P110l fUllng

CHAPTER ONE INTRODUCTION

7. Set implemenlation goals and IJmelables;

3.2.1 P110l fUllng

3.2.2

,c

e Questionnaire

ha data for thisrvooarch was ,r;:ollecllKl through a questionnaire. Leedy ,(1997, p191) defl es a questlonnaire as "a dala galherlng technique which is particularly sUllable when the dBla needs to be obtained from geographically dispersed peoplo·. The quesTIonnaire designed in this dlss rlalioo conlained Ihree types of measuring 'instruments asdisplay-ed in Flgure 3.2 below,

Figure3.2M9asunng Instruments

Type of Instruments Example from

Questlo,n:naire Adininislmtjve- k!§/rumenls .. How long have you been employed

by

the IBM Ask general, baCkg round feCS) S&C?

Inlonnalion

CJass}ficarto,a Insrrumenrs " What sub-solution area are you in?

Ask demographic vaJ1lables

^'0

What band are you currently?

Tarwt inslwments '" I am aware tha,t knowledge gaps exist In !he S&C Comprise slruc{ured'cfosed business u

it

(Strongly agree, Disagree, NeFther questions. They provide a agree

~or

disagree, Agree, Strongly agree).

checklist or quesUons 10 " Labour turnover impacts knowledge management choooo from. (Strongly agree, Disagree, Neither agree nor

disagree, Agree. Strongly agree),

Target /nstfllmerns What do you understand

byIne

term knowledge Comprise unstrlJcluredJ open- managemenl gaps?

ended questlons. They do not Do you believe Does liBM (BCS) has a strategy for Ilmil the responses. knowledge mansgemBflI1

.. What changes,

if

any, should IBM (BCS) consfder In t.erms of knOWleClge management/preservation, in orderto survive in the long lerm?

.

.

A lolalc! 30 queslionnalres were dlst.rlbuted, how ver, not all

30

questionnaires were completed due to the number ot ooosullanls who resigned over that period,

l.ntlTC'ltfl f,

3.2.3 Drawing

a

8am plo

Wegner (1993, P 170) delloos sampling as he process of Sl;Ilecting a representalive subsel

of obServalJions from a population

to determine the characterislics

(i.e.

the populalion paramelers) 01 a IOll"lclom variable under study".

The

researcher used a torm of probability sampling refelled to as proportionate stratified samp1in9. This means Ihat the

poplIration

selecled (·or

Ihis stlldy was

drawn Iroma subpo-PlJlation 01the broader business consulling group. The busmess consulting group oomprises 7

clearly

dlsllngulsl1able

sUbgroups,

(Application

Innova1ion; Bus;ness

Transformalion

OlllSOllrcing (BTO):

Customer Relationship Maoagemenl (CAM);

Financial ManagelTlE!lltj Human Capital Management;

Strategy

and Change; and Supply

Chain Management). Thereooarcher selected the entire population

ffO/Tl

the Strategy

and

Change as a targel

papulalion

for U1~study. "In proportlonale slratified sampling eacn

slralum

lsproperly represented so lhat

the

sample drawn

from

~

lS

proportionate

to the

stralun;'$ share 01the

100alpoplJJaUonr"

(Cooper&Schindler 2003, p195).

The benefit of probabifity sampl1ng is mora ,reliability am;! it creales a Sf;!nso of comfort U1al

lhe

sample selecled ~s representative of that population.

The

limitation with sel'ecling stralllied sampling ls that results c~m.notbe applied to any of the olher solullon areas or the broader IBM populallon.

3.3 Identifying Oats Requirements

According 10Cooper

&

Sclhlndler(2003),

dala

identification

is

genl;l/lllly categorized inlo three calegories, primary, secoooary nd tertiary d ta sources. The researcher identified the following data requiremenls:

:U..1 Primary ID..la SQI.lrt'es

Primary dela was collected from the IBM lntranel and human resources stalJslical

records reflecting nllmber

of resignations over [he period:. This data source

was-

used during theexploralory phase of the research 10 deverop Ihe research

problem

and subsequenthypolheses.

31.3;2 S - .and

ry

t Sour,ce '

S

condary dalB

was

use or

rticl

:5,

b

.~n $ " m

Is

n@Mpap TS nd

case

studies"

I I - Souree ;

frQl1il v rim.J$~ tlS

el:s les.

-t le

reme be ttuu aJ I Ilnf' ation

0'

eq

J

valu . As

I in ic

J ,

^[JJ "mary SOUI'"(: _S ,., v mQr _ 'It IUf!! lh f1 $M:orula ,SOurces

. SOI!J ,"

hav'

m' V 1

th,

t,.

iary c ree Co

r Sc'hindl r

3 ,D ,Coil ',n PI Accoathng to

^CO'

er

&

OUm

tOllr irnpo ' Iltq;u. tion ~

2003), the ililteiDn of the d t coll'ed0 pi· n is [0

0, ' t n rl how:

1 , 1 1 0'

n1S' a^I'll

q

s" nalreAppend" 1)is(fs~ 'e le' ilL tons tan e' I@yed In the S C SOl tion Ar,ea as ,t LI - 2 { l .

e

questionn re as eil - ¹ Hed or repied dl hamteOllo msponc:lents. -e a "gin I

nurn

b Jdistri t:lutl13d was 30 but ani, 23

q.

$'I - r ,complet .:.'

d

⁰ th - n mlb r of tfSILI n", .ho r si

n

^DV r th

"00.

rc· ed

Im . c kno"M.ledc:ra

l·

mover ur

fin;.

1

'.lla~Ie..men.

l/'TIe ca a f'O

10"

. tlon . Hol1s

eses 'ere

... 5 1

Co

e S '. legy n C

inap·

eof

consul; nts,

. red,

not CO peenrt

in

Sfa

e!;fc

'owledge, tools

, ...

^,~,

...

,.~"'""'~_._-,.-

-

Core Sl,al8\ll'

arM!

CIIange

$I<ib

are <liminishing l>!lCause

~are~l8MlecSl.

Core Sl'.legy _

Olange

sl<iIs are

\liminIsIW"og

1>!lCa.- IBM lBCS) is lI<>M>Sl2ing

byfIOI filingvacMl posIlions, 3 .•.3 _

ne ^{IIming 01} thoI PI"liculllll SIW;

ie extremely _~. " _ _~e<l

_ 2

yftar$ _

IBM ~

PIoC Consuttng.

The

rese.n:!lef is awa,a

IhaI

een"", fIe9'lIiva

responses

in

I!>e

Ql.WIioIYIaire

00<Jd ^tl/t !loO h> pOOf

CI'\lJn9ll

~

<luring Iha

acquisiIim proc:esI.

AnolI>ar laclOf is """ IBM IBCS) la

experiEMcIr'll sigoiflcari labour

t... _

me)'

also

lnIIuence ltla1IrdIngs,

3 .•.4 Ho..

T1"e

~, (Appenclx

I), _ . - III oI>lain

il<JIh

quaIitalivoe . . , quantiIalNe

data, CompIeIe<l qr..-lionnaIr9o ... _

9 _

days

all""

b e i n g _ ,

The

app-oacIllO

eacI> _ in

I!>e

'1'.-1-'

^waR10 ... _

!tYoI.V'

_

~ivaetquanti\aIlYa1aCIlrOqun, The ~ioma"o

was

designed

as _ :

S<IclIiotI

il uses

~_

maas..o,..

le

<lal'"'''''''' _ rlOSlX"_1tS "'0 1 _ wim oonc"flb 01

~ ~

en<!

~

Pf8M<Valion. S«:tion B ("!SI pat!) also uses

qwliIa1ive

18<:Iv"OQI.- 10 Iisl

gene<>lI

no<rn<otion par '...-.

The

oeecnd

pan 01 SoIGIIon B uses

~<ltiva

lecl:v1lqI.Ms as a ba5ls lot

l>:lde/standiIng ~

gaps '""""'II5l - . . . . <Xli'lS<lIlanI3. S«:tion C uses a

~iva ~ le ...~ ~ perceQlions ... ltla . . . -

01

labour

t..."" _

~ _I!>eren1..,.,..,., on e><isting ~

gaps

wlttlin IBM (SCSI,

3.. Ope<_

Dellnlllon. 01 011 v ...b1. .

"ComlSion """'"

"...,.ong

01 """""IllS can

<les1roy •

resear<:h SlWy"I .aluo

wiIt'o<.C ltla

"'_ _ ...en

l<no'oW1g •• " I'lIlJfdI ' - "

<*11"""" - . g o

h> "'" pani80 _ ,

then

!hey "'" fIOI

<:<>mmlricating

M ltla

aame

WlI..e1et1g1h

Dehnibons ... one way

10

'-!I"Q <lan\I8t" (Cooper & SctW"der 2003,

~51,

... ^, ... ^, -'- ^{.. ,,, ...}

3.5.1 0 _r,arOll1lia

ope ,tional. e

,i

1'10 ' ~

ne

the meas re e ~ '~, ,"0 USOO,

Sine hi,

d5:Sertation s prlim "Iy foCUSed on measuri as wledge

corn m

illT! f1', 010 .

on c

lit

,tu p, nt'd

by

r 2000).

S. t

s th d 'ini . apet

anal dejrJ • .

s b.eoo as. even m ' e cri lea!,

fa'00 d~''initions

s _ s or Busin

o

o G

Co~

raLe

^J,

'\:j

B d

:Sand

I

v 1 7

'0

10

^1•

tegy.

the enomenon

tbei

res-ea,

ed.

he ~ol owl - ,Iare exam ._~es of varia ] ~ lim !l\no'lMi13lclge

due:

'0111 ' .'

nd n' varia

im t

b,e

vs

3.5,..2

A

V '

dI ~iabilirty

nrn

a

UF ~

ffici n1 ,as si.

e rmJ)OftMC ' 0 leSti

co

wlilalthe rese rchmqui ,

3.6 1 '

~

d Y a Ill) lam: ,- dies

-e, resaa.rc ph' s d pilot s .

means

10

les ..~ ~h'vatl

Ily

, m1

re'liabim ,01

Ihemeasuringlinsftrom '

s.

Th irrst

phas '

Im

stu

f ' .

use ,sUn v f' i

0

he' eraslIJ "ng ns

^I

en'ts

by t

","ewln, 2 senior IB, parlners to de e - , lheEIi1,er:

he research top' _

VilOU

dI b ' IciaJ

0 th organisa

i

I'll'

Cl d u -

e

Si

n hie- a

¹

h r lelJ'8nt

bt ind.

o 8filSaure od:ie51

~Sec

:and

-0

Section B

CCll1ltp "_

,Sub·So .

rI Alii C. S

con

Iy,

-I

Idu I pts m u dersl

~

nd I e orlg' s a knowlBd - g. - -nd i vrtes tliJe respond - s

10 ¹ V

lual

rnl 'Of

I'

OOUT turnover

a.oo

~ bOutr redootion on knoWJed - gaps wlfrl 18 (BCS}_

3 6.2