Strategic Information Management Third Edition Challenges and Strategies in Managing Information Systems_14 pot

Information Systems and Organizational Learning 545During system development, knowledge application took a different formbecause the object of the activity was so different.. Information

Information Systems and Organizational Learning 545

During system development, knowledge application took a different formbecause the object of the activity was so different Rather than producingenergy audits directly, the programmers were responsible for producingsoftware to produce energy audits As mentioned above, the knowledge andartifacts necessary to accomplish this task were quite different than thoseneeded to produce an energy audit But perhaps more important, the criteriafor successful application were different, as well, because the software had toproduce reasonable results over a wide range of different input data, while amanual audit was specific to a given set of facts about a particular building

A successful implementation required, in some sense, a higher standard ofperformance than an individual audit because it had to handle a broader range

of cases As with manual audits, the responsibility for actually implementingconservation recommendations rested with building owners

Automated auditing brought yet another regime of knowledge application.Applying the algorithms embodied in the EnCAP program required a differentset of skills, as described above Technicians needed to know how to identifyequipment and possible improvements, and then the program would take overand complete the computations and the details of the recommendation Asmentioned above, technicians often used tricks to get results they wanted from

a program they did not fully understand The end result (a completed auditreport) was similar in form and content to the manual audit reports, but theapplication of technical knowledge about commercial buildings occurredthrough a very different process This difference was a natural product ofusing an automated tool rather than performing the computations andproducing the audit report manually

Discussion

To help the reader evaluate the strengths and weaknesses of the knowledgesystem framework, it is useful to compare it with some of the main themes inthe large and growing literature on organizational learning Rather thanattempting to review and synthesize all of this literature here, it is more useful

to extract certain key dimensions for purposes of comparison Table 18.2outlines four key themes in the organizational learning literature and theirinterpretation in the knowledge system framework Each of these themes isdiscussed in more detail later

Locus of learning: Individual versus organization

The literature on organizational learning generally distinguishes betweenindividual and organizational learning (e.g., Argote, 1993; Carley, 1992; Fioland Lyles, 1985; Hedberg, 1981; Levitt and March, 1988) Some authors (e.g.,March and Olson, 1976; Nonaka, 1994) make the relationship betweenindividual and organizational learning explicit, while others tend to focus onthe organization as the unit of analysis (Lant and Mezias, 1992) In contrast,the knowledge system framework downplays the importance of individuallearning in favor of an explicitly social conception of knowledge What asingle individual ‘knows,’ in short, is of little value to anyone until it has beensocially ratified in some way The position is similar to that of Attewell (1992,

p 6), who argues that: ‘The organization learns only insofar as individualskills and insights become embodied in organizational routines, practices, andbeliefs that outlast the presence of the originating individual.’

Certain individuals, such as higher level managers, may hold sufficientauthority within the organization to dictate and enforce the legitimacy of theirown beliefs Legitimation and authority are obviously essential aspects ofknowledge construction (Latour, 1987) and may be influential in theorganizational learning effects associated with executive succession (Virany,Tushman, and Romanelli, 1992) This perspective helps call attention to theexplicitly social dimension of knowledge distribution, as well For example,Pentland’s (1992) study of software support hot lines revealed that solvingcustomer problems depended on the ability to distribute knowledge among thegroup (e.g., by getting help) Socially enacted knowledge distributionprocesses allowed members of the organization to collectively solve a stream

of problems that no individual could have solved alone It is reasonable to

Table 18.2 Themes in Organizational Learning Literature

failures of storage of distribution, as well aschanging relevance

Information Systems and Organizational Learning 547

hypothesize that in situations where specialized knowledge is unevenlydistributed, enhancing distribution processes (for example, via email) would

be an effective means of improving organizational performance

In the EnerSave case, before automation, there were many instances where

a single engineer would learn about a new kind of system (for example, a newkind of boiler) and share it with others Until shared, however, it is hard toimagine calling that engineer’s learning organizational After automation,individual learning had to be filtered through a software maintenance routine(designing a new feature, coding and testing) to make the new learningavailable to the organization Although I cannot document it, I find it unlikelythat field personnel outside the main office would have been able to initiatesuch learning Thus, the locus or organizational learning that could enter theknowledge system was probably narrower by automation

Levels of learning: Operational or strategic

The level or kind of learning is another key theme in the organizationallearning literature Argyris and Schon’s (1978) influential distinction betweensingle- and double-loop learning can also be thought of in terms of operationaland strategic learning Lant and Mezias (1992) make a similar distinction,labeling the levels ‘first order’ and ‘second order.’ Single-loop learninginvolves the adjustments necessary to meet a given operational objective, as

in the way a thermostat cycles a furnace on and off to hold the temperature inthe room Double-loop learning, however, involves deciding what thetemperature should be It is conceived of as a higher, more strategic level oflearning because it concerns the definition of goals Argyris and Schon (1978)argue that so-called ‘higher’ levels of learning involve challenging assump-tions and standard procedures

In terms of the knowledge system framework, the main difference betweenthese levels of learning is the content of the knowledge being constructed,organized, stored, and so on One might hypothesize that these processesmight take different forms for operational or strategic knowledge, but theframework itself is indifferent In the EnerSave case, as I saw it, the learningwas primarily operational One can assume that there must have been aparallel change in strategic knowledge over time as the firm moved from oneline of business to another, and one kind of client to another But even withinthe domain of operational knowledge, the shift in content was striking

Source of learning: Experience or example

Broadly speaking, the learning literature points to two distinct sources oflearning: experience and example Learning from experience reflects the usualstrategies of trial and error, successive approximation, and so on Following

the analogy to individual learning, models of learning by experience are oftenbuilt at the organizational level (e.g., Lant and Mezias, 1992) Researchershave also identified the ways in which organizations learn from very limitedexperience, where there is no opportunity to improve based on repeated trials(March, Sproull, and Tamuz, 1991) Often, this entails the use of vicariousexperience, or stories about others’ experiences Alternatively, it may be theproduct of systematic transfer between subunits (Argote, Beckman, andEpple, 1990) While the distinction between experience and example can beformalized and estimated statistically (Epple, Argote, and Devadas, 1991), thedistinction is less clear than it might seem because it depends on the definition

of the organizational boundary That is, examples generated within theboundary (which may be drawn socially, geographically, temporally, or insome other manner) are counted as ‘experience,’ while examples generatedelsewhere are not

Within the knowledge system framework, the distinction between learning

by experience and learning by example closely parallels the distinctionbetween knowledge construction and knowledge distribution Memberstesting the value of their own experiences would be constructing knowledge,while members testing the value of others’ examples could be seen asengaging in knowledge distribution Given the potential subtlety of some ofthese distinctions, it seems like it might be difficult to sustain the analyticaldistinction between construction and distribution Within a particularknowledge system, the process of knowledge construction can draw upon avariety of sources, including members’ experiences and observations ofothers Thus, in practice, it is not clear how important this distinction wouldreally be Construction and distribution have very similar effects: they makeknowledge available where it previously was not

At EnerSave, before and after automation, learning was primarily byexperience To my knowledge, they spent very little time assessing oranalyzing how other organizations performed similar work While there weremany firms offering automated residential audits, there were very few firmscapable of producing an automated audit for commercial buildings Thus, withrespect to their core operations, there were few examples to learn from

Persistence of learning: Short or long term

Empirical studies of organizational learning (Argote, Beckman, and Epple,1990; Darr, Argote, and Epple, forthcoming) have shown that whileorganizations learn, they also forget A significant component in this loss of

knowledge can be attributed to turnover in personnel (Carley, 1992; Darr et al., forthcoming) These studies have also shown that recent experiences are

more valuable than older ones Part of this effect is due to the changing nature

of the environment; old skills and information may not be equally useful in the

Information Systems and Organizational Learning 549

face of changing conditions Knowledge becomes obsolete Hedberg (1981)postulated the existence of forgetting processes and the critical importance ofreplacing outdated knowledge More generally, there has been an increasedinterest in organizational memory (Walsh and Ungson, 1991) and inmechanisms to enhance it (Ackerman, 1993)

Questions of persistence or memory have a natural interpretation within theknowledge system framework The storage and distribution processes arecritical in maintaining the availability of knowledge to members Failures ineither of those processes could be viewed as forms of forgetting In effect, theorganization either cannot store or cannot access relevant knowledge Theproblem of changing relevance, however, could be viewed more as a failure

in application When old methods are tried and no longer work, then it is thefinal link in the chain of knowledge processes that has broken

At EnerSave, the use of software for storage and distribution hadpredictable effects: persistence was excellent, but continuing relevance couldnot be guaranteed Software is an excellent vehicle for storage and distribution(and thus for long-term memory), but it tends to suffer from the problem ofchanging relevance for just that reason The basic engineering computationsgenerally retained their validity, but many of the ‘rules of thumb’ depended onassumptions about standard construction techniques, typical system effi-ciencies, and so on These factors differ from region to region, and they tend

to change over time Thus, as the context of use changed, these assumptionsneeded to be surfaced, examined and, if necessary, changed In short, thesoftware required maintenance

It would be a mistake, of course, to generalize too broadly from thisexample The information system described here was specifically designed

to embody technical knowledge and automate key aspects of a job that wasgenerally performed by engineers In many respects, the results reportedhere are understandable by-products of automating the work: the peopledoing the work were no longer in a position to fully comprehend or modifythe tool they were using Zuboff (1988) makes similar points concerning thework in the organizations she studied In the extreme case, the very tool thatwas intended to encode the knowledge of the organization could havedestroyed the organization’s capacity to learn by interfering with variousknowledge processes As it turns out, in this particular case, EnerSaveseems to have maintained a strong engineering base (by diversifying intoother areas besides auditing), and has maintained a strong connection tothe larger knowledge system concerning energy use in commercialbuildings

Nonetheless, this example illustrates clearly that introducing an tion system can have more profound effects than merely altering the storage,

informa-or retrieval, informa-or distribution, informa-or richness, of infinforma-ormation These basicinformation processing enhancements are well known and should, in theory,affect organizational learning But I would argue that information systemscan also change the membership of an organization, the objects of itsknowledge, and its criteria for truth These are the basic elements of socialepistemology; they are the core of any social knowledge system They areheld constant in most treatments of organizational learning, thus obscuringthe possibility that information systems might change them Whether or notall of these elements belong under the umbrella of ‘organizational learning,’information systems can change them In doing so, information systemschange the fabric of social epistemology and the backdrop against whichorganizations construct, organize, store, distribute, and apply knowledge.More broadly, the example suggests a kind of technological epistemology,where our ways of knowing are mediated through machines and theirmaintenance Should we be satisfied with a knowledge system wheredebugging and finding workarounds are a dominant mode of learning? Tothe extent that we view the world through a technological lens (Barrett,1979; Heidegger, 1962), this problem becomes increasingly important.Ironically, technology may dull our senses, taking away the direct involve-ment, social interaction, and reflective conversation that has traditionallygiven rise to understanding (Rorty, 1979) The very systems that are meant

to increase our information processing capabilities, thereby increasingunderstanding, may have the opposite effect by restricting the range of ourinquiry and experience, effectively putting us in a kind of epistemologicalbox Whether information systems enhance or dull our senses is a difficultquestion to answer, but it is clearly an important question to ask

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Questions for discussion

1 To what extent is the EnCAP system considered in this chapter aknowledge management system as opposed to a typical IT-basedinformation system?

2 Compare and contrast the approaches adopted by Leidner in Chapter 17and Pentland in this chapter What do you conclude from thiscomparison?

3 Pentland refers to the work of Lave (1988) and Brown and Duguid (1991)

on what the latter term ‘communities of practice’ To what extent is ituseful (or not) to consider IT professionals in an organization ahomogeneous community of practice? Relate your discussion back to thematerial introduced in Chapter 10

4 To what extent might so-called knowledge management systems restrict

rather than enhance organizational learning? Draw on case examplesintroduced in this book and on your own experiences when discussing thisquestion

5 ‘Knowledge management systems are like “old wine in new bottles”.’Discuss

6 What ideas introduced thus far in the book and in this chapter in particularmight aid organizational learning?

19 Information Technology and

Customer Service

Redesigning the customer

support process for the

electronic economy: insights

from storage dimensions

O A El Sawy and G Bowles

This chapter provides insights for redesigning IT-enabled customer supportprocesses to meet the demanding requirements of the emerging electroniceconomy in which fast response, shared knowledge creation, and inter-networked technologies are the dynamic enables of success The chapterdescribes the implementation of the TechConnect support system at StorageDimensions, a manufacturer of high-availability computer storage systemproducts TechConnect is a unique IT infrastructure for problem resolutionthat includes a customer support knowledge base whose structure isdynamically updated based on adaptive learning through customer inter-actions The chapter assesses the impacts of TechConnect and its value increating a learning organization It then draws insights for redesigningknowledge-creating customer support processes for the business conditions ofthe electronic economy

Effective customer support in the electronic economy

Effective customer support and service has become a strategic imperative.Whether a company is in manufacturing or in services, what is increasinglymaking a competitive difference is the customer support and service that is builtinto and around the product, rather than just the quality of the product (cf.Henkoff, 1994) Customer intimacy is becoming an increasingly acknowledgedstrategic posture (Treacy and Wiersema, 1995) and the traditional distinctionbetween products and services is becoming increasingly irrelevant (Haeckel,

1994) Companies are moving closer to their customers, expending more effort

in finding new ways to create value for their customers, and transforming thecustomer relationship into one of solution finding and partnering rather thanone of selling and order taking Customer support and service comprises theway that a product is delivered, bundled, explained, billed, installed, repaired,renewed – and redesigned As a growing envelope that can manage and growsuccessful long-term customer relationships, customer support and service isbecoming one of the most critical core business processes

The emphasis on customer support and service needs are driving IS prioritiesmore than ever before There has been research work on measures of service

quality for information system effectiveness (Pitt et al., 1995) Furthermore,

results of the annual surveys of critical issues of IS management conducted bysystems integrator Computer Sciences Corporation show that ‘connecting tocustomers and suppliers’ has jumped from sixteenth place in 1994 to seventhplace in 1995 and 1996 (Savola, 1996) The 1996 survey also revealed that thecorporate goal with which IS is aligning itself most is learning about andfulfilling customer needs more effectively, and that applications to supportcustomer service is the number one focus of current systems developmentefforts (60% of 350 IS executive respondents) Similarly, a 1995 survey by

Information Week (Evans, 1996) to identify the top criteria by which

organizations evaluate the performance of IS professionals showed that two ofthe top five criteria centered around customer support and service The twocriteria were the ability to use IT effectively to improve customer service (76%

of respondents) and how well they deployed IT to meets the needs of customersoutside the organization (67% of all respondents)

However, there is more to this than just bringing more IT to customersupport and service The increased focus on customer support is taking place

in a business environment that is characterized by unprecedented speed, rapidknowledge creation, increasing complexity, and spreading electronic net-works: we are experiencing the emergence of the electronic economy Thisnew business environment breeds many more complex products with shorterlife-cycles, and these products are used in customer contexts that are alsocomplex and fast-moving Customer support in such environments is muchmore demanding – especially in business-to-business situations – and thatrequires:

• Much faster response to resolving customer queries and problems as thebusiness tempo escalates

• Smarter and faster ways of creating, capturing, synthesizing, sharing, andaccessing knowledge about complex products and services

• More dynamic support for – and faster learning about – products that arefrequently morphed due to rapid product innovation and dramaticallyshorter product life-cycles

Information Technology and Customer Service 557

• More collaborative problem-solving with other (possibly competing)companies as products from multiple vendors increasingly have to work inconcert

• Taking advantage of new electronic channels and open networks forcommunicating and collaborating with customers and

• More fail-safe customer support as it becomes most critical to thecustomer

Given these stringent requirements, how can customer support processes betransformed and IT-enabled to be effective in this new electronic economy?That is the challenge this chapter addresses

The evolution of customer support for complex products

Customer support traces its origins to the 1850s when the Singer SewingMachine company set up a program that used trained women to teach buyershow to use the sewing machine (Lele and Sheth, 1987) Traditionally,customer support has referred to after-sales support, which consists of all theactivities that help increase customer satisfaction after they have purchased aproduct and started to use it The marketing literature (cf Lele and Sheth,

1987) has differentiated between specific support services and feedback and restitution Support services refer to activities such as parts and service,

warranty claims, customer assistance and training, technician training, andoccasionally trading-in of older equipment Feedback and restitution refers toactivities such as complaint handing, returns and refunds, and disputeresolution As manufacturers started to compete by bundling services withproducts (cf Chase and Garvin, 1989; Shostack, 1977) the scope of customerservice and support for products has expanded cross-functionally to includeexpert help from the manufacturing, engineering, and R&D functions Morerecently, as long term customer relationships and partnering with customershave become very important (cf Henkoff, 1994) the notion of customersupport has expanded beyond ‘after-sales’ and has colored the whole way thatcustomer service is provided While, the terms service and support are looselyused interchangeably in some contexts, they are not the same Customersupport has a long term partnering flavor that signifies that the supplier wants

to help the customer do their job effectively, and in this age of ence and alliances it seems to be a more apt term for the bundle of activitiesthat comprise it

interdepend-Customer support is more critical and difficult for high technology complexproducts, especially with the breakneck speed in new product development forthose products Many customer support innovations and strategies in the lastdecade have originated from the computer and telecommunications industry.These include automated help desks, toll-free hot-lines, computer bulletin

board systems, 7×24 service, remote online troubleshooting, and, mostrecently, the use of the Internet As organizations have become criticallydependent on information technologies and telecommunication networks forthe operations of their business, so has the criticality of response time insupporting those products and services – and it has risen to unprecedentedlevels The cost of providing effective customer support has also risen morethan proportionately The high technology industry has sought solutions thatmay provide ideas for other industries.

In order to improve overall service levels and reduce overall costs, theinformation technology industry has adopted a hybrid model for customersupport (Entex, 1994) This includes having personnel on-site at majorcustomer accounts (what IBM has been traditionally known for), using thirdparty resellers or other vendors who can provide localized customer supportfor smaller accounts and consumers, and providing high-tech long-distanceremote support through a centralized pool of talent whether in-house orthrough an external service (very common in commodity and low marginitems such as PC hardware and software) Each of these options has a differentcost structure and service advantage Direct on-site support is expensive butprovides superior service Going through resellers requires heavy investments

in training and qualification to assure good service Remote high-tech support

is a challenge for complex products and can be very impersonal if not verycarefully managed Different vendors in different market segments havedifferent hybrid blends depending on their support strategy

These options are further challenged when products interact with othervendor products, response time is critical, and the stakes in downtime are veryhigh Figure 19.1 illustrates how the required customer support level risesvery quickly when there is an increase in the combination of complexity andconnectivity of the product and its criticality to customer operations For high-end products that are in non-stop heterogeneous networked environmentswhere down-time is prohibitively expensive for the customer, the requisitelevel of customer support rises exponentially It requires very fast responsetime, highly skilled personnel, and an ability for customer support personnel

to learn very quickly about product innovations and quirks in their ownproducts and those of other vendors’ (that their product interacts with) Thatquick learning requires a radical rethinking about how learning occurs duringthe customer support process The challenge is to find a way to very quicklycapture and disseminate new learning around the customer support processthrough all the participants that come into contact with it in a simple and costeffective way

This challenge was examined in the context of the customer support process

at Storage Dimensions, a manufacturer of high-availability computer storagesystem products Moreover, we believe that the lessons of this experienceprovide insights for rethinking the customer support process in all industries

Information Technology and Customer Service 559

as the electronic economy makes such customer support levels more the rulethan the exception

The customer support challenge at Storage Dimensions

Storage Dimensions is a vendor of high-availability disk and tape storage forclient/server environments It was founded in 1985 in the heart of SiliconValley in Milpitas, California, and went public in March 1997 Its 1996 saleswere $72 million The company designs, manufactures, markets, and supporthardware/software products that provide open systems storage solutions formission-critical enterprise applications Its high-end storage solutions aretargeted to organizations with enterprise-wide client/server networks that mustkeep mission-critical data protected and available 24 hours a day Thecompany’s customer base is mainly Fortune 1000 companies in information-intensive industries that live and die by their data These include airlines,banking, finance, insurance, retail, utilities, and government agencies StorageDimensions products are sold through distributors and resellers in the USA,Europe, and the Pacific Rim The company also has a direct sales force tomore effectively serve its key vertical market customers More detailed

Figure 19.1 Rising customer support levels for complex products

information about the company and its products can be found atwww.storagedimensions.com.

Storage Dimensions’ products fall into three main categories: availability RAID disk storage systems, high capacity tape backup systems,and network storage management software for multi-server networks RAID(Redundant Array of Independent Disks) is a fault-tolerant disk subsystemarchitecture that provides protection against data loss and system interruptionand also provides improved data transfer/access rates for large databases Thisprotection ranges from simply mirroring data on duplicate drives to breakingdata into pieces and ‘striping’ it across an array of three or more disks; if onedrive goes down, the controller instantly reconstructs the lost data and rebuilds

high-it on a spare drive Other features include a combination of redundant swap hot-spare power supplies, fans, and disk drive components to ensurenon-stop operation and continuous access to data

hot-Following a 1992 buyout from Maxtor, company management refocusedStorage Dimensions to become a higher-end and faster-response industryplayer It was clear that exceptional customer support would be essential tosuccess, and a customer-support-focused corporate strategy was put in place.The customer support process was reexamined and it was apparent that it wasbecoming inadequate for the growing customer base and expanding productline Furthermore, with increased globalization the customers were dispersedgeographically and in different time zones The customer support process wastoo slow (as much as two to three hours to return a phone call in somecircumstances), too haphazard (no organized online knowledge base for repeatproblem solutions), too expensive (repeat problems frequently escalated todevelopment engineers, long training periods), and very stressful to bothsupport personnel (overloaded) and managers (little visibility for the what,who, why, when) Top management saw the need for a radical solution.Given the mission-critical nature of its customers’ network environments,the company expended much effort in providing exceptional customersupport It differentiated itself in the market by helping customers minimizetheir total life-cycle cost of ownership for network storage in the context ofmission-critical applications A storage system’s total life-cycle cost-of-ownership is much more than the purchase price Service, support, anddowntime for RAID storage systems account for 80% of the total cost over thelife of the system as per a Gartner Group study – and downtime is especiallycritical to customers A Computer Reseller News/Gallup Organization 1994study found that hourly losses due to network downtime in Fortune 1000companies were $3,000 to $5,000 per hour (median), could often be $10,000,and sometimes $100,000 or more (6% of companies) Storage Dimensionsinstituted several customer support programs and innovations to enhance thislower total life-cycle cost-of-ownership customer support strategy [Foradditional information on Storage Dimensions, see Chabrow, 1995.] One key

Information Technology and Customer Service 561

element of that strategy was TechConnect, an online technical support system.The development of TechConnect is described in the next section

The development of the TechConnect support system

As the customer support process was being reexamined in mid-1992, itbecame apparent to the management team that an IT-enabled solution with anartificial intelligence component had to be part of the remedy They put theircommitment behind it and a project was initiated The core management teamfor the project consisted of the executive VP for marketing and customerservice (who was also the project sponsor), the director of customer serviceand support, and the director of information systems (Figure 19.2 shows theorganization chart) In addition, a cross-functional task force was formedconsisting of three people: one from the customer support group, one from the

IS group, and one from engineering Together, and with input from bothcustomers and others in the company, the management team and the task forcecame up with a list of the top operational objectives (see Table 19.1) and keytechnical usability requirements (see Table 19.2) for what they genericallyreferred to then as the customer support management system They then

Figure 19.2 Organization chart for Storage Dimensions

Table 19.1 Top 10 operational objectives of customer support management system

in mid-1992

1 Provide consistent, accurate responses to customer inquiries

2 Document and track all known problems and proven solutions

3 Create centralized sources of information about customers, known problems,solutions

4 Assist in developing solutions to new problems

5 Create a closed loop escalation process

6 Promote cross-training of support staff

7 Provide remote access for customers of problem solutions

8 Improve call tracking and problem reporting

9 Improve accountability and responsibility with clear audit trails

10 Improve productivity of customer support staff

Table 19.2 Technical usability requirements of customer support management system in mid-1992

IT Infrastructural/compatibility requirements

1 Multi-user, runs off current Ethernet network lines

2 Works under Microsoft Windows with a GUI interface

3 Dial-in capability for remote user access

4 Provides initial access for 25 users, expandable to 50 within one year

5 Must interface with cc:Mail for notification purposes

6 Must have data import/export capability

Usability Requirements

1 Call tracking capability

2 Problem/solution tracking capability

3 Keyword search for problems/solutions

4 Must have a method for assisting technical support staff with answering calls(Al or other)

5 Must have a report generator with user-definable reports without generatingprogramming code or a script

6 Ability to create and define call queues

7 Have at least five user-definable fields

8 Have automated call escalation process

9 Must have a closed loop problem solving process

10 Provides call audit trail

11 Tracks and reports customer configuration data

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searched the market for software packages that could help meet thoserequirements

The search included various types of artificial intelligence shells, databasemanagers, call management packages, and help desk software – most of whichwere not the least bit suitable and were quickly eliminated Only fourpackages in the help desk software category came close, and these wereevaluated in detail These help desk software packages were not an off-the-shelf fit to the application context First, the approaches of the packages andvendors were geared mostly to internal help desks rather than externalcustomer support with different customer types Second, the knowledgecapture/update and keyword search capabilities (if any) were too primitive forcomplex products that changed quickly and had interactions with othervendors’ products Third, Storage Dimensions had a fairly sophisticatedclient/server network, and it wanted to link the customer support system to itse-mail and to its internal information systems and databases in otherfunctional areas As the help desk software vendors themselves acknowledged

at the time, this would be a stretch

The comparative analysis among the four help desk software packages wasmade based on how the software features fit the operational requirements TheApriori GT help desk software from Answer Systems (since 1995 a part ofPlatinum Technology Inc.) was selected mainly based on its unique ‘bubble-up’ technique that could prioritize likely problem solutions (discussed in moredetail later in this section), its good incident management capabilities, its goodreporting capabilities, and its technical compatibility with Storage Dimen-sions’ client/server network infrastructure and the Windows graphical userinterface Other Apriori GT capabilities at the time included call tracking,incident escalation, various search and retrieval features, custom notificationand routing, e-mail and fax integration, accountability features, and tailor-ability for application integration

While no programming changes would be made to the source code, therewas much work to be done in structuring Apriori GT to fit the complexity ofthe Storage Dimensions environment and linking it (through Perl scripts andmacros) to the internal information system infrastructure and e-mail For thenext 90 days the task force worked together with the software vendor toinstall, customize, script, and test the customer support application Simulta-neously, the customer support process and the way it was managed was beingreengineered to take advantage of this new technology Much input wassought and enthusiastically received at that stage from various parts of thecompany, and a pilot was run with selected customers Fortunately,implementation was successful both technically and organizationally Tech-Connect was online in late 1992

The TechConnect system was set up on a Sun Sparc 670 MP server and cost

$160,000 for hardware and software It costs $15,000 to maintain per year

Customer Customer

inquiry Dispatch Incident TechnicalSupport

Engineer

Resolved problem RMA

Resolved problem by document

Escalated incident ApplicationsEngineer

Engineer problem resolution

New document

Resolved problem by document

Escalated incident ManagerPTR

Level 1 problem resolution

Level 2 problem resolution

Level 3 problem resolution

The cost justification for TechConnect was not difficult based on pocket expenses In the first year alone the reduced call-backs (due to higherproblem resolution rate on first customer call) saved about $70,000 in longdistance phone bills In addition, the productivity gains obviated the need tohire more technical support engineers to handle the growing customer supportload, saving another estimated $150,000

out-of-The new IT-enabled customer support process

TechConnect enabled the redesign of the customer support process such that

it could be more effective and better managed Some key aspects of how thisnew online customer support process was managed follow

• Improved escalation paths for problem management: A simplified

diagram of the three-level escalation sequence is shown in Figure 19.3.After dispatch, the customer call goes to a level 1 technical supportengineer He/she tries to resolve the problem through an on-lineTechConnect solution document If it includes a request for materialauthorization, then an appropriate customer service representative isnotified through TechConnect If the problem is not resolved at level 1, it

is automatically escalated and queued (path depends on the operatingsystem used by the customer’s client/server network hardware) to a level

2 applications engineer who is more skilled and who investigates itthoroughly If the applications engineer is unable to resolve it, then it is

Figure 19.3 Escalation sequence in customer support process

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automatically escalated to the problem tracking request (PTR) managerwho verifies the problem and must decide whether to escalate it to adevelopment engineer

• Closed loop problem resolution: As the incident moves along the

escalation path, both the caller and the customer support staff (andmanager) always know who has the incident and what its status is Theprocess also ensures that the customer is informed in a timely manner.TechConnect keeps track of all the information related to the incident andstores it in the TechConnect database

• Analysis and reporting capabilities: TechConnect provides a multitude

of management and activity reports that help manage the customer supportprocess and identify bottlenecks It is possible to automatically flagunusual events and for customer support staff to spend more time onproactive rather than reactive customer support

• Automatic cross-triggering capabilities: TechConnect is integrated into

the Storage Dimensions network of information systems to automaticallyflag other business areas or information systems via e-mail based onproblem incidents This facilitates cross-functional coordination betweencustomer support and other departments

• Amplified shared knowledge creation: The intensity of shared

knowl-edge creation through customer interactions around the customer supportprocess is greatly amplified through TechConnect The continuousproduction of online solution documents steadily creates a valuable

knowledge base that is accessible to all: everyone can be an expert, and everyone can contribute to the learning That transforms the way that the

customer support process is carried out and managed, as does itsknowledge-creating capacity That critical aspect is discussed in moredetail in the next section of the chapter

With the use of the TechConnect system and a transformed customersupport process, the customer support department has remained at the samesize despite increasing sales volume The group consists of eight technicalsupport engineers, three applications engineers, and one manager They work

a basic 11-hour shift between them and also have a 24 hour on-call system

TechConnect as an adaptive learning IT infrastructure

The TechConnect system is based on a knowledge base software architecturethat adaptively learns through its interactions with users It is based on aunique software-based problem resolution architecture (patented in 1995 byAnswer Systems) that links problems, symptoms, and solutions in a documentdatabase All problems or issues are analyzed through incident reports, andresolutions are fed back into the online knowledge base in the form of solution