Pakm paper

1

Developing a Model for Linking

KMS and IC Measurement

Mário Paulo Pinto

Polytechnic Institute of Porto

International Conference on

Practical Aspects of Knowledge Management

Mário Paulo Pinto Maria Filomena Lopes Maria Paula Morais 2

Agenda

Introduction

Intellectual Capital (IC) Measurement Models

IC Measurement in Portuguese Organizations

Knowledge Management Systems (KMS)

The Proposed Model

Model Validation

Conclusions


KMS and IC Measurement System are normally viewed as separate and

discrete systems, without linkages and connections.

Linking them can facilitate the evaluation of the benefits and the impact of

KMS in the value creation

Introduction: clarifying the problem

Organizational knowledge

IC measurement

system KMS

Operational perspective Strategic perspective

Gap


IC Measurement Models Review IC Measurement Model

Skandia Navigator

Balanced Scorecard

Intangible Assets Monitor

Intelect Model

Intellectual Capital Index

Nova Model

Intangible Value Framework

IC Rating

Intellectual Capital Rating

Heng Model

Meritum Guidelines

Danish Guidelines

Value Chain Scoreboard

Chen, Zhu & Xie Model

Intellectus

Technology Broker

Citation-Weighted Patents

Inclusive Valuation Methodology

Total Value Creation

The Value Explorer

The 4-Leaf Model

IC Components

IC measurement metrics

(stock & flows)

Human

Capital

Structural

Capital

Relationship

Capital

40 metrics 70 metrics

33 metrics


IC Measurement in Portuguese Organizations

A study was conducted in Portugal based on a

questionnaire

Two main aims:

To know the current practices of Portuguese organizations

relating with IC management & measurement

To complement the IC metrics systematization with a

practical perspective


IC measurement in Portuguese organizations

Metrics Services Industry Metrics Services Industry

% employees of full-time X X Motivation index X X

% employees of part-time X X Employees satisfaction index X X

% temporary employees X X Nº of employees X X

% specialized employees X X Nº of expert employees X X

Absenteeism rate X X Nº of managers X X

Alternation rate X X Average IT literacy X

Average age of employees X X Average staff literacy X X

Years on company service X X Time spent in training X X

Distribution by age group X X Investment in training programs X X

% male and female X X Nº employees in training programs X

Experience index X X Value added per capita X X

Initiative capacity X X Profits by employee X X

Innovation capability X X Employees turnover X X

Leadership index X X

HUMAN CAPITAL




% critical processes in compliance with manuals

X Nº accesses to organizational bases X

% critical processes with procedure manuals

X Rate of knowledge distributed X X

Process efficiency index X X Diffusion of best practices X

Information systems capacity X X Rate of knowledge accessed/reutilized X

Nº of certificate products X Nº projects in collaboration with external entities

X X

Quality performance (ISO 9000) X X Protocols with innovation entities X X

Nº of tested products X X Nº projects with partners X X

PCs by employee X X New business opportunities identified X

Employees satisfaction index X X New products X

Nº customers per employee X Upgrading projects X X

Employees alternation rate X Employees until 40 years X X

Hours in development X X Innovation capability X X

Hours in training X X Nº innovative ideas that generate new products/services

X

STRUCTURAL CAPITAL




Investment in training X X Investment in TI per employee X

Investment in new methods and processes

X Administrative expense per employee

X X

Investment in relationship with stakeholders

X Administrative expense/total revenues

X X

Investment in IT X X Investment in new competences X X

Investment in IS X X Productivity rate X X

STRUCTURAL CAPITAL (cont.)




% small, medium, high customers X X Average time between first contact and close transaction

X

Customers geographic distribution X X Customer visits to the company X X

Average duration of customer relationship

X X Business alliances and partnerships X X

New customers/customers lost X X Company image X X

Orders repetition frequency X Market share in segment X X

Customer satisfaction index X X Investment in marketing X

Nº of customers X X Customer relationship investment X X

Nº of lost customers X X Investment in TI X X

Nº customers /employee X X Revenues per customer X X

Nº of customers claims X X Administrative expenses per customer

X

Sales rate to new customers X X Annual sales per customer X X

Sales rate to new markets X X

RELATIONSHIP CAPITAL



IC metrics identified

27 metrics for human capital

36 metrics for structural capital

23 metrics for relationship capital

Considerations

There aren’t strongly differences between the metrics identified

by service and industry organizations

These metrics will be used to complement the metrics

systematization


KMS Classification

Business intelligence

Collaboration systems (groupware)

Competence management systems

Corporative portals

Document management systems

E-learning systems

Expert systems

Knowledge discovery systems

Knowledge maps

Workflow systems


The proposed Model Id

en

tify

ing

inta

ngib

le a

sse

ts

IC measurement

model

IC measurement

system

Knowledge

Management systems

Measures provided

by KMS

A MODEL FOR LINKING KMS AND IC MEASUREMENT

Measures provided by

other systems

Other systems

ER

Ps &

CR

Ms

Fin

an

cia

l syste

ms

Qu

alit

y s

yste

ms

Oth

ers

IC measurement model

and selected metrics

Re

alig

nin

g c

ritica

l in

tan

gib

le a

sse

ts w

ith

str

ate

gic

obje

ctive

s

Strategic Objectives & Success Factors

Ide

ntify

ing

KM

S c

ate

go

rie

s

Inte

gra

tin

g

KM

S w

ith

IC

me

asu

rem

ent

Eva

lua

tin

g

resu

lts

IC measurement

report

Cause-effect relationship

Ide

ntify

ing inta

ngib

le

asse

ts

A MODEL FOR LINKING KMS AND IC MEASUREMENT SYSTEM

Measures

provided

by KMS

IC measurement model and

selected metrics

Me

asu

res p

rovid

ed

by o

the

r syste

ms

IC measurement report

Rea

lign

ing

cri

tica

l in

tan

gib

le a

sse

ts w

ith

str

ate

gic

ob

jective

s

OTHER SYSTEMS

Fin

anci

al s

yst

ems

Qual

ity s

yst

ems

ER

ps

& C

RM

s

Oth

er s

ourc

es

OTHER SYSTEMS

Intangible assets

IC MEASUREMENT MODEL

Human capital

Structural capital

Relationship capital

IC metrics Human

capital

Structural

capital Relationship

capital

Metrics

specification

Intangible assets

IC MEASUREMENT MODEL

Measurement

model

Metrics

Intangible

assets

IC measurement

Measures


Knowledge maps

E - learning systems

Business intelligence systems



Workflow systems

Expert systems

Collaborative systems

Corporative portals

Knowledge creation

Knowledge storage

Knowledge distribution

Knowledge application

KNOWLEDGE MANAGEMENT LIFE CYCLE KNOWLEDGE MANAGEMENT LIFE CYCLE

KNOWLEDGE MANAGEMENT SYSTEMS

Knowledge distribution

Knowledge storage

Knowledge creation

Knowledge application

IC MEASUREMENT SYSTEM

Corporative portals


Collaborative systems

Expert systems

Workflow systems

E-learning systems


Business intelligence systems

Knowledge maps


Fin

ancia

l syste

ms

Qualit

y syste

ms

ER

Ps &

CR

Ms

Oth

er

sourc

es

Ide

ntify

ing

KM

S c

ate

go

rie

s

Inte

gra

tin

g K

MS

with

IC m

ea

su

rem

ent

Eva

lua

tin

g

Strategic Objectives & Success Factors


Measures provided by KMS to quantify IC

metrics: methodology

IC measurement

models

Survey from

Portuguese organizations

Main Issues & functionalities

IC metrics

systematization

52 software tools from different KMS categories were analyzed

IC MEASUREMENT

KMS CATEGORIES

Measures provided by KMS to quantify IC metrics

theoretical approach practical approach



metrics KMS categories Measures provided by KMS

Knowledge Maps

-Rate of knowledge availability

-Rate of knowledge accessed/reutilized

-Contributions to organizational knowledge base (#)

-Rate of knowledge reutilized/distributed knowledge

Collaboration Systems

-Contributions to organizational knowledge base (#)

-Projects in collaboration with external entities (#)

-Projects developed in collaboration with other workgroups (#)

-Rate of best practices diffusion

-Questions reported and answered in forums (#)

-Rate of knowledge distributed according employees profiles

-Expert employees (#)

Expert systems

-Experts with specialization degree (#)

-FAQs accessed (#)

-Contributions from experts: rolls, best practices, advices, suggestions (#)

-Rate of expert knowledge reutilized

-Contributions to organizational bases (#)




Workflow systems

-Critical processes completed without errors (%)

-Critical processes in compliance with manuals (%)

-Processes upgraded (%)

-Processes completed in time (%)

-Automated business processes (%)

Knowledge discovery

systems

-New patents (#)

-Patents in registration (#)

-Years average of registered patents

-Rate of knowledge reutilized in new contexts

-New ideas to upgrade products, services or processes (#)

-New business opportunities identified by innovation processes (#)

E-learning systems

-E-learning training programs (#)

-Hours spent in training programs

-Employees with specialization degrees based on e-learning programs (#)

-Rate of employees in training programs





-Employees by group age (%)

-Average age of employees

-% of female and male employees

-Rate of absenteeism

-Rate of employees rotation

-Employees with advanced degrees

-Employees satisfaction index

-Average years in service

-Average literacy & average literacy in IT

-Recent employees (less two years) (%)

Business intelligence

-Market share in the segment

-Rate of investment in new markets

-Geographic customers distribution

-New costumers/costumers lost (%)

-Rate of sales to new markets

-Rate of sales to new customers

-Customers distribution (%): small, medium, big customers

-New business opportunities captured





-Accesses to knowledge repositories (#)

-Contributions to knowledge repositories (#)


Corporative portals

-Rate of knowledge distributed according employees profiles

-Rate of knowledge distributed/applied



Model validation

The model has been evaluated by an expert panel

in order to test his validity.

A questionnaire was sent to 40 experts (researches,

practitioners and consulters)

It includes 9 questions with a five-point scale

14 valid answers were received, corresponding to a

response rate of 35%


Model validation

Scale

Questions

Totally Much Little Nothing Don’t know

1. Do you consider the model useful? 46% 54% 0% 0% 0%

2. Do you consider the model comprehensive? 15% 77% 8% 0% 0%

3. Do you consider the model complete? 0% 50% 33% 0% 17%

4. Do you agree with the model components? 8% 84% 8% 0% 0%

5. Do you consider the model structure coherent? 8% 92% 0% 0% 0%

6. Do you agree with the IC measurement model component? 31% 61% 8% 0% 0%

7. Do you agree with the KMS component? 15% 85% 0% 0% 0%

8. Do you agree with the IC measurement system component? 8% 84% 8% 0% 0%

9. Do you agree with the measures provided by KMS to quantify the IC metrics? 8% 76% 8% 0% 0%


Conclusions

The model is an attempt to show the KMS contribution to the

IC measurement, filling the gap between these systems

It contributes to evaluate the success (benefits) or failure of

KMS initiatives

It enables a more automated and systematic IC measurement


Conclusions and future work

Future work

Improve the model specifications

Model validation through case studies

Mário Paulo Pinto

Email: [email protected]

Thank you for your attention!

mailto:[email protected]

Education

Pakm paper