I need assistance and advice for my backlog prioritization

My Kanban team has been given a small backlog that needs to be cleared quickly. Low capacity is my main problem, which is affecting throughput. We essentially have one experienced full-time developer and one less experienced developer on loan at 80% capacity. I’ve taken several steps to prioritize it;

  1. T-shirt sized the items.

  2. Added a priority as it pertains to which client is bringing more business, SLA, and weighed that against medium size clients with the loudest voice. I don’t have hard data on this.

  3. I’ve not had the opportunity to take into account impact to business, ours and the clients. This is because this is a new team and I’ve not had the time to get into the weeds of that.

My question: What scoring system should I use, which will help precisely prioritize the backlog?


I guess you already know RICE. Here are two more: Assumption testing and BUC Method.

  1. Assumption testing method score = Risky of the assumption (1-10) + Importance (1-10)
  2. BUC score = Business benefits (1-10) + User benefits (1-10) + Cost (1-10)

I would choose the weighted scoring option, even though it could seem a little complicated at first. It enables you to take into account certain criteria, weigh objects using a predetermined number scale, and can be adjusted until you find the ideal balance.


There are several scoring systems that you can use to prioritize your backlog. Here are a few options:

  1. Value vs. Effort: This scoring system involves assigning a value score to each item on the backlog based on its potential impact on the business or customers. This score could be based on factors such as revenue impact, customer satisfaction, or strategic alignment. The effort score is based on how difficult it is to complete the item. You can then divide the value score by the effort score to get a prioritization score. This will help you identify items that have a high potential impact and are relatively easy to complete.
  2. MoSCoW: This is a prioritization technique that categorizes items as Must Have, Should Have, Could Have, or Won’t Have. The Must Have items are essential and must be completed in order for the project to be considered a success. The Should Have items are important but not critical. The Could Have items are nice to have, but not necessary. The Won’t Have items are not included in the current project. This method can help you focus on the most critical items first.
  3. Cost of Delay: This scoring system involves calculating the cost of delaying each item on the backlog. The cost could be based on factors such as lost revenue, missed opportunities, or increased risk. You can then use this score to prioritize items based on their potential impact if they are not completed quickly.
  4. Kano Model: This model helps you prioritize items based on customer satisfaction. It categorizes items as Must-Have, Performance, and Delighter. Must-Have items are basic features that customers expect. Performance items are features that improve customer satisfaction. Delighter items are unexpected features that can delight customers. You can use this model to identify items that will have the biggest impact on customer satisfaction.

Ultimately, the scoring system you choose will depend on your specific needs and priorities. It’s important to involve your team in the process to ensure that everyone is on the same page and understands the reasoning behind the prioritization.


Do you work for a product company or an advertising firm? To put it another way, do you create products that are sold to a single consumer or do you prefer to “build once, sell many”? If the latter, the following information should assist you identify the cause of your problem:


The concept of weighted scoring, which includes your own unique elements, appeals to me. For instance, at the cybersecurity firm where I used to work, guaranteeing PCI & HIPAA compliance was our main focus, thus stories that enhanced our coverage in either area would benefit from a force-multiplier that would assist them surface above less important items. Additional instances included the quantity of consumers affected, mandates (if we must comply with them and don’t have the option of delaying or ignoring them), etc.

If you have access to Pragmatic Marketing’s post-training materials, they provide some excellent examples of this strategy.


There are different ways, I like the RICE method . Reach (# of customers) Impact (H,M,L), Confidence (50, 80, 100) and Effort (man months)


Can your product be broken down into various features? Like such:


Assign each box a weight like a heatmap. Obviously features that “all of the people use all of the time” will get highest weight, and the inverse for the other corner.

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@RobMartin, the product is a file output that is ingested by our clients.

Superb article.

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Are the user stories about an application crunching the data faster? It sounds very unique, hard to offer any suggestions without more info on what kind of work is in your pipeline.

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