Is a good total hiding a bad mix?
Forecast accuracy and bias by product family, market and customer, so a 14% miss is fixed before it becomes a stock-out.
Fast-Deploy Systems Data Solutions for Your Enterprise
Thousands of Data Points. Multiple ERPs. One Single Source of Truth.
We transform fragmented enterprise systems into unified, governed data models. Stop reconciling spreadsheets and start driving decisions.
Value Drivers
More than 20 years in supply chain and finance taught us where governed data moves the numbers.
Top-Line Impact
Accelerate revenue growth with clear, governed data visibility across all sales and operational channels.
Cash & Working Capital
Unlock trapped cash. Reduce working capital by optimizing inventory health and supply network efficiency.
S&OP & IBP Excellence
Align demand planning, supply planning and inventory management into a single, seamless Integrated Business Planning cycle.
Technical Edge
What sets our builds apart once the dashboards are live.
Power BI Write-Back
Close the loop. Don't just analyze data: update your ERPs and planning parameters directly from your Power BI dashboards.
Enterprise Data Governance
Establish a certified "managed self-service" semantic layer. Every metric traces back to a governed, single source of truth.
Multi-ERP Integration
Harmonize SAP and legacy systems seamlessly into modern architectures on Microsoft Fabric and Snowflake.
One data model, six decisions
How we build it
Four layers, one team: from the SAP tables to the answer an agent gives your planners. Every number can be traced back to where it came from.
Book a Diagnostic CallView Architecture
- 60%of AI projects without AI-ready data will be abandoned through 2026Gartner
- 35%of FP&A time is left for high-value analysisFP&A Trends 2024
- 1 in 3planning organisations spend about 80% of their time collecting data instead of decidingAIMMS
How the stack works
Which items stock out before March?
3 items in Southern Europe drop below 2 weeks of coverage in February.
Traceability
AI agentsCoverage (wks)fct_supply_planSAP · MARD · EKPO
Planners ask in plain language and get answers from the same governed measures as the dashboard.
From demand to cash, in one report
We have run these numbers for more than 20 years in supply chain and finance. This is the kind of Power BI report we deliver: demand, supply, inventory, orders, order-to-cash, margin and cash on one data model, so every page agrees with the others. Click through the pages.
- FY2026 vs FY2025
- All markets
- Rx and hospital
- Forecast accuracy87.2%+3.4 pp vs PY
- Forecast bias−0.8%−1.3 pp vs PY
- Units sold38.4 M packs+9.7% vs PY
- Demand vs budget103.5%+3.5 pp vs PY
Demand: actual vs forecast (M packs)
In total the forecast looks close, but by product family it misses by up to 14%: oncology was under-forecast and cardio over-forecast, which drives stock-outs and excess at the same time.
- Actual
- Forecast
- Forecast range
Largest forecast errors by product family
- Oncology−14.0%Under-forecast after a hospital tender win.
- Cardiovascular+11.0%Over-forecast: a competitor generic took share.
- Respiratory+7.0%Late flu season moved demand by a month.
- Anti-infectives−6.0%Under-forecast in two regions.
- Gastroenterology+2.0%Within tolerance.
The questions we answer
Every leadership team asks them every month. We turn them into answers that are ready when you need them.
Which products are at risk of a stock-out in the next three months?
Coverage by item and site, with alerts already calculated.
How much cash is tied up in excess or near-expiry stock?
Inventory valued by age, batch and expiry date.
Can we trust the demand forecast?
Forecast accuracy and bias by product, market and customer.
Why has gross margin changed versus last year?
Price, volume, mix and cost effects, separated and explained.
Where will we land at year end?
A year-end landing that combines actuals, forecast and the supply plan.
What changed versus last month?
Prior-month and prior-year comparisons on volumes, prices and costs, at every close.
Could machine learning improve our forecast?
An ML forecast compared with your current one, on the same accuracy measures.
Is our data ready for AI?
A check of quality, structure and documentation, with a plan to close the gaps.
Solutions
Four solution lines on one data model, from demand all the way to the P&L.
- Supply Chain SolutionsThe right service level with the right inventory.Demand PlanningSupply planningInventory managementExplore the solution
- Finance SolutionsAlways know why margin moves.FP&AGross margin and variancesCost and price analysisExplore the solution
- AI SolutionsBetter forecasts, faster decisions.AI and ML demand forecastingAI inventory optimizationBuilding dashboards with AIExplore the solution
- Data PlatformOne version of the truth, from every ERP.Multi-ERP integrationDashboards and reportingExplore the solution
Industries
We know the processes, constraints and language of these markets.
Pharma and Life Sciences
Batches, expiry and shelf life, multi-country distribution networks, service levels to hospitals and distributors.
Consumer goods (CPG)
Promotions and seasonality, thousands of SKUs and channels, constant pressure on prices and margins.
Our approach
We start from the decisions you need to make, not from the tools. Visible value within weeks, then we scale.
Diagnose
In the first weeks we map decisions, KPIs and data, and find where value is created or lost.
Design
Together we define the data model, indicators and calculation rules, and the value case to prove.
Pilot
A first use case on your real data, measured against the way you work today.
Scale and hand over
We extend to markets, products and processes, and train your team to run it on their own.
About us
Orbit DataWorks (Orbit Data Works) brings together consultants with more than 20 years of experience in supply chain and finance, gained at multinational groups in Pharma, Life Sciences and consumer goods.
We have built planning control towers, margin models and data platforms that integrate multiple ERPs. Now we bring that experience to companies that want to decide faster, with numbers they can trust. We work in English, Italian, Spanish and German.
Today we also apply AI and machine learning to forecasting, inventory and reporting, always on data that has been prepared and checked first.
Technologies we use
- Snowflake
- dbt
- Power BI
- Microsoft Fabric
- SAP
- SQL
- Python
- Excel
Frequently asked questions
Can you integrate multiple ERPs into Snowflake?
Yes. We bring data from SAP and other ERPs into Snowflake with documented dbt models, and from there into Power BI or Microsoft Fabric.
Do you build Power BI supply chain dashboards?
Yes: control towers for demand, supply and inventory, with forecast accuracy, coverage and service levels.
What is a price volume mix analysis?
It splits the change in revenue or gross margin into price, volume, mix and cost effects, so you can see why margin moved versus prior year or prior month. We deliver it as a gross margin bridge in Power BI.
Do you work with pharma and life sciences companies?
Yes, including batch, expiry and shelf life analytics for inventory, and multi-country distribution networks.
Is integrated business planning only for large companies?
No. We set it up for mid-size companies too, with one monthly cycle that links the volume plan to the financial plan.
How can AI improve demand forecasting and inventory?
Machine learning models pick up seasonality, promotions and trends that manual forecasts miss. Better forecasts let AI set safety stock and reorder points that protect service levels with less inventory.
Is our data ready for AI?
Most companies need some preparation first. We check data quality, structure and documentation in your ERPs, then build an AI-ready layer in Snowflake or Microsoft Fabric.
Let's talk about your data
Tell us in a few lines what you want to see more clearly: inventory, margins, forecasts or the month-end close. We reply within two working days.
Write to info@orbitdataworks.com