Enterprise Information System, Agility and Complexity

What is the Relationship?

Hakima Mellah

and Habiba Drias

Research Center in Scientiﬁc and Technical Information, CERIST, 03 Rue des Fr´eres Aissou, Ben Aknoun, Algiers, Algeria

Houari Boumediene University of Sciences and Technology, USTHB, Algiers, Algeria

Keywords:

Complexity, Enterprise Information System, Agility.

Abstract:

The term complexity is present everywhere. Complexity surrounds information, information system, orga-

nization as well as computing systems. In this work we present some challenges that deal with complexity.

Why can enterprise organization be seen as complex? From what, complexity can arise within enterprise in-

formation system? What is relationship between complexity and agility? What are factors that may evolve

complexity within enterprise information system? How computing system led information system towards

complexity? To response to all this challenges, several dimensions dealing with complexity are displayed such

as dynamics in enterprise information system components, while interacting, that can be tolerated by compo-

nents autonomy; intelligibility that causes knowledge evolving; and inter-connectivity that is necessary with

distribution. All these factors inﬂuence each others, within a three dimensional system. UML modeling of

enterprise information system that includes complexity parameters is given.

1 INTRODUCTION

Technological advances means of information pro-

cessing and dissemination encourage new uses emer-

gence putting users at the center of the computing sys-

tem. This leads us to more complex systems, whose

evolution is guided by the use, which is in its turn

modiﬁed. We can cite in this context, the evolution

of the Internet and Web for example or Web1.0 to

Web2.0. Future computing systems and their use are

facing an increasing complexity due to the following

changes:

• Emergence of new computing environments such

as large-scale as well as mobile ad hoc networks

• Emergence of new uses and needs from this evo-

lution, requiring sophisticated applications, using

large complex data volumes

• A strong need for user-centered applications,

where Information Technology (IT) system user

is considered as a major component or as an im-

portant integral part entity of the system. The de-

velopment of these applications and their evolu-

tion are driven by user-system interactions. We

can consider the system as a set of IT components

interacting with each other and with the environ-

ment

• The advent of service technology, the web, large-

scale networks, etc., making the computing envi-

ronments more open and distributed and compo-

nents are no longer under the control of a single

organization

• Computing environment is heterogeneous, thus,

becoming difﬁcult to conﬁgure, maintain and

troubleshoot

In this context, thinking about IT system engineer-

ing requires the integration of its complexity as an

essential characteristic. IT system complexity arises

from its opening to its environment, itself complex,

distributed and dynamic (Hassas, 2006), (Benatallah

et al., 2003), (Hassas, 2003). These IT developments

and their features have a strong impact when it comes

to be deployed in environments like that of the en-

terprise. The enterprise, taking advantages of these

evolutions, ﬁnds itself constraint to change its orga-

nization and its information system. These devel-

opments are also dictated by the enterprise business

environment evolution, beyond its computer system,

and rely on informational and structural entries made

by the Enterprise Information System (EIS). The lat-

ter belongs to complex systems category because it

interacts with other EIS, computer systems, resources

and users. These information systems are distributed,

Mellah, H. and Drias, H.

Enterprise Information System, Agility and Complexity - What is the Relationship?.

In Proceedings of the 1st International Conference on Complex Information Systems (COMPLEXIS 2016), pages 74-80

ISBN: 978-989-758-181-6

heterogeneous, decentralized, interdependent, and of-

ten operate in a dynamic and unpredictable environ-

ment (Mordinyi and Kuhn, 2011). EIS represents

the mean used by the enterprise to protect its data,

to have a memory, retrieve, store, process, dissemi-

nate, exchange information that is the foundation of

business intelligibility and knowledge. According to

(Peaucelle, 1997) it embodies the language used to

represent the organization reliably and economically

aspects, it is seen as as the organization. However, in-

formation is considered as one of the main resources

of the enterprise’s business, that is being evolved

through interaction and communication.

Figure 1: Information system, Organization, information

ﬂow: A complex framework.

What is noticed is that the activity in the enter-

prise generates information ﬂows (ﬁgure 1), and for

that some authors such as Hugues Angot (Angot,

2006) addressed the organization in information ﬂows

terms, and what is emphasized are structured rela-

tions between the different information sources com-

ponents. This what explains the JJ Lambin (LAM-

BIN, 1990) vision, for the EIS, as structured relation-

ships complex network, where are involved humans,

machines and procedures, which aims to generate rel-

evant information ordered ﬂows from the enterprise

internal and external sources, intended to serve as a

basis for decisions and solutions presented to the user.

EIS can be viewed through the dynamic organiza-

tion (and even self-organization) of its ﬂow. Informa-

tion ﬂow generated during the execution of an activity

or task is susceptible to disturbances that may block

its routing, thus making the system obsolete. In or-

der to overcome the disturbance, one solution would

be through other network topologies, thus generating

new communication links, which did not exist a priori

between different interacting entities. This explains

our vision of ﬂow management problem, as a self-

organization problem. And consequently a solution to

the problem mentioned above would be the induction

of a self-organizing mechanism that is a key feature of

complex systems. With the large scale processors net-

works evolution like Internet, considered as the most

used mean for information exchange between enter-

prises, new practices are highlighted and new needs

have emerged towards the computing environment. It

is therefore necessary to think about computing sys-

tems developmentable to work intelligently with their

environment systems. Tackle EIS in a holistic view

considers it as a whole or ”holism” without separating

the user from the EIS contents and the environment in

which this system interacts. This is especially true

in a dynamic environment context where interactions

between different parts of the computing system are

constantly changing, requiring challenges of its struc-

ture, organization, interactions and its dynamics. Cur-

rently the information ﬂow increasing systems’ com-

plexity is a characteristic of enterprises and manufac-

turers regarding products, services to offer, and all

information exchange. This complexity also comes

from changing environments that are disturbance sur-

rounded, in which EIS operate. Difﬁculties arise and

the system has to solve unforeseen problems on the

basis of available information that is generally incom-

plete and imprecise.

A complex system is a system, characterized with self

organization, adaptation, evolution, etc., it consists of

plenty of constituents which interact in a hierarchi-

cal frame to function as a whole. Emergence, adapta-

tion, evolution are the elementary properties of com-

plex systems, where emergence is the most essential

feature (Zundong et al., 2010).

2 COMPUTING SYSTEMS AND

ENTERPRISE INFORMATION

SYSTEMS

Computing systems evolution, evolved by fact and in

the same direction EIS. Computing systems evolution

and the emergence of new technologies, reveals evo-

lution needs in the same direction of information sys-

tems, which is seen at the same time as an opportu-

nity for EIS to beneﬁt from these evolution. Further,

EISs as complex systems are systems whose compo-

nents interact to accomplish goals. The developers

of such systems must, in addition to the application

logic expressing the reaching goal, to include a man-

agement and supervision logic in order to overcome

the environmental problems for which the organiza-

tional goal cannot be reached. The management logic

is important, for example, in case of EIS components

non functioning (Mordinyi and Kuhn, 2011).

2.1 Enterprise Organization

Evolution in enterprises organizations was clearly no-

ticed in the last decade (Mintzberg, 1994). It took

Enterprise Information System, Agility and Complexity - What is the Relationship?

into account the networks, knowledge and skills man-

agement, cooperation, enterprise organizational struc-

ture, for the following reasons:

• The economic transformation that requires re-

sponsiveness

• The competitive nature that is a factor of organi-

zational requirement

• The costumers/users growing power pushing en-

terprises to reshape their organization to better re-

spond

• The facility offered by the IT for information ex-

change internally and externally

The reasons cited above showed that the organiza-

tional implementation of strategies is a key perfor-

mance factor and the organization became a part of

the enterprises competitiveness. These organizational

changes result in two heavy and common trends to

many enterprises that are exploding the organization

boundaries and the transversal management. The

basic elements constituting an organization (Mellah

et al., 2007) are connected by a variety of complex

ﬂows that are all important and explain how an or-

ganization operates (considering all of these ﬂows).

(ﬁgure2 )shows the environment in which EIS evolves

considering different dimensions that make the sys-

tem complex. The characteristics of this ﬂow are:

• The massive character. Given the important need

of customers/users that is increasing and the ﬂows

variety and their complexity. These ﬂows connect

all the basic elements of an organization and may

involve authorities, materials, or simply commu-

nications and all these parameters need control to

assure their connectivity and survive. Informa-

tion uses increase its intelligibility that is a key

for knowledge management.

• Dynamic and autonomy. Tolerated by the advent

of communication IT (eg intranet), in the sense

that IT break formal organization barriers to form

working groups that are non formal organizations.

ITs endow EIS of autonomy.

• Distribution and inter-connectivity. ITs provide a

growing organization, the means to be split into

different parts distributed on the network that can

communicate later with each other. Maintaining

this distribution, inside or outside the enterprise,

must be assured by means like self organizing

protocols (Mellah et al., 2007). Interaction net-

works link organizational positions to form orga-

nizational structures. In the context of cooperative

distributed problem solving (CDPS), an organiza-

tional structure can be seen as a way to specify the

coordination strategy (pa S. Young and Edmund,

1993).

Figure 2: Complexity parameters surrounding information.

2.2 System-environment Coupling

The vision adopted by (Hassas, 2003) considers the

computing system as a set of components in inter-

relational and retroactive interactions, evolving in a

shared, dynamic and uncertain environment that cor-

respond to that of a complex system, is inspired from

autopoetism/Enactivism characteristics. But we must

not be confused by autopoetism abstract conceptual-

ization and by complexity theory which treats sys-

tems as entities that we see outside ourselves. We

are part of the problem and of the solution (Cachon,

1999). The challenge of this type of system is to

ﬁnd an effective organization of its components (by

self-organization), in organizational structures imple-

menting or highlighting a coherent behavior towards

the environmentcomplexity. However, living systems

have managed such a challenge for millions of years.

As supported by the Enactivism (Hassas, 2006), we

believethat this ability to living systems is due to their

coupling with the environment. Natural phenomena

are an inspiration source in different computer sys-

tems areas (Bonabeau et al., 1999)(Drias et al., 2005).

This phenomenon is due to the fact that living sys-

tems have properties that allow them to adapt to a

complex environment. Systems such as cell organ-

isms, insect colonies or societies of individuals ex-

hibit complex global behavior that self organizes their

components into robust and ﬂexible structures. These

systems are characterized by a high reactivity, robust-

ness to individual failures, and a great capacity to

adapt to environmental changes. Several computing

areas have referred (Hassas, 2006) to bio-inspired ap-

proaches. Rats, spiders, ants, ﬁsh, birds, bacteria, etc.,

are all natural living systems that attracted researchers

attention, for differentiation, information dissemina-

tion, aggregation, optimization,...etc. All these works

mainly refer to the Stigmergy mechanism (Grasse,

1959) which was discovered by P.P Grasse, and is

COMPLEXIS 2016 - 1st International Conference on Complex Information Systems

used by insect colonies to coordinate their behavior.

Coordination is assured through the persistent effects

left in the environment by previous actions on the fu-

ture actions of agents. The environment is considered

as a space ﬁt these traces of actions and interactions.

Structures and processes emerge in a autopoetic vi-

sion (ie the permanent co- evolution of the process

and structure as a result and process support (Hassas,

2003).

To overcome the deadlock situations that may en-

counter a distributed system and that will disturb its

inter-connectivity, IT designers (or sellers) recognize

that it is necessary, even essential to think about de-

signing systems that assume themselves, their man-

agement. This is recognized in academic and indus-

trial settings by Oriented Autonomic Computing, rec-

ognized in 2001 by ”Paul Horn” (senior vice presi-

dent of IBM Research) as analogous to the human’s

nervous system (Markus and Julie, 2008). The Dis-

tributed Autonomic Computing or DAC is accom-

plished mainly through the implementation of self *

properties which can be classiﬁed according to a tax-

onomy of criteria and in this taxonomy we ﬁnd the

resource allocation, which is characterized by the fact

that a system needs to allocate limited services or allo-

cate tasks to resources,etc. (Frei and Giovanna, 2011).

Information delivered by an EIS is captured in a com-

plex way. It can be framed in a three-dimensional

system with content, use and structure dimensions

(Mellah et al., 2008), as it is considered that infor-

mation content must be related to other content, and

is nothing without external factors (environment), to

this information, without the value given by the user

and without context raised pertinence (Mellah et al.,

2013b).

3 COMPLEXITY AND AGILITY

The ﬁrst changes, in perspective, known by orga-

nizational theory, is the transition from a closed to

the perspectives of an opened system (Mellah et al.,

2008) taking into account organization’s external

factors. To evolve, an EIS must be opened to its

environment. We ﬁnd this openness and evolution

in the characteristics of agile information systems.

Agility is deﬁned by Gartner as ”the ability of an

organization to sense environmental change and

responds efﬁciently to that change”(Mellah et al.,

2013b). Agile information system is a system able to

adapt to the functional and technical developments,

it is often more open to absorb management process

with third parties, and allow organization evolution

without challenging business applications. In prac-

tice, agility is materialized by ”services” orientation

[wikipedia].

Deﬁnition. We deﬁne an agile information system

as a self organizing system or a system endowed with

a self organizing mechanism. We consider the agility

of an EIS as a new class in the taxonomy of self *

properties criteria.

This deﬁnition underlines that an agile information

system as it is characterized by self organizing prop-

erty is a complex system. The computing resources

offered by an agile information system are expressed

in terms of services. They have the following fea-

tures(Mellah et al., 2013a):

• May extend beyond the enterprise boundaries

through transit interfaces such as Internet.

• Are requested by the mean of interfaces used to

interact with a variety of enterprises (other orga-

nizations).

Conversely an organization providing any service is

often called upon to interact with a set of service re-

questers (Benatallah et al., 2003) the service can have

the following characteristics:

• changing and evolving over time(Thompson,

1967).

• appearing in a new version instead of the old one.

• new version of services with advanced features

can be offered by organizations integrating inter-

action process.

”Computer services” create the technological

foundations and management required to support en-

terprise agility (McCoy, 2007) and complexity. To

ensure this agility and enabling services use in or-

der to meet the business process and the user, it is

important to have a software service-oriented archi-

tecture (SOA) (McCoy, 2007)(Mecella and Pernici,

2006). System-environment coupling, that charac-

terizes agile information system, is among the ar-

guments justifying the consideration of the above

issues in terms of EIS modeling through informa-

tion ﬂows, their inter-dependencies, their dynamics.

Within MAS paradigm, this coupling can be assured

by a self organizing protocol (Mellah et al., 2007)

and can be projected within SOC (Service Oriented

Computing) as an SOA solution for agility (Mellah

et al., 2013a) that leads systematically an SOA to an

ASOA (Agile SOA). Consequently an ASOA is de-

ﬁned as being a SOA whose components self orga-

nize while encountering disturbance within environ-

ment. Agility as it is matched to complexity consid-

ers EIS in two levels: (i) a core centered data, users,

and connectivity between them, (ii) a shell evolving in

Enterprise Information System, Agility and Complexity - What is the Relationship?

Figure 3: Agility parameters within EIS.

three dimensions, which axis are supported by intel-

ligibility, dynamics and inter-connectivity. The three

parameters are involved and represent the support of

knowledge, autonomy and distribution intra and extra

enterprise (ﬁgure3).

4 ENTERPRISE INFORMATION

SYSTEM MODELING

Organization theory deals with complexity as a struc-

tural variable that characterizes organizations and

their environments (Zaho et al., 2007). Draft (Syn-

tec, 2007) matches complexity to the number of ac-

tivities or subsystems, which basically composes the

organization. This implies that a complex system is a

system of systems. More the system has subsystems

and more it is complex. Complexity can be decom-

posed into three dimensions: vertical, horizontal and

spatial, corresponding respectively to the number of

levels in the organizational hierarchy, the number of

posts or departments within an organization, and the

number of geographical locations. We can identify

the following understandings (Zaho et al., 2007):

• Activities/subsystems. Each subsystem can be

composed by other subsystems

• Activities/subsystems have a geographical loca-

tion (network’s node) that may change well.

Therefore, they do not have a persistent physical

location

• Activities/subsystems can be decomposed to

highlight features that are invisible at ﬁrst sight.

That is an important characteristic of complexity.

The decomposition can be done based on relative

uses that characterize subsystems. While they are

decomposed, a structure or a pattern is generated

(ﬁgure 4).

Figure 4: EIS classes diagram in relation with entities im-

plied in information ﬂow.

These points highlight the key features of agile in-

formation systems, well supported by a SOA (McK-

elvey, 1999). The key features appear to be compati-

ble with Drafts proposal. In order to tackle informa-

tion system complexity, it is required to harmonize

the quality of service offered to users internally and

externally. A new version for the design of complex

systems is called organic computing (Mellah et al.,

2013a). The latter satisﬁes conventional requirements

for trustworthy systems, which autonomously adapt

to dynamic changes of the environment, and have

self-x (self-organizing, self-healing, etc.) properties

(McKelvey, 1999) as postulated for autonomic com-

puting (Markus and Julie, 2008). From our perspec-

tive, we recognize the information complexity, issued

from a set of interacting EIS or from a SOA, in a

three-dimensional system, handling service, context

and service discovery structure (Draft, 1992).

Each EIS represents one or more organizations,

one or more subsystem. We can note a mapping be-

tween our work and that of Draft, interpreted in the

following points:

• Each level of an organizational hierarchy corre-

sponds to the existence of services, and the num-

ber of departments in an organizational level may

correspond to the number of contexts that we as-

cribe to services.

• The geographical locations constitute the service

discovery structures generated by the various ser-

vice discoveries, to meet the needs of the user and

achieve the desired goals.

Considering these technicalities, we conﬁrm that

complexity theory is easily supported by a SOA, in

the sense that SOA offers issues to integrate self-

organization within a SOA as it is a key feature of

complex systems(ﬁgure 5). Self organization can be

handled on the basis of layered architecture(Mellah

et al., 2013b) and a Self Organizing (SO) protocol

(Mellah et al., 2009; Mellah et al., 2010). The SO

protocol controls interaction between nodes support-

ing EIS contents, by the mean of checking and routing

COMPLEXIS 2016 - 1st International Conference on Complex Information Systems

Figure 5: Illustrative schema on agility, complexity and system-environment coupling.

process to maintain connectivity of the hole system

(Mellah et al., 2009; Mellah et al., 2010).

5 CONCLUSION

In this work we have presented some challenging sit-

uations that deal with complexity and that turn around

information, EIS, computing system. The complexity

parameters that surround information, and that make

complex EIS, are presented. A self organizing view

to agility (that is matched to complexity) is given.

While discovering contents, offered by a EIS or its

subsystems, a structure is generated. Without consid-

ering the use context which can be either relative use

characterizing the content itself (can varied), or global

use, characterizing the system in its hole, the structure

represents itself a complexity support(Mellah et al.,

2013b), because it is this structure that gives robust-

ness to the system, by self organization, recognized as

a feature of complex systems and of agile information

systems.

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