What is Agile Kanban?   Different from Kanban for JIT manufacturing! Visualization of workflow Limit work in process (WIP

Korniejczuk, Kevin

Kryk, Steven

Lau, Sharon

MacKenzie, Cameron

Rivero, Iris

Weflen, Eric

English

What is Agile Kanban?   Different from Kanban for JIT manufacturing! Visualization of workflow Limit work in process (WIP) This presentation is from the 2018 IISE Annual Conference held on May 19-22, 2018 in Orlando, Florida. Weflen, Eric, Kevin Korniejczuk, Sharon Lau, Steve Kryk, Cameron MacKenzie, Iris V. Rivero. "Application of Bayesian Belief Network for Agile Kanban Backlog Estimation." Posted with permission.</p

Digital Repository @ Iowa State University (ISU)

Application of Bayesian Belief Network for Agile Kanban Backlog Estimation

Weflen, Eric D.

Kryk, Steven S.

MacKenzie, Cameron A.

Rivero, Iris V.

Iowa State University Computer Science Technical Reports

This paper presents an approach based on influence diagrams for reducing uncertainty in Agile Kanban backlog feature completion time. Agile project management techniques, including SCRUM and Kanban, are prevalent in software development and spreading to other product development fields. A key artifact of Agile is the product backlog, containing work which needs to be completed by the development team. Internal and external stakeholders often require projections for completion of backlogged requests or features. Current estimation techniques such as duration assignments through planning poker and the use of story points to calculate velocity require persistent team input, while task counting has limited accuracy. Therefore, an influence diagram (also known as a Bayesian belief network) was generated to probabilistically assess factors influencing the completion time of backlog items. Statistical functions and uncertainty nodes were validated through data collected from a product development team practicing Agile Kanban. In addition to lowering the barrier to adopting backlog estimation, this model accounts for factors influencing lead time that current techniques disregard such as re-prioritization and feature or request additions. This approach can provide a simpler, more robust representation of project backlog while effectively using team resources.This proceeding was published as Weflen, Eric, Kevin Korniejczuk, Sharon Lau, Steve Kryk, Cameron MacKenzie, and Iris V. Rivero. "Application of Bayesian Belief Network for Agile Kanban Backlog Estimation." In Proceedings of the 2018 IISE Annual Conference. K. Barker, D. Berry, C. Rainwater, eds. (2018). Posted with permission.</p

https://dr.lib.iastate.edu/bitstreams/825bb219-563c-40b3-8b6c-688e5739eab1/download

Application of Bayesian Belief Network for Agile Kanban Backlog Estimation

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Digital Repository @ Iowa State University (ISU)

Iowa State University Computer Science Technical Reports

Digital Repository @ Iowa State University (ISU)