How can you prioritize product backlogs with the Weighted Shortest Job First (WSJF) framework?

First we need to understand the WSJF components, CoD (Cost of Delay), Job Size. Then, define the steps to prioritize with WSJF: 1. Calculate WSJF - the higher the score, the higher the priority. 2. Define CoD factors - We need to engage the stakeholder to determine the impact of delay on revenue, customer satisfaction, compliance etc., 3. Estimate the Job size - use story point or relative sizing. 4. Sort the product backlog - based on the WSJF. By leveraging the WSJF framework, delivery managers can prioritize product backlogs more effectively, focusing on delivering the highest value and minimizing the cost of delay for the product development team.

WSJF - Weighted Shortest Job First (WSJF) is a prioritization framework used in Agile, It helps organizations prioritize work items by considering not only the urgency of the job but also its business value and the size of the job. Formula - WSJF = (Business Value + Urgency + Risk)/ Job Size Example - Ecommerce Clothing App 1. Add guest checkout Business value = 7 out of 10 Urgency = 6 out of 10 Risk = 8 out of 10 Job size = 5 story points WSJF = (7+6+8)/5 = 4.2 2. User can add their video testimonials of product Business value = 8 out of 10 Urgency = 3 out of 10 Risk = 4 out of 10 Job size = 3 story points WSJF = (8+3+4)/3 = 5 Here feature 2 has higher WSJF value so It should be prioritised first.

Weighted Shortest Job First (WSJF) is a prioritization model used to sequence work for maximum economic benefit. In SAFe, WSJF is estimated as the relative cost of delay divided by the relative job duration. In a flow-based system, priorities must be continuously updated to provide the best economic outcomes.

To calculate WSJF, teams need to estimate cost of delay and duration. ? For duration, use job size as a quick proxy for duration ? Relative estimating is a quick technique to estimate job size and relative value ? WSJF stakeholders: Business Owners, Product Management, POs, and System Architects

WSJF (Weighted Shortest Job First) prioritizes items in a product backlog. Generally used a formula: Economic Value (factors like user value, strategic alignment, and potential revenue) / Time Sensitivity (factors like market opportunities, regulatory deadlines, or customer demand) + Risk Reduction. This method helps teams focus on delivering high-value, time-sensitive, and risk-reducing features. For example, if a backlog item brings substantial revenue (economic value) and needs quick implementation to meet a market window (time sensitivity), it would have a higher WSJF, making it a high priority. Consider dependencies between backlog items, their impact, ensure alignment with short & long term product & business goals on overall WSJF.

WSJF helps Product Owner for Value based prioritization We are considering the time while we calculate which would help us to decide if this feature is how Time critical As WSJF are often calculated collaboratively it helps in Decision Making It also helps Lean portfolio management to take decision on Portfolio level

Calculating Cost of Delay (CoD), job size, and risk reduction is a complex formula Difference in opinion when defining above mentioned attributes

It is equally important to identify reasons of backlog while aiming to resolve it at earliest. Track the process from PRD writing to sprint planning to identify the bottleneck. Most probably, the reason is improper resource allocation or overestimation of current bandwidth. Take this learning as a pinch of salt and assume worst case scenarios in future sprint planning.

It's not just about tackling the easiest tasks first; it's a strategic approach that balances the complexity of tasks with their potential impact and urgency. For instance, in a recent project, we had a mix of high-value features and critical bug fixes. Using WSJF, we were able to quantify and compare these diverse items effectively. We assigned weight based on factors like business value, risk reduction, and opportunity enablement, then divided by the job size. This method helped us prioritize tasks that offered the highest value in the shortest time, significantly improving our delivery efficiency