Shop Inventory App

The inventory system wasn't failing because people didn't know how to use it. It was failing because it didn't match how stock was actually handled on the ground. This was an internal inventory management tool used by operations teams to track stock across multiple shops and warehouses. On paper, the system worked. In practice, it slowed everything down.

The Problem

Stock levels were hard to trust, simple questions required manual checks or analyst support, and teams spent more time reconciling data than acting on it. With these inefficiencies operations was continually becoming expensive—missed stock, delayed decisions, and growing operational friction. The product wasn't failing because of UI quality. It was failing because the system reflected how inventory was stored, not how teams actually worked.

Context and Stakes

KOKO Networks has a high-volume inventory environment supporting daily operations across a distributed retail network. Errors were expensive: stock mismatches affected fulfilment, reporting, and trust between field agents and central teams. On paper, the system worked. In practice, it slowed everything down. Stock levels were hard to trust, simple questions required manual checks or analyst support, and teams spent more time reconciling data than acting on it. As the operation scaled, these inefficiencies became expensive—missed stock, delayed decisions, and growing operational friction.

What Wasn't Working

Although the system was functionally capable, usability quality was poor:

• Critical actions were buried behind dense navigation and unclear labels
• Teams struggled to discover key inventory insights without guidance
• Simple questions ("what stock do we have?", "where is it?", "what's missing?") required unnecessary effort
• The interface reflected the underlying system structure rather than how operations teams actually worked

As a result, the tool added friction to workflows that were meant to be fast, repeatable, and reliable.

My Role

I was brought in to figure out why an essential internal tool was slowing teams down, despite having the right data and functionality underneath. My role sat between product, UX, and operations. I worked closely with internal users to understand how inventory decisions were actually made, where teams got stuck, and which parts of the system created the most friction.

Rather than redesigning everything, the focus was on:

• Identifying which information and actions mattered most in daily workflows
• Reducing cognitive load in high-frequency tasks
• Making key features easier to discover and use without training or hand-holding

Key Decisions

A critical decision was to prioritize clarity and task visibility over configurability. Instead of exposing everything the system could do, the experience was reshaped around:

• Making stock status immediately understandable
• Clear entry points for critical tasks
• Predictable patterns that reduced cognitive load
• Surfacing exceptions and risks early

Features that were technically powerful but rarely used were de-emphasized, while high-impact workflows were surfaced and simplified. That also meant saying no to flexibility that added complexity, and yes to opinionated views that helped teams act faster.

Outcome

The redesign improved:

• Discoverability of key inventory actions
• Speed and confidence for day-to-day operational tasks
• Reducing the need for secondary tools or analyst intervention
• Overall usability quality without changing the underlying system

More importantly, it shifted the tool from something teams worked around to something they could rely on.