Skip to content
CodexSmith
Case study

Power BI · 2025

Bringing sales and inventory into one reporting view

Client · ITC

See how CodexSmith organized sales and inventory reporting in Power BI to support commercial analysis and purchasing decisions.

ITC — Bringing sales and inventory into one reporting view
Client
ITC
Category
Power BI
Engagement
Sales & inventory intelligence
Timeline
2025
Scope
Power BI · Analytics · Insights

The brief

Sales, customer, product, inventory, and branch data produced thousands of records — but raw exports and static reports still left leadership stitching numbers together by hand.

  • The problem

    The business needed one place to track revenue, orders, customers, and AOV; compare periods; separate new vs. repeat contribution; benchmark branches; evaluate acquisition; estimate revenue lost to stockouts; and prioritize manufacturers — without waiting on another analyst report.

  • The mandate

    Build a dashboard leadership could act on. Organize commercial data around decisions instead of disconnected charts — so teams can see where revenue is growing, which branches need attention, and which shortages are costing money.

The challenge

Commercial teams had the data — sales, customers, branches, inventory — but not a system that answered the questions leadership actually asks in the moment.

  • Executive sales overview — Leadership gets an immediate snapshot of revenue, orders, average order value, customers, and average daily sales—with historical comparisons and trend views so performance direction is obvious at a glance.

  • New vs. repeat revenue context — Monthly revenue sits alongside new and repeat customer activity, clarifying whether growth comes from retention, acquisition, spending changes, or specific commercial periods—not only the topline number.

  • Customer acquisition intelligence — New-customer growth is compared with acquisition cost and advertising performance in the same environment, so commercial and marketing teams can see when spend converts—and when it does not.

  • Branch & business-unit benchmarking — Revenue, orders, AOV, customers, and average daily sales can be ranked across branches and sub-units, turning the report into a management tool for spotting leaders, laggards, and unusual swings.

Static reports weren't enough. The product needed interactive Power BI — decision views, lost-sales estimates, and filters management could drive itself.

ITC · Sales & inventory · Illustrative view

Revenue

By branch

Orders

By period

Lost-sales opportunity

Estimated

Reporting areas

9

Top lost-sales products

  • SKU A · OOSHigh
  • SKU B · Low stockHigh
  • SKU C · Slow refillMedium
BI

Who to call

Manufacturers ranked by estimated lost opportunity

Top 3 suppliers · replenishment priority · branch filter on
Open action list

What we built

Seven capabilities that turn sales and inventory noise into a single environment leadership can explore, benchmark, and act on.

  • Executive sales overview

    Leadership gets an immediate snapshot of revenue, orders, average order value, customers, and average daily sales—with historical comparisons and trend views so performance direction is obvious at a glance.

  • New vs. repeat revenue context

    Monthly revenue sits alongside new and repeat customer activity, clarifying whether growth comes from retention, acquisition, spending changes, or specific commercial periods—not only the topline number.

  • Customer acquisition intelligence

    New-customer growth is compared with acquisition cost and advertising performance in the same environment, so commercial and marketing teams can see when spend converts—and when it does not.

  • Branch & business-unit benchmarking

    Revenue, orders, AOV, customers, and average daily sales can be ranked across branches and sub-units, turning the report into a management tool for spotting leaders, laggards, and unusual swings.

  • Inventory & lost-sales intelligence

    Availability is tied to financial impact: opportunity loss, average daily loss, in-stock rate, and out-of-stock exposure—so operations ask how much potential revenue a shortage is costing, not only whether an SKU is empty.

  • Product & manufacturer action lists

    Products and manufacturers are ranked by estimated lost opportunity, creating a clear replenishment and “who to call” workflow for purchasing and supply-chain teams.

  • Interactive filtering

    Users explore by customer class, status, owner, product attributes, date periods, branch/unit, and currency views—moving from executive summary to segments without requesting a separate analyst report.

The pipeline

Four stages between scattered commercial exports and a dashboard leadership can act on — without waiting on another report.

  1. 01

    Data modeling

    Sales, customer, branch, product, and inventory sources modeled into a single Power BI model leadership can trust across periods and filters.

  2. 02

    KPI layer

    Revenue, orders, AOV, customers, daily sales, in-stock rate, and estimated lost opportunity computed as consistent, comparable metrics.

  3. 03

    Decision views

    Executive overview, acquisition, branch rankings, inventory leakage, and product prioritization — each framed around a question teams already ask.

  4. 04

    Action workflows

    Manufacturer “who to call” lists and interactive filters so purchasing and management move from insight to next step without a new report request.

Coverage

Nine decision areas, one system

Sales, customers, marketing, branches, inventory, leakage, products, suppliers, and management exploration — unified so teams stop stitching exports by hand.

  • Executive KPIs

    Sales

    Revenue, orders, AOV, and daily sales trends with historical comparison.

    In dashboard

  • Growth mix

    Customers

    New vs. repeat behavior and contribution to monthly revenue.

    In dashboard

  • Acquisition

    Marketing

    New-customer growth alongside acquisition cost and ad performance.

    In dashboard

  • Benchmarking

    Branches

    Ranked performance across branches and business units.

    In dashboard

  • Availability

    Inventory

    In-stock analysis and out-of-stock exposure tied to financial impact.

    In dashboard

  • Lost sales

    Revenue leakage

    Estimated opportunity loss when items are unavailable.

    In dashboard

  • Prioritization

    Products

    High-impact SKUs ranked by estimated lost opportunity.

    In dashboard

  • Who to call

    Suppliers

    Manufacturer-level opportunity lists for purchasing action.

    In dashboard

  • Exploration

    Management

    Interactive filtering and drill-down without a separate analyst report.

    In dashboard

Why choose CodexSmith

Choosing a technology partner usually comes down to trust in their judgment as much as their technical ability. Here's what that looks like in practice.

  • One team across the full stack

    AI, engineering, infrastructure, and security sit under one roof — so a recommendation in one area accounts for its impact on the others, instead of optimising a single service in isolation.

  • Senior-led delivery

    You work with engineers who stay involved throughout the engagement, supported by a technical lead accountable for quality.

  • Transparent, milestone-based progress

    You review working software as it progresses, with clear documentation of what has been built and what is still in progress.

  • A practical handover

    Documentation, tests and handover are part of the engagement, so your team can operate and extend what we build.

Why these services work together

Many projects need more than one service. A SaaS platform may need software development and cloud delivery, and AI features only where there is a clear business case. Because these areas sit inside one team, you do not have to re-explain your product each time the scope shifts.

It also keeps recommendations grounded in what is feasible to build and maintain.

  • AI and automation

    AI and workflow automation, including retrieval-based knowledge search, tested against representative examples.

  • Product engineering

    Custom software, web applications and mobile apps, from initial architecture through launch.

  • Integration and data

    System integration, data modeling and analytics, so teams work from consistent information.

  • Cloud, design and support

    Cloud and DevOps, product UI/UX design, and separately scoped ongoing support after handover.

More case studies

Make your reporting more useful.

Tell us what you're measuring and we'll come back with a scope, a timeline and a number.

Discuss your analytics project