All work

    Jayga

    A warehouse system that cut order processing from 3 days to 2–3 hours

    Jayga rents storage to small businesses that cannot afford a whole warehouse. The space is divided into grids: a grid is what a customer rents, what their stock is assigned to, and what their bill is calculated from. I led product on the internal system that tracks all three.

    3 days → 2 to 3 hrs

    Order processing time

    3x (modeled)

    Projected revenue per m²

    3 apps

    Client, admin, and warehouse floor on one record

    Role
    Product lead
    Team
    8 people, no dedicated researcher
    Timeline
    4 months, 2023. Two months design
    Platforms
    Web (client, admin), mobile (warehouse floor)
    Tools
    Figma, Notion

    Three decisions that shaped the product

    1. 01

      One unit carried pricing, storage, and billing at once, so the business could see which space earned money.

    2. 02

      Client, admin, and floor staff each do a different job on the same data, so every fact is entered once.

    3. 03

      Contextual inquiry found stock laid flat on the ground. Rack level pricing was the fix. The pricing was accepted but never built, so the gain stays a projection.

    Contextual inquiry to pricing0 to 1 strategyWorkflow structureOperations UXDesign led deliveryWorking across teams

    Problem

    Disconnected work

    Initially, inventory and warehouse work ran on spreadsheets, handwritten logs, and separate steps. Orders took days to process and warehouse space went to waste. Storage, billing, and delivery each stayed hidden from the others.

    Process mapping

    Two phases

    Phase one · 4 months, 2023

    Core system

    Stakeholder interviewsSurvey with the founder

    Phase two · After the tool was live

    Optimization research

    Contextual inquiry on billingWarehouse staff interviewsMarket research

    Approach

    How the build ran

    I started with the flow. I gathered the requirements through stakeholder interviews with the team. I also ran a small market survey on the problems Bangladeshi businesses have with inventory storage. Those requirements went into process maps, and once the team agreed on the flow I moved to rough wireframes. Built in 2023, with no AI help.

    Process, pace, and the delivery mapLean-Agile loop, the team, and the style guideShow
    • I used a Lean-Agile method throughout, to keep a close loop with the founder and the engineers.
    • The founder was the subject matter expert, and the engineers were the ones who would build it.
    • A project charter, a Kanban board in Notion, and short sprints kept the work moving.
    • Flow, agree, design, build, repeated in phases across a four month build. Two of those months were design time.

    The delivery map: how feedback from the founder, design, and building stayed in step

    Phase One

    Process mapping and core system

    Four months in 2023, on the founder's knowledge of the business. This phase shipped the client dashboard, the admin console, and the grid model the business prices against.

    Three apps, one shared record

    Three connected apps on one shared record. An action in one shows up in the other two, so each fact is entered once.

    The order flow: client to admin to warehouse, and the status travels back on its own

    The delivery blueprint runs the other way, and the daily bill follows the emptied grids

    Client dashboard

    Web · Client

    Takes the order

    Admin console

    Web · Admin

    The desk work: requests, billing, and oversight

    Warehouse Manager

    Mobile · Floor

    The floor work: assignment and stock checks

    One screen from each web app shows the split.

    Admin console: active grid requests by warehouse, user, item, quantity, length of stay, and status

    Client dashboard: space used, open requests, and the running daily bill

    The grid: what it is and what it costs

    A grid is the unit the business sells.

    Problem

    Space was rented in blocks of square feet, so a half empty rack earned the same as a full one. Nobody could see which space was making money.

    Decision

    I split the floor into grids: fixed size, assignable one at a time, each with an ID. A grid is what a client rents, what stock is assigned to, and what a bill is worked out from.

    Why

    That one unit is what makes the rest of the system work. Every item belongs to a named grid, so the physical work turns into data: grid IDs, item counts, and check status. Empty space becomes visible, and good space gets priced for what it is worth.

    The price is set per grid by:

    • How close it is to the warehouse
    • The condition of the rack
    • How secure it is

    An admin starts an order with the client's details and a warehouse. A client can also start one from the web portal.

    Client details and warehouse, the only place a client record is created

    The challan is attached in the same flow, so the paperwork stays with the order

    Splitting one item across grids

    Problem

    One item often needs more than one grid.

    Decision

    A quantity can split across several grids, or stay unassigned until later. I kept the split on a single item card.

    Why

    Warehouse staff told me why that matters. Logging each split as a new entry made stock hard to trace back to its delivery.

    One grid at a time

    Problem

    Managers said batch assignment failed whenever the space was uneven or half full.

    Decision

    Grids are assigned one at a time. The system makes you confirm one grid before the next opens.

    Why

    It removes the work of undoing a bad batch.

    Tradeoff

    Slower per click, faster overall.

    Assign grids: quantity splits in place, one grid confirmed at a time

    Once the grids are set, the system rolls the splits into one summary before payment: item, grid, quantity. The admin checks the whole order before the client is charged.

    Payment: the splits rolled into one summary, with duration, space, and the advance due

    Phase Two

    Inventory optimization research

    Once real orders were moving there were people to learn from. Research drove a third app for the warehouse floor, the delivery flow, and the billing rework.

    Field research

    Contextual inquiry on site was about billing. I watched how space was used day to day, and how charges were worked out. Goods were left unstacked and racks were used inconsistently, which reduced income per square metre. During one of the early visits I found inventory laid flat on the ground. The racks were not being used. I proposed rack level pricing. The modeling put that at roughly 3x the space and 3x the revenue per square metre.

    Contextual inquiry: watching a warehouse aisle during a working day, which is where the pricing problem showed itself

    Market research

    Market research answered a different question: who to sell this to. A survey of 23 businesses told me what they weigh when they pick a storage provider. It also told me how many of them need racking.

    Survey findings: price, distance, security, and how easily goods could be retrieved mattered most

    From there I mapped six possible customer groups: ecommerce sellers, event organizers, NGOs, distributors, farm businesses, and raw material suppliers. I then ran opportunity sizing on each one. I scored them in a cost and demand matrix on item value, upkeep, quantity, how easy the storage was to reach, and room to grow.

    The customer segments scored

    Opportunity sizing: cost against demand, used to pick which customers to chase

    Delivery

    Stock gets checked on the warehouse floor. It is one of the two flows the mobile app was built for, along with handling new order assignments. A delivery request still starts on the admin side: pick the user, then pick the items from what they have in storage.

    Warehouse staff interviews shaped the grid assignment rules and showed why a mobile app was needed. Managers described the errors batch assignment caused, and how often a physical count and the record disagreed.

    Delivery request: items picked from what the client has in storage, by grid and quantity

    The request goes to the Warehouse Manager app. Warehouse staff work the floor, so they can act on it from the aisle.

    The app lists the grids the items come out of before anyone touches stock. That list comes from the original assignment, so it is ready before they start.

    The request as it reaches the floor

    Which grids to pull from, generated from the original assignment

    Counts confirmed against the record, or reported as a mismatch

    Billing

    Bills are built from the order record. Invoices use the duration and space already recorded at intake and grid assignment. The system calculates the bill. The admin reviews it and sends it.

    Invoice: dates, space, and duration come straight from the order

    Client side: upcoming and due, with the invoice as a file

    On the client side, billing splits into upcoming and due, and the invoice downloads as a file. Clients run their own operations on a schedule. They need to see what is coming and keep a copy for their records.

    The bill also falls on its own when a delivery empties a grid. Once the stock has left and the Warehouse Manager has confirmed it, the client stops paying for that space.

    Outcomes

    Faster work, priced space

    Measured

    3 days → 2 to 3 hrs

    Order processing, before and after the system was in use

    3 apps on one record

    Client, admin, and floor staff working from the same data, each fact entered once

    Modelled

    3x income per square metre

    A projection from grid pricing and from selling space that previously earned nothing

    Hindsight

    • The Assigned tag works around a backend that tracked grid space on a delay. It should have been a live occupancy count.
    • The mobile app should have been in the first version. I built the admin console with no way for floor staff to write back. Admins worked from old numbers for months.
    • Keeping the design system light was right for the first phase and wrong by the second. I left it too late, and by then the three apps had visible inconsistencies.

    Jayga shows a different side of my work than Zevian: more operations, service design, field research, and workflow structure. What the two share is the same: product direction, system design, and build quality grew together.