Establishing a Unified Cost Data Model for Category-Level Decisions

Cost visibility wasn’t the problem.

Decision clarity was.

This work focused on redesigning how category managers made high-impact cost decisions across fragmented systems, incomplete data, and regulatory constraints.

Company: Kroger

My Role: Product Design Lead

Scope: Internal, cross-functional decision systems supporting item to category level pricing and data-heavy workflows for complex operational decision-making

Constraints: Fragmented data sources, legacy systems, regulatory requirements, and downstream dependencies

The Real Problem

Category managers were making frequent, high-impact cost decisions using data that was:

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Fragmented across legacy systems
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Interpreted differently across teams
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Structurally rigid and slow to reconcile

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Prone to downstream operational risk
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Existing tools aggregated data — but they did not clarify the decision space.

This led to:

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Workarounds and shadow tracking
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Duplicate analysis across teams
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Timing misalignment across categories
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Increased exposure to pricing and margin risk

The system optimized for visibility.
It did not optimize for judgment.

Reframing the Decision Space

At its core, cost management required four recurring decisions:

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Approve or defer cost changes
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Validate and resolve exceptions
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Assess downstream margin impact
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Coordinate timing across categories
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These were not UI problems.
They were decision architecture problems.
The opportunity was to design around the decision logic itself.

Why This Was Hard

The challenge wasn’t a lack of data.

It was the interaction between:

Multiple teams interpreting cost signals differently

Legacy systems enforcing structural rigidity

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Regulatory and audit requirements
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High cost of timing errors
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This required balancing flexibility with governance — clarity with compliance.

My Responsibility

I led the reframing of the problem from “data visibility” to “decision architecture.”

This included:

Mapping recurring decision patterns across categories

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Surfacing tradeoffs and failure modes
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Designing a shared model that scaled beyond a single workflow

Aligning product, engineering, finance, and operations around a unified structure

The result was not just a new interface.

It was a system designed for confident, timely decision-making.

Outcomes (Operational Impact)

The redesigned decision architecture improved clarity, coordination, and execution speed across cost workflows.

Reduced escalation cycles between merchandising, finance, and operations
Decreased manual reconciliation across divisions
Improved timing alignment for cost change execution
Increased confidence in margin-impact decisions through structured auditability
Escalation cycles were reduced by approximately 15% after aligning teams around shared cost interpretation logic.

Organizational Impact

The work shifted cost management from fragmented interpretation to shared decision logic.

As a result:

Cost signals were interpreted consistently across categories

Escalation cycles between merchandising, finance, and operations were reduced

Margin-impact decisions were made with greater confidence and auditability

Governance scaled without increasing coordination overhead

The organization moved from reactive data reconciliation to proactive decision orchestration.

The Unified Cost Model (In Practice)

Instead of reconciling fragmented cost tables across systems, we created a shared category-level view aligned around decision logic.

The Unified Cost View

This view:

Standardized cost interpretation across divisions
Unified case and consumer GTIN relationships
Surfaced downstream impact indicators
Enabled category-level coordination without manual reconciliation

This was not a reporting artifact.

It operationalized shared decision logic across divisions.

Making Time & Risk Explicit

High-impact cost decisions are rarely about the current number.

They are about timing, margin exposure, and downstream impact.

We introduced structured views for:

Historical cost changes
Upcoming cost changes
In-progress adjustments
Effective dates and audit trails

Historical & Future Cost Panels

This allowed category managers to:

See upcoming margin impact before execution
Coordinate timing across categories
Validate exceptions before approval
Reduce escalations driven by misaligned effective dates

Instead of static cost visibility, we created temporal decision clarity.

Rather than organizing around systems or data sources, we structured the model around:

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Inputs required to support judgment
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Shared decision logic across teams
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Operational outcomes
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Explicit constraints and trust mechanisms

By centralizing the decision logic layer, we reduced interpretive drift across teams and created a unified mental model for cost evaluation.