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Case study · 2026

Exact Order Availability Dashboard

The team was opening Exact orders one by one just to answer one question: can we ship this yet?

  • Exact Online API
  • Shopify App
  • React
  • Node.js
Discipline
Order operations · Exact Online · Inventory dashboard
Year
2026
Engagement
Fixed scope
Status
Live
supplier.weldaad.com
weldaad

01Context

  • Pull relevant sales orders from Exact Online.
  • Classify orders by real inventory availability.
  • Provide line-level detail for partial and backordered quantities.

Weldaad receives orders through multiple channels, meaning Shopify alone could not provide the full operational order picture. Exact Online remained the central system of record.

Staff were manually opening individual Exact orders to determine whether each product was available, incoming, or unavailable.

HeapByte built a clearer operational layer inside the Shopify application so fulfilment decisions could be made from one dashboard.

02What was in the way

  1. 01

    Partial quantities

    A line ordering 10 units with only 3 available cannot simply be labeled “in stock.”

  2. 02

    Operational prioritization

    Order status alone does not tell the team whether the value currently available is high enough to justify a partial shipment.

  3. 03

    Multi-channel order source

    All calculations needed to use Exact orders rather than only Shopify-originated transactions.

03Architecture

What we built, and what we deliberately left alone.

  1. 01

    Exact order cache

    Relevant orders and line items are synchronized into the application for faster analysis.

  2. 02

    Line-level allocation

    Each ordered quantity is split between available, incoming, and unavailable quantities.

  3. 03

    Order-level aggregation

    Line results roll up into an overall fulfillment classification and in-stock monetary value.

FIGMA / DESIGNERP · NETSUITECRM · KLAVIYOHEAPBYTE LAYERSTOREFRONT / THEMECHECKOUT EXTENSIONSSHOPIFY FUNCTIONS

Delivery

  1. Exact Sales Order API
  2. Order caching
  3. Stock classification
  4. Order detail UI
  5. QA & launch

04Outcome

Order states
4 categories

Fully available, partial, preorder/backorder only, unavailable item

Priority logic
€350 / €500 thresholds

Visual shipping indicators based on available order value

Order analysis
Line-level

Quantities separated into available, incoming, and unavailable

Performance
Cached sync

Replaced repeated full Exact requests for normal dashboard browsing

05Engineering notes

Quantity splitting
Ordered quantities are distributed between currently available and future/unavailable portions.
Status calculation
Overall order state is derived from all open line items rather than a single Exact status field.
Expected dates
Incoming items can surface expected-stock information inside order details.
Cached synchronization
Order data is periodically synchronized rather than fetched and recalculated from Exact on every page request.

What we took from it

  1. 01Operational dashboards should answer decisions, not merely reproduce ERP tables.
  2. 02Partial fulfillment needs quantity-level math.
  3. 03Monetary thresholds can matter as much as inventory status.
  4. 04Caching external ERP data improves both reliability and UX.

Disciplines applied

Next case study

Dynamic Inventory Reservation Engine

We built reservation logic that subtracts warehouse-picking orders from Exact stock before calculating what inventory is genuinely available to other customers.

Similar problem?

We will tell you whether this approach fits.

Every store is different. Send us yours and we will say what we would actually do — including when the answer is less work, not more.