Maturity Models for Information Systems - A State of the Art

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Procedia Computer Science 100 ( 2016 ) 1042 – 1049

1877-0509 © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the organizing committee of CENTERIS 2016 doi: 10.1016/j.procs.2016.09.279

ScienceDirect

Conference on ENTERprise Information Systems / International Conference on Project

MANagement / Conference on Health and Social Care Information Systems and Technologies,

CENTERIS / ProjMAN / HCist 2016, October 5-7, 2016

Maturity Models for Information Systems - A State of the Art

Diogo Proença

a,b

*, José Borbinha

a,b

a

INESC-ID, Rua Alves Redol 9, 1000-029 Lisboa, Portugal

bInstituto Superior Tlcnico, Universidade de Lisboa, Avenida Rovisco Pais 1, 1049-001 Lisboa, Portugal

Abstract

A Maturity Model is a widely used technique that is proved to be valuable to assess business processes or certain aspects of organizations, as it represents a path towards an increasingly organized and systematic way of doing business. A maturity assessment can be used to measure the current maturity level of a certain aspect of an organization in a meaningful way, enabling stakeholders to clearly identify strengths and improvement points, and accordingly prioritize what to do in order to reach higher maturity levels. This paper collects and analyzes the current practice on maturity models, by analyzing a collection of maturity models from literature.

© 2016 The Authors. Published by Elsevier B.V.

Peer-review under responsibility of SciKA - Association for Promotion and Dissemination of Scientific Knowledge.

Keywords: Maturity Model, Maturity Assessment, State of the Art.

1.

Introduction

A Maturity Model (MM) is a technique that has been proved to be valuable in measuring different aspects of a

process or an organization. It represents a path towards increasingly organized and systematic way of doing business

in organizations. A MM consists of a number of “maturity levels”, often five, from the lowest to the highest, Initial,

Managed, Defined, Quantitatively Managed and Optimizing (however, the number of levels can vary, depending on

the domain and the concerns motivating the model). This technique provides organizations: (1) A measuring for

auditing and benchmarking; (2) A measuring of progress assessment against objectives; (3) An understanding of

* Corresponding author. Tel.: +351213100300; fax: +351213145843. E-mail address: diogo.proenca@tecnico.ulisboa.pt

© 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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strengths, weaknesses and opportunities (which can support decision making concerning strategy and project portfolio

management).

In

2

maturity is defined as a specific process to explicitly define, manage, measure and control the evolutionary

growth of an entity. In turn, in

3

maturity is defined as a state in which an organization is perfectly able to achieve the

goals it sets itself. In

5

and

6

it is suggested that maturity is associated with an evaluation criterion or the state of being

complete, perfect and ready and in

7

as being a concept which progresses from an initial state to a final state (which is

more advanced), that is, higher levels of maturity. Similarly, in

4

maturity is related with the evolutionary progress in

demonstrating a particular capacity or the pursuit of a certain goal, from an initial state to a final desirable state. Still,

in

11

it is emphasized the fact that this state of perfection can be achieved in various ways. The distinction between

organizations with more or less mature systems relates not only to the results of the indicators used, but also with the

fact that mature organizations measure different indicators when comparing to organizations which are less mature

12

.

While the concept of maturity relates to one or more items identified as relevant

14

, the concept of capability is

concerned only with each of these items.

In

1

maturity models are defined as a series of sequential levels, which together form an anticipated or desired

logical path from an initial state to a final state of maturity. In

9

maturity models are defined as tools used to evaluate

the maturity capabilities of certain elements and select the appropriate actions to bring the elements to a higher level

of maturity. Conceptually, these represent stages of growth of a capability at qualitative or quantitative level of the

element in growth, in order to evaluate their progress relative to the defined maturity levels.

Some definitions found involve organizational concepts commonly used, such as the definition of

8

in which the

authors consider a maturity model as a "... a framework of evaluation that allows an organization to compare their

projects and against the best practices or the practices of their competitors, while defining a structured path for

improvement." This definition is deeply embedded in the concept of benchmarking. In other definitions, such as in

the presented by

10

there appears the concern of associating a maturity model to the concept of continuous

improvement. In

14

, the maturity models are particularly important for identifying strengths and weaknesses of the

organizational context to which they are applied, and the collection of information through methodologies associated

with benchmarking.

2.

Maturity Models Analysis

This section provides a synthesis of the analysis of a set of maturity models. The references used for this section

were found after searches on several services, such as, Google; Google Scholar; IEEE Xplore; ACM Digital Library;

Springer Link; CiteSeerX. The search terms included the keywords maturity,

͒

maturity model, capability maturity,

capability maturity model, stages theory, process maturity, among others. The search resulted in an initial set of

papers, of which the references were analysed and selected, if relevant.

͒

In this section, we are analysing maturity

models from the most diverse domains, from software engineering to asset management and information governance.

The goal here was to select different maturity models that reflect the most diverse approaches, some influenced by

other maturity models, others with no name for the maturity levels, others that have a level 0, without focusing on just

one domain.

In

14

it is summarized the major features of various maturity models. According to these authors, the maturity

models can be classified according to several items the most important being the number of maturity levels that make

up the model, its discrete or continuous nature, if the results obtained are quantitative or not, and if they adopt a

philosophy of continuous improvement. In addition to the inherent characteristics of the model design the authors

refer to characteristics that influence model applicability and dispersion. In particular, the associated costs, ease of

use, simplicity of interpretation, consistency in terms of continuity between model versions arising from its iterative

nature and the relative difficulty of the necessary training

15

.

Table 1, Table 2 and Table 3 synthesize the information collected through the selected literature sources in a way

that eases the analysis and according to the variables detailed in

14

and

4

. The simplicity associated with the

development and use of maturity models has its "price", and several authors point out some limitations to maturity

models

16, 12

, for example: (1) Overly simplistic in relation to reality; (2) Lack of fundamentals; (3) They focus on a

single path to reach maturity, neglecting potentially advantageous alternative paths; (4) Its applicability may be

constrained by internal factors (available technology, intellectual property, supplier relations) or external factors

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(market conditions); (5) There are multiple identical maturity models; (6) Lack of information regarding the maturity

model development method. Minimizing the limitations pointed to maturity models can be achieved by ensuring a

continuous and iterative evaluation, as well as a comparison with other models used for the same purpose

16, 17

.

2.1. Model Structure

The model structure analysis focuses on the structural aspects of the maturity model. We analyze the number of

levels, the name and number of attributes, whether the model provides a maturity definition and the practicality of the

model. Table 1 synthetizes the analyzed maturity models regarding the model structure. It uses a set of variables

selected from

14

and

4

. The following variables were selected:

1.

Name of the Maturity Model: The name of the maturity model and the main references;

2.

Number of Levels: The quantity of maturity levels of the model;

3.

Name of the attributes: The name of attributes the maturity model uses, there are several attributes being used.

The attributes aim at three things, (1) Decompose the Maturity Model into easily understandable sections; (2)

Aggregate several business processes into process areas that aggregate processes meeting the same business goal

and (3) Provide different viewpoints of the maturity level subject;

4.

Number of Attributes: The number of attributes used by the maturity model;

5.

Maturity Definition: Shows if the maturity model contains a definition of maturity;

6.

Practicality: Details if the practicality of the recommendations is problem-specific or general in nature.

2.2. Model Assessment

The model assessment analysis focuses on the application of the maturity model. In order to measure the maturity

level of a certain reality there must be available a way to calculate the maturity levels. This can be done by following

a self-assessment questionnaire or by following a full-fledged maturity assessment method. Table 2 synthetizes the

analyzed maturity models regarding the model assessment. It uses a set of variables selected from

14

and

4

. The

following variables were selected:

1.

Name of the Maturity Model: The name of the maturity model and the main references;

2.

Assessment Method Described: Details if the maturity model has an associated assessment method or not;

3.

Assessment Cost: Shows the degree of expenditure of an assessment project;

4.

Strong/Weak Points Identification: Details if the maturity model identifies weaknesses and strong points of

the organization;

5.

Continuous Assessment: Shows if the maturity model strives for a continuous assessment;

6.

Improvement Opportunities Prioritization: Details if the maturity model determines a priority of

improvement in the organization.

2.3. Model Support

The model support analysis focus on the support to the model provided by the maturity model authors or stewards.

The analysis focus on whether training is available, what is the availability of the author regarding model support,

whether there is continuity from different versions of the model, what is the origin of the model, as well as, the

accessibility of the model. Table 3 synthetizes the analyzed maturity models regarding the model support. It uses a set

of variables selected from

14

and

4

. The following variables were selected:

1.

Name of the Maturity Model: The name of the maturity model and the main references;

2.

Training Available: Details if there is training available for the maturity model, in order to become an expert

on the model or an assessor;

3.

Author Support Availability: Shows the degree of the support the author provides for the maturity model;

4.

Continuity from different versions: Details, when there is more than one version of the maturity model, if there

is continuity between different versions of the model. This is important to show if the model is adaptable or not;

5.

The origin of the model: Whether it originated in the academia or from practitioners;

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Table 1. Synthesis of the Analysed Maturity Models regarding Model Structure Maturity Model Number of levels Name of the

attributes

Number of Attributes

Maturity

Definition Practicality

ISO/ IEC 1550435 6 Process Groups 9 Yes Specific improvement

activities

Software Engineering Institute Capability Model Integration (CMMI)34

5 Process Areas 22 Yes Specific improvement

activities

Model-driven Development (MDD) Maturity Model26

5 MDD Practices 3 No General

recommendations

Metrics Based Verification and Validation Maturity Model (MB-V2M2)24 5 Fundamental Factors 4 No Specific improvement activities Documentation Process Maturity Model23 4 - - No General recommendations

Business Process Maturity Model (BPMM)25

5 Elements 4 No General

recommendations

OMG Business Process Maturity Model18

5 Process Areas 30 No Specific improvement

activities

Gartner BPM Maturity Model19 6 Critical Success Factors

6 No Specific improvement

activities

Group IT Controlling (GITC) Maturity Model37 6 Dimension / Sub-dimension 3 / 6 No General recommendations IT Capability Model Framework (IT-CMF)39

5 Process Areas 4 Yes Specific improvement

activities Business-IT Alignment Maturity Model20 5 Key Process Areas 5 No General recommendations

The IT Service CMM21 5 Categories /

Dimensions

3 / 13 No General

recommendations

Records Management Maturity Model30

5 Categories /

Dimensions

4 / 15 No General

recommendations

Gartner Enterprise Information Management Maturity Model22

5 Dimensions /

Category

4 No General

recommendations

Research Data Management (RDM) Maturity Model38 5 IT-business alignment criteria 6 No General recommendations Enterprise Content

Management (ECM) Maturity Model32

5 Process Areas 21 No General

recommendations

Digital Asset Management (DAM) Maturity Model31

4 Section 9 No General

recommendations

Asset Management Maturity Model29

6 - - No General

recommendations

Risk Maturity Model27 4 Attributes 4 No General

recommendations

COBIT Maturity Model40 6 Attributes 6 Yes Specific improvement

activities

Information Governance Maturity Model33

5 Principles 8 No Specific improvement

activities

Stanford Data Governance Maturity Model28

5 Dimensions 3 No Specific improvement

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Table 2. Synthesis of the Analysed Maturity Models regarding Model Assessment Maturity Model Assessment

Method Described Assessment Cost Strong/Weak Points Identification Continuous Assessment Improvement Opportunities Prioritization

ISO/ IEC 1550435 Yes High Yes Yes Yes

Software Engineering Institute Capability Model Integration (CMMI)34

Yes High Yes Yes Yes

Model-driven Development (MDD) Maturity Model26

No ? Yes ? ?

Metrics Based Verification and Validation Maturity Model (MB-V2M2)24

Yes ? Yes ? ?

Documentation Process Maturity Model23

Yes ? No No ?

Business Process Maturity Model (BPMM)25

No ? Yes ? ?

OMG Business Process Maturity Model18

No Medium Yes Yes ?

Gartner BPM Maturity Model19 No Low Yes ? ?

Group IT Controlling (GITC) Maturity Model37

No ? No ? ?

IT Capability Model Framework (IT-CMF)39

Yes High Yes Yes Yes

Business-IT Alignment Maturity Model20

No ? No ? ?

The IT Service CMM21 No ? No ? ?

Records Management Maturity Model30

Yes ? No ? ?

Gartner Enterprise Information Management Maturity Model22

Yes ? No ? ?

Research Data Management (RDM) Maturity Model38

Yes ? Yes ? ?

Enterprise Content

Management (ECM) Maturity Model32

No ? No No ?

Digital Asset Management (DAM) Maturity Model31

Yes ? No No No

Asset Management Maturity Model29

No Low Yes Yes ?

Risk Maturity Model27 Yes ? No No No

COBIT Maturity Model40 Yes High Yes Yes Yes

Information Governance Maturity Model33

No Medium Yes Yes ?

Stanford Data Governance Maturity Model28

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Table 3. Synthesis of the Analysed Maturity Models regarding Model Support Maturity Model Author

Support Availability

Training

Available Origin Accessibility

Continuity from different versions

ISO/ IEC 1550435 High Yes Academic Charged Yes

Software Engineering Institute Capability Model Integration (CMMI)34

High Yes Academic Free Yes

Model-driven Development (MDD) Maturity Model26

Low No Academic Free No

Metrics Based Verification and Validation Maturity Model (MB-V2M2)24

Low No Academic Free No

Documentation Process Maturity Model23

Low No Academic Free No

Business Process Maturity Model (BPMM)25

Low No Academic Free No

OMG Business Process Maturity Model18

Medium No

Practitioner-based

Free No

Gartner BPM Maturity Model19 Medium No Practitioner-based

Free No

Group IT Controlling (GITC) Maturity Model37

Medium No Academic Free No

IT Capability Model Framework (IT-CMF)39

High Yes Academic Charged Yes

Business-IT Alignment Maturity Model20

Medium No Academic Free No

The IT Service CMM21 Medium No Academic Free No

Records Management Maturity Model30

Medium No

Practitioner-based

Free No

Gartner Enterprise Information Management Maturity Model22

Low No

Practitioner-based

Free No

Research Data Management (RDM) Maturity Model38

Low No Academic Free No

Enterprise Content

Management (ECM) Maturity Model32

Low No

Practitioner-based

Free No

Digital Asset Management (DAM) Maturity Model31

Low No

Practitioner-based

Free No

Asset Management Maturity Model29

Medium No

Practitioner-based

Free No

Risk Maturity Model27 Low No Academic Free No

COBIT Maturity Model40 High Yes

Practitioner-based

Charged Yes Information Governance

Maturity Model33

High Yes

Practitioner-based

Charged No

Stanford Data Governance Maturity Model28

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3.

Conclusions and Future Work

This work presented a state of the art on the subject of maturity models. Future research will help Maturity Models

become more relevant for both academia and industry. In this paper we also described the concepts which form the

foundation of maturity models. A description of the different aspects of current maturity models was presented,

combining knowledge from the different domains analyzed.

As future work resulting from this paper, we concluded that current maturity assessment methods focus on highly

complex and specialized tasks being performed by competent assessors in an organizational context

36

. These tasks

mainly focus on manually collecting evidence to substantiate the maturity level calculation

34

. Because of the

complexity of these methods, maturity assessment becomes an expensive and burdensome activity for organizations.

As such, one major area to invest is to develop methods and techniques to automate maturity assessment. Due to

the wide spread of modeling practices of business domains, assisted by modeling tools, makes it possible to have

access, for processing, to the data created and managed by these tools. Also, the recent state of the art

41

demonstrating

how business processes and Enterprise Architecture models in general can be represented as ontologies has raised the

potential relevance of the semantic techniques for the automated processing of these models. As such, the objective is

to analyze the potential, and the main limitations, of the existing semantic techniques to automate methods for the

assessment of MM through the analysis of an existing model representation of a reality.

There are several examples of models used to represent an organization architecture, such as, Archimate

44

, BPMN

43

or UML

45

. These models are descriptive and can be detailed enough to allow to perform, to some extent, maturity

assessment. However, in order for these models to become relevant for maturity assessment there should be a formal

representation for both MMs and model representations. One hypothesis is that building on the knowledge of

ontologies from the computer science and information science domains, these can be used to represent MMs and

model representations. This can be achieved by developing a generic ontology that expresses all these core concepts

(or at least a relevant group of them) and relationships among them, as also the rules for a generic maturity assessment

accordingly Then, by representing MMs and models representations of concrete organizational scenarios using

ontologies we can verify if an organization models representations matches the requirements to reach a certain

maturity level using ontology query and reasoning techniques, such as SPARQL and Description Logics

46

inference.

The final objective is thus to identify how these methods and techniques can be used in existing maturity assessment

methods

36,42

, so that they can be proven as relevant to enable the automation of certain aspects of maturity assessment,

such as, the maturity level determination. In order to do this, there should be an exploration of what types of analysis

can be performed using the information on model representations that is relevant in a maturity assessment effort.

Acknowledgements

This work was supported by national funds through Fundação para a Ciência e a Tecnologia (FCT) with reference

UID/CEC/50021/2013, and by the European Commission under the Competitiveness and Innovation Programme

2007-2013, E-ARK – Grant Agreement no. 620998 under the Policy Support Programme. The authors are solely

responsible for the content of this paper.

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