Are You Ready to Play the Little’s Law Game?

Todd Little, Chairman of Kanban University, invites you to his 2022 Kanban Global Summit workshop

Monday, August 22
4:00 PM – 6:00 PM
Kanban Global Summit
San Diego, California, USA

Yes! I Want to Attend the Kanban Global Summit 2022

Little’s Law has been used in queuing theory for over half a century. It is an elegant explanation of the relationship between average throughput, Work in Progress (WIP), and cycle time.

In a stable environment, it gives us a good understanding of the performance of the system which can be used for forecasting. But where are the estimates? Certainly, size must matter. But does it?

In this workshop at the Kanban Global Summit, Todd Little explores Little’s Law through theory and the experience of simulations. Each attendee will come away with a better understanding of Little’s Law and the core assumptions necessary for it to be applicable and useful in forecasting. Through the simulation, you will experience why the estimation of individual items is often not necessary in an environment where Little’s Law applies.

Watch the video above to hear more from Todd Little and why you should attend his session.

Kanban Week 2022 will follow the CDC’s Covid safety guidelines, along with state and local guidelines for California and the city of San Diego, to ensure a safe event for attendees.

Enterprise Services Planning is a new modular 5-day training curriculum for managing modern businesses involving lots of knowledge work and creative services. If your organization contains people who must think and make decisions for their living then Enterprise Services Planning is the management training framework that will transform your business. While ideally taken together as 5 days of intensive emersion, ESP training is offered in 4 modules.

Map of the Enterprise Services Planning Framework

Enterprise Services Planning Module 3: Project & Capacity Planning

Training class for up to 24 attenedees

Duration: 1 day

Pre-requisites: Recommended KMP (Kanban Management Professional). At minimum understanding of work item type definition from the 2^nd day of “Getting Started with Kanban” Foundation Level training. Knowledge of the use of Little’s Law from ESP Module 2.

A revision exercise to help understand basic work item type and demand analysis is included as an option for this class.

Target Audience

“I am a portfolio manager and I want to know if we have enough capacity to complete our commitments from our strategic plan”

“I am a function manager and I want to know how to allocate capacity across our kanban systems in order to deliver on our commitments and meet expectations”

“I am a service delivery manager and I’d like to know how to make plans and estimates and communicate realistic expectations”

“I am a project manager and I’d like to know how to make plans and estimates and communicate realistic expectations”

Curriculum

Day 4 – Project & Capacity Planning

Demand Analysis
- work item type definition
- recognizing patterns of demand
- classifying demand: value-adding or not; refutable or not; planned or not; speculative or not; disruptive or not
Demand Shaping
- using risk management policy to shape demand
- studying the risk tradeoffs of demand shaping
Capacity Planning
- using Little’s Law to align Kanban system capacity allocation with desired go-to-market or strategic outcomes
- outcome-driven design (ODD)
Large Project Forecasting
- using Little’s Law & the s-curve to model large project delivery
Labor Pool Liquidity
- understanding the concept of liquidity as a task to skills & experience matching problem
- kanban system design strategies to increase Labor Pool Liquidity
- tying career path and staff development to improved Labor Pool Liquidity
- exploring the challenges of scaling Labor Pool Liquidity as a management tool
Kanban System Liquidity
- understanding Kanban system liquidity as a work to worker matching problem
- measuring liquidity
- why Kanban system is a good metric
- understanding how to measure volatility
- using volatility as a method for sampling data sets for lead time distributions and probabilistic forecasts
- validating whether the current system performance, continues to reflect the recent past, and use of reference class forecasting is still valid

Learning objectives

Learning to use advanced demand analysis to understand opportunities for improvement and how to design a Kanban system with adequate capacity and risk hedging to cope gracefully with variation in demand over time. This is particularly useful for areas such as IT operations with lots of irrefutable demand and unplanned demand.

Learning how to trade risk for capacity by using policies to shape demand.

Understanding the outcome-driven design (ODD) approach to capacity planning. Planning delivery rates of work items using WIP limits rather than allocating people, resources or units of time.

Learn how to use Little’s Law and other probabilistic approaches to make quick, cheap but highly accurate project delivery forecasts.

Who should attend?

Portfolio and program managers, project managers, service delivery managers, risk managers, those responsible for corporate governance, product managers, function/line managers or team leads, management trainers, management coaches, individual contributors working in creative or knowledge work service delivery or project environment, anyone responsible for service delivery to customers, anyone wishing to learn how to scale Kanban implementations beyond a single team or a single service workflow.

Applicability

This class is ideally suited to a single corporate for private delivery on premises. Typical scope should be a medium-sized entity or a product or business unit of a larger entity. The class is most suitable for the private sector but is adaptable to public sector environments.

Sales

For open registration classes please consult our training listings https://kanban.university/courses/list If you don’t see a class listing near you please contact us sales@kanban.university

For private classes please email sales@kanban.university

Forecasting