Targeting order fulfillment
Key benchmarking practices are a sure fire way to improve order processing and improve customer satisfaction.
By Sara Pearson Specter, Editor at Large -- Modern Materials Handling, 11/1/2004
Nearly every skill takes practice to perfect—and that goes for warehousing operations too. But you have to know where you stand in order to improve. That's where benchmarking enters the warehousing picture. By regularly monitoring and measuring key metrics in the warehouse or DC, you can come closer to achieving your goals. This is particularly true in order fulfillment, which most directly affects how your customers view your warehouse and DC.
Here, John Hill, partner at ESYNC (419-842-2210, www.esync.com); Maida Napolitano, senior industrial engineer at Gross & Associates (732-636-2666, www.grossassociates.com); and Rosanne Megrath, director of customer logistics for Tropicana Beverages (where fulfillment benchmarking has been in effect for almost 10 years), offer some pointers on what to measure, how, and why it's worth the effort.
Reading the signsCustomer feedback is often the pebble that creates ripples on the benchmarking pond, says Napolitano. 'When customers ask, 'why does it take XYZ company 24 hours to ship orders while it's still taking you 36?' [it should be] enough to jumpstart any company into benchmarking,' she notes.
Other symptoms include customer complaints, chargebacks for incomplete orders, regularly running behind schedule and errors. On the warehouse floor, workers waiting for orders, congestion in the aisles, and picker backtracking are some operational signs that may be resolved in a benchmarking study.
'About 10 years ago, we had a reputation for not providing very good customer service,' recalls Megrath. 'At the time we had about a 92% order fill rate—today our goal is 97%.' The company recognized that its customers demanded a higher degree of order fulfillment. So, as part of a complete customer service overhaul, more thorough and detailed measurements were put in place.
The opportunities for measurements within an operation are practically unlimited, starting with receiving, and working through storage, material movement, orderpicking and on to shipping. The trick is to find the metrics that best suit your unique situation—but at the least, take a look at order cycle time in hours, cases per hour (for full case operations), and lines per hour (for full case/piece pick operation), suggests Napolitano.
Megrath agrees: 'From a total perspective, we rely most heavily on both order fill and on-time delivery metrics, and secondarily on case fill metrics.'
Crunching numbersNearly all of the data required for benchmarking fulfillment should be in any warehouse management system (WMS). But don't rule out other sources.
'Ask your order processing people for a year's worth of sales order data: the number of orders, the number of lines per order, and the number of items per line,' says Hill. 'Then get your warehouse payroll data, which shows how many people worked how many hours.'
From those sources, you can calculate how many orders have been placed, how many lines were processed, and how many items per line were processed. Then, simply divide by the number of days, hours, and/or people it took to fill those orders.
With the numbers in hand, it's time to look for areas of improvement. 'Focus attention on areas where performance is sub-par, then take a deeper look into some of your processes to see if you can streamline, shortcut, or even eliminate some of the steps,' says Hill. 'That's the whole focus of modern day warehousing: to eliminate steps, eliminate touch and eliminate re-handling.'
In addition, the data uncovered in a benchmarking process can provide additional support when justifying capital equipment expenditures to upper management, Hill continues.
And don't forget to measure (and compare the results) again. And again. And again, at a frequency that's right for your operation—whether that's daily, weekly, quarterly or annually.
'We look at the metrics every day,' notes Tropicana's Megrath. 'Generally, if our performance is where we need to be within our targets, then we don't usually dig much deeper. But when we start to fall below, we investigate to find out why and correct the problem.'
Megrath's team conducts a daily root cause analysis on incomplete orders. Major performance discrepancies are investigated even further, with appropriate team leaders meeting weekly to review the results and reacting accordingly.
Don't forget to shareAfter you've collected the data and identified areas for improvement, share the information with other departments, like sales and marketing, finance and manufacturing, suggests Hill. Soliciting outside perspectives can generate buy-in and support for upgrades and improvements, while helping to determine a company-wide value for those projected advances.
Everyday Tropicana shares its most critical metric—the number of incomplete orders and the percentage of orders filled complete the day before—with personnel on the warehouse floor all the way up to upper management.
'We post that metric everyday, so that it's very visible and people can see that if they cut one order, it impacts our total result,' says Megrath. 'By keeping the people who are responsible—in the warehouse and in manufacturing—attuned to those metrics, then you get results. If you can measure it, you can manage it.'
So spend a little time doing your benchmarking homework, and reap the rewards. 'In return, customers will not only get better service,' says Napolitano, 'but they will also perceive you, the supplier, as one who strives to align the company with first-rate, best practices warehousing.'

Click on the icon to see the
warehousing operations benchmark chart.
(Benchmarking warehousing
operations - web exclusive - November 2004)
| Measure | Definition | Calculation | Current | Target | Value |
| On-time Delivery | Orders delivered on time per customer requested arrival date | Total orders on time ÷ Total orders shipped | ___% | ___% | $___ |
| Order Fill Rate | Orders filled completely on first shipment to customer | Orders filled complete ÷ Total orders shipped | ___% | ___% | $___ |
| Order Accuracy | Orders picked, packed and shipped perfectly | Orders shipped without errors ÷ Total orders shipped | ___% | ___% | $___ |
| Line Accuracy | Lines picked, packed and shipped perfectly | Lines shipped without errors ÷ Total lines shipped | ___% | ___% | $___ |
| Order Cycle Time | Time from order placement to customer shipment | Actual ship date – Customer order date | ___Hours | ___Hours | $___ |
| Perfect Order | Orders delivered without changes, damage or invoice errors | Perfect delivery orders ÷ Total orders | ___% | ___% | $___ |
| Source: ESYNC | |||||
| Measure | Definition | Calculation | Current | Target | Value |
| Orders per hour picked and packed | Average number of orders picked and packed per person-hour | Orders picked/packed ÷ Total warehouse labor hours | ___Orders/Hour | ___Orders/Hour | $___ |
| Lines per hour | Average number of order lines picked and packed per person-hour | Total lines picked/packed ÷ Total warehouse labor hours | ___Lines/Hour | ___Lines/Hour | $___ |
| Items per hour | Average number of order items picked and packed per person-hour | Total items picked/packed ÷ Total warehouse labor hours | ___Items/Hour | ___Items/Hour | $___ |
| Cost per order | Total warehouse costs Fixed: space, utilities, depreciation Variable: labor/supplies | Total warehouse costs ÷ Total orders | $___/Order | $___/Order | $___ |
| Cost as a % of sales | Total warehousing cost as a % of total company sales | Total warehouse cost ÷ Total revenue | ___% | ___% | $___ |
| Source: ESYNC | |||||
| Measure | Definition | Calculation | Currency | Target | Value |
| Inventory Accuracy | Actual inventory quantity vs. system-reported quantity | Actual quantity/SKU ÷ Reported quantity by SKU | ___% | ___% | $___ |
| Damaged Inventory | Damage measured as a % of inventory value (cost) | Total damage $ ÷ Total inventory value $ | ___% | ___% | $___ |
| Days on hand | Average sales days of inventory on hand based on historical sales | Average inventory value ($) ÷ Average daily sales during past month ($) | ___Days | ___Days | $___ |
| Storage Utilization | Inventory square feet as a % of storage capacity square feet | Average inventory square feet ÷ Storage capacity square feet | ___% | ___% | $___ |
| Dock-to-Stock Time | Average hours from truck arrival to product availability for orderpicking | Average dock-to-stock ÷ Hours per receipt | ___Hours | ___Hours | $___ |
| Inventory Visibility | Time from physical receipt to customer service notice of availability | Time of host system receipt data entry – Time of physical receipt | ___Hours | ___Hours | $___ |
| Source: ESYNC | |||||
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