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The platform for consequential decisions

The most consequential work in organizations is deciding what to do.

1D2A brings people, information and AI together to prepare decisions, challenge the rationale, compare alternatives, govern commitments and preserve why they were made.

No account required to start.

DECISION Which inventory strategy for high-variance replacement parts? Open

A Make to stock for priority parts 97% service opposesTraps capital in slow-moving finished goods

B Make to order for most parts $0.9M holding opposesLead times customers may reject on a repair

C Assemble to order $1.8M capital supportsCommon components serve many variants

D Segmented hybrid by demand pattern recommended supportsHigh service where availability mattersrequiresParts classified by demand pattern

CRITERION Customer service level A 97% ▲ B 82% ▼ C 93% D 96% ▲

AINo option is assessed on manufacturing lead time. For the hybrid it differs by policy class, and no value is attached.

Organizations run on decisions

Some decisions are routine. Others determine where capital goes, what gets built, which risks are accepted, which technologies are adopted and what people do next.

Yet the work behind those decisions is usually scattered across meetings, documents, spreadsheets, messages and individual judgment.

The choice gets recorded.

The reasoning often does not.

1D2A gives consequential decisions a place of their own.

BEFORE PRESENTATIONSlide 12 — Stock vs make-to-order for service partsSPREADSHEETservice_parts_ABC_XYZ_v7_FINAL(2).xlsxEMAIL THREADRe: Re: can we still promise 48h on the gasket sets?MEETING NOTESS&OP: Finance wants turns up, Sales wants breadth. No decision.CHAT MESSAGEdoes anyone know the real lead time on the housings?

AFTER

Which inventory strategy for high-variance replacement parts? OPTIONSMake to stock · Make to order · Assemble to order · Segmented hybridCRITERIAService level · Holding cost · Capital · Speed · Flexibility · Forecast dependenceRATIONALE9 supporting · 8 opposing · 4 requirementsEVIDENCESCOR 2020 · Syntetos 2005 · Pinçe 2021 · Barros 2021PEOPLE1 decision-maker · 3 approvers · 5 functions

A system for the work of deciding

Important decisions are not single moments.

They are work: structuring the problem, comparing alternatives, challenging the reasoning, making the commitment and preserving what was learned.

1D2A keeps that work connected from the first question to the organizational memory it creates.

DECISION Which inventory strategy for high-variance replacement parts? Tree view

question Choose the inventory strategy for high variance automotive replacement parts M. Rossi

answers D · Segmented hybrid by demand pattern

supports Reserves high service levels for parts where availability matters most S. Okonkwo

opposes More complex to govern — a policy class and exception process per part R. Haas

requires Parts classified by demand pattern, margin, criticality and lifecycle S. Okonkwo

answers A · Make to stock for priority parts

opposes Traps working capital in slow movers before platform decline J. Lindqvist

answers B · Make to order for most parts

opposes Lead times customers may reject when a repair needs the part now P. Ekman

answers C · Assemble to order

refines Postponed final configuration for families sharing components R. Haas

01 · STRUCTURE

Structure the decision

Turn an issue into an explicit decision.

Bring together the question, credible alternatives, evidence, assumptions, constraints and dependencies so people can see how the decision is taking shape.

1D2A makes the relationships between those pieces explicit rather than leaving them buried in documents or discussion.

AIAI can help identify alternatives, surface assumptions, suggest missing considerations and organize the initial decision structure.

question Choose the inventory strategy for high variance automotive replacement parts M. Rossi

answers D · Segmented hybrid by demand pattern

supports Reserves high service levels for parts where availability matters most S. Okonkwo

opposes More complex to govern — a policy class and exception process per part R. Haas

requires Parts classified by demand pattern, margin, criticality and lifecycle S. Okonkwo

answers A · Make to stock for priority parts

opposes Traps working capital in slow movers before platform decline J. Lindqvist

answers B · Make to order for most parts

opposes Lead times customers may reject when a repair needs the part now P. Ekman

answers C · Assemble to order

refines Postponed final configuration for families sharing components R. Haas

02 · COMPARE

Compare what matters

Make tradeoffs explicit.

Define the criteria that matter, record values and uncertainty for each alternative, and compare options on a consistent basis.

1D2A keeps criteria separate rather than collapsing them into a single score unless the organization deliberately chooses to do so.

AIAI can suggest comparison criteria, propose values where evidence is available, identify missing values and explain what information would improve the comparison.

CRITERION A · Make to stockB · Make to orderC · Assemble to orderD · Segmented hybrid

Customer service level% of demand met, no stockout 97 ▲82 ▼9396 ▲

Inventory holding costUSD per year 4.2M ▼0.9M ▲2.1M2.4M

Capital investment requiredUSD, one-off 1.1M0.4M ▲1.8M ▼TBC

Order fulfilment speeddays to delivery 1 ▲18 ▼42 ▲

Flexibility to demand variabilitylow / moderate / high Low ▼High ▲ModerateHigh ▲

Impact of forecast accuracydependence on forecasts High ▼Low ▲MediumUnknown

AIManufacturing lead time for the hybrid is unrecorded because it differs by policy class. The setup-family data in the planning system would settle it.

03 · CHALLENGE

Challenge the rationale

Make reasoning explicit enough to examine.

Build arguments for and against alternatives. Question assumptions. Identify unsupported claims, missing evidence, contradictions and unresolved uncertainty before they disappear inside a recommendation.

AI1D2A's AI works with the structure and context of the decision itself.

It can:

assess the strength of arguments;
generate counterarguments;
identify unsupported claims;
challenge assumptions;
expose missing information;
suggest alternative interpretations;
identify what evidence could change the conclusion.

People decide what matters, what information to accept and what conclusions to draw.

General AI answers questions. 1D2A helps you work through the decision.

OPTION A · ARGUMENT · SUPPORTS

Finished goods stock supports immediate shipment for high demand parts and customers with vehicle downtime risk.

AIUNSUPPORTED CLAIM

No evidence in this decision identifies which parts carry downtime risk, or shows that they are the parts the current stocking range covers. “Priority parts” is asserted and never defined.

COUNTERAssemble to order preserves shipment speed for configurable families without stocking every variant. MISSINGThe classification of parts by customer urgency and part criticality.

Add counterargument Ask P. Ekman Dismiss

04 · DECIDE

Make the commitment explicit

Move from analysis to commitment.

Name the decision-maker. Involve the people whose input matters. Select an option, collect approvals and record when the organization commits.

Then connect the decision to the actions that follow.

AIAI can identify unresolved questions, gaps in the rationale or outstanding information before commitment, but authority remains with the people responsible for the decision.

SELECTED OPTION D · Segmented hybrid inventory strategy Selected 13 Sep by M. Rossi · Commitment pending two approvals ACTIONS THAT FOLLOW Classify every active part by demand patternS. Okonkwo · due 31 OctBuild the service, stockout and changeover cost modelJ. Lindqvist · due 14 Nov

PEOPLE MR M. RossiDecision-maker · COO SELECTED JL J. LindqvistApprover · Finance APPROVED RH R. HaasApprover · Manufacturing PENDING PE P. EkmanApprover · Aftermarket sales PENDING SO S. OkonkwoContributor · Planning 6 CONTRIBUTIONS

05 · REMEMBER

Preserve why the decision was made

Keep more than the final answer.

Preserve the alternatives considered, evidence available, assumptions made, uncertainties, tradeoffs, approvals and history so that the decision can later be reviewed, explained and reused.

Past decisions become organizational memory.

AIOver time, prior decisions can provide context for new ones. AI can help identify similar past decisions, retrieve relevant alternatives and criteria, and bring prior reasoning into the preparation of a new decision.

Opened 04 Mar 2027 · from search “service parts stocking policy” FROZEN v3

Which inventory strategy for high-variance replacement parts? Decided13 Sep 2026SelectedD · Segmented hybrid inventory strategyDecision-makerM. Rossi, Chief Operations OfficerAlternativesMake to stock; make to order; assemble to orderKey criteriaService level, holding cost, capital, fulfilment speed, flexibilityEvidence4 published sources, 11 attachments, archivedActions7 · 5 completed

HISTORY 02 AugDecision created19 AugAssemble-to-order option added by R. Haas28 AugHolding-cost values updated · cost model attached11 SepApproved by J. Lindqvist (Finance)13 SepCommitted · frozen as v3

AI that works on the decision with you

1D2A's AI does not sit beside the decision as a separate chat.

It works with the structure and context of the decision itself.

It can help identify alternatives and criteria, develop and challenge rationale, assess arguments, surface assumptions, expose gaps and investigate questions relevant to the choice.

People remain responsible for what matters, what information to accept and what to decide.

OPTIONSThree options listed AISUGGESTED OPTIONA segmented hybrid: stock for stable high runners, assemble to order for configurable families, make to order for lumpy low runners.

CRITERIASix criteria AIMISSING CRITERIONObsolescence exposure is absent, and it is what most separates stocking from making to order on aging platforms.

ARGUMENT · OPTION AStock supports immediate shipment AICHALLENGE“Priority parts” is undefined; no classification of customer urgency is attached.

REQUIREMENT · OPTION AForecast reliable per part AIUNSUPPORTED38% of part numbers had zero demand in six or more of the last 14 months.

OPTION CAssemble to order AIQUESTION TO RESEARCHHow much component commonality actually exists across the configurable families?

Built around the work itself

01

Structure

Turn an issue into an explicit decision.

Organize alternatives, rationale, evidence, assumptions and dependencies so people can see how the decision is taking shape.

question · 4 options · 11 contributions

02

Compare

Make tradeoffs explicit.

Define what matters, record values and uncertainty, and compare alternatives on a consistent basis.

6 criteria · 2 values open

03

Challenge

Improve the reasoning.

Use colleagues and AI to question assumptions, assess arguments, identify gaps and strengthen alternatives before commitment.

1 unsupported claim · 1 counter

04

Decide

Move from analysis to commitment.

Establish authority, gather input and approvals, select an option and record the point at which the organization commits.

selected D · 1 of 3 approvals

05

Remember

Keep the reasoning with the decision.

Preserve history, evidence, changes, approvals and actions so future teams can understand what was known and why the decision was made.

frozen v3 · 11 attachments · 7 actions

See the same decision from different perspectives

A decision is not a document.

Read it as a focused line of reasoning. Explore its structure as a tree or graph. Compare alternatives in a table. Read the whole decision as a document. The information stays connected whichever view you use.

Selected: D · Segmented hybrid

QUESTION Choose the inventory strategy for high variance automotive replacement parts ANSWERS D · Segmented hybrid by demand pattern SUPPORTS Reserves high service levels for parts where availability matters most OPPOSES More complex to govern — a policy class and exception process per part REQUIRES Parts classified by demand pattern, margin, criticality and lifecycle

Built for consequential decision work across the organization

Strategic and investment decisions

Evaluate alternatives where capital, direction and long-term consequences are at stake.

Examples: investments; market entry; portfolio choices; acquisitions; major organizational changes.

Enter a new regional market. ADirect entry with local officeBDistribution partnerCDefer 18 months Payback · Revenue at year 3 · Regulatory exposure Decision-maker: CEO · 3 approvers · 5 contributors

Cross-functional management decisions

Bring together functions that see different parts of the same problem.

Examples: operating-model changes; sourcing decisions; product launches; major procurement; transformation choices.

Select a sourcing model for a critical component. ASingle supplier, long contractBDual sourcingCIn-house production Unit cost · Supply risk · Lead time · Quality Operations, Procurement, Finance, Engineering

Technical and expert decisions

Structure decisions where evidence, assumptions and specialist judgment matter.

Examples: engineering design; architecture; technology selection; safety; manufacturing; infrastructure.

Choose an architecture for a new data platform. ALakehouse on managed cloudBWarehouse plus streaming layerCExtend current platform Latency · Cost at scale · Team skills · Lock-in Decision-maker: Head of Data · 4 engineers contributing

Governance and approval decisions

Create a record where authority, review and accountability matter.

Examples: policy approval; regulatory decisions; risk acceptance; AI governance; formal investment approvals.

Approve an AI system for a regulated process. AApprove with human reviewBApprove for pilot onlyCDo not approve Error rate · Auditability · Regulatory fit · Residual risk Risk committee · Legal · Model owner

Every important decision becomes an organizational asset

A finished decision should remain useful after the meeting ends.

With 1D2A, future teams can see:

01what was being decided;
02which alternatives were considered;
03what evidence was available;
04which assumptions mattered;
05where people disagreed;
06how the alternatives compared;
07what was selected;
08who approved it;
09what actions followed;
10what changed afterwards.

Past decisions become context for future ones.

Search decisions Operations · 2024–2027 · 18 decisions

Choose the inventory strategy for high variance replacement parts DECIDED Sep 2026 Operations · Selected: Segmented hybrid · inventory, service parts, postponement · related: Calgary stocking policy (2024) PRESERVED RATIONALE Considered: make to stock, make to order, assemble to order, segmented hybrid.Chosen for balance: service where it matters, capital where it does not.Disagreement: Sales wanted broad stocking; Finance wanted lower inventory.Open at commitment: manufacturing lead time per policy class unrecorded.

Consolidate the two regional distribution centres DECIDED May 2026 Operations · Selected: Keep both, shared inventory · logistics, cost

Replace the demand-planning system OPEN Feb 2027 Operations · 3 options · 2 approvals pending · technology selection

Stocking policy for the Calgary distribution centre DECIDED Nov 2024 Operations · Selected: Segmented by demand class · reused by: inventory strategy (2026)

Built for decisions made by organizations, not isolated individuals

Invite the people who hold relevant information or authority.

Give participants clear roles. Ask for contributions against specific parts of the decision. Assign decision-makers and approvers. Record agreement and commitment without losing the reasoning that preceded them.

The result is not simply collaboration around a document.

It is a traceable decision process.

MR M. RossiDECISION-MAKER Owns the selection and the commitment. Accountable for service level, inventory and factory performance.

SO S. OkonkwoCONTRIBUTOR Asked to classify parts by demand pattern before the policy matrix is set.

JL J. LindqvistAPPROVER Approval requested against the working-capital limit. Approved 11 Sep.

RH R. HaasAPPROVER Approval requested against capacity and changeover impact. Pending.

TN T. NakamuraACTION OWNER Define release and traceability controls for assemble-to-order, due 30 Nov.

Built for decisions that need to withstand scrutiny

Consequential decisions may need to be revisited months or years later.

1D2A preserves the history of the decision, controls who can access it, protects supporting attachments, records changes and approvals, and allows published decisions to be frozen as read-only versions.

The record stays connected to the reasoning that produced it.

HISTORY 02 Aug — created28 Aug — holding-cost values updated (cost model)13 Sep — committed, frozen as v3

ACCESS Organisation · Operations14 people can read4 people can edit

APPROVAL RECORD J. Lindqvist — approved 11 Sep 09:12R. Haas — pendingRationale unchanged since approval

ATTACHMENTS · PUBLISHED VERSION scor-digital-standard-2020.pdf — scan cleandemand-classification-14mo.xlsx — scan cleanv3 published 13 Sep · read-only

Do not start every decision from zero

Previous decisions can provide useful starting points for new ones.

Reuse structures, alternatives and criteria from similar decisions. Learn from published examples. Build a growing body of organizational knowledge around how important choices are made.

AI can use that context to help develop subsequent decisions more effectively.

RELEVANT PRIOR DECISION Stocking policy for the Calgary distribution centre. Decided Nov 2024 · Selected: Segmented by demand class · 3 options · 5 criteria

NEW DECISION Inventory strategy for European replacement parts.

AISuggested reuse from Calgary:

Segmented-by-demand-class optionAddCustomer service level criterionAddInventory holding cost criterionAddObsolescence exposure considerationAdd

Consequential decisions deserve a system

Organizations have systems for managing money, customers, projects, documents and operations.

Important decisions are still too often assembled across meetings, messages and files.

1D2A gives the work of deciding a system of its own.

Explore example decisions