# Backlog ordering done right!

Various methods exist for helping product owners to decide which backlog item to start first. That this pays off to do so (more or less) right has been shown in blogs of Maurits Rijk and Jeff Sutherland.

These approaches to ordering backlog items all assume that items once picked up by the team are finished according to the motto: ‘*Stop starting, start finishing*‘. An example of a well-known algorithm for ordering is *Weighted Shortest Job First* (*WSJF*).

For items that may be interrupted, this results not in the best scheduling possible. Items that usually are interrupted by other items include story map slices, (large) epics, themes, Marketable Features and possibly more.

In this blog I’ll show what scheduling is more optimal and how it works.

## Weighted Shortest Job First (WSJF)

In *WSJF* scheduling of work, i.e. product backlog items, is based on both the effort and (business) value of the item. The effort may be stated in duration, story points, or hours of work. The business value may be calculated using Cost of Delay or as is prescribed by SAFe.

When effort and value are known for the backlog items, each item can be represented by a dot. See the picture to the right.

The proper scheduling is obtained by sweeping the dashed line from the bottom right to the upper left (like a windshield wiper).

In practice both the value and effort are not precisely known but estimated. This means that product owners will treat dots that are ‘close’ to each other the same. The picture to the left shows this process. All green sectors have the same ROI (business value divided by effort) and have roughly the same value for their *WSJF*.

Product owners will probably schedule items according to: green cells from left-to-right. Then consider the next ‘row’ of cells from left-to-right.

## Other Scheduling Rules

It is known at least since the 1950’s (and probably earlier) that *WSJF* is the most optimal scheduling mechanism if both value and size are known. The additional condition is that *preemption*, i.e. interruption of the work, is not allowed.

If either of these 3 conditions (known value, known size, no preemption) is not valid, *WSJF* is not the best mechanism and other scheduling rules are more optimal. Other mechanisms are (for a more comprehensive overview and background see e.g. Table 3.1, page 146 in [Kle1976]):

**No preemption allowed**

- no value, no effort: FIFO
- only effort: SJF / SEPT
- only value: on value
- effort & value: WSJF / SEPT/C
- Story map slices: WSJF (no preemption)

FIFO = First in, First out

SEPT = Shortest Expected Processing Time

SJF = Shortest Job First

C = Cost

*Examples*: (a) user stories on the sprint backlog: *WSJF*, (b) production incidents: *FIFO* or *SJF*, (c) story map slices that represent a minimal marketable feature (or short *Feature*). Leaving out a single user story from a *Feature* creates no business value (that’s why it is a minimal marketable feature) and starting such a slice also means completing it before starting anything else. These are scheduled using *WSJF*. (d) User stories that are part of *Feature*; they represent no value by themselves, but all are necessary to complete the *Feature* they belong to. Schedule these according to *SJF*.

**Preemption allowed**

- no value: SIRPT (SIJF)
- effort & value: SIRPT/C or WSIJF (preemption)
- SIRPT = Shortest Imminent Remaining Processing Time

SIRPT/C = Shortest Imminent Remaining Processing Time, weighted by Cost

SIJF = Shortest Imminent Job First

WSIJF = Weighted Shortest Imminent Job First

The ‘official’ naming for *WSIJF* is *SIRPT/C*. In this blog I’ll use *Weighted Shortest Imminent Job First*, or* WSIJF.*

*Examples*: (a) story map slices that contain more than one *Feature* (minimal marketable feature). We call these *Feature Sets*. These are scheduled using *WSIJF*, (b) (Large) Epics that consist of more than 1 *Feature Set*, or epics that are located at the top-right of the windshield-wiper-diagram. The latter are usually split in smaller one containing most value for less effort. Use *WSIJF*.

**Summary**

*User Story*(e.g. on sprint backlog and not part of a*Feature*): WSJF*User Story*(part of a*Feature*): SJF*Feature*: WSJF*Feature Set*: WSIJF*Epics, Story Maps*: WSIJF

## Weighted Shortest Imminent Job First (WSIJF)

Mathematically, *WSIJF* is not as simple to calculate as is *WSJF*. Perhaps in another blog I’ll explain this formula too, but in this blog I’ll just describe what *WSIJF* does in words and show how it affects the diagram with colored sections.

WSIJF: Work that is very likely to finish in the next periods, has large priority

What does this mean?

Remember that *WSIJF* only applies to work that is allowed to be preempted in favour of other work. Preemption happens at certain points in time. Familiar examples are Sprints, Releases (Go live events), or Product Increments as used in the SAFe framework.

The priority calculation takes into account:

- the probability (or chance) that the work is completed in the next periods,
- if completed in the next periods, the expected duration, and
- the amount of time already spent.

*Example*. Consider a Scrum team that has a cadence of 2-week sprints and time remaining to the next release is 3 sprints. For every item on the backlog determine the chance for completing it in the next sprint and if completed, divide by the expected duration. Likewise for completing the same it in the next 2 and 3 sprints. For each item you’ll get 3 numbers. The value divided by the maximum of these is the priority of the backlog item.

Qualitatively, the effect of *WSIJF* is that items with large effort get less priority and items with smaller effort get larger priority. This is depicted in the diagram to the right.

## Example: Quantifying WSIJF

In the previous paragraph I described the basics of *WSIJF* and only qualitatively indicated its effect. In order to make this concrete, let’s consider large epics that have been estimated using T-shirt sizes. Since *WSIJF* affects the sizing part and to less extent the value part, I’ll not consider the value in this case. In a subtle manner value also plays a role, but for the purpose of this blog I’ll not discuss it here.

Teams are free to define T-shirt sizes as they like. In this blog, the following 5 T-shirt sizes are used:

- XS ~ < 1 Sprint
- S ~ 1 – 2 Sprints
- M ~ 3 – 4 Sprints
- L ~ 5 – 8 Sprints
- XL ~ > 8 Sprints

Items of size XL take around 8 sprints, so typically 4 months. These are very large items.

Of course, estimates are just what they are: estimates. Items may take less or more sprints to complete. In fact, T-shirt sizes correspond to probability distributions: an ‘M’-sized item has a probability to complete earlier than 3 sprints or may take longer than 4 sprints. For these distributions I’ll take:

- XS ~ < 1 Sprint (85% probability to complete within 1 Sprint)
- S ~ 1 – 2 Sprints (85% probability to complete within 3 Sprints)
- M ~ 3 – 4 Sprints (85% probability to complete within 6 Sprints)
- L ~ 5 – 8 Sprints (85% probability to complete within 11 Sprints)
- XL ~ > 8 Sprints (85% probability to complete within 16 Sprints)

As can be seen from the picture, the larger the size of the item the more uncertainty in completing it in the next period.

*Note*: for the probability distribution, the Wald or Inverse Gaussian distribution has been used.

Based on these distributions, we can calculate the priorities according to *WSIJF*. These are summarized in the following table:

Column 2 specifies the probability to complete an item in the next period, here the next 4 sprints. In the case of an ‘M’ this is 50%.

Column 3 shows that, if the item is completed, what the expected duration will be. For an ‘M’ sized item this is 3.22 Sprints.

Column 4 contains the calculated priority as ‘value of column 2’ divided by ‘value of column 3’.

The last column shows the value as calculated using *SJF*.

The table shows that items of size ‘S’ have the same priority value in both the *SIJF* and *SJF* schemes. Items larger than ‘S’ actually have a much lower priority as compared to *SJF*.

*Note*: there are slight modifications to the table when considering various period lengths and taking into account the time already spent on items. This additional complexity I’ll leave for a future blog.

In practice product owners only have the estimated effort and value at hand. When ordering the backlog according to the colored sections shown earlier in this blog, it is easiest to use a modified version of this picture:

Schedule the work items according to the diagram above, using the original value and effort estimates: green cells from left to right, then the next row from left to right.

## Conclusion

Most used backlog prioritization mechanisms are based on some variation of ROI (value divided by effort). While this is the most optimal scheduling for items for which preemption is not allowed, it is not the best way to schedule items that are allowed to be preempted.

As a guide line:

- Use
*WSJF*(*Weighted Shortest Job First*) for (smaller) work items where preemption is not allowed, such as individual user stories with (real) business value on the sprint backlog and*Features*(minimal marketable features, e.g. slices in a story map). - Use
*SJF*(*Shortest Job First*) for user stories within a*Feature*. - Use
*WSIJF*(*Weighted Shortest Imminent Job First*) for larger epics and collections of*Features*(Feature Set), according to the table above, or more qualitatively using the modified sector chart.

## References

[Kle1976] *Queueing Systems, Vol. 2: Computer Applications*, Version 2, Leonard Kleinrock, 1976

[Rij2011] *A simulation to show the importance of backlog prioritisation*, Maurits Rijk, June 2011, https://maurits.wordpress.com/2011/06/08/a-simulation-to-show-the-importance-of-backlog-prioritization/

[Sut2011]* Why a Good Product Owner Will Increase Revenue at Least 20%*, Jeff Sutherland, June 2011, https://www.scruminc.com/why-product-owner-will-increase-revenue/

## Comments

Thanks for the comprehensive overview! Looking at the various formulas and options, I’m a bit surprised that these don’t seem to have been integrated into many of the popular tools in which teams actually manage their backlogs (or have I missed some features?).

What does this imply about the adoption of these formulas? Is there any literature on how much teams have benefited by switching to the “right” method?

Hi Andrew,

You are right that the fact that tools don’t support the SIJF prioritization raises questions as to whether it usable at all: surely there must be a good reason they did not implement SIJF?

I always try to keep an open mind for new stuff and an opportunity will come by to apply it.

Main reason I believe is that people simply are not aware of SIJF although it is known since the ’70s.

Especially on portfolio level it may be interesting.

pieter

I’m intrigued by the different tactics used depending on the conditions. Deciding which feature to build first is different to how can we deliver the feature faster. I always think of prioritisation of features as strategy and prioritisation of stories in a feature as tactics.

Great article.

@Andrew, there are tools that do use formulas to provide insight to your features. I also used to use excel for feature prioritisation.