Use cases

What teams decide with DCZion

22 worked examples across six kinds of decision. Each one shows what the team entered, what the engine returned, and the arithmetic in between — because a number nobody can reproduce is a number nobody trusts.

Hiring & promotion · 3Performance & remuneration · 4OKRs & planning · 4Strategy & direction · 3Product & engineering · 4Ops, vendors & risk · 4

Figures are illustrative sample runs used to show the method, not customer data.

Hiring & promotion

Someone has to choose between people. The panel walks in with four different impressions of the same interview, and the most senior voice tends to win. Here, every interviewer scores the same candidates against the same criteria before the debrief, and the panel sees where it agrees and where it does not.

groups3–7 interviewers · 2–4 candidates · result: one candidate plus the criteria the panel split on

Executive hire — VP of Engineering

Five interviewers, three finalists. Each interviewer scores all three candidates as a range before seeing anyone else's numbers.

CriterionPriorityCandidate A (domain expert)Candidate B (hyper-growth leader)Candidate C (generalist)
Execution & track record98.67.17.9
Values & team multiplier87.48.98.0
Strategic thinking & autonomy86.28.47.2
Compensation & start date6.55.87.07.6
Weighted total (priority × score, summed)223.9247.8242.1

Cells are the mean of the panel's estimates. Each interviewer entered a range (for example 7–10, not 8.5), and the ranges — not the means — are what the simulation samples, so one unsure interviewer widens the uncertainty instead of shifting the average.

check_circleRecommended: Candidate B. Condorcet winner — beats Candidate C head-to-head and Candidate A head-to-head, in 58% and 71% of 10,000 simulations.
functionsHow those inputs became that answer: Candidate A wins the heaviest criterion (execution, priority 9) but comes last on strategy and on start date. B is second-best everywhere and first where strategy and team culture carry weight: 9×7.1 + 8×8.9 + 8×8.4 + 6.5×7.0 = 247.8, against C 242.1 and A 223.9. B is not the panel's favourite on any single line — it is the only candidate that no other candidate beats one-on-one, which is the question the run actually asks.

Internal promotion — senior to staff engineer

Four peers plus the engineering manager, two candidates. Scored blind, so the peers cannot anchor on the manager's opinion and vice versa.

CriterionPriorityCandidate A (platform)Candidate B (product)
Scope owned at the next level99.07.4
Quality & craft88.69.1
Collaboration & unblocking others87.98.5
Communication78.27.6
Weighted total (priority × score, summed)270.4260.6

Cells are the mean of the panel's estimates. Each interviewer entered a range (for example 7–10, not 8.5), and the ranges — not the means — are what the simulation samples, so one unsure interviewer widens the uncertainty instead of shifting the average.

check_circleRecommended: Candidate A. Weighted result 270.4 to 260.6; the disagreement flag marks one criterion as high-disagreement.
functionsHow those inputs became that answer: The peers and the manager split on scope: peers scored A 9 and 10, the manager scored 7–8. Every other criterion agrees. So the run both picks A and tells you the promotion rests on a criterion your data is not settled on — the conversation starts there rather than on the total, which is the part a spreadsheet comparison hides.

Leadership election — rotating team lead

Six members, three candidates including one self-nomination. Everyone scores all three; nobody sees the running totals while scoring.

CriterionPriorityCandidate 1Candidate 2Candidate 3
Trust98.47.68.0
Delivery88.08.77.4
Fairness & inclusivity8.58.87.08.2
Availability77.28.67.9
Weighted total (priority × score, summed)264.8257.7256.2

Cells are the mean of the panel's estimates. Each interviewer entered a range (for example 7–10, not 8.5), and the ranges — not the means — are what the simulation samples, so one unsure interviewer widens the uncertainty instead of shifting the average.

check_circleRecommended: Candidate 1. Wins the heaviest two criteria and both head-to-head comparisons.
functionsHow those inputs became that answer: The result is close on totals (264.8 / 257.7 / 256.2) but decisive pairwise: Candidate 2 leads only on availability, which is the lowest-weight criterion at 7. An election where the answer comes from the pairwise order rather than from one weighted total is much harder to contest after the fact — which matters when the winner will manage the people who lost.

Performance & remuneration

The quarterly or annual cycle, and the pay decisions that follow it. Everyone on the list is scored on the same criteria, blind, and the person running the review is scored too — their own row is their self-evaluation. The result is a per-person number for reviews, promotion and remuneration that the team can see the reasoning behind.

workspace_premium4–12 people · criteria agreed in advance · result: a ranking, the self-versus-team gap, and the disputes named

Quarterly review — five-person team

Everyone scores everyone against the agreed criteria, blind, and each person's own row is their self-evaluation. The lead is on the list like everyone else.

Person
Team score
Self
Gap
Reading
Member D
8.6
8.1
peers 0.5 higher
Top of cycle
Member A (Team Lead)
8.5
9.2
self 0.7 higher
Top of cycle — own row is the self-evaluation
Member B
7.8
7.6
aligned
Solid
Member C
6.9
7.4
self 0.5 higher
Below the bar — development plan
Member E
6.2
6.4
aligned
Below the bar — development plan
check_circleRanking Member D → Member A → Member B → Member C → Member E, with the self-evaluation shown next to each team score.
functionsHow those inputs became that answer: Every member's estimate of a person counts once in that person's number, self-evaluation included, weighted by the criteria priorities. The self column sits beside the team score so the gap is visible instead of being averaged out of sight. Because the lead is scored on the same list and the same criteria, the "who reviews the reviewer" question never comes up.

Annual cycle with a raise pool of two

Six people, one pool. The band boundaries are agreed and frozen before scoring opens, so nobody can renegotiate the line after seeing the numbers.

Person
Team score
Self
Gap
Reading
Engineer 1
8.9
8.4
peers 0.5 higher
Band A — funded
Engineer 4
8.2
8.6
self 0.4 higher
Band A — funded
Engineer 2
7.7
7.5
aligned
Band B
Engineer 5
7.1
7.0
aligned
Band B
Engineer 3
6.4
7.2
self 0.8 higher
Band C
Engineer 6
6.0
6.1
aligned
Band C
check_circleTwo people above the pool line; the two largest self-versus-team gaps are the ones with a conversation attached.
functionsHow those inputs became that answer: Remuneration is the least reversible outcome in the catalog, so the process matters more than the arithmetic: criteria and bands fixed in advance, every member scoring every member blind, and a recorded trail. The team score is the mean of all the estimates; the gap column is where a review meeting should look first, because a 0.8 self-versus-peers gap is either a communication problem or a real misread of the role — both are worth knowing before the band is set.

Calibration — two squads on one scale

Seven people across two squads. Each person is scored by their own squad plus two reviewers from the other squad.

Person
Team score
Self
Gap
Reading
Squad 1 — dev
8.4
8.0
peers 0.4 higher
Calibrated above squad 2's top scorer under the same criteria
Squad 2 — dev
7.9
8.1
self 0.2 higher
Cross-squad reviewers scored 0.6 lower than own squad
Squad 1 — dev
7.2
7.0
aligned
Consistent across both squads
Squad 2 — dev
6.6
7.3
self 0.7 higher
Own squad 0.9 above the cross-squad mean
check_circleOne comparable scale for both squads, with the cross-squad gap visible on every row.
functionsHow those inputs became that answer: Two squads rate to their own anchors: a 7 in one team is a 9 in another. Each member's priorities are normalised against their own top criterion before anything is averaged, and the cross-squad reviewers pull the scored range toward one scale. Where the own-squad and cross-squad views disagree by 0.9 points, that is a calibration question with evidence attached, not a manager's hunch.

Off-cycle promotion — "now" against "next cycle"

Not a ranking of people but a two-option decision about one person: promote this cycle, or build the case and revisit.

Person
Team score
Self
Gap
Reading
Promote now
Criteria: evidence at the next level (priority 9), peer benchmark (8), budget & headcount (6), retention risk (7)
Recommended
Wait a cycle
Same criteria, same four reviewers, including the person's own manager and two peers
Beaten on evidence and on retention risk
check_circleRecommended: promote now. The comparison is not close on evidence at the next level, and retention risk raises the cost of waiting.
functionsHow those inputs became that answer: The person is the subject, not the scorer, and the manager is one of four inputs rather than the only one. Framing it as a two-option decision also produces the thing a promotion case usually lacks: a written record of what the team believed about the evidence at that moment, which is exactly what a later challenge to the decision will be tested against.

OKRs & planning

Quarterly planning: five objectives, four initiatives, three roles, one budget. The work is choosing, and the argument is usually about which criterion matters — not about the facts. Scoring each candidate objective against weighted criteria turns that argument into a number the room can check.

track_changes5–10 leaders · criteria include reversibility, urgency and confidence · result: a ranked order and where it is fragile

Q3 OKR prioritization — five candidate objectives

Nine people across product, engineering, sales and support. Criteria: revenue impact (9), strategic fit (8), effort (7), risk (6). Scores below are the team's mean per objective, expressed on a 0–100 weighted scale.

1. Onboarding activation
80.3
Decided it: strategic fit 9.2 — the least contested criterion in the round
2. Enterprise SSO & audit logs
79.9
Decided it: revenue 9.0. Contested: effort, scored 4 by engineering and 8 by sales
3. Self-serve billing
75.4
Strong revenue, weakest effort score of the top three
4. AI assistant beta
62.9
Fit is good, risk score is the lowest of the five
5. Mobile app rebuild
53.9
Lowest on every criterion; effort scored 4.8 across the team
check_circleRecommended: commit to both onboarding activation and enterprise SSO.The top two are 0.4 points apart, so the run splits its win share between them almost evenly rather than pretending one is the answer — and it flags the effort estimate on SSO as the criterion the team is genuinely divided on.
functionsHow those inputs became that answer: an objective's score is its per-criterion means multiplied by the criteria priorities and divided by the priorities' total. Onboarding: (9×7.0 + 8×9.2 + 7×8.4 + 6×7.6) ÷ 30 × 10 = 80.3. Enterprise SSO: (9×9.0 + 8×8.8 + 7×5.6 + 6×8.2) ÷ 30 × 10 = 79.9. Half a point of effort separates the two — engineering scored SSO's effort 4, sales scored it 8, and that 4-point spread is what the disagreement flag is pointing at.

Budget allocation across four initiatives

Four initiatives competing for $400k of the quarter's budget. Same scoring as above, with TCO and opportunity cost added as criteria.

check_circleA defensible order for the split, so the arguments happen about criteria and evidence instead of about whose programme is louder.
functionsHow those inputs became that answer: Every initiative was scored by the same people on the same criteria before anyone knew the order. If someone disagrees with the split, the disagreement is a specific criterion score they can point at — which is a resolvable argument, unlike "my project matters more".

Three roles, two headcount slots

Platform engineer, product designer and data engineer are all argued for. Two slots.

check_circleTwo opened, one deferred with the reason written down.
functionsHow those inputs became that answer: Deferring a role is a decision too, and the run gives the deferred role an evidence trail: which criteria it lost on and by how much. That is the difference between "we did not get to it" and "here is what would change the answer next quarter".

What to stop doing

Four running programmes, and the decision is which to wind down.

check_circleOne programme wound down, three kept, with the cost of restarting as the stated reason.
functionsHow those inputs became that answer: When the choice is between stopping things that all look worth doing, the deciding evidence is usually the reversal cost rather than the benefit. Scoring it as a criterion makes that reasoning explicit instead of leaving it as an unspoken tiebreaker.

Strategy & direction

Market entry, positioning, build against buy, go or no-go. These are the decisions where a weighted total is least persuasive, because everyone can argue that their favourite criterion was underweighted. So the run reports the head-to-head result instead: how often option A beats option B when only the two are compared.

flag6–12 people · 3–5 options · result: every pairwise comparison, plus a warning when the team is split

Market entry — now, through a partner, or later

Eight people across sales, product and finance. Each scores the three routes per criterion as a range; the run samples those ranges 10,000 times and counts the head-to-head wins in each draw.

Enter the EU now
Partner with a local reseller
Wait two quarters
Enter the EU now
42%
54%
Partner with a local reseller
58%
63%
Wait two quarters
46%
37%

Row beats column in that share of 10,000 simulations. Green means the row option wins that pairing, red means it loses.

check_circleRecommended: partner with a local reseller. It is the Condorcet winner — it beats both other routes head-to-head — and it beats the runner-up in 63% of simulations.
functionsHow those inputs became that answer: The matrix is the whole answer, and it is read one row at a time: the partner route wins against "enter now" in 58% of the sampled draws and against "wait" in 63%. No option beats it anywhere. That is a stronger claim than being first on a weighted total, because it holds in every one-on-one comparison the group could be asked to accept.

Positioning — premium, mid-market or product-led

Six people, three positions, and a genuinely split room.

Premium
Mid-market
Product-led
Premium
47%
52%
Mid-market
53%
45%
Product-led
48%
55%

Row beats column in that share of 10,000 simulations. Green means the row option wins that pairing, red means it loses.

check_circleNo Condorcet winner. The run reports a cycle: premium beats product-led, product-led beats mid-market, mid-market beats premium — and falls back to the option with the most pairwise wins, which here is a tie.
functionsHow those inputs became that answer: A cycle is the honest output of a split team, and the software says so instead of manufacturing a winner. The useful part is the follow-up: the disagreement tab shows which criterion the three positions actually diverge on (mid-market and premium disagree on pricing power, product-led and premium on time to first value). Re-score that criterion and the cycle usually breaks — either way, you learned the decision is not ready rather than learning it three months later.

Corporate development — acquire, invest, or build

Seven people including finance and legal. Integration cost carries the highest priority and the widest ranges.

Acquire
Minority investment
Build in-house
Acquire
49%
61%
Minority investment
51%
57%
Build in-house
39%
43%

Row beats column in that share of 10,000 simulations. Green means the row option wins that pairing, red means it loses.

check_circleRecommended: minority investment — barely. It beats acquire in 51% of simulations, which the run flags as fragile rather than settled.
functionsHow those inputs became that answer: A 51% margin is a coin flip with paperwork. The fragility check is the point of the example: the winner is named, the margin is stated, and the sensitivity view shows which single input decides it — here, the integration-cost range. Tighten that estimate with two weeks of diligence and the same team can re-run the decision with better data instead of re-arguing the conclusion.

Product & engineering

Roadmap bets, architecture, migrations, whether to stop and pay down debt. Engineering calls are usually not disputed on the facts — they are disputed on one estimate, made by people who see different parts of the system. This layout puts that estimate and the result side by side.

architecture4–10 engineers · 2–4 options · result: the decision, the contested criterion, and the input that would flip it

Roadmap bet — rebuild the import pipeline or keep patching it

Six engineers and the product lead. Three criteria carry real disagreement: effort, reliability gain, and cost of delay.

Where the team disagrees

Effort

Scored 4 by two engineers who have worked in the pipeline, 8 by two who have not — a 4-point spread, the widest in the run.

What would change the answer

One point lower on effort for the rebuild (6.4 → 5.4) and the rebuild wins outright instead of tying.

Patch 52%Rebuild 48%
functionsHow the numbers became the answer: every member scores each option on a range, the run samples those ranges 10,000 times, and the split above is the share of samples each option wins. A criterion the team is far apart on shows up as high dispersion, which is why the run names it instead of hiding it inside the average.

Architecture — modular monolith, microservices, or leave it alone

Five people across platform and product engineering, scoring operational cost at the current team size.

Where the team disagrees

Operational cost at our team size

Platform scored microservices 7–9, product scored it 3–5. The same option, a five-point split, decided entirely by who is carrying the pager.

What would change the answer

If the headcount plan doubles, microservices takes the pairwise lead and the recommendation changes.

Modular monolith 61%Microservices 39%
functionsHow the numbers became the answer: every member scores each option on a range, the run samples those ranges 10,000 times, and the split above is the share of samples each option wins. A criterion the team is far apart on shows up as high dispersion, which is why the run names it instead of hiding it inside the average.

Re-platform — now or after the busy season

Four people, two options, and a hard external date.

Where the team disagrees

Risk exposure in the busy window

Scored 3–8 depending on whether the scorer assumed the migration can slip. That assumption, not the technical work, is the whole disagreement.

What would change the answer

A migration that can be paused mid-flight flips the answer to "now" on the same scores.

After the season 67%Now 33%
functionsHow the numbers became the answer: every member scores each option on a range, the run samples those ranges 10,000 times, and the split above is the share of samples each option wins. A criterion the team is far apart on shows up as high dispersion, which is why the run names it instead of hiding it inside the average.

Tech debt against the feature freeze

Eight people across engineering and support, with churn data from the previous quarter as shared evidence.

Where the team disagrees

Cost of carrying the debt

Support scored it 8–9, engineering 4–6. Engineering is carrying it; support is hearing about it.

What would change the answer

If the freeze runs two sprints instead of four, the debt work no longer outranks the committed features.

Freeze 58%Features 42%
functionsHow the numbers became the answer: every member scores each option on a range, the run samples those ranges 10,000 times, and the split above is the share of samples each option wins. A criterion the team is far apart on shows up as high dispersion, which is why the run names it instead of hiding it inside the average.

Operations, vendors & risk

Procurement, tool selection, compliance sign-off, deal approval. These decisions are cross-functional by nature: the person who owns the budget, the person who owns the risk and the person who has to run the thing all have a say. A weighted sheet with the weights stated up front is how those three interests get compared instead of traded.

storefront3–8 stakeholders · 2–4 vendors · result: one recommendation and an auditable record of how it was reached

CRM selection — three vendors, four departments

Sales, support, finance and IT score all three platforms before the demo debrief, so the loudest demo of the week cannot set the room.

CriterionWeightPlatform AlphaPlatform BetaIn-house build
Total cost of ownership8.56.08.45.2
Security & compliance9.08.67.89.2
Team experience8.07.48.85.4
Implementation speed & lock-in7.56.28.04.6
Weighted total234.1272.0204.7

Weights come from the group, not from the person who set up the run: each member's priorities are normalised against their own top criterion, then averaged, so a member who scores everything high does not outweigh a member who scores sparingly.

check_circleRecommended: Platform Beta. Weighted 272.0 against 234.1 and 204.7, and it beats both alternatives head-to-head.
functionsHow those inputs became that answer: The in-house build is the safest on security (9.2, the highest single score in the run) and loses everything else: 8.5×5.2 + 9×9.2 + 8×5.4 + 7.5×4.6 = 204.7. Because security carries weight 9, the run shows exactly how much it would have to matter — or how much the other criteria would have to be wrong — before building wins. That is the sentence the security reviewer needs, and it is written down.

Cloud provider — three options, one migration clock

Six people, including the two who will run the migration and the one who owns the bill.

CriterionWeightProvider XProvider YStay where we are
Total cost of ownership8.57.28.69.0
Security & compliance9.09.18.48.8
Team experience8.06.48.99.4
Migration speed & lock-in7.55.88.29.6

Weights come from the group, not from the person who set up the run: each member's priorities are normalised against their own top criterion, then averaged, so a member who scores everything high does not outweigh a member who scores sparingly.

check_circleRecommended: stay where we are — the run refuses to move on a cost argument that the migration and the learning curve both outweigh.
functionsHow those inputs became that answer: The cheapest option loses on the two criteria that only the people doing the work can see. This is the case where a weighted ranking of "best technology" and the run's answer part company, and where the disagreement tab earns its place: cost was the one criterion everyone agreed on, and it was not the deciding one.

Build or buy the compliance tooling

Four people: the security lead, the engineer who would build it, and two stakeholders who own the audit.

CriterionWeightBuyBuild
Audit surface we own9.08.84.6
Fit to our controls8.07.28.4
Ongoing maintenance7.58.65.2

Weights come from the group, not from the person who set up the run: each member's priorities are normalised against their own top criterion, then averaged, so a member who scores everything high does not outweigh a member who scores sparingly.

check_circleRecommended: buy. The build wins only on fit to our controls, and loses on the two criteria that outlive the project.
functionsHow those inputs became that answer: Three criteria, two options, no totals to argue about: the run compares them head-to-head and the answer follows from which criteria survive the year. Sign-off decisions are usually made on the strength of a demo; scoring audit surface and maintenance in advance is what makes the sign-off defensible.

Agency selection — three pitches

Five stakeholders watching three pitch decks, scored before the internal debrief.

CriterionWeightAgency AAgency BAgency C
Evidence from comparable work9.08.26.87.9
Team we actually get8.57.68.46.2
Cost & pace7.06.47.88.6

Weights come from the group, not from the person who set up the run: each member's priorities are normalised against their own top criterion, then averaged, so a member who scores everything high does not outweigh a member who scores sparingly.

check_circleRecommended: Agency A, on the strength of comparable work — the criterion the room disagreed about most.
functionsHow those inputs became that answer: The highest-weight criterion was also the most contested: two stakeholders read the case studies as directly comparable, two read them as a different market. The run names it as a high-disagreement criterion, so the follow-up is a reference call on that evidence rather than another round of pitches.

How the numbers become a conclusion

The same five steps run under every example on this page, whether there are two options or five, three people or thirty.

1

Each member scores every option as a range, and sets a priority per criterion

A range (say 6–8) records honest uncertainty; a single number records false precision. The priority is 0–10 per criterion, and 0 means "this does not apply to me" — not a low score you are obliged to give.

2

Priorities are made comparable across people before they are combined

Your 9 and my 9 are not the same 9, so each member's priorities are divided by their own highest one. Everyone's top criterion becomes 1.0 and the rest become fractions of it. A member who scores everything high no longer outweighs a member who scores sparingly, and a 0 stays "not applicable for me" without dragging the group's other weights down.

3

Each criterion becomes one 0–10 priority, and each option one score per criterion

The averaged, normalized priorities round to the 0–10 priority shown on the screen, and the option scores are the mean of the members' estimates. If most of the team marks a criterion "does not apply", it is dropped from the run — the whole set is never dropped, and criteria the run drops stay visible in the audit. Members who said they were unsure have their ranges widened before averaging, so their doubt reaches the simulation instead of being flattened out.

4

10,000 simulated scoreboards, then every option against every other option

Each draw takes one plausible score from every member's range and asks: in this version of the team's judgment, which option does the group prefer? Within each draw, options are compared pairwise. An option that beats every other option in a majority of draws is the Condorcet winner — a stronger claim than winning on a weighted total, because it holds in every one-on-one comparison. If the comparisons form a loop (A beats B, B beats C, C beats A) the run says a cycle was detected and reports the option with the most pairwise wins instead of inventing a winner.

5

The result comes with its own doubt attached

Win share is the percentage of draws the recommendation won, and the margin against the runner-up is stated on the same line — a 51% result is labelled as fragile, not as settled. Disagreement diagnostics then rank the criteria by how far apart the team is, so the discussion goes to the one criterion that actually moves the answer. Sensitivity runs ask what would flip it. Everything is exported as a PDF or JSON, and the roster, reminders and audit trail show who took part.

Run one of these on your own decision

Pick the closest template, replace the options with yours, and invite the people who should have a say. Free to start, no card.

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