Machine Learning applied to Project Management
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This is a R&D project between Sopra Steria and Université de Lorraine in France. We want to predict project performance using project maturity models and artificial intellifence
![89%
36%
97%
<30%
HOW IMPORTANT IS PROJECT MANAGEMENT FOR YOUR
ORGANIZATION ?
High
performance
Low
Performance
All ProjectsOrganisations
Of organizations believe project management is critical to business
performance and organizational success
High-performing organizations complete 89% of their projects
…while low performers
of those projects successfully completed on time and on
budget
But only
[PMI, 2014], [PWC, 2016]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Machine Learning applied to Project Management
- 1. Delivering Transformation. Together. *Réussirlatransformation.Ensemble. THESE: ACCOMPAGNER LA TRANSFORMATION DE LA GESTION DE PROJETS D'UNE ENTREPRISE SOPRA STERIA- ERPI (UNIVERSITÉ DE LORRAINE) Felipe SANCHEZ
- 2. 89% 36% 97% <30% HOW IMPORTANT IS PROJECT MANAGEMENT FOR YOUR ORGANIZATION ? High performance Low Performance All ProjectsOrganisations Of organizations believe project management is critical to business performance and organizational success High-performing organizations complete 89% of their projects …while low performers of those projects successfully completed on time and on budget But only [PMI, 2014], [PWC, 2016]
- 3. YOU ARE NOT THE ONLY ONE HAVING THIS PROBLEMS 130% 500%20% 75% AVERAGE COST OVERRUN IN BIG PROJECTS [Atif Ansa et al. 2017]
- 4. ONE SOLUTION IN PM LITTERATURE IS BY DEVELOPING PROJECT MANAGEMENT MATURITY MODELS (PMMM) Maturity Level 1 Maturity Level 2 Maturity Level 3 Maturity Level 4 & 5 There are not any project management practice stablish, the project is first in its type in the company (ad hoc), it doesn’t have a defined team or senior management support. there are some good practices in place and there is a small team engage, also the organization have done some similar work before. The project management practices are standardize within the organization, there is a clear project team that have informal skill and training in project management. There is a team with strength teamwork and formal training in project management, they benchmark best practices and formally report the information. . [PMI, 2008], [CMMI, 2006], [Ibbs et al., 2000], [Crawford, J.K. 2002] , [OGC, 2008]
- 5. 90% OF THEM ARE UNDER LEVEL 2 The maturity models have several problems: Level 2 Level 3 Level 4 & 5Level 1 22% 6% 68% 4% 100% Can’t make any prediction of the success of projects 90% Can’t take account of strategy problems in the environment of the company 72% Not created for the adequate level of complexity of the project 65% Are too long to apply, they give best practice but didn’t help the company to get to the next level BUT, AFTER THE EVALUATION OF MORE THAN 200 ORGANIZATIONS… [Grant & Pennypacker. 2016 ]5
- 6. PERFORMANCE 01Project Management Maturity Level 02Organization Maturity level (business and support process) 03NES: Strategic Exposure Level SO, WE ARE DOING THIS PROPOSITION:
- 7. FOR DEVELOPPING IT, WE START STUDING THE KM OF SOPRA STERIA CONSULTING: AREVA Evaluation of Maturity in project management for 20 projects 01 02 04 03 05 Chrous Evaluation of the complexity of projects Project Health Check Evaluation of problems to turnaround of drift projects PnM Tool created to evaluate Project Management Maturity Tender M4 Tool created to evaluate Bid management maturity
- 8. WE PROPOSE THIS CLASSIFICATION OF PROJECTS IN ORDER TO ANALYSE THEIR MATURITY LEVEL: 2 4 1 ComplexityLevel Strategic Value Complexity Strategic Agile Complicate Leverage Complex Projects’ classificationComplex Projects 2 3 1Complicate Projects Agile Projects 3 Leverage Projects 4
- 9. Project: evaluation Black Box Organization Maturity Business Maturity Investment Requirements Project Management Maturity Performance D Risk Environment AND EVALUATIONG PMMM AS BLACK BOX: D Cost D Quality ComplexityLevel Strategic Value D KM ...
- 10. Practices Practices Practices Criterion Practices Practices Practices Maturity Level 5 Maturity Level 4 Maturity Level 3 Maturity Level 2 Maturity Level 1 Dimension Criterion Practices Practices Practices Criterion Practices Practices Practices Dimension Criterion CriterionCriterionCriterionCriterion ML Algorithm Performance EfficiencyEfficacity FINALLY, CONVERGING THE BLACK BOX MODEL INTO A WHITE BOX MODEL (USING MACHINE LEARNING) TO PREDICT PERFORMANCE: RETEX KM Interviews
- 11. PLANNING FOR THE NEXT 3 YEARS State of the art PM, AI, ML Criteria, interviews 01 Model development Bayes Networks, Quantitative data02 Test of the model: EOI, Sopra Steria, Customers03 Publications Articles, sustentation04 S1 2017 S2 2017 S1 2018 S2 2018 S1 2019 S2 2019
Editor's Notes
- Maturité et performance de la gestion projet appliqué à la TD => Learning Maturity https://www.weforum.org/agenda/2017/03/learning-about-creativity-from-formula-1?utm_content=buffer364ce&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer
- When was the last time you lead or participle in a project? 97% of organizations believe project management is critical to business performance and organizational success (Source: PWC) PMI organization affirm that $122 million was wasted for every $1 billion invested in the United States, due to poor project performance. Fewer than a third of all projects were successfully completed on time and on budget over the past year. (Source: Standish Group) 18. High-performing organizations successfully complete 89% of their projects, while low performers complete only 36%. (Source: PMI.org)
- Project Management Maturity: An Assessment of Project Management Capabilities Among and Between Selected Industries Kevin P. Grant and James S. Pennypacker
- NES and PM
- Dimension = Domain du PM BOK