional size measurement methods, due to the wide range of customization possibilities. This shift from a typical predefined solution scope to a highly customizable landscape poses a challenge to project estimation practitioners as the functional size estimation techniques used in the past for ERP solutions address a fixed scope deployable in multiple landscapes, and hence are no longer suitable for dynamically definable scope. Today's highly volatile and customized ERP landscape demands a new approach to estimate effort by leveraging ERP professionals' tacit knowledge and expert judgments. This paper presents the ERP Service estimation method that leverages the strengths of expert-judgment-based estimation techniques while using a more structured approach to reduce the effects of expert bias and avoid common pitfalls associated with judgment-based estimation.
Original languageUndefined
Title of host publication2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 8th International Conference on Software Process and Product Measurement
EditorsO. Demirors, A. Abran
Place of PublicationUSA
PublisherIEEE Computer Society
Pages104-109
Number of pages6
ISBN (Print)978-0-7695-5078-7
DOIs
Publication statusPublished - 23 Oct 2013
Event2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 2013 8th International Conference on Software Process and Product Measurement, IWSM-Mensura 2013 - Ankara, Turkey
Duration: 23 Oct 201326 Oct 2013

Publication series

Name
PublisherIEEE Computer Society

Conference

Conference2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 2013 8th International Conference on Software Process and Product Measurement, IWSM-Mensura 2013
Abbreviated titleIWSM-Mensura
CountryTurkey
CityAnkara
Period23/10/1326/10/13

Keywords

  • SCS-Services
  • EWI-25389
  • Effort Estimation
  • Memory Bias
  • Empirical Research Method
  • Empirical Study
  • METIS-309704
  • Project Estimation
  • IR-93997
  • Bias Correction Techniques
  • Action Research
  • Expert Judgements
  • Enterprise Resource Planning

Cite this

Erasmus, I. P., & Daneva, M. (2013). ERP Effort Estimation Based on Expert Judgments. In O. Demirors, & A. Abran (Eds.), 2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 8th International Conference on Software Process and Product Measurement (pp. 104-109). USA: IEEE Computer Society. https://doi.org/10.1109/IWSM-Mensura.2013.25
Erasmus, I.P. ; Daneva, Maia. / ERP Effort Estimation Based on Expert Judgments. 2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 8th International Conference on Software Process and Product Measurement. editor / O. Demirors ; A. Abran. USA : IEEE Computer Society, 2013. pp. 104-109
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title = "ERP Effort Estimation Based on Expert Judgments",
abstract = "A new technology shift brings to the ERP domain a change in the industry and a new platform build on in-memory optimized databases, introduced and known as SAP HANA [1]. This technology shift in the ERP domain led to SAP's ERP on HANA, the solution where the ERP suite is offered on the same platform as ERP Services such as Business Analytics. The integration of ERP Services and the ERP suite brings to the industry new opportunities to {"}fine tune{"} customer and industry specific business processes. This radical shift in innovation brings with it new challenges in terms of ERP effort estimation. No longer can we rely on a single method such as functional size measurement methods, due to the wide range of customization possibilities. This shift from a typical predefined solution scope to a highly customizable landscape poses a challenge to project estimation practitioners as the functional size estimation techniques used in the past for ERP solutions address a fixed scope deployable in multiple landscapes, and hence are no longer suitable for dynamically definable scope. Today's highly volatile and customized ERP landscape demands a new approach to estimate effort by leveraging ERP professionals' tacit knowledge and expert judgments. This paper presents the ERP Service estimation method that leverages the strengths of expert-judgment-based estimation techniques while using a more structured approach to reduce the effects of expert bias and avoid common pitfalls associated with judgment-based estimation.",
keywords = "SCS-Services, EWI-25389, Effort Estimation, Memory Bias, Empirical Research Method, Empirical Study, METIS-309704, Project Estimation, IR-93997, Bias Correction Techniques, Action Research, Expert Judgements, Enterprise Resource Planning",
author = "I.P. Erasmus and Maia Daneva",
note = "The research project is EFFES (with the SAP company) The first author is an external PhD student, an employee of SAP.",
year = "2013",
month = "10",
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isbn = "978-0-7695-5078-7",
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Erasmus, IP & Daneva, M 2013, ERP Effort Estimation Based on Expert Judgments. in O Demirors & A Abran (eds), 2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 8th International Conference on Software Process and Product Measurement. IEEE Computer Society, USA, pp. 104-109, 2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 2013 8th International Conference on Software Process and Product Measurement, IWSM-Mensura 2013, Ankara, Turkey, 23/10/13. https://doi.org/10.1109/IWSM-Mensura.2013.25

ERP Effort Estimation Based on Expert Judgments. / Erasmus, I.P.; Daneva, Maia.

2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 8th International Conference on Software Process and Product Measurement. ed. / O. Demirors; A. Abran. USA : IEEE Computer Society, 2013. p. 104-109.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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PY - 2013/10/23

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N2 - A new technology shift brings to the ERP domain a change in the industry and a new platform build on in-memory optimized databases, introduced and known as SAP HANA [1]. This technology shift in the ERP domain led to SAP's ERP on HANA, the solution where the ERP suite is offered on the same platform as ERP Services such as Business Analytics. The integration of ERP Services and the ERP suite brings to the industry new opportunities to "fine tune" customer and industry specific business processes. This radical shift in innovation brings with it new challenges in terms of ERP effort estimation. No longer can we rely on a single method such as functional size measurement methods, due to the wide range of customization possibilities. This shift from a typical predefined solution scope to a highly customizable landscape poses a challenge to project estimation practitioners as the functional size estimation techniques used in the past for ERP solutions address a fixed scope deployable in multiple landscapes, and hence are no longer suitable for dynamically definable scope. Today's highly volatile and customized ERP landscape demands a new approach to estimate effort by leveraging ERP professionals' tacit knowledge and expert judgments. This paper presents the ERP Service estimation method that leverages the strengths of expert-judgment-based estimation techniques while using a more structured approach to reduce the effects of expert bias and avoid common pitfalls associated with judgment-based estimation.

AB - A new technology shift brings to the ERP domain a change in the industry and a new platform build on in-memory optimized databases, introduced and known as SAP HANA [1]. This technology shift in the ERP domain led to SAP's ERP on HANA, the solution where the ERP suite is offered on the same platform as ERP Services such as Business Analytics. The integration of ERP Services and the ERP suite brings to the industry new opportunities to "fine tune" customer and industry specific business processes. This radical shift in innovation brings with it new challenges in terms of ERP effort estimation. No longer can we rely on a single method such as functional size measurement methods, due to the wide range of customization possibilities. This shift from a typical predefined solution scope to a highly customizable landscape poses a challenge to project estimation practitioners as the functional size estimation techniques used in the past for ERP solutions address a fixed scope deployable in multiple landscapes, and hence are no longer suitable for dynamically definable scope. Today's highly volatile and customized ERP landscape demands a new approach to estimate effort by leveraging ERP professionals' tacit knowledge and expert judgments. This paper presents the ERP Service estimation method that leverages the strengths of expert-judgment-based estimation techniques while using a more structured approach to reduce the effects of expert bias and avoid common pitfalls associated with judgment-based estimation.

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KW - IR-93997

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KW - Action Research

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KW - Enterprise Resource Planning

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Erasmus IP, Daneva M. ERP Effort Estimation Based on Expert Judgments. In Demirors O, Abran A, editors, 2013 Joint Conference of the 23rd International Workshop on Software Measurement and the 8th International Conference on Software Process and Product Measurement. USA: IEEE Computer Society. 2013. p. 104-109 https://doi.org/10.1109/IWSM-Mensura.2013.25