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RICE template

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How this template works

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To use this template, you do not need to know how things are working under the hood here. But if you’re curious about relational databases, want to change the formula (perhaps you do something similar to RICE but not 100% aligned to the framework, like ICE), or just want to do learn more about Coda, this is a helpful guide.
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Deleting this section will not impact any data or calculations above. Any tables referenced here are of the source data above.

Example

Let’s take a look at the
@Example
product feature and how we calculate the score.
Example feature 2
3
Feature name
Reach
Impact
Effort
Confidence %
RICE Score
1
Example
Small
Medium
M
000
39
16
No results from filter

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Formula

Screen Shot 2023-01-04 at 10.53.53 AM.png
This solution uses a in the Score column that calculates the RICE score. Instead of referencing cells like A1 or B2 with Sheets, this Coda formula understands what your data is all about. This means that columns have names and you can refer to them as such! Basically, it’s doing all the hard work of for you.
Screen Shot 2023-01-04 at 11.01.22 AM.png

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To see the formula (and make any changes), hover over the column and click the f (formula icon) or right click the column title and select Edit Formula


References

Each of the reach, impact, and effort columns looks and functions like a select list, but the options (and underlying data) are actually coming from another table. In this example, hover over the reach column title and click the table icon, you’ll see that it’s a connected to the table.

Screen Shot 2023-01-04 at 11.07.58 AM.png

The 3 options in the reach column—Small, Medium, Large—correlate with the 3 rows in the reach table. If you were to add a new row to the reach table—let’s say, Tiny—you’d then see “Tiny” show up as an option in the reach table.
Screen Shot 2023-01-04 at 11.12.43 AM.png
Reach column options
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Reach table

Ok, back to the how this plays into the formula. You can’t do math like adding or multiplying on words (small x high = ???), so we’ll need to get some numbers into this formula by associating values to each of the options. In the reach table, you’ll find that Small = 1000, Medium = 4000, Large = 10,000.
Screen Shot 2023-01-04 at 11.12.04 AM.png
To get the numbers into your formula, you’ll need to pull the associated value from the table into your table.

Screen Shot 2023-01-04 at 11.03.14 AM.png
Check out Reach, Impact, Effort in the formula. See the “.” after each of the column names with different colored names after that? What we’re doing is “” which uses the “dot operator” after the column title and allows you to “get into” the other table. This is basically what a is doing in Sheets.

Bringing it all together

Below you’ll see how RICE works in Coda (and any application that calculates it), a sort of ER (entity relationship) diagram in relational database lingo. Select Medium from the Reach column and it puts 4000 in the formula. High in Impact brings us a 3. And our Confidence is 60% (it’s already a number is we get raw select list 60 into a percent by dividing it by 100). And lastly, we divide it all by 12 which is the Effort’s number of hours.

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Stack ranking

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Now that RICE score is flowing through based on the inputs within the columns, how do we bring the most promising features to the top of the list? For example, if the
@New mobile app
we decide isn’t a small Reach but in fact has a Large Reach after more research and understanding our TAM. See how the score changes from 19 to 185 and moves the feature closer to the top of your stack.

We then based on the RICE score in descending order so that the most promising features rise to the top of your product roadmap.
Screen Shot 2023-01-04 at 11.37.35 AM.png

Summary

And that’s a wrap on how to do RICE in Coda. If you use another prioritization framework like Big Bets, ICE, MoSCoW, please drop a comment here
@Prioritizing features for the roadmap
and we can get more examples going in this space.
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