Workshop: Fit-for-Purpose and Forecasting

Lean Kanban Brazil 2018: Atos de Liderança Desempenhados por Pessoas como Você

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Neste Workshop você vai aprender:

The Fit-for-Purpose (F4P) Framework is about how modern businesses find, satisfy and keep customers. It gives them a system to understand why their customers choose their products and services and the criteria involved in such choices.

The first half of this workshop will give you the essentials of the Fit-for-Purpose (F4P) Framework. First, how to break down fitness-for-purpose into design, implementation and service delivery components. Second, how to see different market segments where customers may have different fitness criteria. Third, how to recognize different types of metrics and avoid using them for a wrong purpose, which could lead to customer dissatisfaction. Fourth, how to survey your customers to monitor and analyze the current fitness-for-purpose of your products and services. Fifth, the most commonly occurring fitness criteria. Finally, we will outline the strategic applications and integrations of the F4P Framework.

Having established the time-to-market (lead time) as a key fitness criterion in your technology or professional services business, we will turn our attention in the second half of the workshop to the current sound guidance on how to forecast deliveries and projects.

First, we’ll consider forecasting service delivery: how to establish a service-level agreement (SLA), how much data you need, what risk factors are responsible for the variation in delivery, when and how to offer customers better than the probabilistic SLA. Second, forecasting delivery of work item batches: projects and marketable product feature sets. What are the essential ingredients of such forecasts? What are the danger signs that your forecast isn’t sound or relevant to your business? Where will the biggest risks come from? You’ll be surprised how much action you can drive before even trying Monte-Carlo. Third, we need to deal with the reality that some variables in your process may exhibit extreme variability (Taleb’s Extremistan). Presence of Extremistan changes both the underlying math and the appropriate actions of managers and executives substantially. How to detect such problems? What to do? More importantly, what not to do? Finally, we’ll reinforce Kanban cadences as a proven way to validate your forecasting model and to encourage the data-driven decision culture in your company.

Learning objectives for this workshop:

What essentials do I need to know about the Fit-for-Purpose (F4P) Framework and why is it important to my business? Since time-to-market (lead time) is such an important fitness criterion, I want to apply delivery metrics and forecasting in my company effectively. What essentials do I need to know? What are the latest insights and guidance in this field?

Topics covered in the workshop:

  • Fit-for-purpose components: design, implementation, and service delivery
  • Market segmentation by purpose (not demographics)
  • Four types of metrics: fitness criteria – they should be your KPIs, then health indicators, improvement drivers, and everything else – vanity metrics
  • How to assess fitness of your product or service using F4P Cards and F4P Box Scores
  • Common fitness criteria: lead time (duration, predictability, timeliness), quality (functional, non-functional), safety and conformance
  • F4P connection to strategy and integrations with several other approaches
  • Lead time as a key fitness criterion in your technology or professional-service business
  • Differentiating between forecasting delivery of a single item (service-level agreement, SLA) and a batch of such items (project, minimally marketable product feature set, etc.)
  • How to establish an SLA based on the actual service performance data? How much data do we need?
  • Before you use Monte-Carlo: how to make a simple project forecast on a napkin
  • How to create a project forecast from the essential ingredients
  • Differentiating between Extremistan (extreme variability, possibility of extreme outcomes) and Mediocristan (tame variability). Extremistan both increases your project risk and limits your forecasting options. What to do and not to do.
  • Understanding the nature of lead time, modeling lead time and its dominant factors (customer feedback, delays due to queuing, blockage in flow, dependencies)
  • Validating inputs into any SLA and forecast, the importance of Kanban cadences, particularly the Service Delivery Review (SDR)

Managers, C-level, Change Agents

Basic Kanban Knowledge


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