Forecasting using Data
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Book this workshop along with Advanced Modeling and Forecasting and receive a £200 discount; combined 2 day workshop price £990 + VAT.
Based on availability. Cannot be combined with any previous offers.
This one-day workshop introduces all aspects of data capture and probabilistic forecasting using practical exercises. All techniques are explained solving real world problems.
If you currently manage teams or use estimates to forecast how long or how big teams need to be to deliver work, then this workshop will offer immediate skills (and an understanding of why and when to apply them). The techniques are reliable for use across any software development process such as, Scrum, Kanban or combinations (like SAFe).
The challenge of the day is to teach how to use concrete tools and knowledge that allow software and IT projects to be rapidly forecast using historical data when available. Also, how to use range estimates when no relevant history is available.
No prior mathematical knowledge is needed; this session introduces all of the skills needed to perform forecasts without complex statistics or mathematics. Bring a laptop if you have one to follow along on your own data, or just watch me or your colleagues.
Many of the problems solved during the session will use spreadsheets and worksheets that allow you to immediately answer the same questions in your company. After this course you will understand how and why they work.
Problems and examples discussed and solved during the workshop include:
• How to forecast what will fit into a fixed delivery time (eg. sprint, release, quarter)
• How to forecast the flow rate through a development and delivery process
• How to forecast how long a project will take using range estimates or historical data
• How to build a balanced dashboard for team coaching or improvement
• How to estimate the remaining defect counts and ways to assess release readiness
• How to assess staff risk impact due to skills or lack of availability
• How to integrate risk management with feature and project forecasts
Troy introducing the agenda for course:
Sampling and random distributions
Learn how probability is measured
Learn how uncertainty reduces with sample size.
Learn how this changes with different random processes.
What data matters
Understand what data to capture, picking the right measures
How to build a balanced team coaching dashboard
Understand what data needed for making predictions
Capturing reliable data
How to capture reliable data
How to clean and make data consistent
How to analyze data for reliability (gamed, different from last time)
Current forecasting and estimation flaws
Discuss current estimation and forecasting techniques
Discuss the top reasons why they go wrong
Probabilistic forecasting – forecasting with uncertain inputs
Learn about probabilistic forecasting using simple words
Perform probabilistic forecasting using simple dice exercises
Perform probabilistic forecasting on your real world data
Learn how to estimate ranges fast
Learn how to determine what estimates are needed, if any.
Skill capability assessment
Learn how to survey team skills and current capabilities
Learn how to plan and manage team and organization
Understand how team skills align to risk and poor throughput flow
Multiple team backlog planning & flow
How to map and manage team dependencies
Learn multiple team portfolio planning techniques and tools
Learn how to calculate cost of delay for backlog prioritization
How to capture feature and project risks
How to combine risks with probabilistic forecasting
How to manage and communicate risk impacts to others
Communicating uncertainty with others
How to discuss uncertainty like adults.
Strategies for clearer discussions about risk.
If you currently manage teams or use estimates to forecast how long or how big teams need to be to deliver work, then this workshop will offer immediate techniques to get answers.
The techniques are reliable for use across any software development process such as, Scrum, Kanban or combinations (like SAFe). We approach forecasting in a process agnostic way and discuss all necessary concepts during the workshop.
No specific statistical or mathematical knowledge is necessary, but be comfortable adding and subtracting numbers.
This course doesn’t offer any industry certification, how ever much of the material is consistent with the risk management concepts in the PMBOK (PMI).
SEUs: This course qualifies as 8 Scrum Educational Units (SEUs) toward the 70 required to become a CSP.