Prioritize

Vote on the nodes that matter most, then read the result together.

Purpose

Find where the group's attention should go next. Votes show where the group's concern is concentrated. The discussion that follows shows why.

When it starts and ends

Prioritize starts after Connect, once the tree has a visible shape.

It ends when the group agrees which nodes matter most, and which of them go to Decompose.

Steps

Decide what to vote on. Usually it is one kind of node: the problems, to find the most fundamental ones, or the outcomes, to find the goals that matter most.
Give each participant fewer votes than there are items. With as many votes as items, everyone votes for everything and no signal emerges. A good guide is about 20 to 30% of the items: 6 to 9 votes each for 30 items, or 3 to 5 on the smaller board of a first session.
Vote. Participants place dots, tally marks, or digital votes on the nodes they choose. A participant may put more than one vote on a node.
Read the results together, and ask about the surprises.

Does this ranking make sense? Are there any surprises?

See the prioritization pattern for how to run this discussion.
Mark the top-voted nodes so they stand out: a star, a bold label, or an accent within the node.
Choose what comes next. In a full session, pick the 2 to 5 nodes that go to Decompose. In a first session, agree on next steps instead.
Close Prioritize.

Now let's go deeper on the areas that matter most.

Timing

Group size	Suggested time	What to expect
3-7 participants	10-15 min	Dot voting, or verbal agreement
8-15 participants	15-20 min	Leave time to discuss the results
16-30 participants	20-30 min	Dot voting, then discussion of the top results

For the whole session, see timing.

Tips

If you facilitate from inside the group, vote last. Your votes then cannot steer anyone else's.
Ask for the case for a node with few votes. A node 1 person argues for may be the hidden issue the group has been avoiding.
Use the blocked outcomes view. For an outcome with many votes, the blocked outcomes view shows every problem in its way.

Traps

Reading the tallies and moving on. The count shows where concern is concentrated. Only the discussion explains it.
Treating the vote as a decision. Votes say where to look first. Deciding what to do about it happens after the tree has done its job. See what it is and is not.

Example

The 12 participants of the renewals session voted on the 14 problems. Each had 3 votes, about 20% of the problems. The facilitator voted last.

Only the problems near the top votes are shown. Outages, sales promises, and escalations got the most.

Diagram as text: Votes on the problems of the renewals tree

Nodes:

Root / Problem: "Sales promises custom features to close deals" (7 votes)
Root / Problem: "On-call ignores alerts because most are noise" (1 vote)
Root / Problem: "The roadmap is reshuffled for every big deal"
Root / Problem: "Large customers run custom code paths" (1 vote)
Root / Problem: "Tier 1 support cannot see a customer's setup" (1 vote)
Root / Problem: "Outages hit during the morning dispatch rush" (8 votes)
Root / Problem: "Most tickets are escalated to engineering" (6 votes)
Root / Problem: "Customers hear about outages from their technicians" (4 votes)
Root / Problem: "Reliability work never makes it into a sprint" (5 votes)

Arrows:

"Sales promises custom features to close deals" influences "The roadmap is reshuffled for every big deal"
"Sales promises custom features to close deals" influences "Large customers run custom code paths"
"Large customers run custom code paths" influences "Most tickets are escalated to engineering"
"Tier 1 support cannot see a customer's setup" influences "Most tickets are escalated to engineering"
"The roadmap is reshuffled for every big deal" influences "Reliability work never makes it into a sprint"
"Most tickets are escalated to engineering" influences "Reliability work never makes it into a sprint"
"On-call ignores alerts because most are noise" influences "Outages hit during the morning dispatch rush"
"Outages hit during the morning dispatch rush" influences "Customers hear about outages from their technicians"

Three problems stood out: outages during the morning rush, sales promises of custom features, and escalations to engineering. Each one went to a subgroup in Decompose.

One result surprised the group. Following the arrows under a problem with 5 votes led to one of its deepest roots, a problem with a single vote. The prioritization pattern tells that part of the story.