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Inventory Intelligence Hub Dashboard

Inventory Intelligence Hub

A retail operations dashboard built to help store managers monitor stock health, identify urgent inventory risks, and take action in time. The project focused on turning scattered inventory signals from NetSuite POS into a single, structured, tablet-friendly decision view.

Role

Consultant, BI Developer & Designer

Tech Stack

Power BI, DAX, SQL, NetSuite POS

Duration

3 Weeks

Year

2024

The Challenge

What the Client Was Struggling With

The retail team had access to inventory data but no structured way to act on it. Stock issues were discovered too late, decisions depended on tribal knowledge, and managers were spending significant time checking systems that were not designed to support fast operational decisions.

  • Low stock issues discovered too late to prevent stockouts

  • Delayed transfers between store locations

  • Limited visibility across stores from a single view

  • Reactive decision-making driven by ad-hoc checks

  • Too much time spent across multiple disconnected systems

The Solution

A Centralized Inventory Decision Layer

Inventory Intelligence Hub was built as a centralized reporting and decision-support layer on top of the client's existing NetSuite POS data. Rather than replacing their systems, the goal was to surface what already existed in a structured, actionable format.

The solution shifts store managers from reactive stock checks to structured monitoring. Instead of logging into multiple systems or waiting for weekly reports, managers get a single tablet-friendly view that shows them exactly where attention is needed and why.

Every panel and metric was mapped to a specific operational question a manager would ask during their shift. The dashboard was designed around the decisions people actually make, not around the data that happened to be available.

The Dashboard

What It Looks Like in Action

The main view surfaces the most critical inventory signals immediately — low stock counts, urgent alerts, transfers in progress, and the inventory risk heatmap by category. Recommended actions appear alongside with clear priority levels so managers know exactly what to do next.

Inventory Intelligence Hub — Main Dashboard View

The Approach

How We Got There

01

Discovery

Mapped existing inventory pain points through stakeholder conversations and reviewed how stock decisions were currently being made across locations.

02

KPI Design

Defined the core metrics and reporting logic anchored to specific operational decisions, not just available data fields.

03

Data Modeling

Built the Power BI data model on top of NetSuite POS exports with DAX measures for stock risk, transfer urgency, and replenishment signals.

04

Review and Refine

Iterated on the dashboard layout with the client to ensure the final views reflected how managers actually think during a shift.

What Was Built

What the Solution Included

Centralized Inventory Visibility

A single dashboard covering all store locations, eliminating the need to check multiple systems or spreadsheets.

Low-Stock and Overstock Monitoring

Automatic flagging of items below reorder thresholds and identification of overstock situations by category and location.

Category and SKU-Level Tracking

Drill-down views by product category and individual SKU, giving managers the granularity to act on specific items rather than broad summaries.

Trend-Focused Reporting

Movement trend charts showing how stock levels have shifted over recent periods, supporting smarter ordering decisions.

Decision-Ready Dashboard Views

Tablet-optimized layouts designed for use on the shop floor, with panels structured around the decisions managers make during a shift.

Simplified Management Reporting

Clean summary views for management review, without requiring technical knowledge to interpret the data.

My Contribution

My Role in This Project

This project was led end-to-end from the business analysis side. My focus was on understanding the operational context first, then translating that into a reporting structure that made sense for the people who would actually use it daily.

  • Business analysis and requirements definition

  • Reporting strategy and KPI definition

  • Power BI data modeling and DAX development

  • Dashboard planning and UX design

  • Stakeholder-focused structuring of information

  • Translating inventory pain points into actionable decision views

Tools and Stack

Reporting: Power BI Desktop
Query Language: DAX, Power Query (M)
Data Source: NetSuite POS exports, SQL
Delivery Format: Tablet-optimized dashboard
Methodology: Business Analysis, KPI Design
Design: Dashboard UX, Information Architecture

The Impact

Outcomes and Results

Improved Inventory Visibility

Managers gained real-time visibility into stock movement across all locations from a single view.

Faster Stock Decisions

Time spent identifying stock attention areas was significantly reduced, supporting faster ordering and transfer decisions.

Structured Management Reporting

Management now has a consistent reporting format for inventory reviews, replacing scattered manual checks.

Reduced Manual Dependency

Key inventory signals consolidated into one decision-ready dashboard, reducing reliance on multiple manual system checks.

Takeaway

Turning Retail Data into Clearer Decisions

Inventory Intelligence Hub is a good example of what happens when you start with the operational question rather than the data. Retail environments generate a lot of inventory signals, but without structure those signals stay as noise. The real work here was translating scattered stock information into a format that made the next decision obvious. That is the kind of outcome business analysis, done well, consistently produces.

Work Together

Need Clearer Visibility Into Your Inventory or Operational Data?

If your team is making decisions from scattered reports or reactive stock checks, there is a better way. Let's talk about what a structured decision-support layer could look like for your operations.

Let's Talk
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