Every order, on time and in full.
Delivery Performance turns your order, planning and MES data into a live OTIF dashboard for planners and customer service. See which orders are at risk, where line load is tight, and what to replan, built on the systems you already run.
Built on your ERP, MES and planning data · structured on Azure · delivered in Power BI.
See it in action.
An interactive Delivery Performance dashboard, running on sample data. The same layout runs on your orders and lines, live.
This is one example view, on synthetic data. On the same governed foundation we shape the screens to your orders, your lines and your roles, so a different layout is a configuration, not a rebuild.
You're looking at one view of it.
Everything here runs on the same governed data foundation. Build the views you need now, and the ones you need later, on top of it.
Production Performance
OEE, downtime and deviations per line
Delivery Performance
OTIF, schedule adherence, line load
Quality & Yield
First-pass yield, scrap, defect causes
Your own view
Shaped to your KPIs, no rebuild
Built once, shaped to you. Because every view runs on one governed foundation, a different view, or a new one next year, is a configuration, not a rebuild.
Order control, on one screen.
At a glance: what's inside the Delivery Performance dashboard, and what it means for the orders going out today.
Delivery KPIs at a glance
OTIF, on-time, in-full, schedule adherence and orders at risk, in one header that updates through the day.
Orders at risk, ranked
Every order behind plan, ranked by due time, with the line, the cause and the next action attached.
Line load & capacity
Plan versus capacity per line for the week, so overloaded and slack lines are obvious and you can rebalance before it bites.
Why orders slip
A ranked view of the reasons orders run late, material, capacity, changeover, so the recurring causes are obvious, not anecdotal.
OTIF per customer
The same KPIs split by customer, retailer and channel, so service knows which accounts are exposed this week.
Activate: proposed replan
For an order at risk the system proposes a reschedule or rebalance with reasoning and a reason code. Your planner validates, and the choice is logged.
How Delivery Performance works.
One reusable path from order and line data to dashboard. Built once, then applied across every line and every site.
Built once. Every new line and site inherits the same model, no rebuild.
The people behind the dashboards.
StriData was built by industrial data practitioners who got tired of two things: dashboards no one acts on, and delivery data that stays stuck between ERP, planning and the floor. We work where operational reality meets business outcomes, one foot in IT and one on the floor.
We build the foundation and the analytics on top of what you already run. We are honest about scope, and we say no to work we can't do well.
“An order is a promise to a customer. Our job is to make the data behind that promise something you can act on in time.”
Questions teams ask us.
What if this view isn't exactly what we need?
That's the point. What you see is one example. Because it runs on a governed data foundation, a different view is a configuration, not a rebuild: we reshape the KPIs, layout and screens to your orders, lines and roles without touching the plumbing underneath. The modules show what's possible; your version is shaped in the Quick Scan.
What data source does it run on?
ERP order and delivery data (SAP and others), MES production progress, and planning or APS data where you have it. We work vendor-neutral and add the analytics layer on top of what is already there, we do not replace your ERP or planning system.
How is OTIF calculated?
On-time (delivered by the promised date and time) and in-full (the complete ordered quantity) combined into one figure. You set the cut-off, the tolerance and the target, for example 96%, so the number matches how your customers actually measure you.
Is the dashboard real-time?
Near real-time. Data is loaded incrementally (typically every 15 minutes for the pilot, tunable per setup). Order progress, at-risk flags and line load update through the day.
How long until we see a working dashboard?
After a Quick Scan and a short order- and line-mapping workshop, a first working dashboard on a pilot site typically lands in a few weeks. New lines and sites then inherit the same model.
The proposed replan, is that AI?
No black box. The Activate layer proposes a reschedule or rebalance from transparent, rule-based logic on real order and line state (for example a capacity conflict or a faster line for the SKU) with a reason code. Your planner always validates before acting, and the decision is logged.