Voice-Enabling Your SAP Warehouse: Building the Business Case for Voice Technology
Introduction
Voice technology has great appeal for users of SAP who want to extend their logistics
and fulfillment processes. It offers the promise of hands-free, eyes-free wireless access
to the information needed to drive key warehouse processes and has become an
important ingredient in the success of a company’s IT strategy.
Before Voice, no other technology had a greater impact on the evolution of warehouse
management systems (WMSs) than the wireless local area network (LAN), and mobile or
Radio Frequency (RF) terminal. While they are popular with many organizations, RF
terminals and barcode scanning do have some drawbacks. They require operators to use
their hands to scan and key data. They also require operators to read instructions on
terminal displays. For many operations, these activities disrupt the normal flow of
warehousing and limit the benefits provided by the technology.
Despite these drawbacks, LANs and RF have provided the opportunity for many
distribution operations to substantially increase accuracy, productivity, visibility, and
control of core warehousing functions. In many ways, the integration of RF
communications and barcode scanning into WMS solutions in the 1990s put information
and data collection into the hands of warehouse floor personnel.
Like traditional RF-based barcode scanning terminals, Voice solutions center on a small,
wireless mobile computing device that warehouse associates typically wear on a belt. The
difference is that Voice delivers application instructions verbally through a headset and
captures worker responses through a microphone – with no stopping to look at a screen,
key in a quantity, or scan a barcode.
Voice Becomes Mainstream
Voice is not new to SAP users. But until recently, it has been more of a niche application
than a mainstream solution offering. This has changed as the technology has matured and
evolved and as SAP users have focused more on improving their logistics and fulfillment
processes. Voice technology now plays a major role within the warehouse and distribution
center for users of SAP and non-SAP systems.
The key drivers in this movement are:
Proliferation of Wireless LANs - Warehousing has been at the forefront of the
development of wireless LANs since the late 1980s. But early deployments of this
technology were costly, custom propositions. The evolution of 802.11 standards
propelled wireless LANs from custom to commonplace. Today, most top and midtier
distribution operations use RF terminals with barcode scanners over 2.4 GHz
wireless LANs. Voice logistics solutions can share this common backbone with traditional RF
scanning applications. Even operations that currently do not use RF scanning
terminals are not put off by the prospect of installing an 802.1 1x (a,b,g) wireless
network, since the technology has become commonplace in this increasingly
mobile society.
More Powerful Mobile Devices and Standardization - The processing power
of mobile computers and terminals has grown dramatically since the late 1990s.
This, coupled with the continued evolution of Microsoft’s family of mobile
operating systems, has allowed Voice vendors to offer powerful and robust
solution sets. The Windows-Embedded product line provides hardware and
software suppliers with a standard operating system to build upon.
More Vendors and Solutions - The number of vendors offering Voice logistics
solutions has steadily grown over the past few years. Voice logistics providers today
mostly team up with WMS vendors, offering a standard jointly developed direct
interface between the Voice vendor’s client software and the vendor’s WMS. The
VoiceDirect ERP for SAP WM and EWM from Vocollect is an example of such a
product offering. Under this paradigm, a WMS package can support Voice
functionality out-of-the-box, just like RF, with their Voice client communicating
directly with the WMS application. For the SAP user, the ability to directly interface
with the SAP Netweaver application integration layer adds another level of support
for seamless system to system integration.
Going Beyond Promises to Proven Potential
More choice, greater flexibility and a standard infrastructure – it is no wonder that interest
in this technology continues to grow. Voice now offers widely documented evidence of
improved performance and rapid return on investment. Trade journals, vendor product
literature, and web sites are full of customer case studies and client testimonials that make
a compelling business case for the technology. Anyone who has worked with the
technology knows that Voice has the potential to deliver on its promises.
But this does not mean that Voice is the right solution for every operation. While the
benefits reported by one organization may be enticing, they may be much more limited or
unobtainable for another operation. Also, implementation costs can vary significantly
depending upon legacy fulfillment or warehousing system, existing network infrastructure,
and operational requirements.
So how does Voice actually stack up in the warehouse? Are vendor claims about benefits
and quick ROI really valid? Obviously, the answers to these questions will vary based on
the nature of the operation considering the technology. As with any technology
investment, Voice implementation needs to be built on a solid business case in order to
truly succeed. The depth and components of this justification can vary across operations.
But it should always start with a thorough understanding of the operational and business
requirements.
It also needs to be based on a basic understanding of Voice’s:
• Typical usages and alternatives;
• Prospective benefits measured against the alternatives;
• Key technology components and application integration; and
• Cost factors and implementation approaches.
Building a solid business case may require a fair amount of effort beyond this basic
evaluation framework. Detailing benefits and costs to the extent necessary to adequately
determine ROI takes work. But even if initial findings indicate that Voice is currently not
practical for a specific operation, it will not be a wasted effort. While Voice may not be
justifiable today, it may well be viable tomorrow for certain organizations.
Typical Uses and Alternatives
Voice is typically employed to support tasks such as order selection, put-away,
replenishment and cycle counting within the warehouse. Industries with a high degree of
human touch, such as Grocery and Food and Beverage, were early to embrace Voice
technology. But, Voice has made significant inroads in other industry segments, including
Automotive and Service Parts, Personal Care, Office Supplies, Food Manufacturing,
Industrial/MRO Hard Goods Wholesale Distribution, Healthcare and Pharmaceuticals, and
Specialty Retail. Picking, or selection, remains a core focal point of interest for most Voice
applications, given its proportion of overall labor activity in the DC and its direct impact on
customer service levels. Typically, selection is the key component of establishing a
business case for Voice in the warehouse.
The most commonly cited Voice alternatives are paper/label processing, RF terminals
with barcode scanning, and pick-to-light.
Paper/label processing is typically coupled with after-the-fact data entry using
desktop terminals. Associates perform warehouse tasks off of pick lists, put-away
labels, printed VAS instructions, and other paper documents. Upstream processes
(such as how the information is sorted on the documents), and downstream
processes (such as scan and verify on a desktop terminal), directly impact
paper/label processing’s performance and functionality.
Paper/label processing is a good fit for many warehouses, especially smaller
operations with relatively straightforward transaction requirements. Even operations
that rely on RF scanning for the bulk of transactions usually employ paper/label
processing for some functions. It can be purely a manual proposition or part of an
automatic flow, such as a label case pick-to-belt, where the pick is confirmed by an
in-line conveyor scan.
RF scanning terminals have been considered a prerequisite for larger, more
complex operations. But RF scanning can be found in all different types and sizes of
operations primarily due to direct support by most warehouse management systems.
Even operations running non-RF enabled legacy fulfillment systems can turn to
automated data collection software for this functionality.
RF scanning offers some distinct advantages over paper/label processing. It can
provide positive verification that the warehouse associate is at the right location or
picked the correct SKU through a barcode scan or key entry. Work can be pushed
out to associates based on location and task priority instead of handed out from a
manually managed queue. Transaction data is captured in real time as associates
perform tasks. Furthermore, RF scanning makes some functions like multi-order cart
selection possible or more practical than paper/label processing.
Pick-to-Light (PTL) remains a popular selection technology due to its ability to
support high pick rates and its ease-of-use. It is typically used in a zone-based, pick
and pass flow where an associate scans a tote or carton barcode label. (The PTL
software activates light displays for every location that shows the required quantity
needed for the tote or carton.) The associate walks the zone, selecting SKUs and
confirming picks by pressing display buttons. Pick quantities can be shorted or
increased by button presses. Displays can also be provided to show SKU, order, or
other relevant information. Some vendors even have LCD displays that show SKU
pictures.
PTL technology has a number of different variations. Instead of a full quantity
display with confirmation buttons per location, a simple light indicator can be
provided for each pick face with quantity shown and confirmed on a bay display.
This configuration is generally employed in pick modules with slower moving
SKUs. The technology can be used to support put-to-light packing, in which an
associate scans a case barcode and the PTL software identifies all the staged
cartons that require the case’s SKU and associated quantity.
Some vendors offer PTL “smart” carts, meaning that totes or cartons are associated
with light-enabled cart slots. Associates push these carts through the pick module
based on the location shown on the cart’s light display. Once the location is
confirmed through a wireless barcode scan, the PTL software illuminates the
quantity needed for each slot requiring the SKU.
Also, as its name implies, PTL technology is about the order selection process.
Unlike the other technologies discussed in this paper, it is not employed to drive
other warehousing functions such as receiving, put-away, and cycle counting. This
means any investment in the technology cannot be leveraged beyond the confines
of the PTL module and order selection process.
There are many other data collection and material handling technologies that are used to
drive warehouse processes. But paper/label, RF, Voice, and PTL remain the most popular
selection technologies. This observation is borne out by a recent Supply Chain
Consortium survey (see .pdf for pictures). So it is no surprise that Voice vendors typically highlight
their wares against the other three pick methods.
Weighing the Potential Benefits of Voice
Vendors point to a variety of potential benefits for employing Voice within the
distribution center. They typically provide metrics for these improvements based on
actual case study data from their client base. Moreover, the quantitative benefits of
Voice and associated metrics have been well documented in numerous trade journal
articles and white papers.
These reported improvements or reductions are usually impressive, but must be
viewed within the context of before and after points. They must also be examined
against the nature of the operation, product being handled, and systems involved.
However, testimonials do provide a general indication of what Voice can do in the
warehouse.
Typical Vendor Data
While classifications and measurements may vary between case study and web site, they
fall along the following lines:
• Increased productivity and pick rates;
• Reduced errors and increased accuracy;
• Improved throughput and fill rate;
• Reduced supply costs;
• Improved control and visibility;
• Decreased training time;
• Improved safety;
• Reduced damage and breakage;
• Faster worker training; and
• Enhanced worker satisfaction.
Voice vendor web sites provide case study data quantifying many of these benefits,
especially productivity and accuracy gains. Reported productivity increases usually range
from 8-40%. Occasionally, higher increases may occur. Using RF scanning will see
higher productivity gains than with paper.
Most vendors report one or more customers who have at least doubled pick rates.
Generally, the featured operation for which the performance measurement is provided is
moving from paper or label-based selection to Voice, with a growing number of case
studies based on implementations replacing RF scanning or pick-to-light.
Accuracy rates typically cited in these case studies are at least 99.5%, with most reporting
higher rates. Corresponding reported reduction in pick error rates range from 80-100%.
Some studies detail significant cost savings in supplies (moving from label to Voice
selection) and increased fill rates due to reductions in miss-picks.
Figures for other benefits, such as improved safety and reduction in breakage, are also
obtained, but rarely used, in the justification and analysis effort. Given Voice’s handsfree
and heads-up processing flow, these benefits make intuitive sense. Vendors
generally showcase customers who obtained an investment payback within 9 to 12
months.
Voice appears to be an attractive investment proposition in the warehouse. But are the
numbers realistic for a specific operation? While there is no reason to doubt the numbers,
they must be viewed in the context of the starting point and processes involved.
Measuring Gains in Productivity and Accuracy
Potential productivity gains can be quite significant for an operation moving from paper
to Voice. In general, these gains are due to a number of factors beyond the hands-free
flow of Voice, including:
• Changes in pick process, such as moving from discrete order selection, using paper
pick lists to multi-order cart selection, and using functionality provided by the Voice
application software;
• Reduction in personnel needed for post-pick checking, packing, and auditing, due to
positive pick verification of Voice over paper picks; and
• Real-time information on inventory levels, order status and picker transaction
rates provided by the Voice application software.
Depending on the functionality provided by the underlying software, the above factors
generally do not play a significant role when comparing RF Scanning to Voice. From a
productivity perspective, the comparison between the two pick methods centers more on
the hands-free nature of Voice.
The Tompkins Associates White Paper, Order Selection for the 21st Century, Voice vs.
Scanning Technology, documents an implementation of the Vocollect Voice solution at
Associated Wholesale Grocers (AWG). The implementation covered five pick areas:
dairy, dry, freezer, meat, and perishables.
Figure 2 (in .pdf version) shows the productivity gains after Vocollect Voice was installed. The two areas,
dry and freezer, which were previously supported by a paper-based process, experienced
modest gains. The areas previously supported by RF scanning saw much higher
increases. This is not surprising, because RF scanning can be more disruptive to selection
flow, since it typically requires the user to scan or enter information at multiple points.
Equally understandable are the higher gains in the refrigerated meat and dairy areas, where RF
scanning terminals can be more difficult to handle.
While the relatively modest gain in selection productivity for Voice over paper may be
expected, other factors should be considered when comparing paper to other selection
technologies. Paper generally requires post-pick data entry, either at a packing or clerical
key entry.
Overall productivity gains of moving off of paper need to account for reduction in these
efforts. Since picks are not systematically verified as each line is processed, errors are
more likely to occur; correcting these errors requires additional labor. Paper also requires
manual management that covers preparation, assignment, and post-pick processing. This
all entails additional direct and indirect labor that should be considered when quantifying
prospective labor productivity gains.
Voice versus RF scanning comparisons should also account for the different types of the
RF scanning devices, generally categorized as handheld, wearable, or truck mounted.
Handheld terminals typically require users to holster or set the device down during certain
steps in a process. This can add to the overall time to complete a transaction. Wearable
units are worn on arms or attached to belts. These lightweight devices capture barcode data
through “ring” scanners worn on the index finger. Truck mount units are mounted on
material handling equipment such as reach- and order-picker trucks and motorized pallet
jacks. Truck mounted devices generally capture barcode data through tethered scanners.
While wearable and truck mounted units do not require users to pick up or lay down the
device, warehouse associates still must read the display and key data at certain steps in a
process, potentially slowing down the overall transaction time.
Pick-to-light vendor web sites also claim similar benefits for their light-based solutions.
As with Voice, productivity and accuracy are typically the cornerstones of any pick-tolight
business case. Some vendor web sites cite four- or five-fold productivity
improvements over paper-based selection, with individual pick rates approaching 450 lines
per hour. While these numbers may seem high, pick-to-light is generally acknowledged as
providing the highest pick rate potential of the four selection technologies when pick
densities are relatively high.
Some sources assert that Voice provides a greater accuracy potential than RF scanning and
pick-to-light. All three technologies can provide significantly lower pick errors than paper,
since they all require positive real-time confirmation of the pick. However, some studies
report lower error rates with Voice than the other two methods, due to the freeing of hands
and eyes from data entry steps.
RF scanning does require the picker to break the flow of the process to perform scans, read
displays, and key quantities. Arguably, these breaks in flow can interject errors into the
process. But pick-to-light only requires the push of a button to verify the pick. The actual
speed of pick-to-light may generate slightly higher error rates than Voice in certain
situations, as pickers may concentrate too much on speed at the expense of paying attention
to the pick task at hand.
Quantifying Benefits
Case studies can provide a good general indication of the potential of Voice. But they
tell stories for specific operations, making them less applicable to any individual
distribution center. The potential fit of Voice or any other selection technology is
dependent on a variety of underlying factors, including:
• Order profile – lines per order and units per lines;
• SKU weight and size;
• Pick container weight and size;
• Travel distance between picks;
• Pick line layout and product accessibility;
• Special data capture requirements such as lot, batch, serial number, or catch weight;
• Workforce composition, including percentage of temporary workers;
• Growth potential and need for flexibility; and
• Functionality of the supporting software application.
Since these factors can vary across operations, building a business case for Voice on the
benefits obtained at other sites can be risky. Benefits can certainly be quantified by
conducting pilot tests. On the other hand, pilot programs are generally costly and
impractical. This leaves two viable alternatives when quantifying benefits: 1) Using case
study data and assumptions or 2) Developing engineer-based analysis of anticipated gains.
Case Study Data - Certainly the risk involved in using case study data and
generalized assumptions to quantify benefits is a function of how much the target
operation differs from the case study operations or falls outside of the “norm” that is
the basis for the general assumption. For many operations contemplating Voice, this
should be a perfectly acceptable risk, especially if conservative numbers are used.
Using 10-12% as the anticipated labor productivity increase in moving from paper
or RF scanning to Voice is generally a good rule of thumb. But it does not account
for variances in operational flow, layout, product, personnel, and legacy systems.
Engineer-based Analysis - Quantifying potential benefits through an engineerbased
analysis can account for these variances. This approach breaks down the
elemental processes and steps for current and prospective processes. It can probably
be best appreciated in the context of developing expected pick rates from
predetermined elemental tasks and associated time. Employing this approach for
quantifying potential pick rates allows for comparisons between technologies and
process flows, as well as accounts for variations in the above factors, if properly
done. It is a method requiring specific skill sets in order to produce reliable results
and is generally performed by an industrial engineer.
Figure 3 (in .pdf version) shows an example of the results of a predetermined time element analysis
performed for a Tompkins client. It summarizes anticipated case pick rates in cases per
hour between paper, RF scanning, and Voice in a refrigerated pick module. Detailed
analysis for Voice selection appears in Figure 4 (in .pdf version). The analysis was developed using time
sampling of existing paper-based pick processes, as well as elemental step evaluation for
the potential use of RF scanning and Voice. The results show pick rate increases of 6%
and 12%, respectively, for moving from paper and RF scanning to Voice.
Figure 5 (in .pdf version) shows an example in which pick-to-light and Voice were analyzed for different
pick modules and order types. The software solution being evaluated for this operation
provided pick-to-light, RF scanning, and Voice selection functionality. The summary
results in Figure 5 show that pick-to-light provides a significantly high pick rate for store
orders, especially in the carton flow module. But Voice and pick-to-light have compatible
pick rates for service orders in shelving. These rates were incorporated into a cost-benefits
analysis that recommended deployment of both technologies in separate pick modules.
Pick-to-light presents some fit challenges that go beyond pick rates and raw productivity
numbers. It is an inherently more costly and complex technology that typically requires a
significantly higher start-up investment and a relatively rigid product flow. Totes and
cartons are generally routed between fixed pick zones via a conveyor system. Managing
workflow can be an ongoing issue, because of daily workload fluctuations between zones
that result in bottlenecks in some and under-utilization in others.
Voice offers much more flexibility to redeploy resources to match daily changes in
overall workload on the warehouse floor. Furthermore, changing the configuration of a
pick-to-light module can require additional changes to the light displays, communications
backbone, and pick-to-light software as well as physical storage media and WMS
changes. Reconfiguring pick modules supported by Voice is a much simpler proposition
that generally only requires labeling in addition to storage media and WMS changes.
An engineering-based approach can be used to quantify other benefits. However,
assumptions may have to be made in certain situations. In this case, sensitivity analysis
can gauge the impact of varying these assumptions on the results. Knowing how the
software application truly functions is critical to quantifying realistic benefits. It may also
factor in the cost portion of the analysis in the event that software modifications are
required. Appreciation of how Voice application software performs for any specific
operations starts with a general understanding of its key technology components and
integration to warehouse systems.
Technology Components & Application Integration
For the most part, Voice logistics solutions share a common hardware and software
architecture approach. SAP users are the major exception. The exception is because SAP
users’ IT integration infrastructure is comprised of SAP’s Netweaver middleware layer.
SAP Netweaver is the main approach systems integrators use to design and author
additional system integration between inventory, order management and warehouse
functionality.
For many operations, Voice can be approached as a shrink-wrapped application in which
vendor quoted costs and performance will typically match the results experienced. Once
again, the SAP user is an anomaly. This is because each and every SAP user has a unique
configuration, and thus, a one size fits all interface may not maximize the existing SAP IT
investment.
Making assumptions about how Voice works (or any other data collection technology) in
any particular situation – based either on generalizations or how the solution performs at
other operations – creates the risk of unexpected and potentially unpleasant results during
implementation. Organizations can minimize this risk by taking the time and effort to
understand Voice’s basic components and how it interacts with other warehouse systems.
In many ways, Voice employs a similar technology infrastructure as RF scanning. It is a
distributed technology that uses an 802.1 1x standard wireless LAN that supports
communications between client mobile computers and backend servers. The mobile
devices typically employ the Windows CE operating system. Client software running on
these devices manages data presentation and input services, which in the case of Voice
means speech recognition and text-to-speech functionality. Servers provide business
application and database functionality, as well as Voice client administration.
Client Components
Within this distributed framework, Voice solutions can vary significantly in how these
components function both from the client and server perspective. Client speech
recognition components are either speaker-dependent or speaker-independent. Speakerdependent
requires users to train the system to recognize the specific nuances of their
voices. This process involves the system prompting the user to repeat digits and terms.
Individual voice templates are stored on a management server and downloaded to the
mobile devices as needed. Generally, it takes 15-20 minutes for a user to create his/her
voice template. During this time, the user is also trained on how to actual use the new
voice device. It is recommended that this ‘training time’ be fully leveraged against each
associate with his or her new mobile device and headset.
The speaker-independent approach does not require the user to train the system on
specific nuances to their voice, but still requires the same approximate user training
time. This is the method employed by voice-enabled telephone customer service
applications, in which callers respond verbally to system prompts. Most Voice
vendors support only one approach.
Those offering a speaker-dependent solution generally claim that the speakerindependent
approach is not as dependable in recognizing responses in the relatively
noisy environment of most warehouses. Also, the speaker-independent method can
be challenged by regional dialect variances. Other factors such as headset quality
can impact Voice performance and reliability in the warehouse.
Voice recognition works best in the warehouse when user responses are limited to short
distinct phrases and digits. Location verification is generally done by repeating three-digit
numeric check digits associated with each location. Lengthy responses can present
challenges, both from recognition and performance perspectives. Voice may be an
excellent tool for capturing check weights, but barcode scanning may be a better choice for
recording serial numbers.
Voice solutions can also vary in how their client software interacts with backend
application servers. Most employ operation specific programs or task files that are
downloaded to the voice-enabled devices. Communication between the client and
application servers is controlled by these code sets, as well as support for client-side
functional processing.
Some Voice solutions use a model that dispenses with client-side voice-specific application
code. These solutions treat voice as another input/output stream, no different than text
displayed or entered on a handheld computer. Input and output mapping is handled by
server-based processes. Client-based software handles the local presentation and data
capture functions. Performance factors and application integration typically govern which
approach is employed.
SAP Server Components
Voice clients communicate with backend servers for application processing and database
services. While some functionality may reside on client devices, most data validation and
processing logic occur on application servers. For SAP users, Netweaver is the integration
layer that supports virtually all integration between data components, such as WMS,
inventory management or order management.
Direct Interface, Standalone Approach or Netweaver Direct Interface
There are three basic approaches for integrating Voice: direct interface, standalone
application or Direct Netweaver interface. Under direct interface, client software
exchanges information in real time directly with the WMS or ERP. This is done through
a predefined set of application programming interfaces or service messages that each
side can use to send or receive data from the other side. A number of Voice vendors
facilitate this approach by publishing a standard library of message transactions. While
most top-tier WMS solutions support a direct Voice interface, many WMS packages do
not. Moreover, WMS vendors that support a direct interface typically only do so for a
single Voice vendor. For SAP, the preferred approach is a direct interface to Netweaver.
Most Voice vendors provide standalone application software capable of supporting core
warehousing operations much like a lower-end WMS package. Order and inventory data
is downloaded from the higher level host system. All transaction processing occurs on
the standalone application, with resulting pick confirmation and inventory data uploaded
to the host system. This approach provides the potential for WMS integration through a
relatively limited set of interface points. For example, selection demand can be
downloaded upon waving and selection responses uploaded after the transaction has
been completed.
Building this batch-like interface may be more economical in certain situations than
constructing a real-time direct interface. Furthermore, it allows operations using order or
inventory management systems to take advantage of warehousing functionality that may
be unavailable in their legacy systems. For example, implementing a Voice standalone
application may allow an operation to move away from discrete order selection to a more
efficient zone, batch, or multiple order selection process.
A direct interface is more attractive from a cost and performance basis if it is already
supported by the WMS vendor. These interfaces provide “out-of-the-box” Voice
functionality that requires no additional programming or development – provided the
functionality meets the specific requirements of an operation. Generally, this is the case.
But in certain situations, both Voice client and WMS must be modified to meet
requirements. Care should be taken when comparing specific requirements to the base
Voice functionality supported by a WMS vendor. It should never be taken for granted that
WMS Voice and RF scanning functionality work exactly the same.
The direct Netweaver interface is preferred by SAP users who already have teams trained
and educated on Netweaver. The other main advantage of this approach is that the SAP
specific skills can be leveraged to rapidly create and support the Voice interface. Figure 6 (in .pdf version)
below, provided by Vocollect, is an example of a vendor’s approach to offer a direct SAP
Netweaver interface alternative.
This approach uses the SAP Internet Transaction Server (SAP ITS) to connect Vocollect
VoiceDirect ERP applications to the SAP infrastructure. The SAP ITS is integrated into the
kernel of the SAP Netweaver Application Server. SAP ITS presents SAP WM or EWM data
in the form of HTML templates and pages to a Java-based Protocol Translator (PT).
The SAP ITS has been designed by SAP to extend business applications to a web browser
or the Internet, by converting SAP Dynpro screens into HTML format. SAP ITS provides
web access for several SAP products including the SAP ERP and SAP Supplier
Relationship Management (SRM). As part of the Vocollect VoiceDirect ERP solution, the
mobile RF screens of SAP WM (i.e., LM05 and LM45) have been voice-enabled. HTML
templates have been generated for these screens with voice tags to allow the Protocol
Translator to read and translate the complete process flow.
Conclusion: Moving Forward with Voice
Voice is not for every distribution center or warehouse. However, the benefits cited in
numerous Voice case studies are real and may be obtainable for any individual operation.
Voice has moved beyond cutting edge to become an established warehouse technology.
Any distribution operation concerned with improving productivity, accuracy, and
throughput should give the technology serious consideration.
This should start with the realization that Voice is not a mutually exclusive proposition in
the warehouse. Many operations that use Voice employ other technologies such as RF
scanning and pick-to-light. What it boils down to is selecting the right tool for the job.
Managers of distribution operations need to approach any process or system improvement
project from this perspective. Voice is merely one of the technology tools to be considered,
and developing a sound business case that looks across available tools is a necessary first
step.
Building a business case for Voice or any other technology in the warehouse requires
careful delineation and quantification of benefits and costs. It entails an ability to detail
current processes and requirements, map how these processes will change, and plan how
requirements will be supported using the new technology. Some key factors to keep in
mind when evaluating Voice for a particular warehouse operations are:
Keep the proper goal in mind – The objective of any evaluation is not to figure
out how to get Voice into the warehouse. It is about selecting the best tool for the
job.
Employ an evaluation approach appropriate to the situation – The details and
depth needed for a successful evaluation are dependent on the current operation
and systems. For example, an operation already using a WMS solution may want
to consider using the package’s direct Voice interface in a particular pick module
that is currently supported by RF scanning. Costs, application, and integration
components in this situation are much more concise than a paper-based operation
without a WMS that is being compelled to significantly expand its capacity. The
former may be able to get a relatively high-level review, but the latter needs a
comprehensive analysis.
Do your homework – Operations managers do not need to become experts in the
technology to consider its use. However, anyone evaluating Voice needs to know
enough about its usage, alternatives, benefits, components, cost structure, and
integration to make an informed decision. While Voice and WMS vendors can
provide guidance and support in developing a business case, any organization
contemplating the technology must be prepared to critically challenge its
applicability within its distribution center.
Put together the right team – Evaluating, implementing, and using Voice are
multidisciplinary propositions. The success of any Voice evaluation project is
contingent on putting together a cross-functional team that represents
management, operations, and IT. Since it may entail a significant investment,
finance may also be needed to help frame the business case approach. If adequate
internal resources are not available or the evaluation is inherently complex,
consider retaining the services of a third-party consultant.
Be realistic and above board – The ability to adequately state benefits and costs
is the crux to any successful evaluation of a technology or system in the
warehouse. However, assumptions and estimates are an inherent component of
even the most structured evaluation process. No mater how scrupulous an
organization is in its process, there is always the potential of some unknown factor
compromising the end results. Some operations respond to this risk by being
conservative on benefits and factoring in a contingency line item on costs. Others
bracket minimum, expected, and optimistic savings/gains by benefit. Regardless
of the approach employed, any operation evaluating the technology needs to
occasionally step back and question whether the numbers being employed are
realistic.
Treat your business case as living document - Be prepared to live by the
business case you develop. Track its performance during implementation and
beyond go-live. Measure whether the anticipated ROI was achieved in projected
timeframe. Many organizations do not perform post go-live assessments of their
systems projects for a variety of reasons. This is wrong. Even if a project has
missed its mark, knowing the root causes for the situation can present an
opportunity to change course.
The expansion of interest in Voice is not a fluke or hype. Voice has a real role to play
within the warehouse and rapidly has become a mainstream technology. While it may not be
viable in the near or even long term for many operations, many others stand to gain from its
employment. The first step in this process is determining how it stacks up within the
warehouse. Given the evolutionary aspect of Voice technology and applications, this is not a
static proposition. If the technology is not a good fit today, it may be eminently viable
tomorrow.
Contact Information
Tom Singer, Principal
Tompkins Associates
tsinger@tompkinsinc.com
About Tompkins Associates
Tompkins Associates transforms supply chains for profitable growth. An industry leader for
more than 30 years, Tompkins designs and integrates value-based, end-to-end supply chain
solutions that encompass growth and business strategy, global supply chain services,
distribution operations, information technology, material handling integration, and
benchmarking and best practices. The company is headquartered in Raleigh, NC. For more
information, visit www.tompkinsinc.com.
References
Tompkins’ Supply Chain Consortium is the premier source for supply chain benchmarking
and best practices knowledge. With more than 300 participating retail, manufacturing and
wholesale/distribution companies, the Consortium sponsors a comprehensive repository of
17,000-plus benchmarks complemented by search capabilities, online analysis tools, topic
forums and peer networking for supply chain executives and practitioners. The Consortium is
led by the needs of its membership and an Advisory Board that includes executives from
Campbell Soup Company, Hallmark Cards, Hewlett Packard, Ingram Micro, Kraft Foods,
Miller-Coors, The Coca-Cola Company, Target, and True Value Hardware. To learn more about
how your company can become a member of the Supply Chain Consortium, contact John Foley,
919-855-5461 or visit www.supplychainconsortium.com.