We love supporting the community; especially in our home town. Come see us talk about agile metrics, risk reduction and cost of delay at the Modern Management Methods Conference in San Francisco May 5th to 8th. Troy Magennis and Dan Greening are both speaking on the Risk Management and Metrics track, click here for more details. Register for the main conference (Wednesday and Thursday) to attend our talks. Sign up for the 4-day option to attend our interactive tutorials.
Get 15% off conference registration by using the discount code LKSPEAK when registering through the website.
Risk-Reduction Metrics for Agile Organizations
Dr. Dan Greening
Wednesday, May 7 • 2:20pm – 3:00pm
Agile and lean processes make it easier for organizations to measure company and team performance, assess risk and opportunity, and adapt. My colleagues and I have used delivery rate, concept-to-cash lead-time, architectural foresight, specialist dependency, forecast horizon and experiment invalidation rate to identify risk, and focus risk-reduction and learning efforts. With greater knowledge, we can eliminate low-opportunity options early and more deeply explore higher-opportunity options to maximize value. We’ve used these metrics to diagnose agility problems in teams and organizations, to motivate groups to improve, to assess coaching contributions, and to decide where to spend coaching resources. We face many problems in using measurement and feedback to drive change. Manager misuse or misunderstanding of metrics can lead organizations to get worse. Teams or people that mistrust or misunderstand managers often game metrics. And yet, what we can’t measure, we can’t manage. So part of a successful metrics program must involve creating and sustaining a collaborative, trusting and trustworthy culture.
Understanding Risk, Impediments and Dependency Impact:
Applying Cost of Delay and Real Options in Uncertain Environments
Troy Magennis
Wednesday, May 7 • 4:20pm – 5:00pm
Many teams spend considerable time designing and estimating the effort involved in developing features but relatively little understanding what can delay or invalidate their plans. This session outlines a way to model and visualize the impact of delays and risks in a way that leads to good mitigation decisions. Understanding what risks and events are causing the most impact is the first step for identifying what mitigation efforts give the biggest bang for the buck. Its not until we put a dollar value on a risk or dependency delay that action is taken with vigor.
Most people have heard of Cost of Delay and Real Option theory but struggle to apply them in risky and uncertain portfolios of software projects. This session offers some easy approaches to incorporate uncertainty, technical risk and market risks into software portfolio planning in order to maximize value delivered under different risk tolerance profiles.
Topics explored include
- how to get teams to identify and estimate impact of risks and delays
- how to identify risk and delays in historical data to determine impact and priority to resolve
- how risks and delays compound and impact delivery forecasts, and what this means to forecasting staff and delivery dates
- how to calculate and extend Cost of Delay prioritization of portfolio items considering risk and possible delays
- how Real Options can be applied to portfolio planning of risky software projects and how this can change the bottom line profitability
Capturing and Analyzing “Clean” Cycle Time, Lead Time and Throughput Metrics
Troy Magennis
Thursday, May 8 • 11:00am – 12:30pm
On the surface, capturing cycle time and throughput metrics seems easy in a Kanban system or tool. For accurate forecasting and decision-making using this data, we better be sure it is captured accurately and free of contaminated samples. For example, the cycle time or throughput rate for a project team working nights and weekends may not be the best data for forecasting the next project. Another choice we have to make is how we handle large and small outlier samples (extreme high or low). These extreme values may influence a forecast in a positive or negative direction, but which way?
This interactive session will look for the factors attendees have seen that impair data sample integrity and look for ways to identify, minimize and compensate for these errors. The outcome for this session is to understand the major contaminants and to build better intuition and techniques so we have high confidence in our historical data.
We’re really looking forward to this conference and hope to see you there!
— Troy and Dan
