- Infinite backlog problem
- Incredible shrinking backlog
- Backlog abstraction layer ←
The infinite backlog problem describes how ‘stakeholders’ pollute software development teams’ backlogs with feature requests, and the waste that causes. Development teams need to shrink their backlogs.
Just enough backlog
Developers only need items on the backlog just in time. In an ideal world, developers wouldn’t need a backlog at all. In practice, it takes time to decide what to work on next, and split the work into development-sized chunks, so teams need to queue up some work in advance.
A small team that plans a week ahead only needs a small backlog. A week’s work for 4-6 developers leaves so few backlog items that you can use really simple tools, and have much shorter meetings.
The small backlog solution requires two things:
- continuous delivery, or at least weekly releases
- another way to manage feature requests.
Modern software development covers continuous delivery, but redirecting feature requests requires something else. It requires product management.
Product feedback databases
Product managers routinely collect product feedback from various internal and customer sources. This feedback firehose would drown development teams if they tried to consume it directly, so product managers consolidate this feedback into something more useful than a stream of feature requests.
First, you reframe feature requests as feedback. When a customer says they want a feature, they don’t necessarily actually need it, but they did just give you feedback that they need something.
A feedback database captures this raw feedback, ideally including direct customer quotes, for classification and analysis. Instead of using this feedback database as a development backlog, product managers use it as supporting evidence for product prioritisation decisions.
Feature wish hierarchies
Next, consolidate customer feedback into a list of unique feature requests, showing how many customers requested each feature. However, these feature wish lists quickly become longer than my product management books wish list, and like the difference between blog posts and books, some features would require significantly more time and effort than others.
To cope with its size, the wish list becomes a feature wish hierarchy, for example grouping requests for different kinds of data exports into a more abstract data export feature. Organising every feature request into a huge feature hierarchy gets you a horrific preview of a huge monster product with every possible feature.
Please don’t build Godzilla software. Instead, you can further analyse feature requests, discover patterns, and create a more valuable abstraction. And then you add another layer of abstraction.
Abstract problem space
After grouping various features into data export features in general, you can recite the standard product management inquiry: what problem do you want to solve? This reframes the abstract feature as an opportunity.
For example, data export becomes sharing data with other people or using multiple software tools, or however else your customers talk about their corresponding problems, frustrations and needs. As with the feature hierarchy, you can also organise these opportunities into a hierarchy of opportunties at difference levels of abstraction, i.e. an opportunity solution tree.
Ironically, programmers love both tree structures and extra levels of abstraction, so you won’t find it difficult to explain replacing the development backlog with a hiearchical problem space abstraction layer, even if you normally call it something else.