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Replacing Voice Input With Technology That Provided Immediate Visualand Audio Feedback to Reduce Employee ErrorsDavid T. Goomas a

a Supply Chain Operational Consultant, Dallas, Texas, USA

Online publication date: 12 March 2010

To cite this Article Goomas, David T.(2010) 'Replacing Voice Input With Technology That Provided Immediate Visual andAudio Feedback to Reduce Employee Errors', Journal of Organizational Behavior Management, 30: 1, 26 — 37To link to this Article: DOI: 10.1080/01608060903472478URL: http://dx.doi.org/10.1080/01608060903472478

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Journal of Organizational Behavior Management, 30:26–37, 2010Copyright © Taylor & Francis Group, LLC ISSN: 0160-8061 print/1540-8604 onlineDOI: 10.1080/01608060903472478

WORG0160-80611540-8604Journal of Organizational Behavior Management, Vol. 30, No. 1, Feb 2010: pp. 0–0Journal of Organizational Behavior Management

Replacing Voice Input With Technology That Provided Immediate Visual and Audio

Feedback to Reduce Employee Errors

Smart WandD. T. Goomas

DAVID T. GOOMASSupply Chain Operational Consultant, Dallas, Texas, USA

In this report from the field at two auto parts distribution centers,order selectors picked auto accessories (e.g., fuses, oil caps, toolkits) into industrial plastic totes as part of store orders. Accu-rately identifying all store order totes via the license plate numberwas a prerequisite for the warehouse management system (WMS)to track each tote to the correct sorting lane, the correct shippingdoor, the correct route, the correct store, and to invoice the store.Using voice technology, the order selector uttered the license platenumber; however, in the event the utterance did not match thelicense plate number affixed to the lid of the tote, the tote wasrouted to a “penalty” area of the sorting lanes as a misidentifiedtote. Each misidentified tote cost the company approximately$500 in lost labor and lost sales. Replacing the utterance of theorder selector with a scanning stylus that provided both a “goodread” light indicator and a “good read” auditory beep informedthe selector that the license plate had been scanned and reliablydecreased the number of misidentified totes. The role of the orga-nizational behavior management (OBM) practitioner in indus-trial settings in designing interventions that increase accuracyand productivity was examined.

KEYWORDS auditory feedback, order selection, visual feedback,warehouse management systems

Address correspondence to David T. Goomas, 107 Willowbrook Drive, Duncanville, TX75116, USA. E-mail: [email protected]

Downloaded By: [University of Texas - Arlington] At: 22:18 12 March 2010

Smart Wand 27

Experimenters and practitioners have begun to use technology as a meansof delivering immediate feedback in large industrial settings such as distri-bution centers, warehouses, and manufacturing plants. Results suggest thatusing technology to provide feedback immediately following behavior sub-stantially improves employees’ performance in terms of both productivityand accuracy (Berger & Ludwig, 2007; Goomas & Ludwig, 2007). In theselarge industrial settings there are often hundreds of employees that handleand transport millions of cases, totes, boxes, carts, and pallets per year,containing anything from consumer goods, auto parts, general merchandise,dry goods, pharmaceuticals, food, and beverages, to name a few. Thesuppliers typically ship their product(s) to a facility, such as a distributioncenter, where it is handled, stored, and picked as part of store orders. Items(the terms “product” and “item” are interchangeable) come in many differ-ent shapes, sizes, and weight, and thus have different handling characteris-tics. Some items are picked as full pallets (e.g., a pallet of 54 cases of motoroil), others are picked as individual cases (e.g., a 24-pack of 12-oz cans ofgreen beans packaged in a corrugated box), some items (e.g. fan belts,fuses, accessories) are picked and placed in a plastic tote (a containermeasuring 13 in. high × 23 1/2 in. long × 19 1/2 in. wide with a 2.6 cu ftcapacity), yet others are picked to a cart (e.g., a tire cart that can hold up to60 tires). Interventions that can either increase productivity and/or raiseaccuracy within the four walls of these facilities represent a tremendoussavings to the host company.

Order selection, that is, picking items for store orders, is the mostlabor-intensive, error-prone, and time-critical activity (Keeney, 1994). If anitem is picked that is not part of a store order—called a “mis-pick”—thereare very few corrective opportunities to fix the error once the incorrect itemis picked. A picking error represents a non-sale (an item the store did notorder), a lost sale (the store didn’t have the item in order to sell it), and lostlabor (a warehouse associate has to place the returned product back intostorage).

Recent studies (Berger & Ludwig, 2007; Ludwig & Goomas, 2007) havereported on the performance gains using voice technology in large indus-trial settings. In a “voice selection” system, the order selectors wear a battery-powered waist unit and a headset with an attached microphone that connectsvia radio frequency to a warehouse management system (WMS). The binlocations and quantities are spoken to selectors by the voice computer thatprompts selectors to walk (or drive, if on a motorized vehicle, such as apallet jack or a fork lift, depending on the handling characteristics of theitem) to a bin location and select a certain number of the product. They cancomply with these instructions without having to divert their eyes to view apaper order sheet or a hand-held computer. There are no pages of the ordersheet to turn, nor is there a belt holster needed to holster and unholster ahand-held computer.


28 D. T. Goomas

The selector hears a bin location, for example, “four four two seventwo one.” Upon hearing this prompt, he knows to look for the overheadplacard depicting aisle 44. There he will corner into aisle 44 and drive toBay 27, level 2, location 1. Selectors utter the “check digits” printed on anadhesive label affixed to the horizontal bar at the bin location. These checkdigits are used as a validity check to insure the order selector is standing infront of the correct bin location. For example, if the check digits are “21” hewill utter “‘two one.” The digits uttered are compared to the digits listed inthe computer databank for this bin location. If the correct check digits areuttered, that is “two one,” the unit states the ordered quantity (e.g., “selectthree”). This statement evokes the next behavior in the behavior sequence,namely for the selector to transfer three units (or cases) from the bin loca-tion into his tote (or pallet) used to collect product to fulfill the customerorder. The order selector utters “three,” thus informing the system that hepicked three units (or cases). If a selector speaks the wrong check digitswhile standing in front of a wrong location, the system responds by repeat-ing the correct bin location. Hence, a selector comes in contact with a con-sequence of his/her behavior immediately upon arriving at a bin location(the end of one behavior) but before engaging in the next behavior in thebehavior sequence (selecting the ordered quantity). Additionally, the voicetechnology will not present the number of units (or cases) to be selectedfrom the bin location until the correct check digits are spoken in the pres-ence of the correct bin location.

The Distribution Center Challenge: Tote Identification

At the host company, the voice technology order selection is done inconjunction with an adhesive label with a stamped bar-coded number,called a “license plate number,” each a unique number, placed on the lid ofeach tote (see Figure 1). Accurately identifying all store order totes via thelicense plate number was a prerequisite for the WMS to track each tote to

FIGURE 1 An adhesive label with the bar-coded license plate number “3C8491.”


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the correct sorting lane, door, route, and store, and to invoice the store. Theworkflow repeated by order selectors for each store order was as follows:

1. Order selector “signs in” to the voice system and work is transferredfrom the WMS to each selectors’ voice computer based on their assignedwork section within the facility.

2. Order selector retrieves an empty plastic tote from a tote dispenser andplaces the tote onto a handcart.

3. Order selector peels from a roll of tags an adhesive tag with a stampedlicense plate number (see Figure 1) and affixes it onto the lid of the tote.

4. Order selector utters “new container.”5. System prompts “container.”6. Selector utters the license plate number “three see eight four nine one.”7. System prompts “to receive work, say ‘ready.’”8. Order selector utters “ready.”9. Order selector hears the first/next bin location (e.g., “four four two

seven two one”).10. Order selector walks the handcart with the tote to the prompted loca-

tion (in this instance, aisle 44, bay 27, level 2, location 1).11. Order selector reads the posted check digits (in this instance, “21”) and

utters the digits (in this instance, “two one”).12. Voice unit prompts with the quantity to be picked, “pick three,” for

example.13. Order selector picks 3 units (or cases, depending on the product in the

bin) from the bin and places them inside the tote.14. Order selector utters “three.”15. Voice returns the workflow back to Step 9 for the next bin location in

the order until he hears “end of assignment.”16. At end of assignment, order selector seals the lid on the plastic tote and

places the tote onto a moving conveyor belt.17. Order selector continues the workflow back to Step 2 for more work.

Once on the conveyor belt, the tote enters an 8-lane automated sortingsystem where an overhead bar code reader scans the license plate and directsthe tote to one of the 8 staging lanes that correspond to 8 store orders. Anassociate then takes the totes from each staging lane, loads them onto a palletjack, drives the totes to the corresponding shipping door, and places the totesinside a waiting truck for subsequent delivery to the store(s).

Observations and feedback from inventory control managers indicatedthat incorrect utterances of the string of license plate digits in Step 6 werecausing totes to be misidentified. Let’s assume the order selector utters“three bee eight four nine one” for the license plate number in Figure 1. TheWMS records this tote as “3B8491.” At Step 16 the tote is sealed and placedon the moving conveyor. The overhead scanner scans the label “3C8491,”


30 D. T. Goomas

but because the order selector uttered “three bee eight four nine one,”identified in the WMS tables as “3B8491,” there is now a mismatch betweenthe bar code license plate number label on the tote, “3C8491,” and the iden-tification of the WMS of “3B8491.” As such, the automatic sorting systemplaces the tote in the penalty area of the sorting lanes. Unlike the bin loca-tion “check digit” verification, there was no verification that the license plateuttered was correct.

Given that the tote had no paperwork, as it had been voice-picked, theonly recourse was to put the contents of the tote, ranging from 30 to 80items, back into the bin locations they were picked from. In general, a mis-identified tote resulted in $500 in lost sales and 30 minutes to 1 hour for aninventory associate to put the product back into storage. On average, therewere two misidentified totes per day, or $1,000 in lost sales and $50 to $75in nonproductive time out of a daily total of approximately 700 totes. Thisamounted to more than $250,000 in annual lost sales.

The challenge, mandated by the Vice President of Distribution, was toimprove the tote identification process to reliably decrease the number ofmisidentified totes. Using technology available for the WMS, an interventionwas designed in the order selection process to insure that the license platenumber was always correct and provided the order selector with immediatefeedback. In addition, the solution had to be compatible with the workflowin that it did not disrupt the order selectors from performing their jobs. Thetechnology selected consisted of a stylus scanner that was configured toemit a “good read” beep and a “good read” light indicator when the bar-coded license plate number (Figure 1) was successfully scanned.

Using an intervention that provided auditory and visual feedback viascanning technology insured that the license plate had been scanned. A suc-cessful scan meant the license plate number was accurately input into theWMS. Thus the prediction was that the number of misidentified totes wouldreliably decrease.

METHOD

Participants

The intervention took place in two of the host company’s distributioncenters, one following the other. In distribution center A (DC-A), partici-pants were 16 order selectors at a regional distribution center in the south-west United States. Participant ages ranged from 22 to 39 years (M = 29.9)and all participants had worked at the facility about 2 months, as this was anewly started order selection distribution center. From the moment the distri-bution center started order selection, all order selectors used voice picking.There was no turnover amongst order selectors at DC-A during the study.The size of DC-A was approximately 600,000 sq ft. In the second distribution


Smart Wand 31

center (DC-B), a regional distribution center in the northeastern UnitedStates, there were 12 participants. Participant ages ranged from 21 to 43years (M = 25.2) and the participants had worked at the facility ranging from3 months to 2 1/2 years. There was no turnover at DC-B during the study.The size of DC-B was approximately 400,400 sq ft. All order selectorsworked 8 1/2 hour days, Sunday through Thursday. The company providedfor two 15-min paid breaks and a 30-min lunch.

Task

Order selectors used a stylus scanner (www.OpticonUSA.com) equippedwith a ballpoint tip, a small speaker, and a light indicator. The stylus wasconnected to the voice computer (see Figure 2). The stylus unit was pro-grammed with a series of bit-codes, as supplied by the manufacturer’sinstructions; it was also programmed to detect the bar code symbology,to emit a beep and a light, and to import the license plate number to theWMS (www.infor.com) for each successful scan of a bar-coded licenseplate.

As indicated earlier, prior to the introduction of the stylus the orderselector uttered “new container” (Step 4) and heard the system prompt “con-tainer” (Step 5), and the selector uttered the license plate number (Step 6).For the intervention, Step 6 was revised to where the order selector placedthe tip of the stylus 1/4 inch to 1/2 inch to the left or right of the bar code,tilted at a 35-degree angle, and moved the wand over the bar code withuniform speed, much like a scratch-off motion. If the bar code was success-fully scanned, the “good read” beep would sound and the “good read”

FIGURE 2 An order selector wearing the voice headset and grasping the stylus with her righthand for the purpose of scanning the tote tag held in her left hand.


32 D. T. Goomas

indicator light would appear. If not, the user reversed the scratch-off motionrepeatedly until the “good read” beep sounded and the “good read” lightappeared.

Seen below is the Step 6 workflow revision, along with the accompa-nying consequences:

From:• Selector uttered the license plate number:

• No feedback whether the utterance matched the bar-coded licenseplate number on the label (Figure 1);

• workflow continued to Step 7.To:• Selector scanned the license plate number with the stylus:

• Successful scan?• An indicator light appeared and a beep sounded and workflow continued

to Step 7.• Unsuccessful scan?• No light and no beep; workflow remained at Step 6 until successful

scan.

Meeting With the Order Selectors

One week prior to the intervention at the respective distribution center, theorder selectors were informed of the styluses during a shift meeting. Theorder selection supervisor, in addition to going over the shift notes (e.g.,“we have 15,000 units to pick today”) with the selectors, also held up thestylus and demonstrated several scanning motions with a tote label. The sty-lus and label were passed around for visual inspection and the selectorswere encouraged to “scan” the label.

The supervisor explained that “the scanners will improve accuracy ofthe license plate numbers and will reduce misidentified totes. Instead ofreading the license plate, you will scan it instead. If you successfully scanthe license plate you will hear a beep and a light will come on.”

Research Design

In both distribution centers the implementation of the stylus was done oneorder selector at a time until each order selector had the stylus programmedinto the voice system. This was the system requirement in the voice technol-ogy where the stylus could only be programmed into the workflow whenthe order selector heard “container” (Step 5). At that time a series of bit-codes were set by the experimenter, thus interfacing the stylus scanner withthe voice system.


Smart Wand 33

BASELINE

For DC-A there was a three-week baseline and for DC-B there was a one-week baseline. Baseline consisted of equipment setup, testing each stylus,and data collection of misidentified totes.

INTERVENTION

For DC-A there was a three-week period of observation following the intro-duction of the intervention, which replaced the utterance of the license platenumber in Step 6 with the stylus scanning the bar-coded license plate number.

In order to forego having all the order selectors congregating at theexperimenter’s workstation waiting on the bit-codes to be set, and thus neg-atively impacting the picking operation, an order selector was randomlyselected to have the new technology implemented. When the order selectorcompleted Step 5 he was instructed to stop any further work, walk to theexperimenter’s work station and have his/her voice unit programmed toaccept the stylus. Setting the bit-codes took about two to three minutes perselector. Once the bit-codes were set, the experimenter asked the orderselector to scan the bar-coded label at the experimenter’s work station tocomplete Step 6. Once the beep sounded and the light indicator appeared,the order selector was sent back to their warehouse section to continuetheir picking assignment. If there was no beep and no light, the order selec-tor was asked to rescan the bar code. Three to four hours later, all selectorswere using the new intervention. By the second day of the new technology,order selectors became proficient in achieving a successful scan of the barcode on the first stroking motion of the license plate number.

For DC-B, there was a one-week period of observation following theintroduction of the same intervention; again, this was done with one orderselector at a time. There was a two-week period between the conclusion ofDC-A and the start of DC-B.

Dependent Variable

The experimenter counted all misidentified totes that collected in the pen-alty area at the automated sorting lanes. A tote that collected in the penaltyarea was counted as one misidentified tote. A count was made at the begin-ning of the shift, and in two-hour increments until the end of the shift, for atotal of five counts each day. In order to ensure interobserver reliability, theexperimenter also sat in on the daily warehouse meetings where the inven-tory control manager’s report to the operations manager included the num-ber of misidentified totes. There was no difference in misidentified totecounts between the experimenter’s counts and the two inventory controlmanagers’ counts reported at their respective distribution centers.


34 D. T. Goomas

RESULTS

A typical daily total of picked totes averaged 450 at DC-A and 250 at DC-B.During baseline, there were a total of 22 misidentified totes, averaging 1.46totes per day (SD = 0.87) at DC-A, and 6 misidentified totes, averaging 1.20totes per day (SD = 0.63), at DC-B. After the intervention, there was a singlemisidentified tote on day 26 at DC-A (three-weeks postimplementationcounts) and none at DC-B (one-week postimplementation counts) on anestimated 3,500 totes that were picked, sorted, staged, shipped, and invoicedper work week (see Figure 3).

A t-test of correlated means on the same selectors indicates that replacingthe uttered license plate number with the stylus resulted in reliably fewer

FIGURE 3 Misidentified totes for DC-A and DC-B.


Smart Wand 35

misidentified totes (df = 14, t = 6.56, p < .001) for DC-A and DC-B (df = 4,t = 6.00, p < .005) as compared to the baseline.

Costs and Benefits

The cost of the intervention was approximately $30,000 ($24,000 in consultingfees + $2,000 in expenses + $3,680 spent on styluses and connector cords).

Decreasing the number of misidentified totes to practically zero meantincreasing store sales by approximately $250,000 annually. The savings tothe company the first year alone were approximately $220,000, with areturn on investment realized within two months following the intervention.The intervention continues to remain in place at both distribution centers.

DISCUSSION

Prior to the implementation, if the utterance of the license plate number didnot match the adhesive label’s bar-coded license plate number, it created amismatch between the WMS and the overhead scanner of the automatic sor-tation system. The tote ended up in the penalty area of the sorting lanes.Misidentified totes occurred nearly every day. When replaced by a stylusscanner programmed to emit a beep and a light upon a successful scan ofthe bar-coded license plate number, the number of misidentified totes reli-ably decreased. In the event the order selector did not properly scan thelicense plate number, neither the beep sounded nor did the indicator lightturn on. This would require the order selector to repeat his scanningmotion, much like a scratch-off motion, over the bar code until the beepsounded and the indicator light flashed. In general, the order selectors wereable to master the scanning motion of capturing the license plate bar codeafter three to four picking assignments.

After the implementation of the stylus, antecedents took on the form ofan auditory beep and a visual indicator light as feedback programmed intothe stylus informed the order selector that a license plate number had accu-rately been scanned. In a combined four weeks of postimplementationobservations and daily team meetings with the inventory control managersat both distribution centers, only one tote was misidentified. Given this onemisidentified tote, any explanation would be speculative.

The findings of this study showed how a relatively inexpensive inter-vention within a large industrial setting could be accomplished by retoolingpart of a workflow. However, caution is advised in that participants werenot randomly selected nor did the design include comparison groups orreversals or a multiple baseline design. A reversal would have meant remov-ing the styluses (and resetting the bit-codes) from the workforce for a periodof several days or several weeks, increasing the cost of the implementation.


36 D. T. Goomas

A multiple baseline design across subjects would have meant staggering theimplementation of the stylus over several days or several weeks, alsoincreasing the cost of the implementation. The resistance to the reversal ofpositive effects has been noted by Gaetani, Hoxeng, and Austin (1985). In afield setting such as this one, gains in realism may well offset concerns withinternal validity (Komaki & Goltz, 2001). When an intervention achieves theperformance improvements of the magnitude reported here, reversals arenot well tolerated by operations managers.

This field report is an example of how OBM can leverage technology inorder to deliver technical solutions to operational issues. A key concern wasthe type of equipment that would be used; in this case, deciding on whattype and size scanner to use. It was imperative that the selection of hard-ware did not interfere with the workflow of the order selection process. Forexample, using a hand-held scanner that included a grip to scan the licenseplate would have worked, except the hand-held unit would have requiredholstering and reholstering and would have slowed down the order selec-tion process. Another challenge was that the implementation (the stylus)was dependent on preexisting technology (voice) where the roll-out couldonly be done one order selector at a time. Suffice to say that OBM practiti-oners will be forever challenged to implement interventions that retrofitwithin the workflow of the workforce, in this case a large industrial settingthat can deliver immediate and accurate feedback in order to increase per-formance and drive up accuracy without negatively impacting or disruptingthe operation.

REFERENCES

Berger, S. M., & Ludwig, T. D. (2007). Voice assisted technology providing immediatefeedback to reduce employee errors. Journal of Organizational BehaviorManagement, 27(1), 1–31.

Gaetani, J. J., Hoxeng, D. D., & Austin, J. T. (1985). Engineering compensationsystems: Effects of commissioned versus wage payment. Journal of Organiza-tional Behavior Management, 7(1/2), 51–63.

Goomas, D. T., & Ludwig, T. D. (2007). Enhancing incentive programs with proxi-mal goals and immediate feedback: Engineered labor standards and technologyenhancements in stocker replenishment. Journal of Organizational BehaviorManagement, 27(1), 33–68.

Keeney, A., Jr. (1994). Personnel planning. In J. A. Tompkins & D. Harmelink(Eds.), The distribution management handbook (pp. 21.1–21.21). New York:McGraw-Hill.

Komaki, J. L., & Goltz, S. M. (2001). Within-group research designs: Going beyond pro-gram evaluation questions. In C. M. Johnson, W. K. Redmon, & T. C. Mawhinnery(Eds.), Handbook of organizational performance: Behavior analysis and man-agement (pp. 51–80). New York: Haworth.


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Ludwig, T. D., & Goomas, D. T. (2007). Performance, accuracy, data delivery, andfeedback methods in order selection: A comparison of voice, handheld andpaper technologies. Journal of Organizational Behavior Management, 27(1),69–107.


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