Agile Process Consultation -- An Applied Psychology Approach to Agility
April 05, 2019 Β· Declared Dead Β· π Americas Conference on Information Systems
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Lucas Gren
arXiv ID
1904.06284
Category
cs.SE: Software Engineering
Citations
0
Venue
Americas Conference on Information Systems
Last Checked
5 months ago
Abstract
An agile change effort in an organization needs to be understood in relation to human processes. Such theory and accompanying tools already existed almost 50 years ago in applied psychology. The core ideas of Agile Process Consultation are that a client initiating a change toward more agility often does not know what is wrong and the consultant needs to diagnose the problem jointly with the client. It is also assumed that the agile consultant cannot know the organizational culture of the client's organization, which means that the client needs to be making the decisions based on the suggestions provided by the consultant. Since agile project management is spreading across the enterprise and outside of software development, we need situational approaches instead of prescribing low-level practices.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted