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Oracle SCM Manufacturing

Parallel Operations
in Work Definition

A visual modeling tool enabling manufacturers to define parallel operations — turning complex manufacturing logic into something anyone on the floor could understand.

Timeline
3 Months
Role
UX Designer
Tools
Figma
Company & Team
Oracle · SCM Manufacturing
Parallel Operations — Operation Dependencies Datagrid and Diagram

01 — The Challenge

Breaking the Sequential Bottleneck

Manufacturing in electronics, furniture, and packaging requires the ability to run certain tasks in parallel — to fully utilize labor and equipment with minimal downtime. But Oracle's Work Definition only modeled operations sequentially, forcing engineers into workarounds that distorted their data and inflated their timelines.

Users were setting "one-minute lead times" to trick the software into allowing parallel starts — a sign the product had a real gap to close.

Sequential Execution vs Parallel Execution diagram

Sequential vs. parallel execution — the same operations take significantly longer when forced to run one at a time.

Business Impact

  • Inflated Lead Times Parallel tasks modeled sequentially artificially extended production — a 2-hour process showed as 6 hours.
  • Resource Inefficiency Labor and equipment sat idle during "sequential" steps that could run simultaneously.
  • Clunky Workarounds Users set "one-minute lead times" to trick software into allowing parallel starts — a signal the model was fundamentally broken.
The Goal

Design a solution allowing manufacturing engineers to specify which operations run in parallel — based on dependency relationships between operation start and completion — without compromising data integrity or established workflows.

02 — Research

Understanding the Users

I consulted Oracle Cloud Customer Connect for peer feedback and mapped the experience across three distinct user types — each with different needs and contexts around parallel operations.

Three user types: Planning, Scheduling, and Execution

The parallel operations experience spans three roles — from planning to floor execution.

The Planner

Manufacturing Engineer
Defines complex dependency relationships (Finish-to-Start vs. Start-to-Start) to minimize overall lead time. Needs a way to author and validate parallel logic without leaving their authoring context.

The Manager

Production Supervisor
Monitors real-time progress and intervenes if bottlenecks appear. Needs to see which parallel operations are running and approve changes without disrupting the floor.

The Doer

Production Operator
Needs to know exactly which operation to start — right now. Parallel logic needs to be surfaced clearly so they can act immediately when a Start-to-Start dependency is satisfied.

03 — Design Principles

Four anchors before sketching a single frame

Before exploring any solutions, I established four guiding principles to keep every design decision tethered to real user needs.

1
Wayfinding Provide clear visual cues for the "next step" in a complex, multi-stage setup.
2
Context Awareness Help users orient within the macro-process even while deep in micro-tasks.
3
Clear Workflow Visualization Make non-sequential flows easy to digest — highlight dependency types and transfer percentages.
4
System Validation & Error Handling Proactively catch circular dependencies and invalid sequences with clear recovery paths.

04 — Information Architecture

The Operation Dependencies Tab

I restructured the Work Definition experience to accommodate new data points without overwhelming existing users. The solution centers on a new dedicated tab that introduces three new relationship types:

Finish-to-Start
The previous operation must complete before the next one can begin — the traditional sequential model.
Start-to-Start
A scheduling dependency where the next operation can start as soon as the previous one starts — enabling true parallelism.
Transfer Percent
The percentage of completed quantity that moves to the next operation — enabling accurate yield calculations across parallel branches.

05 — Exploration

Navigating the Redwood Design System

The core challenge: balancing the user's need for a robust, interactive flowchart against the technical boundaries of Oracle's Redwood Design System. Oracle requires consistent UI across the SCM suite, which means using existing, tested components over custom code.

I explored four low-fidelity architectural options, each representing a different tradeoff between authoring power and visual clarity:

Three wireframe options for visualizing operation dependencies

Early wireframe exploration — three distinct approaches to surfacing the dependency diagram.

Option 1: Diagram + Bottom Drawer
Option 1 — Diagram + Bottom Drawer
Focus on the flow with a read-only data grid visible below — keeping both views in context simultaneously.
Option 2: Diagram + Properties Panel
Option 2 — Diagram + Properties Panel
A side configuration drawer for real-time editing alongside the visualization — authoring and validating in one place.
Option 3: In-Tab Canvas
Option 3 — The In-Tab Canvas
A large diagram opened in a drawer directly from the Operation Dependencies tab — keeping the diagram within the same page context.
Option 4: Toggle Approach
Option 4 — The Toggle Approach
Switch between "Data Authoring" and "Visual Model" views — reducing cognitive load by separating concerns.
Redwood Office Hours — Three Critical Constraints
1
Release Readiness The Configuration Drawer component wasn't available until the following quarter — eliminating Options 2 and 3.
2
Performance Limits Large drawers caused significant latency with complex manufacturing datasets — ruling out any drawer-based approach.
3
Template Fidelity The Toggle idea deviated from established Redwood guidelines, risking inconsistency across the SCM suite.
The Final Strategy

Constraints shifted focus from "interactive editing" to "visual validation." The diagram's primary value isn't authoring — it's giving manufacturing engineers a sanity check for the data they've already entered in the grid. This reframing unlocked the dedicated Canvas Page approach.

06 — The Solution

Bridging Data and Visualization

The final design pairs two complementary surfaces: a structured datagrid for precise authoring, and a dedicated canvas page for visual validation — connected by a strict save flow that protects data integrity.

Operation Dependencies datagrid in Work Definition

The Operation Dependencies tab — structured authoring of parallel relationships in a datagrid.

01

The Datagrid: Precise Authoring

A new "Operation Dependencies" tab in Work Definition gives manufacturing engineers a structured space to author complex relationships. Each row defines a dependency between two operations, including:

  • Finish-to-Start (sequential) and Start-to-Start (parallel) relationships
  • Transfer Percent — the quantity moving between operations
  • Initialize and Validate actions for batch setup and error checking
Operation Dependencies Diagram canvas page

The Dependencies Diagram — a dedicated canvas page for visual validation of the authored flow.

02

The Visualization Page: A Mental Model Map

From the datagrid, engineers navigate to a dedicated Canvas Page to view their Operation Dependency Diagram. Rather than a duplicate authoring surface, the diagram functions as a read-only validation tool — letting engineers confirm that what they entered in the grid matches their actual shop floor mental model before execution begins.

The Redwood Diagram Node component represents each operation visually, with arrows and transfer percentages showing exactly how work flows between parallel branches.

Two-page flow: datagrid and diagram synced via save behavior

The two-page flow — datagrid and diagram stay in sync via a strict save behavior.

03

Save Behavior: Protecting Data Integrity

Since the diagram opens in a separate browser window, I designed a strict save flow to handle the state between views. When a user edits the datagrid after opening the diagram, the diagram is flagged as stale and must be refreshed — ensuring engineers always validate against the latest authored data, never a cached snapshot.

Error state in the Dependencies Diagram showing invalid circular dependencies

Invalid dependency state — circular loops and bad transfer percentages surface clearly with recovery guidance.

04

Proactive Error Validation

Parallel logic introduces risks invisible in a standard grid — circular dependencies, multiple last operations, transfer percentages that don't sum to 100%. I collaborated with developers to categorize every client and server-side error, then designed banners and inline messages that explain exactly what's wrong and how to fix it.

The diagram turns red for invalid nodes and renders the problematic edges in a distinct error color — making issues unmissable at a glance.

Cross-Product Impact

Designing for the Entire Ecosystem

The parallel operations data defined in Work Definition needed to flow downstream into every product that touches the shop floor. I updated three downstream surfaces to surface parallel operation awareness:

Work Orders Management showing parallel operations

Work Orders Management — parallel status visible in the work order list.

Production Supervisor Workbench with parallel operations

Production Supervisor Workbench — real-time monitoring of parallel operation progress.

Operator Workbench showing which operations can start

Operator Workbench — operators see exactly which parallel operation they can start now.

07 — Impact

Results

Lead Time Accuracy
Processes previously modeled as 6 hours restored to their true 2–4 hour duration — eliminating phantom time from the production schedule.
Yield Information Accuracy
Transfer Percentages enable yield to be calculated based on the actual quantity moved between parallel operations — not estimated totals.
0
Wait Time for Operators
Production Operators reported decreased wait-time — starting parallel operations immediately upon Start-to-Start dependency satisfaction.

08 — Reflection

What I learned

01
Innovation Through Constraints
Working within the Redwood Design System revealed that constraints filter better decision-making. The desire for interactive side-by-side editing shifted toward a streamlined "validation-first" strategy — and the result was cleaner and more focused than the original idea.
02
Bridging the "Reality Gap" with Data
The project highlighted a massive disconnect between legacy software logic and actual shop floor reality. Sequential modeling inflating a two-hour process to six hours demonstrated why UX matters deeply in SCM — restoring flexibility eliminated inefficient workarounds and gave engineers back their time.
03
Visualization as a Form of Validation
Complex logic benefits from a visual "error-checker." Focusing the diagram on validation gave manufacturing engineers a sanity check for catching circular dependencies or multiple last operations — impossible to spot in a standard data grid. Good UI allows data entry while helping users recognize and recover from modeling errors.
04
Designing for the Entire Ecosystem
The core work in Work Definition only succeeded because the data flowed into Supervisor and Operator Workbenches. Ensuring Production Operators know exactly which operation they can start — based on parallel constraints — is what translates "Plan" into actual floor "Action."
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