Abstract:The abstract concept of flow or a "pull system" is not easily understood by those who have not experienced it for themselves. Yet, the real pains of overburdening workers, lack of transparency, and degrading quality are all too familiar and widely felt across entire organizations when work is "pushed" on individuals and teams in the name of resource efficiency. Standard attempts to educate management through rational explanations of lean thinking along with the values and principles of agility are generally ignored, and soon requests for velocity metrics to show points per sprint, points per team and points per person are mandatory measures to show an expected increases in efficiencies as a result of "going agile".
Does this closely describe a pattern you have observed or specifically your situation? If so, you might be asking: "Is there a more effective way of ingraining managers with the knowledge that any work method that does not address balancing demand with capability to achieve flow will likely revert back to a push system?"
The answer: YES! Okaloa Flowlab is a simulation tool that provides experiential learning through simulations and experiments, which enable participants to gain a deeper learning of flow through actual experience. Creator, Patrick Steyaert, created Okaloa Flowlab for the purpose of giving teams the experience between pushing work versus pulling work through a system.
"Experiential learning is the process of learning through and is specifically defined as learning through reflection on doing." (Source: Wikipedia)
In this workshop participants will participate in a highly interactive hands-on simulation to learn about flow through actual experience, reflection and decisions they will make about the policies that affect how work flows through a system. Participants will also gain a deeper understanding of Kanban and the general practices that enable flow to occur: Visualize, Limit Work-in-Progress, Make Policies Explicit, Manage Workflow, Implement Feedback Loops, Improve Collaboratively and Evolve Experimentally.
Learning Outcomes:- Understanding for the importance of visualizing knowledge work in order to understand where work exists in a system via simulation
- Understanding of what causes work to queue-up and slow down by experiencing a system that is at first overburdened
- Understanding that policies will either help or hinder how work flows through a system by experimenting with incremental policy changes
- Understanding about the correlation of limiting work-in-progress to focus, collaboration, and quality through reflection of experimentation
- Understanding about how Lead Time is directly impacted by Work-In-Progress and Throughput of a system as stated by Little's Law
