SELF-AD

APTIVE CUSTOMIZING WITH DATA MINING METHODS

A Concept for the Automatic Customizing of an ERP System with Data Mining

Methods

Rene Schult and Gamal Kassem

Institute of Technical and Business Information Systems

Otto-von-Guericke-University Universityplace 2, Magdeburg, Germany

Keywords:

ERP systems, reference model, data mining, workﬂow.

Abstract:

The implementation of an ERP system is a long and cost intensive process. Functions of the ERP system,

which are delivered in an enterprise neutral but sector speciﬁc fashion need to be adjusted to the speciﬁc

business requirements of an enterprise. Exact knowledge of the ERP system is required because each ERP

system has its own technical concepts and terminologies. Therefore many enterprises employ ERP system

experts in order to customise the ERP system to be introduced as well as to further enhance the customisation

after its introduction. A concept for the implementation of a Self-Adaptive ERP System should allow for

the automatic customisation of an ERP system on the basis of the of enterprise process models provided and

analysis of the ERP system usage.

1 INTRODUCTION

Customising is the main phase of an ERP implemen-

tation process. The behaviour of the ERP applications

is controlled by the customisation. Changes within

the conversion of the ERP application parameters are

executed at this level (Peßl, 2004). First workﬂow

models of the enterprise are modelled. The work-

ﬂow, according to Gierhake, represents a work pro-

cess, which is extensively supported by technology

and is based on a triggered event, leading along a de-

ﬁned chain of part steps towards a deﬁned work re-

sult whereby the completion level of the work result

increases with each step. A workﬂow is the descrip-

tion of a speciﬁcation that deﬁnes which elementary

functions or tasks, that can be put into a standard, are

to be executed by a person, who has been assigned

a speciﬁc role at a given process state. If necessary,

required data processing application for object pro-

cessing are to be provided (Gierhake, 2000), pp. 57

ff.). At the implementation level, Rautenstrauch de-

ﬁnes workﬂows as ”...a part of a business process ...,

that consists of sequentially or parallel arranged op-

eration sequences (activities). Therefore it describes

subprocesses of the sequence organisation within en-

terprises. The activities themselves are implemented

as functions within applications systems. The cross-

applications are controlled and therefore can be bro-

ken out of the application systems ...” (Rautenstrauch

and Schulze, 2003), p. 269). The workﬂow model en-

compasses a description of all relevant aspects of the

workﬂow, which includes all incidental tasks, their se-

quences and dependencies. The model of workﬂows,

specially business processes of an enterprise, is a pre-

condition or basis for the customisation of an ERP

system. During the implementation of an ERP system

enterprise neutral sectoral functions are adjusted util-

ising the customisation on the basis of the modelled

enterprise workﬂows to the speciﬁc business require-

ments of an enterprise. ERP system reference models

are available as guideposts for experts in customising.

Reference models generally describe objects and re-

lations of the business reality. ERP reference mod-

els are pre-modelled on standard enterprise models

and shapes the business architecture of an ERP sys-

tem. Reference models often provide ”best practice”

business processes in the form of a software library

(Peßl, 2004). Therefore, the customisation is used for

the adjustment of the ERP system to the enterprise

requirements. The adjustment itself is done by the

speciﬁc ERP customising experts (consultants for the

ERP system to be introduced). With the help of ref-

erence processes all business operations that are sup-

ported by an ERP system are mapped. The separate

processes show tasks of a business situation that be-

long together logically. This can include a purchase

order processing with the focus set on the lowest

priced material, the vendor selection and order trac-

Schult R. and Kassem G. (2008).

SELF-ADAPTIVE CUSTOMIZING WITH DATA MINING METHODS - A Concept for the Automatic Customizing of an ERP System with Data Mining

Methods.

In Proceedings of the Tenth International Conference on Enterprise Information Systems - ISAS, pages 70-75

DOI: 10.5220/0001676800700075

 SciTePress

ing or a complete sales order processing from the cus-

tomer inquiry to the delivery and the billing. Through

the dependency of the processes on each other an un-

derstanding of cross-enterprise processes can be cre-

ated with the user and on the other hand the inter-

action of operational function units can be depicted.

The main task of customising experts is the imple-

mentation of the enterprise speciﬁc workﬂow models

in the ERP System. Reference models may be used

as a pattern for the system adjustment. The reference

models are to be considered here as supporting infor-

mation that helps customising experts to try and (re-

ality true) map the enterprise speciﬁc workﬂow mod-

els in the ERP system. With this experts should ac-

complish (resolve) two main problems: the terminol-

ogy problem that can arise through the different terms

used and their meaning in an enterprise on the one

hand and the terminology of the ERP system on the

other hand. A further problem may arise at the selec-

tion of the adequate processes from the ERP reference

models. The ERP processes should be selected and

adjusted so that the enterprise processes are depicted

in the system without developing new ERP functions

or changing the structure of the enterprise itself. In

this paper a self-adaptive customising concept is in-

troduced that leads to the solution of the above men-

tioned problems through the usage of different data

mining methods and which automates the customis-

ing procedure. Furthermore the concept should pro-

vide for the automatic execution of further customis-

ing procedures in the future. For that purpose the

structure of a self-adaptive customising middleware

system (SACMS) is presented that acts as a means of

mediation between the workﬂow models of an enter-

prise and the ERP system. The SACMS should pro-

cess different process modelling languages and ERP

systems of different vendors.

2 THE SAC CONCEPT

The idea of the concept consists of the creation of

an ”intelligent” layer between the workﬂow models

of an enterprise, which should be mapped into a par-

ticular ERP system, and the ERP system itself. This

layer provides for the automatic customisition of the

ERP system in which two customising types are to

be distinguished: the initial customising will be done

immediately at the implementation of an ERP sys-

tem, while the ”post-customising” is continually per-

formed within the scope of a Continuous Improve-

ment Process (CIP) and provides persistent improve-

ment of the ERP customising.

2.1 Initial Customising

At the time of the implementation of an ERP system

the enterprise neutral and sectoral speciﬁc function-

ality is adjusted to the speciﬁc business requirements

of an enterprise during the initial customising. The

initial customising covers three phases: conversion,

evaluation and implementation (see ﬁgure 1).

2.1.1 Conversion Phase

In this phase enterprise workﬂow models as well

as ERP reference models are converted in formal

workﬂow model formats such as e.g. workﬂow nets

(van der Aalst et al., 2003). Workﬂow nets stem from

Petri nets (Baumgarten, 1990). The enterprise spe-

ciﬁc terms used in enterprise workﬂow models are

translated in the terminology of the ERP system in

the conversion phase. With this special text mining

methods are used to recognise the meaning of a term

and translate it into a terminology of the ERP system.

Details to those text mining methods are shown at the

end of this section. As the sequence of activities or

functions of a workﬂow deﬁne its structure the main

task of the text mining is to recognise which workﬂow

activity is equivalent to an ERP transaction. Therefore

not only the activity term is to be considered, the busi-

ness objects involved in the transaction, the so called

”workﬂow reference objects” are to be considered as

well. The workﬂow reference object encompasses all

business objects processed by a function of a work-

ﬂow. The workﬂow reference objects can be divided

into following:

Output Objects. The result of a function is a trans-

formation of data for the processing of one or

more workﬂow objects. This object or these ob-

jects are denoted as output objects.

Input Objects. For the processing of output objects

by a function, data from other objects may be re-

quired. These objects are denoted as input objects.

For example during creating a sales order (an out-

put object), data about articles and the customer is

required.

Workﬂow Activity Object. A workﬂow activity ob-

ject is a workﬂow reference object that uniquely

denotes a workﬂow. For example at the execu-

tion of the workﬂow ”Production order process-

ing” the functions ”Create a production order”,

”Conﬁrm a production order”, ”Posting goods re-

ceipt for production order” and ”Release a pro-

duction request” are performed. The workﬂow

activity object in this workﬂow is the object ”Pro-

duction order”, as it is part of all functions of

SELF-ADAPTIVE CUSTOMIZING WITH DATA MINING METHODS - A Concept for the Automatic Customizing of

an ERP System with Data Mining Methods

Figure 1: Self-Adapting Customising plan for the ﬁrst customising.

the workﬂow: as output object in ”Creating pro-

duction order”, ”Conﬁrm a production order” and

”Release a production order” and as an input ob-

ject in ”Posting goods receipt for production or-

der”.

Workﬂow reference objects can be classiﬁed into the

following object types:

Organisation Objects. are business objects that rep-

resent the organisation units of an enterprise,

e.g. purchasing department, warehouse, company

code, plant, etc.

Resource Objects. are all business objects other

than the organisation objects. Such as customer,

vendor, order, invoice, purchase order, article, etc.

A function of an enterprise workﬂow model can be

converted via text mining methods if the function term

(notation) and the involved workﬂow reference ob-

jects are equivalent to the ERP transaction term and

its workﬂow reference objects.

Text mining use syntactical rules for the recogni-

tion of term structures and mining methods for the de-

tection of the semantic meaning of terms. During the

usage of text mining large data sets are used which

describe the terms from the real enterprise world as

well as from the ERP technology world. One exam-

ple for such large dataset could be an ontology with

the content of words of the real world and the map-

pings to the words of the ERP technology world. But

it should not be limited to the vocabulary of only one

ERP system. It is also possible that an ontology for

both workﬂow models exists, the enterprise and the

ERP speciﬁc workﬂow model, or one for each model.

If we have both ontolgies, it is possible to match both

ontologies to one ontology for the formal workﬂow

model (Euzenat and Shvaiko, 2007).

Another example for such large data set is the us-

age of synonym lists. In which each word of the

ERP technology world and the enterprise world are

mapped to the equivalent of the formal model termi-

nology. An algorithm search for each word the equiv-

alent synonym from such a list to create an uniform

vocabular for the enterprise and the ERP workﬂow

model.

2.1.2 Evaluation Phase

In the evaluation phase an converted ERP reference

model is compared with the converted ERP workﬂow

model and a suitable workﬂow or a workﬂow from the

workﬂow combinations form. The reference model is

constructed for the implementation phase as an ”ex-

tended workﬂow model”. The workﬂow selection is

based on the comparison of model objects as ERP

workﬂow structures and the functions and objects in-

volved on the one side, and how they are mapped in

the ERP reference model and whether they are linked

to other model objects on the other side. The link-

ing of objects in the ERP reference model can lead

to the cascading of further objects that have to be

considered in the implementation phase. An exam-

ple is the selection of a workﬂow from the ERP ref-

erence model for ”Processing Sales Order”. Here it

is considered whether the sales order is linked to fur-

ther sub-workﬂows, for example for economic and/or

technical checks, and whether these sub-workﬂows

are linked to further sub-sub-workﬂows. Through the

consideration of the linked objects all ERP transac-

tions necessary for the execution of a workﬂow are

provided and adjusted. Attention should be paid to

the fact that not all transactions can actually be used

in the future. In the post-customising phases the ERP

system can be further improved and customised after

the actual usage of the system.

ICEIS 2008 - International Conference on Enterprise Information Systems

2.1.3 Implementation Phase

At the implementation phase ERP customising object

data are adjusted based on the selected workﬂows (the

extended workﬂow models) from the ERP reference

model. ERP customising objects are ERP repository

objects which are necessary for the adjustment of an

ERP system. For this purpose historical ”best prac-

tice” information, stored for the customising of the

ERP reference models, are used. This information

allow that user roles, authorisation proﬁles, organi-

sation units, currency unit and all other customising

objects are automatically implemented in this phase

based on the extended workﬂow models.

2.2 The Post-Customising

During the implementation of an ERP system the

functionality provided within the initial customising

is adjusted to the speciﬁc business requirements of an

enterprise. With the provision of the linked model

objects or customising objects, the system parameter

settings are dimensioned in a large-scale fashion, so

that all possible functionalities of the enterprise can

be supported by the ERP system. Parts of the ERP

functionality set are not used in the daily operational

work which may lead to greater system complexity.

The underlying Self-Customising System takes

place in the post-customising phases. The system is

modiﬁed, respectively improved and adjusted to the

needs of the enterprise on the basis of the system us-

age over time. In this process methods of Application

Usage Mining (AUM) are used. AUM is a system

technically realisable procedure for the reconstruction

of actual workﬂow models of an ERP system. AUM

should be an auxiliary means for the automatic mod-

elling of a detailed actual workﬂow model of an en-

terprise.

ERP systems support enterprise-wide business

processes and implement them as workﬂows. During

the work with an ERP system, the ERP users leave

traces in the form of ERP trace data that reﬂect the

user interactions with the system. A supporting tool

for this purpose is the methodology of the Application

Usage Mining which automatically reconstruct actual

workﬂow models from ERP traces that vulnerabili-

ties in the system usage can be detected and removed

through customising adjustments.

The post-customising is constantly executed in the

frame of a Continuous Improvement Process (CIP) in

order to provide a constant improvement of the ERP

customising. The post-customising covers, similar

to the initial customising, three phases: provision of

the actually executed ERP workﬂow models (actual

workﬂow models), evaluation phase and implementa-

tion phase.

2.3 Provision of ERP Workﬂow Models

Instead of using the conversion phase of the initial

customising in order to provide ERP workﬂow mod-

els, in the post-customising phase the actual workﬂow

models are automatically extracted using the AUM

methodology from the ERP system and are provided

for the evaluation phase (see ﬁgure 2).

The existing workﬂow models represent the ac-

tual ERP workﬂow models used within the system.

The AUM itself is a method that uses a KDD process

based on ERP trace data. The AUM process covers

three phases (Kassem, 2004):

In the preparation phase interaction data from

different sources of the ERP system are integrated in

a database (data pool). This are mainly trace data that

protocols the user interactions with the ERP system.

Additionally the data pool contains meta interaction

data that describes the trace data.

In the pattern detection phase the workﬂow

cases of a workﬂow are detected using special min-

ing algorithms (Kassem and Rautenstrauch, 2006). A

workﬂow case displays the sequence of the perfor-

mance of ERP functions of a workﬂow instance. The

algorithms address conﬂicts that may arise at the as-

signment of functions to the workﬂow cases. Based

on theses algorithms task steps (function cases) can

also be detected as a screen sequence at the execution

of a function. It displays which work steps of a task

were performed.

In the pattern analysis phase the workﬂow cases

detected in the pattern detection phase are analysed

with the help of workﬂow algorithms (Agrawal, 1998;

van der Aalst and van Dongen, 2002; van der Aalst

et al., 2002) and are extracted formally as well as

graphically using actual workﬂow models.

The extracted actual workﬂow models can now be

evaluated in the evaluation phase.

2.4 The Evaluation and Implementation

Phases

At the evaluation phase only the actual used func-

tionalities are considered in order to assure that the

workﬂow structures are customised by the requiren-

ments of the enterprise and therefore the model is be-

ing improved consequently. Here analysis methods

can be used for the evaluation of the generated actual

workﬂows and the interaction data, collected in the

data pool. The analysis should address the following

items:

SELF-ADAPTIVE CUSTOMIZING WITH DATA MINING METHODS - A Concept for the Automatic Customizing of

an ERP System with Data Mining Methods

Figure 2: Self-Adapting Customising plan for the ”post” customising.

The connection between the workﬂow process (its

structure) and the workﬂow attributes (i.e. costs, run-

time or attributes of workﬂow used business objects

like customer name or material weight) can contribute

to the detection of vulnerabilities at a workﬂow or,

amongst others, illegal processes. Such kind of infor-

mation can support the process management of an en-

terprise. Therefore mining methods can be developed

to classify the workﬂow structures (like parallelism,

branches, sequenciellity or iterations/constellations of

workﬂow structures) and for comparison with work-

ﬂow attribute values for detection of connections as a

type of patterns.

An the evaluation phase user behaviour can be

analysed. The access paths of the users during

the workﬂow processing are represented as graphs

(Kassem et al., 2003). Different mining methods can

be used to ﬁnd answers to the following questions:

Path Analysis:

• At which step of equal user access paths an error

message appears?

• At which step of user access paths transactions are

often aborted?

• At which step the access paths reach dead ends?

To answer such questions from the workﬂow model

different graph mining methods like classiﬁcation of

graphs (Borgelt and Kruse, 2002) can be used.

Association Analysis: The connection between

events (e.g. input of dataﬁelds and the pressing of a

button) and the screen sequence should be recognised

through the employment of association rule methods.

Here the customising of the system is checked ac-

cording to its correctness. The deviation of the user

access paths from the ideal access paths can be recog-

nised. The business process should be analysed by

such methods. The well known apriori algorithm

from Agrawal and Srikant in 1994 (Ester and Sander,

2000), for instance, can be used in order to create as-

sociation rules from the screen sequences.

Temporal Analysis: Time referenced data is needed

for the temporal analysis of the data. One example for

the goal of such analysis is to examine the effectivity

of the system usage of a user. Following questions can

be asked (and hopefully answered) after the analysis

process:

• How quickly new users are enabled to use the system?

• How much time is needed for a user to process a task?

• Which text ﬁelds always contained the same values and

which values precisely were used?

• Which screens of a transaction were not used?

• From which transactions and from which screen other

transactions were called?

• From which transaction screen help programs were nec-

essary and which topic did they address?

The temporal mining methods like sequence anal-

ysis, detection of pattern evolutions or cluster mon-

itoring gives us the possibility to ﬁnd changes and

movements at the workﬂow model during runtime and

so to adjust the system over time to customise the sys-

tem according to the new requirenments of the enter-

prise (Aggarwal, 2007).

The User behaviour Analysis can be used for per-

sonalisation and for checking the correctnes of the

system customising and for checking the efﬁcency of

the system usage at user tasks. As one result of such

analysis it can be seen, how familiar a user is with the

system and if a user or a user group needs some train-

ing or if the system should be customised or person-

alised for some users. to their needs through personal-

ization. The extended ERP workﬂow models are pro-

vided for the implementation phase. The analysis of

ICEIS 2008 - International Conference on Enterprise Information Systems

the workﬂow structures and the user behaviour forms

the basis for the models. These extended workﬂow

models are after the system usage customised work-

ﬂow models.

The ERP customising objects are modiﬁed by us-

ing the extended ERP workﬂow models at the imple-

mentation phase.

The post-customising process can be seen as a re-

curring process which customises the business pro-

cess of an enterprise dynamically at any given time.

The degree of customisation of an ERP system de-

pends on the ﬂexibility potential of the system. Here

the ﬂexibility of an ERP system means how cus-

tomisable the ERP system is to the business process

changes of an enterprise and how effectively the busi-

ness process activities can be processed by the users

or user groups depending on their roles and knowl-

edge.

3 CONCLUSIONS AND

OUTLOOK

The concept of a self-adaptive ERP system is an idea

for an automatic implementation and a permanent

customisation of an ERP system to the changes of

business processes and user behaviours within the en-

terprise. To implement this idea, we have shown a

structure of a system infrastructure, where the en-

terprise and the ERP-system layer are separated by

an adaptive middleware. The adaptive middleware

should be the interface between both layers. The

function of the adaptive middleware SACMS is to en-

sure the adaption of the system to the requirements of

the enterprise and users through intelligent methods

like data mining methods.

A condition for the successful implementation of

this concept is to have ERP-repository-data from the

ERP system with customised objects like business-

objects, transactions, screens screen-elements. Stan-

dardisation problems of workﬂow models, refer-

ence models and ERP-tracedata-formats inhibit gen-

eral rules for handling ERP-systems of different

providers. One possible solutions of this standardi-

sation problem can be a layer speciﬁc interface be-

tween the SAC-layers which enables the data transfer

between the different layers depending on the layer

standards. Therefore it is necessary to solve the stan-

dardisation problems of workﬂow models and ERP-

tracedata formats in the future.

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SELF-ADAPTIVE CUSTOMIZING WITH DATA MINING METHODS - A Concept for the Automatic Customizing of

an ERP System with Data Mining Methods