Better Backlog Creation & Prioritisation

4 tips for more effective product and feature planning.

As product managers, or leaders in other roles, colleagues often look to us to decide which features to invest in, and when. The reality is there’s rarely a simple answer to the question “what next?”, but rather than guessing, there are several approaches being used in the industry that greatly help in finding opportunities, analysing their impact and shipping them efficiently.

We’ve put some of these to the test at Property Finder and wanted to share several effective backlog creation and prioritisation techniques that are having a real impact on our product development.

Before diving into prioritisation techniques, I wanted to raise the importance of effective decision-making, and in particular, making decisions when you don’t have all the answers. This is a vital skill that anyone making decisions that affect business investment should have, but one that rarely feels comfortable.

All of the techniques listed below are essentially tools designed to help you make more effective, more objective and less risky decisions, and over time I’ve learnt the power of acknowledging my inability to make good decisions without support from data, research and my colleagues.

I can promise you that, instead of needing to have all of the answers, admitting your own uncertainty will allow you to:

  1. Articulate what you don’t know and strive to fill the gaps in your knowledge (with quantitative and qualitative research) before spending x days, weeks, months building a product.
  2. Acknowledge that failure is a possibility, encouraging you to start small and test.
  3. Identify, and quantify, the risks in your decisions and use small tests (read more about Riskiest Assumption Testing (RAT) here) and product iterations to validate or invalidate these risks.

A note before I close this section that a lot of my thoughts on decision-making come from Annie Duke. You can read her book, Thinking in Bets, or listen to an interview with her on the This is Product Management podcast.

Additional thanks to Property Finder’s VP Product, Yi Wei Ang, for bringing Riskiest Assumption Testing (RAT) to my attention.

Several months back, I was faced with a problem. I’d be given the medium-term results our business unit needed to achieve, and I needed to form a backlog to get there.

I’d taken time to do my due diligence. I’d dug into our usage data, drawn on qualitative research we’d run in the weeks prior (we perform explorative quantitative and qualitative research with our users every four months, as well as ongoing usability testing for new-feature releases). However, every time the team and I tried to come up with solutions to meet our goals, we struggled.

I spent quite a bit of time thinking about why were struggling to turn the insights we had from data and research into solutions, and I realised that we had a very solvable problem on our hands.

We knew where we needed to get to, and we had some insights about where we were, but we’d failed to find an effective way to connect the two.

Have you found yourself in this situation? You have insights but you’re struggling to turn them into actionable solutions that drive business results.

I was recommended Teresa Torres’ Opportunity Solution Tree by a fellow product manager, and I felt that this could be a possible solution to my team’s troubles.

In this method, you are forced to take a step back from simply creating solutions. And instead, you are encouraged to turn your insights into opportunities, allowing you to more easily articulate solutions that will drive a desired outcome.

You can read much more about this approach here, but to put it into context, here is a real example of an opportunity solution tree from our business. We added an insights layer to our solution tree, and Teresa Torres also advises that opportunities should come from insights generated through research.

An example of an opportunity solution from the Property Finder consumer team.

I wanted to talk about the Opportunity Solution Tree in this article as we’ve had enormous success using it. Through this approach our team was able to generate a large amount of solutions to drive key consumer and business outcomes, several of which we’ve taken live through experiments over the past two months and have had an enormous impact on the metrics they were designed to drive.

If you’re looking to generate ideas, and particularly if you want to involve a wider team (who may not have in-depth knowledge of your product, customers and market) in this process, I highly recommend it.

It’s worth noting that we paired this ideation process with strong validation and prioritisation, which allowed us to bring the most impactful experiments to our users first. Read on to find out more about how we prioritised our solutions…

Once you have your backlog of ideas, it’s often hard to know where to start. I’ve tried many prioritisation methods over my career including MoSCoW (a simple and fairly effective prioritisation method, and a good place to start if your stakeholders are new to product prioritisation), Effort vs Impact Matrix (slightly more complex and slightly more effective as it factors in the effort to deliver a feature).

The approach I’ve found the most effective, however, is RICE, pioneered by the customer success business Intercom. We used RICE to prioritise the output off our opportunity solution tree ideation exercise and it helped us deliver a large amount of user and business value quickly, giving the business confidence in our approach to meeting the goals they’d set us.

RICE stands for:

  • Reach — How many people you estimate your idea will reach within a given period.
  • Impact — The impact your idea will have on an individual person.
  • Confidence — The confidence you have in your estimations.
  • Effort — An estimate of the total amount of time required from all involved team members to deliver your idea.

For me, the power of this prioritisation method comes in the fact that it not only takes into account Reach, Impact and Effort, but that it also asks you to think about your Confidence of the estimates you’ve given. As mentioned earlier in this article, prioritising and making good decisions is not just about quantifying impact, but also understanding the likelihood of success or failure.

It’s worth noting that RICE is not a pixel-perfect prioritisation method as it can require you to make some assumptions about potential Reach and Impact, and I’ve observed that many people struggle to assign RICE scores to their ideas without a fair amount of self doubt. However, my advice is always — if your ideas have been sufficiently validated, it’s not critical that your get your prioritisation 100% accurate. There’s room for error, and RICE provides and excellent general direction for your product development. Additionally, providing a Confidence score for your estimates reduces the impact on any uncertain assumptions you’ve made.

To start prioritising with RICE, you can use this handy RICE prioritisation template from Intercom.

It’s important to remember that all of the approaches mentioned above are not one-off or linear and that great product management comes from being consistent as well as making improvements to your approach where possible. I’ve been working as a product manager for 7 years and I’m still honing my ideation and prioritisation skills.

We’re often put under pressure to deliver quickly and efficiently, and being a good product manager doesn’t always have to mean doing everything by the book. However, it is crucial to understand that there will be flaws in the decisions we make, and therefore we must acknowledge the importance of working as hard as we can to mitigate the risks caused by this.

If you liked this article and want to be part of our brilliant team that produced it, why not have a look at our latest vacancies here.

Product Manager and Product Leader. Writing from experience. Often caffeinated. Passionate about what I do. Senior Manager for Product @talabat, Delivery Hero