It is essential to train staff consistently so that everyone gets the same message and performs each function exactly the same way
Staff members conducting inventory use ‘count books’ to mark the actual counts as they move from location to location
Every ringmaster knows who’s in control under the big top. But when you’re in peak season and your warehouse resembles a circus, it’s all too easy to let your menagerie run amok. In today’s high-speed distribution facility, who has time to be a trapeze artist and perform high-wire acts for days to count every piece of merchandise? Statistical sampling can help make those tedious physical inventory counts a thing of the past.
In 1995, Rivertown Trading Company (now target.direct), opened a state-of-the-art distribution center with a new warehouse management system. Not being familiar with the WMS and having no set procedures for inventory control, we lost control of inventory during our peak season — a period in which we ship 66,000 packages a day.
When the year ended, we knew we needed to overhaul the way we stored, moved, and handled our 20,000-plus SKUs. We had an opportunity to not only improve our accuracy but eliminate the time-consuming process of a full physical inventory. Target.direct collaborated with accounting firm Deloitte & Touche LLP to create cycle counting practices that would be the starting point of all inventory control procedures and would interface with the WMS.
Bottom line
Before the program could be developed, we had to establish clear project goals. Our objectives were as follows:
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Ensure a high level of accuracy for all data collected, document procedures, and manage the operation to make sure those procedures were followed. It was also essential to train staff consistently so everyone would get the same message and perform each function exactly the same way. It was common for three different team members to have three different ways of arriving at the same solution. The best solution needed to be found for each problem and become the only resolution for that problem.
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Provide feedback for continuous improvement in activities affecting inventory. This would involve using cycle count reports and analysis for operational and financial monitoring and benchmarking. Giving feedback to team members would allow them to make the initial adjustment and help identify the most common causes of inventory exceptions.
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Support various business and seasonal requirements, and satisfy financial partners. A cycle count program must meet audit requirements. We would need to establish a baseline of accuracy, with a full physical inventory to begin the process and estimation sampling. It would be important to document procedures, follow the plan, and record the results.
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Eliminate large-scale annual physical inventories, which cost a lot of money in labor and potentially lost sales. Moreover, a physical inventory would declare an accurate count for only a moment in time. The bottom line was that no certainty of ongoing accuracy would be gained, while sales and service would be lost.
What goes around
The process target.direct uses to execute and manage its cycle count program requires a count team, database, and time to run and analyze reported data. To begin the process, target.direct needed to draw a line in the sand or establish an accurate inventory as a baseline. This can be accomplished in one of two ways, by doing a full physical inventory or by using estimation sampling. This counts 5% to 10% of the merchandise, with standard receiving and shipping cut-offs in place. If you elect to do estimation sampling, the sample must meet the requirements of top management and those of your business partners, meaning that they must have confidence in the inventory’s accuracy when the sampling is complete. At the end of this “final” physical inventory, or, in target.direct’s case, a passed estimation sample of 10%, you can begin the cycle count process.
The reports below show detailed information for exceptions based on the specific criteria selected.
Dollar Variances Exceeding Tolerance
| Report Date: 01-Mar-00 | Qty. Tolerance Specified: 1 | Location: Stock Reserve | Counts: RAN |
| Date Range: 2/1/99 to 1/31/00 | $ Tolerance Specified: 1 | Company: * |
| Location | SKU# | Description | Physical $ Value | System $ Value | Net $ Var. | Reason Code |
|---|---|---|---|---|---|---|
| BH262P05 | 72676M | Giraffe Dress-Long Sleeve | $1,674.40 | $3,348.80 | ($1,674.40) | PA |
| BC289C01 | 50244 | Hyacinth Buckets | $7,304.96 | $8,446.36 | ($1,141.40) | ID |
Quantity Variances Exceeding Tolerance
| Report Date: 01-Mar-00 | Qty. Tolerance Specified: 1 | Location: Stock Reserve | Counts: RAN |
| Date Range: 2/1/99 to 1/31/00 | $ Tolerance Specified: 0 | Company: * |
| Location | SKU# | Description | Retail Price | Physical Quantity | System Value | Net Var. | Reason Code |
|---|---|---|---|---|---|---|---|
| BM283A02 | 39864AUG | Sox of the Month | $1.60 | 1920 | 1689 | 231 | ID |
| BC289C01 | 50244 | Hyacinth Buckets | $8.78 | 832 | 962 | -130 | ID |
At target.direct the cycle count population includes all locations in the facility. The population is divided into two major areas, stock reserve and other primary pick locations. Stock reserve locations hold product before replenishment to the forward primary pick locations. Each SKU is assigned a forward primary pick location upon its initial arrival in the facility. Because of the amount of traffic at primary pick, more time is spent counting primary pick locations than stock reserve.
To facilitate the cycle counts and the reports that would be generated from them, Deloitte & Touche created a software program called Quest (Quality Assurance Using Efficient Statistical Techniques) to facilitate the cycle counts and reports. Quest was linked to target.direct’s warehouse management system through an existing query in Microsoft Excel.
Vision quest
When the baseline inventory has been established, whether a full physical inventory was conducted or an estimation sample was given approval, the next steps are to begin the day-to-day cycle counting procedures.
Step one is to count a statistically valid, random sample of your inventory each day. Target.direct accomplished this by using an Excel spreadsheet to query the inventory population. The query would pull down 50 reserve and 50 forward pick locations; these 100 locations would be supplied to the count teams to start the actual physical counts. The thought behind doing 50 primary pick and 50 reserve locations was to cycle through nearly the entire population. At the beginning of the program, target.direct was cycling through 80% of all locations. Once we attained accuracy goals for the first six months, the level of inventory coverage could be reduced.
At target.direct we have functionality on the warehouse management system that allows us to print “count books” detailing all the locations pulled down in the Excel query. Included on the count books are the location, item number, and actual system quantity. The staff members conducting the inventory use these count books to mark the actual counts as they move from location to location.
You must allocate enough time for physical counting to allow team members an opportunity to produce accurate counts. It’s also important to ensure that during the counts all activities are complete at the locations to be counted. At target.direct, when the counts are finished, the actual quantity and reason codes for any discrepancies are entered in the Excel spreadsheet in preparation for the Quest (Access) cycle count software analysis. It is possible that you may not yet know the reason for a discrepancy, but after investigation you must enter reason codes for reporting purposes.
Root Cause Summary Report
| Report Date: 01-Mar-00 | Qty. Tolerance Specified: 0 | Location: Stock Reserve | Counts: |
| Date Range: 2/1/99 to 1/31/00 | $ Tolerance Specified: 0 | Company: * |
| Reason Code | No. of Variances | System Quantity | Physical Quantity | Net Qty. Variation | System $ Value | Physical Value | Net Value | Net $ Variation |
|---|---|---|---|---|---|---|---|---|
| 99 | No variance | |||||||
| BC | 9097 | 574,788 | 574,788 | 0 | $6,241,517.58 | $6,241,517.58 | $0.00 | 0.00% |
| HB | 16 | 2,023 | 1,989 | -34 | $19,396.69 | $19,732.36 | $335.67 | 1.73% |
| ID | 9 | 591 | 703 | 112 | $906.25 | $1,216.21 | $309.96 | 34.20% |
| NO | 30 | 12,757 | 12,565 | -192 | $38,664.70 | $37,223.86 | ($1,440.83) | -3.73% |
| RC | 5 | 858 | 820 | -38 | $7,274.06 | $6,005.08 | ($1,268.98) | -17.45% |
| SC | 52 | 4,898 | 4,731 | -167 | $52,730.94 | $51,738.01 | ($992.93) | -1.88% |
| Grand Total | 9,212 | 597,952 | -76 | $6,373,036.62 | $6,370,585.11 | ($2,451.51) | -0.04% |
This report shows the most common causes of exceptions in inventory. Examine these carefully to recommend actions for improved controls.
The time required to execute these counts depends on location size, count area, and access to the locations, but should not exceed four hours. This time includes only cycle counting, not the other maintenance activities you must perform to meet the recommended accuracy goals.
Keep in trim
Target.direct uses four maintenance activities to enhance the cycle count procedures. These activities include open location verification, empty location verification, concentrated counts, and problem product counts.
Open location verification and empty location verification are visual checks of all locations reported open but full, or empty but open. Our count team members use a printed checklist as a guide while they travel on rows of reserve. This activity is most effective if reserve locations are limited to one SKU per location. It becomes a much more time-consuming process if reserve locations are mixed with multiple SKUs in one location. Target.direct’s goal is to complete the entire reserve population each week. We research exceptions the following week and make inventory adjustments.
High-velocity locations receive concentrated counts because of target.direct’s continuous efforts to achieve high-density picks from forward pick locations. The high number of picks coming from these locations increases the likelihood of discrepancies in the inventory.
Problem product counts, usually the result of a stock-out or suspicious receipt, can be added to the cycle count list before the Excel query is run to acquire the 50 forward pick and 50 reserve daily cycle count requests.
Maintenance activities improve the chances that random cycle counts will be done accurately, requiring less time to perform and smaller adjustments to inventory. After the counts, extrapolate the level of accuracy to your entire inventory. These activities add another two hours to the day, but the benefits far outweigh the time spent. All exceptions found as a result of maintenance activities should be researched immediately following the count or at the beginning of the next day.
Playbill
Target.direct uses the Quest cycle count software to generate several management reports. The sample reports shown on pages 60, 62, 63, and 64 serve as vital tools for both management and business partners, enabling quick checks, visibility of exceptions, and fast action to improve inventory control.
At target.direct, we found that the advantage of doing a statistically based cycle count program was well worth the cost. The benefits of this program were felt in the first year. The company did not lose sales because of the time taken to do a physical inventory; saved on labor costs for conducting manual counts; and most important, increased customer satisfaction because of greater accuracy.
Project costs included the initial programming investment, extra estimation sampling labor, and the ongoing cycle count teams. The payback for target.direct, using conservative estimates, was 0.061 of year zero.
Grand finale
After a year of implementing the statistically based cycle count program, Rivertown Trading Company was acquired by Dayton-Hudson Corp. (Target), which accepted the methods of inventory valuation without question and without conducting a physical inventory. Perhaps the greatest benefit of statistical cycle counting, in addition to reduced labor, is that Target.direct’s inventory meets audit requirements. Accounting firms such as Deloitte & Touche and Ernst & Young recognize a drop in inventory volatility; specifically, a decrease in the frequency, nature, and size of adjustments. For us, the key improvement is that shoppers from our catalog or Web site can see merchandise availability in real time.
At left are financial estimates for the project. Below is a summary of data gathered during cycle counts. The report serves as a quick check for management and business partners.
| Year Zero | Year One | Year Two | Year Three | Total | |
|---|---|---|---|---|---|
| Costs | $52.313 | $46,080 | $46,080 | $46,080 | $190,553 |
| Benefits | $86,406 | $141,982 | $125,308 | $125,308 | $479,004 |
| Net Annual Benefit (Cost) | $34,093 | $95,902 | $79,228 | $79,228 | $288,451 |
| Payback | $52,313/$86,406 = 0.061 of year zero or by 6/1/97 | ||||
| ROI | $479,004/$190,553 = 251% | ||||
| Note: All dollars were constant and cash flows were not discounted. ROI was based on a three-year time horizon. | |||||
| Year Zero = April-June 1997. Estimates were conservative. | |||||
Cycle Count Summary Report
| Report Date: 01-Mar-00 | Total Population: 32,977.17 | Location: Stock Reserve | Counts: RAN |
| Date Range: 2/1/99 to 1/31/00 | Avg. Total Cost of Population: | $20,832,989.00 | Company: * |
| Total # of SKUs/location | |
| Combinations: 32,977.17 | |
| No. of counts: 9,212 | |
| % of total: 27.93% | Sample Extrapolation: |
| No. of variances: 113 | Estimated maximum variance rate at a 95% confidence level: 1.4560% |
| Percentage of counts with a variance: 1.23% | Estimated total absolute dollar variance: $58,494.74 |
| Total inventory cost: $20,832,989.00 | Estimated absolute variance as a percentage of total inventory cost: 0.28% |
| System inv. value of counts: $6,373,036.62 | Estimated total net dollar variance: ($10,416.92) |
| Percentage of total inventory value: 30.59% | Estimated net variance as a percentage of total inventory cost: -0.05% |
| Absolute dollar variance: $13,766.12 | |
| Net dollar variance: ($2,451.51) | |
| Percentage of net variance to total: -0.04% |
Tom Stute is an operations manager at target.direct. This article includes information from a presentation written by Helen Boyne, director of operations at target.direct. Stute can be reached at [email protected].