Product

Dashboards That Track Throughput, WIP, and the Constraint

If you can’t see the constraint clearly, the shop stays stuck in expediting and “busy” work that doesn’t ship.

These dashboards make flow visible with the few metrics that actually predict delivery: throughput, WIP vs shipments, and constraint schedule stability.

You’ll see the daily signal that changes decisions: hours scheduled vs hours completed (especially at the constraint workcenter).

Microcopy: Get the smallest next step that moves OTD, lead time, and throughput. — or review your constraint + data readiness in 20 minutes.

What these dashboards track

Most reporting tells you what happened last month. These dashboards tell you what will happen next week if nothing changes. They focus on measures that connect directly to on-time delivery and lead time stability.

Throughput and shipments

  • Shipments by day/week (trend)
  • Throughput value (optional) if order values are available
  • WIP rising without shipments rising indicator

WIP that matters

  • Total WIP trend
  • WIP by stage (before constraint, at constraint, after constraint)
  • Aging WIP (what’s stuck)

Constraint stability

  • Hours scheduled vs hours completed daily
  • Queue time trend (where it’s measurable)
  • Missed schedule / priority churn indicator (how often the plan changes)

Due-date performance (OTD)

  • On-time delivery trend
  • Late jobs count and lateness buckets
  • At risk this week list based on capacity signal

The daily signal that prevents surprise late jobs

When capacity is treated as a weekly guess, priorities change all day and expediting becomes the operating system. The simple fix is to measure daily execution at the constraint: hours scheduled vs hours completed.

  • Stable capacity signal you trust
  • Classify new orders as safe / caution / critical
  • Proactive customer communication when risk changes
  • Fewer priority fights, calmer release decisions

This is how shops reduce expedite rate, stabilize lead times, and improve OTD without adding chaos.

What you’ll see in week one

Week one is about clarity, not perfection. We stand up a baseline that shows where WIP is accumulating, how shipments behave, and whether the constraint is being protected.

  • A flow snapshot you can read in 2 minutes
  • A short list of the top drivers of lateness (based on the data you already have)
  • A simple capacity signal and an at-risk view for the next 5–10 working days (where data supports it)

Data sources we can start from

You don’t need a rip-and-replace system to get useful dashboards. We can start from exports and improve the inputs only when it changes the decision.

  • ERP exports (jobs, operations, due dates, statuses)
  • Spreadsheets (dispatch lists, priority flags, due-date lists)
  • Time clock or labor reporting exports (where available)
  • Shipping history (ship dates, quantities)

If 3 out of 5 basics are available, we can start and improve the rest as we go.

What this is NOT

  • Not pretty charts that ignore how the shop actually runs
  • Not an ERP replacement
  • Not a one-time data cleanup project that never ends
  • Not a black box: you control the definitions and decision logic we create

Next step path (text-only links)

If you want the fastest next step:

• Identify the constraint blocking throughput: /root-cause

• Learn what AI scheduling actually requires: /guides/ai-job-shop-scheduling-what-it-requires

• See AI job shop scheduling that works in the real world: /services/ai-job-shop-scheduling

FAQ

What do you mean by constraint stability?

Constraint stability means the plan for the constraint workcenter stays predictable day to day. When it’s stable, upstream priorities calm down, WIP stops piling up in the wrong places, and shipments become more predictable.

Can dashboards reduce WIP without reducing shipments?

Yes, when release is controlled and the constraint is protected, WIP can come down while shipments hold steady or improve. The dashboard makes that relationship visible so decisions stay consistent.

What if our ERP data is messy?

That’s normal. We start from exports and focus on the minimum data needed to make decisions trustworthy. Clean-up happens only where it changes outcomes.

Do we need real-time data?

Not to start. Daily or even end-of-shift updates can provide a stable signal. Real-time comes later if it’s worth it.

Will this work for high-mix, low-volume shops?

That’s the intent. Machine shops, CNC job shops, and fabrication teams need dashboards that reflect sequence, workcenters, and changing priorities.

What metrics matter most for delivery?

Shipments trend, WIP vs shipments, on-time delivery trend, and the constraint’s hours scheduled vs hours completed are the core set.

How fast can we get a useful baseline?

If exports are available, the first useful baseline can be built quickly. Accuracy improves as routings and statuses become more consistent.

Does this replace our existing reporting?

Usually it complements it. The point is decision support for flow, not monthly accounting reporting.

How does this connect to AI scheduling?

Dashboards make the inputs and outcomes visible. AI scheduling works only when the data is clean and sequenced; dashboards help you see what’s trustworthy and what isn’t.

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Constraint consulting • Throughput audits • Embedded advisory