Risks and Forecasting
Introduction to Training
The Risks and Forecasting training provides comprehensive and applied training for professionals who want to increase predictability, understand uncertainties, and manage risks strategically. The journey begins with understanding the fundamental concepts of forecasting, data collection, and data quality, exploring how metrics such as flow, cycle time, and lead time directly influence the ability to predict deliveries. The content merges essential knowledge about predictability with modern statistical analysis practices, highlighting why traditional techniques often fail and how data-driven approaches offer significantly more accurate projections.
As the student progresses, they learn to transform scattered data into reliable forecasts, using robust methods such as Monte Carlo simulation, percentiles, probabilistic analysis, and distribution reading. The training is accompanied by a detailed article that delves into the main concepts of forecasting and risk management, ensuring a solid theoretical and practical foundation. The use of a laptop with spreadsheet software—preferably Microsoft Excel—is essential for applying the techniques presented throughout the course.
Training Requirements
Although no formal prerequisites are required, it is recommended that participants have experience with projects, products, or processes involving flow metrics, as well as basic familiarity with data analysis. Prior knowledge of lead time, throughput, and statistical models adds fluency to the learning process. The exam assesses the ability to interpret scenarios, apply quantitative analysis, and transform historical data into realistic forecasts. Students should be prepared to use percentiles, SLAs, statistical distributions, and simulation models as a basis for decision-making.
Benefits of Certification
The Risk and Forecasting certification highlights the professional as someone capable of handling uncertainties in a technical and pragmatic way. Among the benefits are: greater accuracy in forecasting deliverables, the ability to project multiple scenarios, the skill to objectively quantify risks, and a significant improvement in communication with stakeholders. The combination of data analysis, simulation, and a deep understanding of workflow helps the student reduce variability, anticipate delays, and support safer decisions. This certification strengthens the profile of those seeking to work in modern, data-driven teams focused on sustainable predictability.
For whom it is addressed
This training is ideal for professionals involved in project, product, operations, and finance management—especially those who face high variability or need to deliver results with greater predictability. Scrum Masters, Agile Coaches, Product Owners, managers, business analysts, risk specialists, consultants, and anyone responsible for strategic decisions will find here a practical, analytical training aligned with current market demands. It also caters to entrepreneurs and leaders who want to leverage their business performance through data-driven decisions.
Program content
1. Introduction to Predictability and Data Collection
- What is Predictability?
- What data should we collect?
- Forecasts for single items using cycle time
- Traditional Forecasting Techniques and Why They Fail
2. Lead Time and Risk Analysis
- Lead Time Distribution Analysis and its Relationship with Risks
- Quantifying single-item forecast risk (percentiles and SLAs)
- Improved forecasts for single items
3. Multi-Item Forecasting and Monte Carlo Simulation
- What is Throughput and Why is it Important?
- Introduction to Monte Carlo Statistical Sampling and Simulation Methods
- How to answer “How many items can be delivered in 'X' days?”
- Quantifying multi-item forecast risk
- Improved predictions for multiple items
4. Quantifiable Risk Management
- Understanding risk in developing accurate forecasts
- Risk quantification in analysis charts
- Using changing scenarios to develop an overall risk profile
5. Practical Application and Advanced Forecasting Techniques
- How to immediately apply these techniques to your current project or process
- Pull System Policies and Forecasting
- Deepening Little's Law
- Shortest work weighted first
- Monte Carlo Simulation and Cost of Delay
- Effective selection and use of work system data
Differential
The course's distinguishing feature lies in combining technical rigor with immediate applicability, transforming complex concepts into simple, actionable tools. By integrating financial management, cash flow metrics, risk analysis, and statistical simulation, the program offers a holistic approach rarely seen in traditional training. The combination of theory, practical exercises, case studies, and Excel modeling ensures that professionals learn not just concepts—but a completely new way of thinking about forecasts and risks. With experienced instructors and a results-oriented methodology, the course prepares students to make safer decisions, communicate uncertainties with authority, and significantly increase the predictability of their projects and businesses.
