How is order cycle time different from job duration or cycle time?

Job duration or cycle time usually looks at the active work time on specific operations like cutting, welding or painting. Order cycle time looks at everything the customer experiences from order acceptance to shipment, including waiting on drawings, materials, queues and approvals. Customers do not care that welding only took two days if their order spent three weeks waiting. That is why order cycle time is a better metric for how easy your shop is to buy from.

How should a steel fabrication shop define the start and end of order cycle time?

Shops often disagree on what 'start' and 'finish' mean, so it is important to write down your definition and keep it consistent. Common start points are: purchase order accepted, deposit received or drawings approved. Common finish points are: shipped, ready for pickup or delivered/installed. For most steel fabrication shops, a practical default is: Start = PO accepted or job approved to proceed, Finish = shipped or ready for pickup.

Why does order cycle time matter for custom steel fabrication?

Order cycle time is one of the few metrics that tells you whether your shop is becoming easier to buy from. It helps you quote more accurately based on real lead times, improve cash flow by shortening the time between order and invoice, reduce expediting by improving flow and communicate clearly with customers about where their job is and what is blocking it. In HMLV and make-to-order work, total cycle time is often dominated by waiting, not welding hours, so tracking the full order cycle is critical.

How can a job shop break order cycle time into phases for better analysis?

Instead of only tracking a single start-to-finish number, it is more useful to measure the time spent in key phases. A shop-friendly breakdown includes: engineering/drawings, procurement/material readiness, cutting, forming, fit-up, welding, finishing, assembly, QC/pack and shipping. Once you see where days pile up in this chain, improvement opportunities become obvious. EZIIL helps by letting you structure projects into phases and monitor progress and delays at each stage.

Why should we use distributions (median, 80th, 90th percentile) instead of just averages for order cycle time?

Averages often hide the ugly reality in a job shop. A few very late jobs can skew the mean, while a simple average can make performance look better than what customers actually feel. Tracking the median shows typical performance, while 80th or 90th percentile values show what happens in bad weeks. Those higher-percentile numbers are what protect your quote promises. With EZIIL, you can export or review cycle-time data and look beyond simple averages to the distributions that matter for reliable delivery dates.

What delay reasons should we capture when tracking order cycle time?

You do not need dozens of codes. A short, consistent list works best. Common delay reasons include: waiting on material, drawing changes, rework, subcontract lead time, capacity overload and customer change requests. Categorising delays this way lets you quickly see patterns, such as repeated material issues or constant drawing revisions. EZIIL makes it easy to record blockers via task statuses and comments, so waiting time and its causes are visible rather than buried in spreadsheets or emails.

How does WIP (work in progress) affect order cycle time?

Most shops try to lower cycle time by starting jobs earlier or starting more work, but that usually increases WIP and makes everything slower. Too much WIP means longer queues, more context switching and more jobs partially done and waiting. To genuinely reduce order cycle time, you should gate release by readiness (materials, drawings, approvals), limit WIP per department and protect bottleneck resources with ready work instead of flooding them. EZIIL supports this by showing current load and status by department so you can release work based on real capacity.

What is a good weekly rhythm for managing order cycle time in a job shop?

A practical rhythm is a 30–45 minute weekly review plus a short daily check-in. In the weekly session, ask: Which jobs are trending late? What is blocked? What must move this week to protect ship dates? Use the daily check-in to align on immediate priorities and unblock critical tasks. EZIIL gives you a shared view of active jobs, deadlines and ownership, making these reviews data-driven instead of based on memory or sticky notes.

How can EZIIL help reduce order cycle time in a fabrication shop?

Order cycle time drops when work is visible, handoffs are tight and ambiguity is removed. EZIIL supports this by giving one shared view of active jobs, deadlines and ownership so priorities stop living in someone's head; making blockers visible through statuses and comments so waiting time is exposed and can be addressed; and enabling plan vs actual tracking so you can see where estimates or workflows are consistently wrong and adjust quoting or process steps. Many shops use EZIIL to identify patterns like long procurement phases and then add stronger 'materials ready' gates before releasing work to the floor.

How can we use EZIIL to improve our materials gate and avoid long procurement delays?

By tracking order cycle time phases in EZIIL, shops often notice that the procurement or 'materials ready' stage is where days pile up. When this becomes visible across multiple jobs, you can react by tightening your materials gate: for example, only releasing jobs to production when all key materials are confirmed and on hand, and planning purchasing earlier based on the live backlog. EZIIL helps by linking purchasing status and project phases so that planners see at a glance which jobs are genuinely ready to move and which would just sit as WIP if released.

How does order cycle time data improve quoting and customer communication?

When you know your real order cycle time performance, you can quote lead times based on data instead of best-case optimism. Median and 80th/90th percentile values inform realistic promises, while phase-based analysis shows where you need buffers. During execution, EZIIL lets you see which stage a job is in and what is blocking it, so you can give customers clear updates like 'waiting on drawings approval' or 'in welding, due to enter finishing on Thursday' instead of vague answers, improving trust and reducing escalations.

Order cycle time

Q: What is order cycle time in steel fabrication?

Order cycle time is the total elapsed time from when a customer order is accepted to when the order is shipped or delivered. It captures the customer's full waiting experience, including admin time, procurement waits, queue time on the floor and shipping. It aligns closely with lead time (order to receipt), whereas cycle time often focuses only on active work time at a station.

What is order cycle time in steel fabrication?

Order cycle time is the total elapsed time from when a customer order is accepted to when the order is shipped or delivered. In other words, it captures the customer’s waiting experience, including admin time, procurement waits, queue time on the floor, and shipping.

This aligns closely with lead time concepts (order to receipt), versus cycle time, which often focuses on active work time only.

In steel fabrication, you should define it clearly because shops often disagree on what “start” and “finish” mean. Choose one definition and stick to it for trend tracking.

Common definitions:

Start: PO accepted, deposit received, or drawings approved
Finish: shipped, ready for pickup, or delivered/installed

For most shops, the best default is:

Start = PO accepted (or job approved to proceed)
Finish = shipped/ready for pickup

Why order cycle time matters in steel fabrication?

Order cycle time is one of the few metrics that tells you whether your shop is becoming easier to buy from. Customers do not care that welding “only took two days” if the job spent three weeks waiting on material, approvals, and shop queues.

Tracking order cycle time helps you:

Quote more accurately (lead times based on real performance, not best-case thinking)
Improve cash flow (shorter cycle = faster invoicing and fewer WIP dollars stuck on the floor)
Reduce expediting (rush costs are usually symptoms of poor flow)
Improve customer communication (you can explain what stage the job is in and what’s blocking it)

In HMLV/MTO work, cycle time is often dominated by waiting. That’s why breaking the total into phases matters.

Best practices for measuring order cycle time in a job shop

1) Write down the definition and keep it consistent
You cannot improve what you keep redefining. Pick the start/end points and document them.

2) Track the “phase time,” not just the total
A shop-friendly breakdown is:

engineering/drawings
procurement/material readiness
cutting
forming
fit-up
welding
finishing
assembly
QC/pack
shipping

Once you see where days pile up, improvement gets obvious.

3) Use distributions, not just averages
Averages hide ugly reality. Track:

median (typical performance)
80th/90th percentile (what happens in bad weeks)
This is what protects your quote promises.

4) Capture delay reasons as a short list
Keep it simple: waiting on material, drawing changes, rework, subcontract lead time, capacity overload, customer change request. A few consistent categories beats a messy spreadsheet of 50.

5) Reduce WIP on purpose
Most shops try to lower cycle time by starting earlier or starting more. That usually increases WIP and makes everything slower. Instead:

gate release by readiness (material + drawings + approvals)
limit WIP per department
protect the bottleneck with ready work

6) Build a weekly rhythm
A 30-45 minute weekly review (plus a quick daily check-in) is enough:

Which jobs are trending late?
What’s blocked?
What must move this week to protect ship dates?

How EZIIL helps reduce order cycle time

Order cycle time drops when you can see work clearly, keep handoffs tight, and stop losing time to ambiguity.

EZIIL supports that by:

giving one shared view of active jobs, deadlines, and ownership so priorities stop living in someone’s head
making blockers visible quickly through statuses and comments, so waiting time is exposed, not hidden
enabling plan vs actual tracking so you can identify where estimates or workflows are consistently wrong (and fix quoting or process steps)