The problem with RICE

There's a seemingly popular "framework" for working out which feature to build next, called RICE. RICE was introduced by Sean McBride, while he was a product manager at Intercom.

(I write "framework" in quotes, because to my eyes it is a weighted formula, and not an entire framework.)

I don't think RICE is very helpful.

RICE - and similar "frameworks" - provide an illusion of objective decision-making, while being utterly subjective.

Here's a brief explanation of RICE - but it's better to go and read the article about it on Intercom's website before continuing:

RICE stands for Reach, Impact, Confidence, and Effort. It argues for assessing potential new features using a simple formula made up of these 4 components.

RICE score = Reach * Impact * Confidence / Effort.

While researching Kill the HiPPO, my book on feature prioritisation, I've discovered that many teams who try RICE soon abandon it. Grizzled veterans in our field even mock it.

The reasons for this include:

organisations who try it are not impressed with the results.
it ignores the strategic reasons for choosing what feature to build next.
it purports to be objective, while hiding the reality that it is utterly subjective.
it is predicated on being able to make good estimates for "Impact" and "Effort". Estimating these things for software projects are notoriously hard. Even the most experienced and successful leaders in the software industry admit to not being good at estimating effort.
it is optimised for one company, Intercom, at a specific point in its own history, and not for your company right now.

I'm not alone in my negative view of RICE and similar approaches. Rich Mironov - who calls them "ROI tools" writes:

I’m part of many discussions where tech company execs try to apply Return on Investment (ROI) tools to make hard choices about what to build, or where to invest costly-and-scarce development resources. It rarely turns out to be as useful as we hoped

Gareth Marlow writes:

I'm going to be brutal here. The RICE framework is not adopted because it's highly subjective and pseudo-quantitative which gives the illusion of providing clarity when all it actually does is provide some navel-gazing validation behind existing biases.

Or, put another way, if creating actual, meaningful, game-changing value was as simple as guesstimating four numbers per idea and sticking them into a spreadsheet, the approach would have been universally adopted because it would just work.

Jason Cohen writes:

It’s difficult to predict numbers like “revenue-increase due to feature X"... in every case the number in the spreadsheet contains significant error.

and

Effort is almost always under-estimated

and

No matter how you measure impact, your numbers end up far less precise than they appear in the spreadsheet.

Defending RICE

To be fair to Sean McBride, creator of RICE, he acknowledges its shortcomings. He even recommends that you don't use RICE as an ultimate arbiter, but rather as a means to help guide your decisions. Quoting Sean,

Of course, RICE scores shouldn’t be used as a hard and fast rule. There are many reasons why you might work on a project with a lower score first.

RICE will help you make better-informed decisions about what to work on first and defend those decisions to others.

If you are coming from a chaotic system of feature prioritisation, where you arbitrarily choose what to work on based on your instinct, or based on what looks most exciting to you, or based on what your loudest customer is asking for, then RICE is indeed a good step towards improving by actually considering and comparing systematically.

Improving on RICE

I think RICE - or any such formula-based approach to prioritisation - is good if you use it only as a starting point for your decision. That is, don't use the score generated by RICE as the way to make a decision. Use it to get the conversation started.

But even then, don't use RICE for this. With your team, create a weighted formula that uses the factors that are important to where your team is right now. But again, as a starting point for discussion.

Your team should regularly tweak the formula, changing the weightings, introducing new components in the formula, and dropping those that aren't working well.

One factor I you should include - and I have 100% confidence of this - is the ineffable. Call it "Vision" or "Vibe", or even "X-factor". And give this factor the highest weighting.

Always consider the ranking returned by your own custom prioritisation formula as a starting point. Because these rankings-based approaches only provide an illusion of objective decision-making.