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Busi ness Expert Syst ems- - Gai ni ng A Compet i t i ve Edge

Cl yde W Hol sappl e Andrew B. Whi nst onUni ver si t y of Kent uckyCol l ege of Busi ness Uni ver si t y of Texas at Aust i nDepart ment of Management Sci enceand Economcs and I nformat i on Syst emsLexi ngton, Kent ucky Aust i n, TexasABSTRACT

Thi s paper i dent i f i es and examnes strategi coppor t uni t i es and chal l enges that a new yemergi ng t echnol ogy presents t o managers.Wth t he recent advent of very powerf ul tool sf or i mpl ement i ng busi ness- ori ent ed exper tsystems, practi cal manager i al appl i cat i onsof aut omated reasoni ng t echni ques arebegi nni ng t o appear. Seni or managementshoul d be aware of the st rategi c i mpl i cat i onsof thi s technol ogy for gai ni ng a compet i t i veedge and avoi di ng compet i t i ve di sadvantage.

I nt roducti onConvi nci ng arguments have been madet hat t op management shoul d consi der t hecompeti t i ve oppor t uni t i es af f orded byi nf ormati on syst ems t echnol ogy [l]. Wecont end t hat si m l ar at t ent i on shoul d begi ven t o t he opport uni t i es of f ered by acomparati vel y newcomputer-based technol ogy:expert systems. I nformati on syst ems tech-nol ogy i s concerned w t h t he st orage,mai ntenance, ret r i eval andt ransm ssi on ofi nf ormat i on. Ai r l i ne reservat i on syst ems

and vari ous i nterorgani zat i onal purchasi ngand order i ng syst ems are wel l document edexampl es of i nf ormati on system that provi decompet i t i ve advantages [2].The i nf ormat i on deal t w t h by t heabove syst ems i s but one ki nd of know edge,namel y descr i pt i ve know edge, about anorgani zati on and i t s envi ronment . Anot hert ype of know edge t hat i s very i mportant t oan organi zat i on i s i ts r easoni ng know edge,i t s expert i se about what act i ons or con-cl usi ons are val i d when cer t ai n si t uat i onsexi st. J ust as computeri zat i on of descri p-t i ve know edge i n the gui se of i nf ormat i onsyst ems can l ead t o a compet i t i ve edge, sot oo can t he comput eri zati on of reasoni ngknow edge i n t he busi ness expert syst ems.Consi der t he f ol l ow ng exampl es:

1) A l arge drug company provi des eachof i t s sal es managers w th an expert systemt hat provi des advi ce about establ i shi ng

sal es quot as. The r esul t ant i ncrease i nsal es manager product i vi t y, due t o moreef f i ci ent and ef f ect i ve quot a det ermna-t i ons, t ransl ates i nto an enhanced competi -t i ve st andi ng f or t he company.Management of a chemcal manufac-turer deci des on a competi ti ve strategy thatf ocuses on devi si ng sol ut i ons to i ndi vi dualprobl ems i n order t o sel l chemcal s.Deri vi ng and expl ai ni ng sol ut i ons to compl excustomer probl em requi res extensi ve exper-ti se. The company i mpl ement s i t s st rategyby capt uri ng such expert i se i n exper tsystems t hat are readi l y avai l abl e t o eachmember of i t s sal e force.

3) A retai l bank ai ms to i mprove i tscompet i t i ve posi t i onby of f er i ng auni quei nvestment banki ng servi ce to i ts customers.I t uses an exper t syst em t o recommendcustomzed f i nanci ng pl ans t ai l ored t o meetspeci al i ndi vi dual needs of i t s ret ai lcust omers.The technol ogy of expert syst ems i sj ust begi nni ng t o make i t sel f f el t i n t hebusi ness worl d. Busi ness expert syst emsoff er an i mport ant newmechani smfor creat -i ng sust ai nabl e compet i t i ve advantagesacrossabr oadrangeof i ndustr i es. I den-t i f yi ng such oppor t uni t i es, al ong w th the

chal l enges they present , i s t he cent ralpurpose of t hi s art i cl e. We begi n w t h abri ef l ook at the nature of expert system.

2)

Exver t Syst ems: An Overvi ewExpert syst emt echnol ogy i s a branchof art i f i ci al i nt el l i gence t hat ai ms atmaking computers capabl e of emul ati ng humanreasoni ng behavi or [3]. An expert syst emcan be consul ted i n much t he same spi r i t asadvi ce i s sought f roma human expert . Auser poses a speci f i c probl emt o the expertsystem Li ke i t s human count erpart , i tmght ask the user f or f ur t her i nf ormat i ont ohel pcl ar i f y or more f ul l y descri be t henature of t he probl em Li ke t he humanexper t , i t s obj ecti ve i s t o of f er someadvi ce, recommendati on, or sol ut i on t ot he

user. Tomeet t hi s obj ect i ve, t he sof t wareport i onof anexpert syst emdr aws onr el e-vant f ragment s of reasoni ng know edge t hatexi st i n i ts reposi tory of stored expert i se.

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The stored f ragments of exper t i se canbe thought of as rul es. Each rul e speci f i esthat i f cert ai n condi t i ons can be establ i sh-ed as t rue, t hen cer t ai n concl usi ons can beregarded as bei ng val i d. Exhi bi t I showsa f ewsi mpl e rul es [ 4 ] . The expert syst emsof t ware t hat works w t h such rul es whenat t empt i ng to sol ve a probl emi s cal l edani nf erence engi ne. At var i ous j unctures i nt he process of i dent i f yi ng and appl yi ngrul es t hat ar e rel evant t o a par t i cul arprobl em the i nf erence engi ne ( l i ke a humanexpert ) may need yet more i nformati on f romthe user. I n such cases, i t si mpl y request sthe desi red i nf ormati on. Before answeri ng,the user may want t o knowwhy such a requesti s bei ng made. On demand, t he i nf erenceengi ne can expl ai n why. Provi ded suf f i -ci ent , pert i nent r ul es of reasoni ng areavai l abl e to i t , t he i nf erence engi ne usest hemt o i nf er a sol ut i on f or a speci f i cprobl em

Once a sol ut i on i s r eport ed, the usermay want t o knowwhat l i ne of reasoni ng wasconstructed i n the course of the i nf erence.Li ke a human exper t , an expert syst emi sabl e t o expl ai n i t sel f , st at i ng why t hei nf er red r ecommendat i on i s j ust i f i ed i nl i ght of the speci f i ed probl emand avai l abl eexpert i se f or reasoni ng about that probl emThe di agrami n Exhi bi t I 1 i l l ustr at es thei nt erpl ay bet ween the t hree par t s of anexpert syst emand a user. Human expert s areabl e to r eason w th and about uncertai nt i esi n such a way t hat a r ecommendat i on can beaccompani ed by some degree of cert ai nty.

Si ml ar l y, an exper t syst emshoul d be abl et o st at e i t s i nf er red r esul t i n such a wayt hat i t s cert ai nt y about t hat resul t i scl ear. Li ke a human expert , an expert systemshoul d al so be abl e t o of f er mul t i pl esol ut i ons for a gi ven probl emand i ndi cat ehow sure i t i s about each.I n a busi ness expert systemt hestored expert i se i s concerned w th reasoni ngknow edge about some cl ass of busi nessprobl ems such as set t i ng sal es quotas,eval uati ngpr oduct m xes, r i ci ng, produc-t i on schedul i ng, or f i nanci ng. I t i s nowpossi bl e f or a busi ness expert systemt ogobeyond t he conventi onal noti ons of an expertsystem i n that i ts i nf erence engi ne i s abl et o process much more t han st ored rul es ofreasoni ng. I t i s al so abl e t o process dat abases, spreadsheets, procedural model s,text , g. raphs, and so f ort h on an "as needed"basi s i n t he mdst of sol vi ng a probl emLi ke t he manager t hat i t emul ates, a busi -ness expert syst emshoul d be abl e to l ookup, cal cul ate, present and otherw se mani pu-l at e t he descri pt i ve know edge t hat i s

i ntegral t o the act i vi ty of i nf err i ng asol uti on [ 4 ] . I t i s thi s rel ati vel y newki nd of syst emt hat we now examne f romacompet i t i ve st r ategy vi ewpoi nt .Comweti t i ve St ratesi es

Tradi t i onal l y, the reasoni ng know edgeembodied i n an organi zat i on' s empl oyees hasprovi ded an i mport ant basi s f or achi evi ng,i mprovi ngandmai ntai ni ng t s competi t i veRULE: R1I F: SALES > 1. 15*QUOTA

REASON: I n cases where t he sal es f or t hi s product exceededt he quota by more than 15%, t he base amount f or t henew quota i s set t o the past quota pl us t he excesssal es amount.

THEN: BASE = QUOTA+(SALZS-l.l5*QUOTA)

RULE: R7I F: GROWTH > = . 02 AND GROWTH < . 0 4 AND UNEMPLOYMENT < .055THEN: ECONOMY = "good"REASON: The economc out l ook i s good because proj ect edgrowt h r ate i s between 2 % and 4% .- unempl oyment i s l ess than 5. 5% and the ant i ci pated

RULE: R9I F: GROWTH < -02 OR UNEMPLOYMENT > = - 0 8 2THEN: ECONOMY = f t poor' lREASON: The economc out l ook i s poor because ei t her theant i ci pat ed growt h r at e i s very l ow or proj ectedunempl oyment i s hi gh or both.RULE: R10I F: ECONOMY = "good" AND LOCALADS > 2000THEN: LAFACTOR = LOCALADS/ l OOOOO

REASON: When t he economy i s good and l ocal advert i si ngexceeds $2, 000, t he l ocal advert i si ng f actor i s 1%f or every t housand dol l ar expendi t ure.Sampl e Rul es t hat Per t ai n t o Recommendi ng Sal es Quotasxhi bi t I .

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poses problemUse r

I n t e r f a c easks f o r an d rcce ives -5*

posi t i on. Al l el se bei ng equal , organi za-t i ons w t hout comparabl e exper t i se ar e ata di sadvant age. Wt h busi ness expertsystems, t here i s an opport uni t y t o ampl i f yt he compet i t i ve advant age deri ved f romsuper i or know- how To the extent t hat t heexpert i se capt ur ed i n an expert systemi suni que or not w del y known, a sustai nedadvant age resul t s. Unl i ke i nf or mati onsyst ems, i nterest i ng expert syst ems cannotbe readi l y r eproduced w thout access t o t hedetai l s of t hei r st ored exper t i se. Such anexper t syst emcan be used openl y, but asl ong as i t has suf f i ci ent securi t y provi -si ons to prot ect t he detai l s of i t s reason-i ng know edge f romdi scl osure, t he competi -t i veadvant age i t f ur ni shes endures. I nasense, i t i s an i ntel l ectual propert y r i ght ,si ml ar t o a patent w thout a predetermnedexpi rati on date.

Li ke i nf ormati on syst ems, expertsystems can be used t o i mpl ement a competi -t i ve strategy. M chael Por ter has observedthat compet i t i ve st rategi es f al l i nto threecat egori es [51. One st r ategy i s based ont he i d e a o f p r o d u c i n g good s o r s e r v i c e s a ta l ower cost t han competi t ors. Anotherstrategy i s based on brand di f f erent i ati on,whi ch i nvol ves of f eri ng a uni que and attrac-ti ve mx of product f eatures. A thi rd basi cst r at egy i s t o concent r ate i n a speci almarket ni chew t h apr oduct t hathasl i t t l edi rect competi t i on because of i ts remarkabl ef eat ures or cost advant ages. These basi cst rategi es suggest t hr ee ways i n whi chbusi ness expert syst ems can cont r i but e t oan organi zat i on' s competi t i veness:

enhanci ng i nternal product i vi t yprovi di ng enhanced servi cesprovi di ng new ser vi cesOn a l ar ger scal e, an organi zat i on coul dl ookt obusi ness expert systems as part ofa st r ategy ai med at spawni ng a compl etel ynew i ndust ry. An exampl e of each t ype ofcont r i but i on i s expl ored i n t he sect i onst hat f ol l ow

Enhanci ns I nt er nal Pr oducti vi t yThe nat i onal sal es f or ce of a l argedrug company i s part i t i oned i nto geographi c

l n f e r e n c e S to r e dE n g i n e E x p e r t i s e

0073-1 29/90/~/0249$01.00 1990lEEX

regi ons. For eachregi on, a sal esmanageroversees t he goal s and per f ormance of sal esrepresentati ves. Topmanagement percei vesthat a key to enhanci ng competi t i veness l i esw t h i ncreasi ng t he pr oducti vi t y of i t ssal es managers. One el ement of thi s st rate-gy r evol ves around an expert syst emt hatassi st s each sal es manager i n the determna-t i on of sal es quot as.Each sal es rep sel l s the company' sf i f teen product l i nes to cl i ni cs and hospi -t al s i n a pr escri bed terr i t ory. For each

r ep, a sal es manager i s r equi r ed t o set asal es quot a f or each product l i ne f or eachmonth. Because a r egi onhas anywhere f romt en t o t wel ve reps, a sal es manager mustestabl i sh f rom1800 t o 2160 quotas at t hebegi nni ng of eachnewyear . I deal l y, eachquota shoul d t ake i nto account such f actorsas pr oduct l i ne t r ai t s, seasonal t r ends,t err i t orydemogr aphi cs, pr i or r epper f or -mance, l ocal and nat i onal adverti si ng pl ans,the expected economc condi t i ons f or t heterr i t ory, and compet i t ors' perf ormance i nthe regi on.Top management bel i eves t hat t he scal eof thi s task has hi stori cal l y detracted f romsal es resul t s. Management is al so concernedabout the consi stency and f ai rness of quotasassi gned to reps both w t hi n and across

regi ons. Thi s i s i mpor t ant not onl y f orbonus cal cul at i ons, but al so for sal es forcemoral e and mot i vat i on. The expert syst emf or gi vi ng quot a advi ce addr esses al l ofthese concerns. The rul es bui l t i nto i t aredi st i l l ed f r oma t op sal es manager ' s ap-proach t o r easoni ng about quotas.The expert systemf or set t i ng sal esquotas enhances sal esmanager product i vi t yi n t wo ways. Fi r st , i t can i ncrease ef -f i ci ency by r educi ng t he ti me and ef f ortthat a sal es manager expends on t hi s ac-t i vi t y. The gai n can be appl i ed t o ot heracti vi ti es (e. g. , rep t rai ni ng) t hat posi -t i vel y i mpact sal esw t hi n t he regi on. Asa resul t t he company i s more compet i t i vebecause i ts sal es managers have an ef f i ci en-cy advant age over t hei r count erpar t s i n

compet i ng compani es. Second, t he expertsystemcan i ncrease ef f ecti veness by ut i l i z-i ng exper t i se that i s otherw se unavai l abl e

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t o many sal es managers. The best t hat t hecompany can off er i n thi s area i s repl i catedi n a consi st ent f ashi on t hroughout t heorgani zat i on.A compet i tor may have managers whoseexpert i se r i val s t hat of t he sal es manager

emul ated by t he expert syst em But so l ongas that expert i se i s not di str i buted w thi nt he compet i ng organi zat i on, t operates ata r el at i ve di sadvant age. I t does notmaxi m ze t he producti vi t y of i t s sal esmanagers. I n cont r ast , t he quot a exper tsystemi s easi l y di str i but ed t o al l sal esmanagers i n t he pharmaceut i cal f i rm I tprovi des t i mel y advi ce, i s abl e t o operatearound t he cl ock, does not get si ck, doesnot t ake vacat i ons, and does not resi gn.I t i s not t i ed up i n meet i ngs, away onbusi ness, or otherw se i ncommuni cado. I t sadvi ce i s consi st ent . I t i s thorough andmethodi cal . I t does not overl ook i mport antf actors, ski p steps, or f orget. Al l el sebei ng equal , t he quota expert systemyi el dsa compet i t i ve advant age due t o more ef -ci ent and ef f ect i ve use of sal es managementresources.The sal es quota case i s but oneexampl e of how an organi zat i on can useexper t syst emtechnol ogy to i mpl ement acompet i t i ve st r ategythat ai ms at enhancedi nternal producti vi ty. I t can be appl i edat al l l evel s of organi zat i onal deci si onmaki ng. Anthony has i dent i f i ed three l evel si n t he cont i nuumof deci si on processes:st r at egi cpl anni ng, management cont rol andoperat i onal cont rol [61 . At one end of t hedeci si on maki ng spectrum st rategi c pl anni ngi s concerned w th deci si ons about obj ect i vesand pol i ci es. Management control i s con-cerned w t h managi ng resources to meetobj ect i ves and conf ormt o pol i ci es. At t heother end of t he spect rum operat i onalcont rol i nvol ves t he exerci se of preci sel yspeci f i ed deci si on rul es t o deci de whatact i ons t o undert ake. At one ext r eme,operat i onal cont rol probl ems t end t o berout i ne and hi ghl y structured. At t he otherext reme, s t ra t eg i cp lann ingprob lemst endt o be l ess rout i ne and l ess st ructured(i . e. , l ' fuzzy") [ 7 ] .

I n the case of t he drug company,sett i ng sal es quotas i s an exampl e of amanagement control probl em An expertsystemt hat of f ers sal es quot a advi ce canassi st i n t he ef f ecti ve ut i l i zat i on of asal es manager ' s resources. Adi f f erent ki ndof probl emthat conf ront s the company f romt i me to t i me i s whet her t o t ake on a newproduct l i ne or el i m nat e an exi sti ngproduct l i ne. These are exampl es of st rate-gi c pl anni ng probl ems. They r equi r e con-si derabl e expert i se t o sol ve and coul d al sobenef i t f romexpert systems. Many of t hecompany' s operat i onal cont rol probl ems areal so appropr i ate f or expert systems. Fori nst ance, t he shi ppi ng depart ment has a f ew

si mpl e rul es t hat cl er ks use t o det erm nehowr egul ar shi pment s are t o be sent . Butrush orders are not unusual and they requi remuch greater expert i se t o handl e eff ect i ve-l y. The car r i er sel ected f or such a shi p-ment depends on f actors such as t he t i me ofday, day of t he week, hol i day proxi m t y,dest i nati on, and shi pment si ze. An expertsystemt hat can of f er cust om zed shi ppi ngadvi ce f or t he except i onal cases enhancest he producti vi t y of t he cl er ks and thei rsupervi sor al i ke.At each l evel of deci si on maki ng,there are probl em amenabl e to expert systemassi stance. Al l of t hese shoul d be con-si dered as ways f or creat i ng competi t i veadvantages through enhanced i nternal produc-t i vi t y. Some of t hese producti vi t y i n-cr eases may l ead t o cost advant ages, assuggested by Port er. But l ower cost i s notthe onl y possi bl e mani f estati on of enhancedproducti vi t y. As i n t he case of t he quot aexpert system there i s al so more ef f ecti veand ef f i ci ent deci si on maki ng. I t cani ncrease sal es or market shar e not onl y

through a di rect i ncrease i n "ge produc-t i vi t y, but al so through t he more r espon-si bl e and mot i vat ed sal es f or ce t hat canresul t f romf ai r and consi st ent quot as.Provi di ns Enhanced Servi cesA l arge di vi si on of a chemcal companysuppl i es a broad l i ne of chem cal s t oi ndustr i al customers. Many of t he chemcal shave mul t i pl e uses and of t en t her e may beseveral chemcal s that coul d, al ternat i vel yor i n t andem meet a part i cul ar customerneed. I n many cases a cust omer does notknow what amounts of what chem cal s w l lmeet i t s needs. Management deci des t oi mpl ement a compet i t i ve st r ategy thatenhances the servi ces provi ded to customers.I nst ead of merel y sel l i ng chem cal s, t hecompany w l l provi de sol ut i ons. The companyw l l hel p a cust omer t o cl ar i f y t he probl emf aced, of f er expert advi ce about sol vi ngt hat probl em and j ust i f y t he advi ce t hati s of f ered.Suf f i ci ent i n-house expert i se exi stsfor handl i ng the di verse, techni cal probl emt hat cust omers f ace. But t he cat ch t oi mpl ement i ng t he ful l sol ut i on st rategy i st he del i very of t hi s expert i se. Trai ni ngtechni cal sal es reps to del i ver t he currentpi tch whi ch descri bes t rai t s and uses of thecompany' s product s i s al r eady a cost l y,l engthy and t i me-consumng endeavor . Evenw t h ext ensi ve t rai ni ng, sal es reps of t enf i nd i t di f f i cul t t o mat ch cust omer ' spercei ved needs (typi cal l y descri bed i n veryt echni cal t erms) w t h product of f er i ngs.Furt her t rai ni ng t hat enabl es a r ep to hel pi n cl ar i f yi ng a cust omer ' s actual probl emt o of f er and expl ai n sol ut i ons, w l l not bepracti cal . Such t rai ni ng cannot be expectedt o resul t i n a sat i sf actory i mpl ement at i onof t he competi t i ve st rategy.

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There i s al so the prospect that hi ghl yt r ai nedr eps c anbe l ur ed awaybycompet i -tors, so t hat t he company serves as at rai ni ng ground f or i t s competi t or s.Fur t her more, t here ar e l i mt s t o what asal es r ep can absorb whi l e sti l l acti vel ymaki ng sal es cal l s. Even t he probl emsol vi ng abi l i t y of an i n- house exper t hasl i mt s. I ndi vi dual s who are expert s abouteveryt hi ng are rare i ndeed. However, t hecol l ect i ve know- how of t hese exper t s i sf ormdabl e.

A possi bl e al ternat i ve t o i mpl ementi ngthe f ul l sol ut i on st rategy woul d be to makethe i n- house experts di rectl y accessi bl e t ocust omers. Together they woul d f orm at echni cal sal es suppor t st af f . When a repencount ers a probl em hat he or she cannothandl e, i t i s r ef er red t o an appropr i at eexper t i n t he support staf f . Thi s exper tthen hel ps def ne and sol ve t he probl emandexpl ai ns the sol ut i on. There are sever aldi f f i cul t i es w t h t hi s approach. Theexpert s typi cal l y are not especi al l y ski l l edi n sal es t echni ques. Thei r exper t i se i si mportant for post-sal e customer support andf or t he r esearch and devel opment of newproducts. The experts are nei ther numerousnor i nexpensi ve. As a resul t , cust omerreferr al s woul d need to be queued. Responsesmay not be ti mel y and unheal thy cont ent i onf or exper t suppor t may ari se among sal esreps.

I f i t wer e not f or t he scarci t y andcost of expert s, t he i deal i mpl ement ati onst rategy woul d be f or each sal es rep t o havean agreeabl e techni cal support st af f at hi sor her si de as sal es cal l s ar e made. Therep woul d be i n cont rol of t he sal es cal las i t unf ol ds and woul d be abl e t o di rect l ydrawon t he staf f ' s expert i se i f and wheni t i s needed f or cl ar i f yi ng cust omer prob-l em, off eri ng recommendati ons, and j ust i f y-i ng advi ce that i s gi ven. The company' s topmanagement has opted f or t hi s approach t oi mpl ement i ng i t s competi t i ve st rategy, butw th one except i on. Rather t han the i mprac-t i cal i ty of a techni cal support t eamphysi -cal l y accompanyi ng each sal es rep, t heteams expert i se i s capt ured i n one or moreexpert systems. Wt h a port abl e mcrocomput er, each sal es r ep w l l be accompani edby an appreci abl e port i on of t he suppor tt eam s exper t i se. Rather t han att empt i ngt o t rai n reps t o an expert l evel , t hei n-house experts trai n (i .e. , create) expertsyst ems. The company t her ef ore has acontrol l abl e asset t hat cannot be l ured awayby t he compet i t i on.

The competi t i ve advantage that resul tsf romenhanced ser vi ce may or may not bereproduci bl e. To t he ext ent t hat a compet i t or has equi val ent ( or super i or )i n- houseexper t i seandcanhar ness i t i nacomparabl e way, the ini t i al competi t i ve edgemay not be ful l y sustai nabl e. Nevert hel ess,the f i rst ent rant i nto the marketpl ace w th

thi s enhanced servi ce may have created someentry barri ers f or compet i tors that consi derf ol l ow ng i t s l ead. For i nstance, i t mayestabl i sh i t sel f i n customers' eyes as t hel eader i n pr ovi di ng t hi s servi ce. Thi sposi t i ve i mage can be di f f i cul t f or competi t ors t o overcome. As cust omer s becomeaccust omedtot he l eader ' s expert syst ems,they may fi nd i t i nconveni ent or uni nterest -i ng t o bother w th others. Fur thermore, thel eader has a l earni ng curve edge i n appl yi ngt he technol ogy t o achi eve a competi t i veadvantage. Fol l ower s ar e l i kel y t o be ast ep behi nd as t he sal es support expertsyst ems cont i nue t o evol ve.Pr ovi di ns New Servi cesRel ated t o the i dea of enhancedservi ces i s the not i onof newservi ces. A si n t he case of t he chem cal company anenhanced servi ce i s concerned w th i mprovedf eat ur es, gr eat er t i mel i ness, great ert horoughness, and so on. A compet i t i vest rategy coul d al so be ai med at f urni shi nga new servi ce that draws customers t o acompany. For i nst ance, t op management ofa retai l bank has deci ded t o i ntroduce a newservi ce t hat has not been of f ered by ot herbanks of i t s type and si ze. I n consi der i ngconsumer l oans, t hese banks present l y useri gi d scor i ng protocol s that l ead to ei thert he accept ance or r ej ect i on of a l oanrequest . The r etai l bank noted abovei nt ends t o i ncr ease i t s customer base byoff eri ng an i nvestment banker ' s servi ces toi t s cust omers.I n tr adi t i onal i nvestment banki ng, anexpert works out a customzed f i nanci ngarr angement sui t abl e t o a cl i ent company' sneeds. Thus, t he retai l bank' s compet i t i vest rategy i s based on provi di ng a newservi cei n whi ch l oan i nst rument s are t ai l ored t oi ndi vi dual consumer si t uati ons. I n con-si der i ng howt o i mpl ement thi s st rategy, i ti s cl ear t hat subst ant i al exper t i sewoul dbe r equi red t o ef f ect i vel y handl e thecr eat i on of customzed consumer l oans.However, t he bank woul d not be f i nanci al l yj ust i f i edi nhi r i ng suf f i ci ent i nvestmentbankers t o handl e the rel ati vel y l argenumber of rel at i vel y smal l ( dol l ar - w se)appl i cant s. But an exper t systemt hatembodi es t he sophi st i cated reasoni ng be-havi or t hat an i nvest ment banker woul ddi spl ay f or consumers coul d be f i nanci al l yat t racti ve, especi al l y i f i t were shared bya consort i umof ret ai l banks. As i n t hecase of enhanced servi ces, reproducabi l i t yand entry barr i ers are i mport ant i ssues whenconsi der i ng new servi ces i mpl emented vi aexpert syst ems.Swawni nq New I ndust r i esSome busi nesses may choose t o par-t i ci pat e i n new i ndust r i es t hat are madepossi bl e by t he advent of powerf ul and

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f l exi bl e t ool s f or expert syst emdevel op-ment . Thi s part i ci pati on can pr oduce adi versi f i cat i on t hat hel ps t he companycompetemore ef f ecti vel y. Anexampl e i s anewi ndustry concerned w th the publ i cati onand use of expert i se.There are two tradi t i onal ways ofdel i veri ng advi ce. One i s by means ofbooks, ar t i cl es and l ectures. Thi s of t enrequi res consi derabl e ef f or t t o f er ret outthe pert i nent recommendati on. Someti mes theadvi ce i s not expl i ci t , but must be i nf erredby usi ng reasoni ng expert i se t hat i s pr e-sented i n books, art i cl es and l ect ur es.The second maj or del i very method i nvol vesconsul t i ng f i rms and prof essi onal servi cesoff ered by l awyers, accountants, and physi -ci ans. Here the generat i on of advi ce i smore speci al i zed t o i ndi vi dual cl i ent needs.I t requi res l ess ef f ort by t he cl i ent t hanr eadi ng books or att endi ng l ect ures.However, t he avai l abi l i t y of t hi s del i verymethod i s rel at i vel y l i m t ed andcost l y.Exper t systemtechnol ogy of f ers ast r i ki ng al t ernat i ve, suppl ement , andcompl ement t o t radi t i onal ways of del i veri ngadvi ce. I t woul d not be surpr i si ng t o seet he emergence of a new i ndust ry concernedw th the publ i cati on of computeri zed exper-ti se. For i nstance, t here w l l l i kel y benewbusi nesses concerned w th produci ng anddi str i but i ng chunks of reasoni ng know edge,each addressi ng one of a w de var i ety ofprobl emareas f r omveh i c l ema i n t e n an c e t of i nanci al management . Each chunk w l l becapabl e of bei ng q9pl ugged n" t o a st andard,general i zed i nference engi ne. We may evensee "expert - of the-month" of f eri ngs aki n t ot he i deaof book- of - t he- mont h sel ecti ons.There w l l be subscri pt i on servi ces forprovi di ng new and updat ed expert i se. Thenet ef f ect w l l be w despread di str i but i onof expert i se whi ch, when pl ugged i n to ani nf erence engi ne, resul t s i n responsi veconsul t at i ons at rel at i vel y l ow pri ces.As another exampl e, t here i s a needt o di st r i but e exper t i se on the uses andappl i cati ons of t he masses of knowedge thatw l l soon be commonpl ace on opti cal compactdi sks (e. g. , 500, 000, 000charact ers on asi ngl e smal l compact di sk). Many ki nds ofknow edge coul d resi de on a compact di sk(CD). Ef f ecti ve usage of such know edgest orehouses w l l be a paramount i ssue. Theavai l abi l i ty of expert system that can hel pusers di g out and appl y the i mmedi atel yrel evant subset of know edge i s aki n t ohavi ng the assi st ance of a combi nat i onl i brari an/ teacher. We expect that an ent i rei ndust ry can devel op around t he automated,i ntel l i gent del i very and appl i cat i on of al lt ypes of know edge. I nt er est i ngl y, t hi si ndust ry coul d have a si gni f i cant i mpact onthi rd worl d countri es, by great l y expedi t i ngt he t ransf er of know edge t o them i n acost - ef f ect i ve manner . The resul t ant

comput er- based "peace cor pst 1 oul d be aval uabl e compl ement t o i t s human counter-part.A t hi rd exampl e of a new i ndust rymade possi bl e by advances i n exper t syst emt echnol ogy i s concernedw t hconst r uct i ngart i f i ci al l y intel l i gent appl i cati on systemf or record- keepi ng and deci si on support .Some may pref er t o characteri ze t hi s as ar edef i ni t i on of an exi sti ng i ndustr y. I nany case, t he impl i cat i ons are f ar reachi ng.Rat her t han thei r t radi t i onal passi venature, t hemanagement i nformati on systemsand deci si on support systems bui l t by t hi snew i ndustr y w l l di spl ay an acti ve, i n-qui si ti ve, i nsi ghtf ul behavi or. Art i f i cial -l y i nt el l i gent appl i cat i on systems ar e anatural resul t of t he i ntegral t reatment ofexpert systemand f aml i ar busi ness comput -i ng capabi l i t i es and are a key to the futurereal i zat i on of know edge-based organi zat i ons[81*

Chal l ensesUsi ng exper t syst ems t o i mpl ementcompeti t i ve st rategi es presents t op manage-ment w t h chal l enges as wel l as oppor t un-i ti es. These chal l enges ar e t echni cal ,economc, and manageri al i n nature. Aconvent i onal vi ewof recent years has beent hat expert syst ems are expensi ve, t ake al ong t i me (e. g. , years) t o devel op, andcannot be bui l t by persons w thout advanceddegrees i n art i f i ci al i nt el l i gence [9].Such character i st i cs, of course, l i mt thepract i cal appl i cabi l i t y of expert systemtechnol ogy t o busi ness probl em. The quotaexpert systemwoul d be i mpract i cal i f eachsal es manager needed a $50, 000LISP machi net o run i t on, r ather t han an i nexpensi vemul t i purpose mcrocomputer. The appeal ofan i nvestment banker exper t syst emt o aretai l bank woul d be much more dubi ous i fi t cost $150, 000 r ather t han $15, 000.unt i l very recent l y, t he conventi on-a l v i ewhasbe enagene ra l l y c or r e c t v i ew .The reason f or t hi s i s r oot ed i n t he tool st hat were avai l abl e f or expert systemdevel opment. One t ype of tool i s a programmng l anguage such as LISP or PROLOG. Amore advanced ki nd of t ool , cal l ed an expertsystemshel l , appeared and great l y f aci l i -t ated expert syst emdevel opment ef f ort s.A shel l provi des a general i zed i nf erenceengi ne that i s abl e t o r eason w t h manydi f f erent set s of rul es. Wt h a shel l , t heact i vi t y of devel opi ng an exper t systembecomes one of speci f yi ng a set of r ul esthat i t s i nf erence engi ne can process.

Whi l e shel l s t ypi cal l y al l ow mor ef aci l e expert systemdevel opment t han apr ogr amm ngl anguage, t hey ar e st i l l di f -f i cul t t o work w t h f or many pot ent i albusi ness appl i cat i ons. Because of t hestand-alone nature of a shel l , i ts i nf erence

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engi ne i s i ncapabl e of carryi ng out commonbusi ness comput i ng acti vi t i es such asspreadsheet anal ysi s and data base manage-ment. Thi s i s a cri ppl i ngl i m t at i ont hatmakes many potent i al busi ness expert syst emtechni cal l y or economcal l y infeasi bl e. mti t has been overcome recent l y by a newki ndof devel opment tool : anAI envi ronment f orbusi ness comput i ng [ 4 , lo].

An envi ronment has al l t he capabi l i -t i es of a shel l . However , i t s i nf er enceengi ne i s much more potent because of i t si nnate abi l i ty t o car ry out al l of t he usualbusi ness comput i ngt asks i ncl udi ng spread-sheet anal ysi s, gr aphi cs gener at i on, dat abase management, remote communi cat i ons, textprocessi ng, and so on. Thi s bl endi ng of AIand busi ness comput i ng t echni ques i nto asi ngl e pi ece of sof t ware means t hat t hequota expert syst emi s abl e to do spread-sheet anal ysi s ( e. g. , w t h respect t oadver t i si ngbudget s) , dat abasemanagement(e.g. ,w th respect t o a rep' s past per f or -mance) , and econom c model i ng (e. g. , f orl ocal growt h proj ecti ons) i n the m dst ofi t s i nf erence f or a quota probl emBecause they support f aml i ar busi -ness comput i ng appr oaches t o know edger epr esent ati on, AI envi r onments ar e moref l exi bl e and natural to use than stand-al oneshel l s. Thi s t ransl ates i nto si gni f i cantl yf aster and l ess expensi ve expert systemdevel opment . By t he end of a si ngl e semes-ter course, busi ness students w th no pri orAI exposure ar e abl e to use an AI envi ron-ment t o bui l d i nt er est i ng busi ness exper tsyst ems that woul d be di f f i cul t ( i f evenpossi bl e) f or AI speci al i sts equi pped w thl esser devel opment t ool s. The i mport antpoi nt i s t hat t he convent i onal vi ew ofexpensi ve, l engthy and el i t est devel opmenti s no l onger appropr i ate when consi deri ngbusi ness expert system. The techni cal andeconomc chal l enges posed by pursui ng a

busi ness exper t syst emroute are by no meansi nsurmount abl e, provi ded care i s t aken i nt he sel ect i on of a devel opment t ool .The manageri al chal l enge i s i n l argepar t one of not mssi ng opport uni t i es suchas those di scussed i n t hi s art i cl e. Manage-ment t hat pays att ent i on t o t he st r at egi ci mpl i cat i ons of expert systems and i s al ertt o thei r possi bi l i ti es can fi nd i tsel f w tha compet i t i ve edge, r ather t han bei ng outon a compet i t i ve l edge. Today' s gr eat estobstacl e to meeti ng t he manageri al chal l engei s perhaps a l ack of cl ari t y about whatexpert syst ems are. Management needs t ounderst and what can and cannot be done w tht hi s emergi ng t echnol ogy.I t i s our sense that management

general l y has expectat i ons that are too l owrather t han t oo f anci f ul . Fewmanagers havet he unreal i st i c convi cti on t hat exper tsystems canexhi bi t creat i ve i magi nat i on,

i nt ui t i on, or deci si on maki ng abi l i t i es.Far t oo many, al t hough i nt erest ed, areunsure about j ust what i t i s ( i f anythi ng)t hat t hese syst ems can actual l y do i n abusi ness set t i ng. Thi s gap i n educat i onw l l eventual l y be cl osed as coursework i nbusi ness exper t systems i s i ncreasi ngl yi nt roduced i nt o busi ness school cur r i cul a.An ent i re course may be devoted t o the t opi cor i t may be pr esent ed i n connect i on w t hsuch subj ects as deci si on support syst emsor know edgemanagement . Bywayof hands -on, case study i nst ruct i on, i t w l l be seent hat expert syst ems are not so myst eri ousaf ter al l .

I n t he near term corporate trai ni nggroups and i nformat i on cent ers can hel pcl ose t he gap. Experi ences gai ned f romexperi mental expert systemproj ects can al sobe hel pf ul , provi ded they are "successful . IHowever , i f t hese f i r st exper i ences ar e' 1f ai l ures' 8 here i s a danger of poi soni ngt hewel l . Themai ncauses of unsuccessf ulproj ects seemt o be i dent i f i cat i on of aprobl emthat i s t oo l arge i n scal e, l ack ofexpert cooperati on, devel operdef i ci enci es,and sel ect i on of an i nadequate devel opmentt ool . Care shoul d be taken t o st art outsmal l and l et t he expert systemevol ve i ntoal arger scal e. Acooperat i veexpert f romwhomnecessary reasoni ng know edge can beacqui red must be avai l abl e. A chosendevel oper shoul d be acquai nted w t h theexpert syst emdevel opment cycl e, competentat i nterpersonal deal i ngs, and suf f i ci ent l yadept at usi ng t he chosen tool .

Once t he educati onal hurdl e i scl eared and a commtment i s made to expl oi t -i ng expert syst emtechnol ogy, t here remai nst he chal l enge of gai ni ng accept ance ofbusi ness expert system w thi n the organi za-t i on. The organi zat i on' s cul t ure and t hei dent i t y of t he pr i me mover i n promot i ngthi s technol ogy (e.g. , depar tmental manage-ment , M S depar t ment , nf ormat i on cent er,t op management ) w l l det ermne howaccep-t ance can be engendered. I n any case, i tmust be made cl ear t hat such systems do nott hreaten ei t her human expert s or t hoseseeki ng advi ce. An expert syst emcan reducedemands on a human expert ' s t he , i nsul ati nghi mor her f r ommanyki nds of consul t at i onrequest s. Thi s al l owst hehumanexper t t of ocus on the most chal l engi ng probl ems, adhoc probl ems, and newcr eat i ve acti vi t i es.Conversel y, t hose seeki ng advi ce do notencounter t he usual bott l eneck of compet i ngand wai t i ng f or t he human exper t ' s att en-ti on.

I t must al so be underst ood t hat, l i kei t s human count erpart , an expert syst emsadvi ce i s dependent on the extent andqual i ty of i t s exper t i se. I f t he expertbei ng emul ated of t en gi ves poor advi ce theexper t syst emw l l do t he same. I f t heexpert syst emdevel oper does not accuratel y

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and f ul l y capt ure an expert ' s know edge i nt he syst em then t he emul at i on suf f er scor respondi ngl y. Ul t i mat el y, i t i s up t ot he one recei vi ng advi ce t o put i t i nt oproper perspect i ve and to properl y f actori t i nt o deci si ons t hat are made.I nt roduci ng expert syst emechnol ogyi nto an organi zat i on i s not a one-shotendeavor. Mul t i pl e expert syst emappl i ca-t i ons t end t o be i dent i f i ed. Many cont i nueto evol ve t o keep pace w th evol vi ng reason-i ng know edge. There i s al so a tendency t oundert ake i ncreasi ngl y ambi t i ous appl i ca-t i ons. ~n i mportant aspect of managi ng t hi sgrowt h i s t ool sel ecti on. I n t he i nt erest

Ref erencesE. W McFar l an, l l I nf or mat i onTechnol ogy Changes t he Way YouCompete, " Harvard Busi ness Revi ewMay- J une 1984.J . I . Cash, J r . and B. R. Kon-synski , ''IS Redraws Compet i t i veBoundar i es, Harvard Busi nessRevi ew March-Apr i l 1981.W B. Rauch- Hi ndi n, Ar t i f i ci alI nt el l i sence i n Busi ness. Sci ence,and I ndust rv, Pr ent i ce- Hal l ,Engl ewood Cl i f f s, New J ersey,1986.C. W Hol sappl e and A. B. Whi n-st on, Manauer' s Gui de t o Exver tSvst ems Usi ns Guru, Dow J ones-I r w n, Homewood, I l l i noi s, 1986.

of devel oper producti vi ty, f requent sw tch-i ng among t ool s i s undesi rabl e. However ,a pi t f al l t o be avoi ded i s st andardi zi ng ona t ool t hat i s j ust I f good enoughg1 orpresent appl i cat i ons. Not onl y does t hi sl ack of a growt h path st unt t he evol ut i onof expert systems, i t has a t endency tobl i nd devel opers t o what woul d be possi bl ew t h a more versat i l e and powerf ul tool .I n summary, achi evi ng str ategi cadvant ages w t h expert syst ems depends onsuccessf ul l y addressi ng t he techni cal ,economc, andmanager i al chal l enges i den-t i f i edhere. The r ewards of meet i ngthesechal l enges can be si gni f i cant .

M E. Por t er , I 'How Compet i t i veFor ces Shape Str ategy, HarvardBusi ness Revi ew March- Apr i l 1979.R. N Ant hony, Pl anni ns andCont rol Svst ems, Harvard Busi nessSchool , Bost on, 1965.H. A. Si mon, The New Sci ence ofManaaement Deci si on, Harper, NewYor k, 1960.C. W Hol sappl e and A. B whi n-st on, "Management Support ThroughAr t i f i ci al I nt el l i gence, 11 HumanSvst ems Manasement , vol . 5, 1985.J . Hewet t and R. Sasson, ExvertSvst ems 1986, vol . 1, Ovum Lt d. ,London, 1986.C. W Hol sappl e and M Gagl e, I nAIAppl i cat i on Syst ems1' HardcoDv,vol . 16, no. 2, 1987.

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