How to Measure Schedule Performance in a Manufacturing Facility

QUESTION: How do you measure schedule performance in a manufacturing facility?

ANSWER: It’s a great question and one that I unfortunately find lots of variation in as I tour various plants around the country.  It is the metric that is most “fudged” in my experience, i.e., makes the numbers look better than they really are. 

One story I referenced in my book, The 12 Principles of Manufacturing Excellence, is a classic.  This plant had a manual process where the production control clerk who picked up the report didn’t record the previous week’s delivery performance until after she’d done her Monday and Tuesday chores.  Thus, anything that cleared the plant for shipment by Wednesday a.m. each week was counted as “on time” because the work order was closed by the time the clerk prepared the report.  The only orders that were recorded as late were those prior week orders that had not been transferred into shipping at the time of the report.   

Another example I often find is that when an order shows up short on the ordered quantity a negotiation commences with the customer to see if it’s OK with them to ship it short of the order quantity and consider the order complete.  Sometimes it is, sometimes not. It depends on the customer.  The point here is that any tolerances on quantity must be approved by the customer, in the formal system and part of the assembly, pack and ship instructions.  This is important to avoid the waste of having to bother the customer for an answer every time there is a variance to the quantity ordered.    

A third thing that I see far too often is factories that don’t reschedule missed orders on a timely basis.  Worse, I’m seen other plants that don’t reschedule at all and just allow the late backlog to roll over week by week until it finally ships or is cancelled.

Ok, so what and how should we measure schedule performance in our factories?  How can we make sure we’re telling the truth on these critical measures?  Here are my recommendations.

• Schedule the orders based on the customer’s request date wherever possible, but recognize that constraints may make this impossible in the short term.  When it is clear that the request date cannot be met without overscheduling the shop and putting already committed schedules at risk, then come to an agreement with the customer on what you can confidently promise.  My advice is: Never tell your customers what they want to hear if there is high risk you cannot execute it.  Usually the customer has some flex on their end.  It’s much easier for them to plan based on a truthful quotation of the delivery than it is to call the customer three days before it’s due and say, “Sorry, we’re going to be late.”  At that point we’ve just created chaos in the customer’s business that could have, should have, been avoided.  This could damage what had otherwise been a good relationship that may be hard to mend going forward.  These kinds of gaffes, over time, are likely to cause the customer to find more reliable suppliers, and the incumbent’s market share will start disappearing one order at a time.  Capacity is not infinite.  Never commit to something you can’t do.
• You may want to track your original promise dates against customer request dates so that data can be accumulated and mined for opportunities to reduce cycle times and create more capacity on constrained work centers.  In the short-term, overtime schedules may be required to secure the business while improvements are being made.  Sometimes you’ll find a happy problem, i.e., that sales trends are increasing at a rate that capital expenditure is in order to capitalize on a growing market.

The sum of all of this is that I believe it is prudent to measure plant delivery performance three ways:

Measure customer request date against original schedule date.  This metric is aimed directly at the marketing and capacity planning people.  When data suggest change is required, this is the brain trust that must guide the degree of change necessary on the shop floor for critical work centers.  The formula is simply: 

No. of Work Orders Scheduled to Customer Request Date ÷ No. of Total Work Orders Scheduled

I like to think about the second delivery performance metric as a direct reflection of how reliable the execution is on the shop floor, e.g., how well the product is flowing through the operation.  This is the metric that the manufacturing/value stream managers own.  It measures their effectiveness in delivering work orders on time.  (This always presupposes that the scheduling function has provided an executable schedule for each scheduling period as well as timely rescheduling when “stuff happens” For advanced practitioners who schedule the shop floor visually, my experience is that flow issues are addressed much more quickly and frankly, the execution is typically much better than traditional factories and a lot less “stuff” happens.)

The formula for this key metric is:

No. of Work Orders Delivered by the Original Schedule Date ÷ Total No. of Original Schedule Work Orders Due

The third metric on manufacturing delivery performance is intended to cause more discipline in the rescheduling of late work orders and making a new promise to the customer.   If it’s a make-to-order item, a late order could be OK within a small window of tolerance built in by the customer or it may mean that one of their lines is going down.  Communication with the customer is urgent in these circumstances.   For an item being made for warehouse inventory, the tolerance will be whatever level of safety stock is on hand.  In either case we don’t want late work orders to simply roll over as past due without a “re-promise” to the customer or to the formal MRP/CRP systems.  The formal system uses these schedule updates to regenerate what the needs are, and in what time frame, based on new data.   The metric formula is:

No. of Work Orders Delivered to the Current Schedule Date ÷ Total Work Orders Due Current Period (includes all late orders from prior periods)

This results in the factory getting only one chance to deliver the order.  People with the wrong mindset on service think:  “Well, we’ve missed the original schedule so what’s our incentive to stay after the late orders to get them out the door ASAP?”  This metric requires measuring missed schedules every time there is a reschedule date and/or any late order that gets carried over.  Either way, if the order is not delivered on four occasions, then the plant will be dinged four times for the miss.  Absent this check and balance, some plants play the game of going to work right away on the new week’s schedules instead of giving priority to the late orders.  This is an important process that is typically managed by the scheduling department.

The only other point I’d make on delivery performance is this:  Once the manufacturing team has transferred the inventory to warehouses/logistics, they must close the loop to make sure the order get shipped to arrive on the customer’s dock on time.  It’s a total team effort to provide great service to the customer. 

As Belden’s VP of manufacturing Fast led a transformation of Belden plants in the late '80s and early '90s that included cellularizing about 80% of the company’s equipment around common products and routing, and the use of what is now know as lean tools. Fast is retired from General Cable Corp., which he joined in 1997. As General Cable's senior vice president of operations, Fast launched a manufacturing excellence strategy in 1999. Since the launch of the strategy, there have been 34 General Cable IndustryWeek “Best Plants Finalist awards, including 12 IW Best Plants winners. Fast holds a bachelor's degree in management and administration from Indiana University and is a graduate from Earlham College’s Institute for Executive Growth. He also completed the program for management development at the Harvard University School of Business.