Case Study - Turning distributor POS/sell-through chaos into a single source of truth

The Challenge: Fragmented Data Across 15 Distributors

Airtame sells wireless presentation devices through 15 global distributors, alongside direct web and inside sales channels. While they had clear visibility into what they shipped to distributors, the leadership team cared about a fundamentally different question:

How many end customers are actually buying our products – and where?

The answer lay in POS (point-of-sale) / sell-through data from those distributors. That data existed – in spreadsheets, CSVs, TXT files, and SFTP dumps – but it was fragmented, inconsistent, and expensive to use.

The Reality Before Automation

15 different data sources, each with:

• Different file formats (Excel, CSV, TXT)
• Different delivery methods (email attachments, SFTP)
• Different schedules (weekly, monthly, ad-hoc)
• No standardization in column names, structures, encodings, or detail levels

Manual processing consuming ~2 FTEs just to:

• Download files from emails and SFTP servers
• Clean and map columns distributor by distributor
• Stitch together some form of reporting
• Handle exceptions and data quality issues

Reporting delays of 1-4 weeks, meaning:

• Leadership making decisions on stale data
• Supply chain reacting to problems too late
• Sales unable to quickly follow up on opportunities
• Finance forecasting with incomplete information

Hidden Costs Across the Business

The fragmented POS setup created concrete pain across every department:

Supply Chain

• Hard to see which distributors were building up overstock vs. heading toward stock-outs
• Reactive rather than proactive inventory management
• Suboptimal working capital efficiency

Sales

• Limited ability to quickly follow up on end customers who had purchased via distributors
• Difficult to spot underperforming regions or partners early
• Commission calculations that didn't fully reflect actual sell-through

Finance & FP&A

• Distributor order volumes were harder to predict with confidence
• Modeling revenue, cash flow, and working capital required heavy manual work
• Assumptions-based rather than data-driven planning

Leadership

No single source of truth to answer questions like:

• "Where is demand accelerating or slowing this month?"
• "Which regions are really pulling their weight?"
• "Are our campaigns showing up in end-customer sales?"

The Solution: Automated Ingestion, Standardization, and Activation

We designed and implemented a custom solution that transformed POS data from a liability into a strategic asset.

1. Unified Ingestion from Every Source

We connected to all 15 distributor data sources:

Email endpoints: Automatically detected and pulled attachments (Excel, CSV, TXT) from specific inboxes and folders

SFTP servers: Automated fetch jobs for each distributor's SFTP location with configurable schedules

Custom ingestion service that:

• Parsed each file according to distributor-specific rules
• Logged ingestion status for traceability and debugging
• Triggered the standardization pipeline within minutes of data arrival

2. Standardization into a Canonical Schema

Each distributor's unique format was mapped into a single standardized schema:

Mapped fields including:

• Product identifiers and SKUs
• Quantities and units
• Prices and currencies
• Transaction dates
• Distributor and geography information
• Sales channels and business dimensions

Added enrichments such as:

• Standardized region/geo mappings
• Internal Airtame terminology for channels and segments
• Margin and revenue calculations
• Validation rules to catch anomalies

The result: one consistent POS dataset queryable by region, channel, distributor, product, and time.

3. Operational Integration with Salesforce

Rather than leaving data in a black-box warehouse, we embedded it directly into Salesforce where teams actually work:

Custom Salesforce objects for:

• POS sales (header-level records)
• POS line items (transaction-level detail)

Configured relationships to:

• Distributor and account records
• Products and product families
• Territories and sales teams

Enabled workflows including:

• Using POS data in commission calculations
• Creating automated follow-up tasks for end-customer opportunities
• Supporting pipeline reviews and account planning with actual sell-through data

Don't just centralize data – operationalize it where people work.

4. Data Lake & Real-Time Reporting

We connected Salesforce to Airtame's data lake, ensuring:

• All standardized POS records flow through
• Corrections made by users in Salesforce are reflected in reporting
• The data warehouse never drifts from operational reality

Built dashboards and reports for:

• Leadership: Global demand by region, product, and channel
• Supply chain: Inventory risk by distributor and geography
• Finance: Forecasting distributor orders and channel performance
• Sales: Distributor performance, follow-up opportunities, and territory sell-through

What we did

Measurable Impact Across the Organization

Quantitative Outcomes

99% reduction in manual work: The ~2 FTEs previously spent on file handling and data stitching were effectively eliminated

Reporting delay cut from 1-4 weeks to minutes: Data flows through to standardized reports within minutes of distributor file arrival

~80% improvement in forecast accuracy: Finance and Supply Chain can now predict distributor orders and channel performance much more reliably

Operational Impact by Team

Supply Chain

• See stock risk early – both overstock and potential stock-outs
• Proactively nudge distributors to place orders at optimal timing
• Improved working capital efficiency by aligning inventory with actual demand

Sales

• Target regions and accounts based on real performance data
• Follow up quickly on end-customers purchasing via distributors
• Spot where pipeline indicates demand but inventory lags
• Commissions calculated on accurate POS data, increasing motivation

Finance / FP&A

• Predict distributor orders and revenue with far more confidence
• Build reliable models for revenue, margin, cash flow, and scenarios
• Move from assumptions-based to data-driven planning

Leadership

• Trusted, near-real-time view of global end-customer demand
• Granular insights by region, channel, and product line
• Decision-making based on current reality rather than old spreadsheets

A Blueprint for Any Channel-Based Business

This solution pattern applies to any company that:

• Sells via distributors, resellers, or partners
• Receives POS / sell-through data in heterogeneous formats
• Needs a unified, timely view of end-customer demand

The core blueprint:

1. Automated ingestion from all partner channels
2. Standardization into a canonical schema
3. Operational activation in core business systems
4. Analytics & reporting built on operational truth

If your distributors are still emailing spreadsheets that disappear into manual analysis, you're leaving enormous value on the table.

This is exactly the type of automation, data, and AI-ready infrastructure we design and implement: turning messy external data feeds into clean, trustworthy, and actionable intelligence that drives better decisions across your business.