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Search machine learning: Digital transformation study group (SPE-GCS)
...ntipattern--a frequently used but ineffective solution to a a small global team that runs business-transformation projects in business units, each designed to help staff and management problem quickly realize th...n or an individual process to create more value with less waste from SPE for his work on the 2007 Digital Energy - Pattern--a general solution to a design problem that recurs Conference, and is also acti...ve in the SPE-GCS Digital Energy in many projects ...
...guided experimentation and knowledge transfer. describes some antipatterns in the implementation of digital-oilfield The importance of guided experience in knowledge transfer was projects, refactored solutio...e Program started implementation of An antipattern is a special form of pattern that is ineffective digital-oilfield projects in 2004. The current project portfolio has or has negative consequences but may a...pleased. If you saw lots of people around you having antipatterns for synthesizing key learnings on digital-oilfield adoption the same problem, it would be better for everyone if we could find in programmati...
...there are antipatterns in digital-oilfield rollout projects, where do TABLE 1--SOME KEY ATTRIBUTES OF ANTIPATTERNS they exist and w...hat might they look like? Name Ecology of Digital-Oilfield Antipatterns Background There are two big classes of continuous-improvement opportunitie...s Anecdotes in the digital-oilfield domain: (1) continuous improvement in Antipattern description the assembly line of how p...
Summary Process design patterns are fragments of business processes used as a solution to commonly encountered problems. A process design antipattern is a special form of pattern that is ineffective or has negative consequences, but it may also be routinely followed. The objective in studying process antipatterns is to identify suboptimal performance and replace it with better practices. This paper describes some antipatterns in the implementation of digital-oilfield projects, refactored solutions that enable recovery from those antipatterns, and the root causes that create them. It concludes with a description of how continuous improvement enabled by antipatterns differs from more traditional approaches to project lessons learned and why antipatterns represent a better way to capture and reuse experience-based learning.