Deriving Service Level Agreements from Business Level Agreements
An Approach Towards Strategic Alignment in Organizations
Vitor Almeida Barros
1
, Marcelo Fantinato
1
, Guilherme M. B. Salles
1
and João Porto de Albuquerque
2
1
School of Arts, Science and Humanities, Univ. of São Paulo, 1000 Arlindo Béttio Av., São Paulo, Brazil
2
Inst. of Mathematical and Computer Sciences, Univ. of São Paulo, 400 Trabalhador São-carlense Av., São Carlos, Brazil
Keywords: Strategic Alignment, Business Process Management, Service-oriented Computing, Service Level
Agreement, Business Level Agreement, WS-Agreement.
Abstract: Business Process Management (BPM) can help organizations in their attempts to align strategies between
business and information technology areas. It is not only necessary to address functional properties during
the BPM life-cycle, but also process quality and operating constraints, which are usually grouped together
as Non-Functional Properties (NFP). However, the most prestigious languages for business process
modelling are unable to represent these NFPs, and this creates a gap between the degree of success in
identifying functional properties and NFPs as well as between the process modelling and its
implementation. We have attempted to fill this gap by proposing the StrAli-BPM (Strategic Alignment with
BPM) approach, which is divided in two parts – BLA@BPMN and BLA2SLA: the former seeks to extend
the BPMN language by embodying NFPs, in the form of BLAs (Business Level Agreements); and the latter
semi-automatically derives a set of SLAs (Service Level Agreements), linked with web services, from a pre-
defined BLA. This paper outlines the BLA2SLA part of the StrAli-BPM approach. In addition, it includes a
prototype tool developed to validate BLA2SLA and the results of an experiment undertaken to validate it.
1 INTRODUCTION
The business scenario has undergone major changes
in the area of Information Technology (IT), since IT
has been adding value to business undertakings.
Largely as a result of competition, IT has become a
means of processing information to support
decision-making (Laudon and Laudon, 2009).
Organizations regard high investment in IT as vital
to obtain products and services supported by this
tool, and view it as one of the key factors in
achieving success in their strategic goals (Bruin and
Rosemann, 2010). When integrating Business and
IT, it is an ongoing challenge to prevent the
organization’s investments in IT from being
misdirected through low productivity and poor
quality (Shimizu, Carvalho and Laurindo, 2006).
Furthermore, with the high degree of dependency on
IT and investment in it by organizations, it is
essential to have suitable and well-structured
methods to ensure the solutions it offers are aligned
with corporate expectations and needs.
Business Process Management (BPM) can be
applied in this context to transform business
processes within organizations (Weske, 2007). From
the perspective of BPM, with the support of Service-
oriented Architecture (SOA), strategic alignment can
be achieved by managing and improving the
technological means by which processes can add
value to the organization (Allen, 2006). Process
modelling is critical to guide strategic alignment
and, hence, should not only take account of
functional properties but also Non-Functional
Properties (NFP) as a means of achieving quality
goals effectively and efficiently (Pressman, 2009).
Examples of NFPs are reliability, performance and
scalability, which directly influence the functional
capacity of a process (Sommerville, 2010).
However, there are several issues involved in
handling NFPs in this scenario in terms of the
available methodologies and tools. For example,
process modelling languages, including BPMN
(Business Process Model and Notation) (OMG,
2011), are only concerned with functional capacity
modelling (Pavlovski and Zou, 2008). In terms of
process execution, there are already well-established
concepts of Quality of Service (QoS) (Khaluf, Gerth
and Engels, 2011) and Service Level Agreement
214
Barros V., Fantinato M., M. B. Salles G. and Porto de Albuquerque J..
Deriving Service Level Agreements from Business Level Agreements - An Approach Towards Strategic Alignment in Organizations.
DOI: 10.5220/0004887202140225
In Proceedings of the 16th International Conference on Enterprise Information Systems (ICEIS-2014), pages 214-225
ISBN: 978-989-758-029-1
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
(SLA) (Caseau, 2005) for handling NFPs. Yet, from
the perspective of a strategic alignment, NFPs are
only created during the implementation of the
executable business processes, rather than at the
beginning of the BPM lifecycle.
It is necessary to take account of NFPs related to
organizational goals so that quality constraints can
be introduced at the business level; and this can be
done by Business Level Agreements (BLA)
(Bratanis, Dranidis and Simons, 2010). A BLA can
be understood as a set of SLAs; however, whereas
each SLA is combined with an electronic service (e-
service) and is designed to ensure quality at the
service level, a BLA is combined with a part of the
process model (i.e. a sub-process) that can be
executed by a set of services. Hence, a BLA must
formalize a goal at a business level, and this can be
expressed by a specific NFP linked with a metric
that must be achieved, and represents the broader
requirements of the organization.
Currently, there is still no entirely satisfactory
solution for enabling business and IT areas to work
in alignment with modelling processes and their
subsequent execution, which takes account of both
functional properties and NFPs. In an attempt to
provide a strategic alignment in the context of
BPM/SOA, we proposed the StrAli-BPM (Strategic
Alignment with BPM) approach, which is formed of
two parts: (i) BLA@BPMN – an extension of the
BPMN notation that is designed to include BLAs
and (ii) BLA2SLA – a top-down strategy to refine
BLAs into SLAs which is combined with the e-
services that compose the executable process
derived from the BPMN model. This paper’s main
focus is on the BLA2SLA part since BLA@BPMN
has already been outlined (Salles et al., 2013).
This paper is structured as follows: Section 2, the
main background concepts; Section 3, the
methodology employed; Section 4, an overview of
the StrAli-BPM approach; Section 5, details of the
BLA2SLA part; Section 6, an assessment of the
approach being adopted; and, finally, Section 7,
conclusions and recommendations for further work.
2 CONTEXTUAL BACKGROUND
In the BPM context, NFPs are constraints that have
to be imposed to ensure quality and meet other
business process requirements (Pavlovski and Zou,
2008). However, NFPs are not yet widely accepted
and often receive less attention than the functional
properties in the BPM approaches. BPMN, for
instance, in its official version, does not deal with
NFPs although there are some limited proposals in
the literature. Taking into account some similarities,
BPM approaches should be given the same conduct
as that given to the functional and non-functional
requirements in the Software Engineering
approaches (Sommerville, 2010).
The functional performance of IT services
depends on a number of NFPs, such as: availability,
response time and accuracy. The QoS assurance
provided by IT is one of the most important factors
for business success, as well as improving
competitiveness (Khaluf, Gerth and Engels, 2011).
SLAs can formalize and ensure that these operating
and quality constraints are overcome. SLAs are thus
able to assess whether the service provided complies
with the terms agreed between parties (Theilmann et
al., 2010). With regard to the specific BPM/SOA
context, the most commonly languages employed to
formalize SLAs are WS-Agreement and WS-Policy,
both based on XML and recommended by W3C.
SLAs address the QoS attributes and levels, and are
linked to the web services that provide an executable
process that is implemented to meet the functional
requirements of a process model (Caseau, 2005).
The SLAs specified in one of these two languages
have their own structures and can, for example, be
used to define goals, metrics, fines and bonuses.
A BLA, in turn, can be considered to be
equivalent to a SLA at a business level. SLA
features are, hence, found in a BLA, and include:
agreement validity, fines and bonuses (Bratanis,
Dranidis and Simons, 2010). Thus, a BLA, linked to
a sub-process, can be hierarchically mapped to a set
of SLAs. During the process modelling, a BLA is
regarded as a “father” agreement that is related to a
set of activities in the process model. During the
process implementation, this BLA can derive a set of
SLAs that are linked to the respective services.
These services, in turn, were derived from the
business process model to perform its set of
activities. This top-down derivation, as illustrated in
Figure 1, defines a set of SLAs that, if all are met,
allows the BLA goal to be achieved in an induced
way (Goel, Kumar and Shyamasundar, 2011).
Figure 1: Relationship between BLA and SLAs.
In essence, the structures of the SLAs and BLAs
may be similar. The main difference between them
is the type of goal that each one defines: SLAs must
SLA
BLA
SLA
SLA
SLA
SLA
Business Perspective
IT Perspective
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assure QoS fulfilment, whereas BLAs aim at
determining the strategic requirements and target
values that the organization has to achieve.
These strategic requirements inside a BLA can
be defined through Key Performance Indicators
(KPI), which is a management tool to measure
business effectiveness (Wetzstein et al., 2009). KPIs
are used to support the definition and measurement
of strategic organizational requirements (Parmenter,
2010). Moreover, the definition of the KPIs depends
on the business features and economic or
organizational context (Friedenstab et al., 2012).
Whereas the SLA concept, as well as the QoS, is
firmly established in industry as well as in academia,
BLA is still considered to be a new concept, whose
structure and usage have not yet been mastered
either conceptually or in practice.
A short, illustrative example is given in Figure 2
to clarify the differences between BLA and SLA and
give a better explanation of how BLAs can ensure
that organizational goals are met through KPIs.
Figure 2: Illustrative example of BLA and SLAs.
3 METHODOLOGY
To ensure that the results of this work were
achieved, this study was based on the design science
research methodology (Hevner et al., 2004). This
reflects business needs and finds ways of catering
for them by underpinning the investigation with the
scientific development of solutions as well as
drawing on the results achieved by the research. The
purpose of the artefacts that are being developed is
to address unsolved problems or those that cannot be
solved satisfactorily, which, in this study, is the lack
of any formal representation for BLA, the lack of an
approach to relate BLA to BPMN and the lack of an
approach to derive BLA into SLAs. In this work, the
designed-oriented approach was adopted (Osterle et
al., 2011). This involved conducting an analysis of
business needs to investigate both the external and
internal factors that influence these issues. As a
result, the design and preliminary evaluation of the
proposed solution (i.e. both parts – BLA@BPMN
and BLA2SLA – of the StrAli-BPM approach) were
carried out in the initial stage. Finally, the
communication stage was executed to disseminate
the results obtained.
On the basis of the methodology outlined above,
a theoretical survey and a study on the state of the
art of the context discussed were carried out as a part
of this study. The theoretical survey included topics
such as strategic alignment between business and IT,
BPM, SOA, NFP, KPI, BLA, SLA/QoS and the
BPMN and WS-Agreement languages. This was
followed by a comprehensive development and
evaluation of the BLA@BPMN part of the StrAli-
BPM approach, although it is not strictly within the
scope of this paper since it has already been
examined by Salles et al. (2013). Following this, it
was possible to address, the BLA2SLA part.
A WS-Agreement metamodel was devised, by
using a UML Class Diagram, to allow a better
understanding of the concepts that underpin the WS-
Agreement, and thus link the concepts of the two
parts of StrAli-BPM. After this, there was a
systematic mapping to make a comparison between
the existing BLA@BPMN metamodel and the newly
created WS-Agreement metamodel. This enabled us
to have an exact understanding of how: information
of a BLA that is linked with a BPMN, and exported
in a XML format, can be used to provide
information for the derived SLAs through the fields
specified in the WS-Agreement schema. C# was
used to implement a prototype tool for BLA2SLA.
This tool uses the XML standard for both the data
input (BLAs exported from BLA@BPMN prototype
tool) and the data output (WS-Agreement language).
4 StrAli -BPM
The StrAli-BPM approach proposed by Salles et al.
(2013) employs BPMN as its basis. It was chosen
Organization: a financial institution with nearly twenty
million customers;
Corporative context: in 2013, priority will be given to
customer satisfaction;
Process: loan contracting for account holders;
BLA: following a customer’s loan request, a credit contract
should be created within a maximum of six hours, including
intermediate activities, assuming that the proposal is accepted
by the credit board;
KPI: processing time;
Target value: six hours or less;
SLA-1: activity/service “Send proposal to the credit board for
analysis”;
Service latency 30 seconds;
Service availability 99,95% (from 10am to 4pm);
SLA-2: activity/service “Analyze proposal data”;
Service response time (analyze the proposal and enter the
results into the system) 4 hours;
SLA-3: activity/service “Send response of the proposal
analysis”;
Service availability 99% (from 10am to 4pm);
SLA-4: activity/service “Generate a credit contract”;
Service response time 5 minutes;
Service availability 99.95%;
Service recover
y
in case of failure 25 minutes.
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because of its widespread use and standardization.
The mapping from processes modelled in BPMN to
its executable version in WS-BPEL/WSDL has
already been covered by other studies, such as by
Mazanek and Hanus (2011), and can be called
BPMN2BPEL. StrAli-BPM establishes an analogue
mapping, in which the BLAs, which are represented
as an extension of the BPMN models, can be
mapped to an SLA standard (WS-Agreement, for
example). These SLAs, in turn, are combined with
the web services that compose the executable
process and form relationships that are graphically
shown in Figure 3. The focal point of this paper is
on how a set of SLAs can be derived from a BLA,
i.e. the transformation of the NFPs; and is similar to
the way in which functional properties can be
transformed by BPMN2BPEL.
The conceptual framework outlined in Figure 3
shows more clearly how StrAli-BPM closes a cycle
to achieve the strategic alignment, by using BPMN,
BLAs and SLAs. In terms of phases, the first stage
(analysis and design) usually comes under the
responsibility of business areas, whereas the second
(implementation and execution) is usually performed
by IT. From another perspective, this approach
allows both functional properties and NFPs
(represented through BLA and SLA) to be defined in
an integrated, top-down manner.
The first part of StrAli-BPM, which is not
addressed in this paper, is called BLA@BPMN
(BLA at BPMN) and consists of a BPMN extension
to represent the BLAs, which use KPIs to define
their goals, combined with groups of activities in the
process. This extension includes both a metamodel
to represent the BLAs and a graphical notation.
The second part of the StrAli-BPM, called
BLA2SLA (BLA to SLA), is related to the semi-
automatic derivation of BLAs to SLAs, which are
combined with the web services that compose the
executable process. The next section examines the
structure used to represent SLAs, the mapping
between the BLAs and SLAs, and the prototype tool
employed to validate the BLA2SLA.
In StrAli-BPM, a BLA is accompanied by some
general recommendations with regard to its structure
(Allen, 2006). The general recommendations aims at
identifying: the Goal (and its linked KPI), Penalties
and Rewards (Pourshahid et al., 2009; Friedenstab et
al., 2012). The proposed structure for a BLA is
represented in Figure 4 as a metamodel. A BLA
artefact thus has a well-defined attribute structure
that can be used as a template to create and store
BLAs. Some of the attributes in Figure 4 have
similarities to SLAs, albeit at a business level.
As shown in Figure 4, Goal, which uses the KPI
concept, represents which property or requirement
should be fulfilled or improved by the BLA, together
with the target value that must be achieved. KPIs, as
discussed in Section 2, must be defined in
accordance with business requirements. Penalty and
Reward, in turn, represent indemnities which must
be paid for by the Customer and Supplier,
respectively, depending on the extent to which the
Goal is attained. The Penalty attribute can have one
or more occurrences in each BLA; and, the Reward
attribute, none or more occurrences. The BLA class
Figure 3: StrAli-BPM Approach - Proposed Conceptual Framework.
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relates to a series of class in the BPMN metamodel.
These relationships are not scope of this paper.
Figure 4: BLA Metamodel.
As regards the BLA@BPMN part, a new object
type, designated as BLA, was incorporated into
BPMN (version 2.0) as a Custom Artefact, tested in
the Bizagi tool. Figure 5 shows the BLA artefact
represented in a process model for credit application
(like the example in Section 2), according to the
visual patterns of Bizagi. The BLA artefact connects
to a sub-process through a “Group artefact” and an
“Association connector”, both of which already exist
in BPMN. The BLA object called “6 hours for
contracts origination” involves four activities of the
process model that are associated with the target
goal set, i.e. a BLA goal, which uses the KPI
concept, comprises a set of one or more activities
(which later will be derived to a set of one or more
SLAs). By employing this approach, and taking
account of the nature of the BLAs, two or more
BLAs can have a non-empty intersection with each
other, i.e. the same activity can be contained in two
or more BLAs.
5 BLA2SLA APPROACH
In an attempt to achieve an alignment between
business and IT, BLA2SLA proposes that the goals
established at the business level, that are represented
in BLA, be used as input for defining the SLAs in a
top-down process. This derivation process requires
the work of an IT specialist with knowledge of
business needs and especially of the business
process domain and web services technology. Thus,
after the definition of the KPI-based goals, that are
linked to business processes in a BLA-form, these
BLA-goals will be divided into specific objectives,
(at an operational level), which are represented by
the SLAs and use non-functional properties through
QoS attributes. The next subsections describe
BLA2SLA in terms of: SLA structure, BLA-SLA
mapping and as a support tool.
5.1 SLA Structure
The BLA structure defined for BLA@BPMN,
through a metamodel, was designed to be flexible
enough to allow the BLA-SLA mapping to be
undertaken in different SLA and QoS specification
languages. In the specific case of the StrAli-BPM
approach, the WS-Agreement language was chosen
to carry out the mapping.
WS-Agreement aims at defining and monitoring
the SLAs that have been established between the
customer and supplier for a set of web services
(Andrieux et al., 2007). The task of specification is
done by using XML and monitoring occurs while
the web services are being executed. WS-Agreement
thus describes the related web services and the SLAs
Figure 5: Illustrative example of BLA@BPMN.
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established for them, including their QoS attributes
and guarantees, such as fines and bonuses, which
must be applied in accordance with the fulfilment of
the service level agreements.
The basic structure of an SLA specified in a WS-
Agreement is illustrated in Figure 6. Name serves as
an identifier and Context should mention, at least,
the customer, the supplier and the validity of the
agreement. Terms represent the formal obligations
between the parties. This section should contain at
least: (i) Service Terms, which define the functional
part, i.e. the data with respect to the web services
involved in the agreement; and (ii) Guarantee
Terms, which define the non-functional part, i.e. the
SLA goal and the inclusion of penalties and bonuses
to ensure that the goals are met.
Figure 6: WS-Agreement Framework.
A WS-Agreement metamodel was established to
systematize the derivation rules of BLAs to SLAs,
since no suitable metamodel was found in the
literature. The WS-Agreement metamodel was
formed by means of the language specification
outlined by Andrieux et al. (2007), and maintained
by the Open Grid Forum. The resulting WS-
Agreement metamodel is shown in Figure 7. This is
a slightly simplified version when compared with
the language schema, but it meets the needs of
StrAli-BPMs. All the required classes and attributes
of the scheme were complied with. Additionally,
some of the optional elements which are needed in
the BLA-SLA mapping were also retained.
As shown in Figure 7, in a WS-Agreement,
AgreementId and Name are used as identifiers. In
Context, Agreement Initiator defines the initiator of
the request for an agreement creation; Agreement
Responder defines the entity that responds to the
agreement creation request; and ServiceProvider
Agreement Initiator/Responder defines which of
these parts must be declared as a SLA supplier. Still
in Context, ExpirationTime defines the time at
which the agreement is no longer valid; and
TemplateId and TemplateName optionally define a
SLA template in WS-Agreement (set, respectively,
to an AgreementId and a Name), which is used to
specify an agreement from pre-defined information.
Terms represent the formal obligations between
the involved parties. ServiceDescriptionTerm,
ServiceReference and ServiceProperties compose
the Service Terms (as described in Figure 6), which
define the functional part of the SLAs, i.e. the
description of web services involved in SLAs. Web
services can either be completely described or else
only referenced, when they have been previously
specified in WSDL. ServiceDescriptionTerm, the
only mandatory class, lists all the web services,
through ServiceName, which can be used later while
creating the Guarantee Terms. ServiceReference
Figure 7: WS-Agreement Metamodel (SLA Structure).
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may be optionally used to reference external
information of the web services, through
ServiceName, such as a WSDL specification. And
ServiceProperties may be (optionally) used to
specify non-functional properties of the web
services, also through ServiceName, which can be
used later while creating the Guarantee Terms.
ServiceProperties is composed of VariableSet
which, in turn, is composed of Variable. In Variable,
Name defines the name of the non-functional
property (e.g. availability, latency, cost); Metric
defines the semantics of the non-functional property
(e.g.: percentage, second, dollar); and Location can
store a reference in a local/file – usually in the XML
structure – that describes features in that non-
functional property.
GuaranteeTerm composes the non-functional
and hence most important part of the WS-Agreement
(as described in Figure 6), i.e. the agreement goals
and the possible penalties and bonuses used to
encourage the fulfilment of the established goals. In
GuaranteeTerm, Name defines the name given to a
guarantee, which in practice represents the name of
each SLA that is part of a WS-Agreement
specification. Obligated Service Consumer/Provider
defines what is the part, considering the service
consumer and the service provider, responsible for
meeting the goal. QualifyingCondition, when used,
defines a precondition which is required for the
GuaranteeTerm to hold. ServiceScope defines which
services, specified through ServiceDescriptionTerm,
are included in a given GuaranteeTerm.
ServiceLevelObjective defines the SLA goal in
GuaranteeTerm, through two options: KPITarget
and CustomServiceLevel. In KPITarget, KPIName
and Target defines the SLA goal as, respectively, a
KPI expression and a KPI target expression.
KPIName can use data (i.e. non-functional
properties) defined as Name in Variable. In
CustomServiceLevel, any structure of attributes can
be generically defined to specify the SLA goals
according to needs in exceptional cases.
BusinessValueList defines a set of values for the
GuaranteeTerm, each expressing a different aspect
of the ServiceLevelObjective. In BusinessValueList,
Importance, when present, defines the relative
importance of meeting a ServiceLevelObjective.
CompensationType defines a Penalty or a Reward,
to be applied if the SLA goal is not attained. In
CompensationType, ValueExpression and Value
Unit define, respectively, the type of currency (e.g.:
R$, USD) and amount of money that must be paid in
each compensatory action. A Penalty must be paid
from the provider to the consumer, and a Reward in
reverse. A Penalty or Reward can apply on multiple
occasions for the same GuaranteeTerm, in different
periods. AssessmentInterval defines the application
frequency of a compensatory action, through two
options: TimeInterval and Count. TimeInterval
defines frequency during a given time interval such
as number of days, number of weeks, number of
months, etc. Count defines frequency through the
number of invocations of the service with regard to
the GuaranteeTerm. Preference, when used, defines
alternative ways of achieving the associated Service
LevelObjective. In Preference, ServiceTerm
Reference refers to one or more ServiceName, in
ServiceDescriptionTerm, and can be used as
alternative ways to achieve the ServiceLevel
Objective; and Utility defines respective utilities
obtained by achieving this ServiceLevelObjective.
5.2 BLA-SLA Mapping
Each BLA, which contains a single goal, must be
derived into a set of SLAs, each with its specific
goal. In the light of the use of WS-Agreement to
specify SLAs, a BLA structure should physically
result in a WS-Agreement file, which in turn can
contain various SLAs represented by different
GuaranteeTerm sections in the WS-Agreement file.
In deriving BLA to SLAs, a part of the attributes
mapping is done directly, i.e. the information
specified in the BLA can be automatically forwarded
to the SLA specification. In contrast, the other part is
done indirectly, i.e. the BLA information should be
regarded as simply consisting of suggested values to
be used as SLA attributes or values to be used only
as a reference for specifying the SLA attributes.
Table 1 shows the direct mapping from the
attributes of the BLA metamodel (see Figure 4) to
the attributes of the WS-Agreement metamodel (see
Figure 7). To compose the Agreement Initiator and
Agreement Responder attributes in SLA, a
concatenation of, respectively, the customer_
organization + customer_department and supplier_
organization + supplier_department attributes, from
BLA, is proposed.
Additionally, Table 2 shows SLA attributes that
can be indirectly created as a suggestion or a
reference, from either the information from BLA or
the WS-Agreement framework. The information
supplied in Table 2 should only be used as reference
values, basically to support the specialist work.
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These values can also be used by the support tool
as suggested by the pre-filled values, which can be
changed if the specialist does not agree with them.
In an a priori approach, the total value of
compensatory actions (ValueExpression) of a set of
SLAs must not exceed the value of the
compensatory action (compensation _value) of the
respective BLA used to derive these SLAs.
However, in view of the fact that the application
frequency of BLA and SLA actions may differ, this
systematic control was not predicted for BLA2SLA.
Although they are described in Figure 7, some
classes and attributes of the WS-Agreement
metamodel are not addressed in the BLA-SLA
mapping shown in this section. They are also not
included in this first version of the BLA2SLA
approach being proposed. The following items of the
WS-Agreement metamodel have still not been
addressed: attributes TemplateId and TemplateName
from Context class; attribute Location from Variable
class; attribute Importance from BusinessValueList
class; and the whole of the Preference class.
The BLA goal, which is defined in terms of a
KPI, must be converted to non-functional properties
at the service level, and this can be represented by
QoS attributes. A well-defined list of QoS attributes
was used with the aim of standardizing the SLAs
created by BLA2SLA. Table 3 lists the QoS
attributes used in this study for this purpose.
5.3 BLA2SLA Prototype
The prototype tool for BLA2SLA was designed to
act as a semi-automatic converter. It was developed
in C# language, given its robustness for processing
data in XML format. The tool computationally
interprets the BLAs, exported in the XPDL language
(based on XML) by the BLA@BPMN tool, and
supports the specialist user in the creation of SLAs
to be specified in the WS-Agreement language (also
based on XML), respecting their pre-defined
structure and metamodel (see Figure 7). The XPDL
files exported by BLA@BPMN contain information
from both the business process model specified in
BPMN as well as the linked BLAs.
Table 1: Direct mapping from BLA to SLA attributes (directly automatable mapping).
BLA (from) SLA / WS-Agreement (to)
Class Attribute Type Class Attribute Type
BLA name String WS-Agreement Name String
due_date Date Context ExpirationTime Date
corporative_context String GuaranteeTerm QualifyingCondition String
customer_organization String Context Agreement Initiator String
customer_department String
supplier_organization String Agreement Responder String
supplier_department String
Activity name String ServiceDescriptionTerm ServiceName String
ServiceReference ServiceName String
ServiceProperties ServiceName String
ServiceScope ServiceName String
Table 2: Indirect mapping from BLA to SLA attributes (not directly automatable mapping).
SLA / WS-Agreement (to) Reference – BLA / SLA (from
Class Attribute Type Option From Value
Guarantee
Term
Name String Reference value
BLA /
SLA
name attribute from WS-Agreement class or BLA class
+ KPIName attribute from KPITarget class
KPITarget
KPIName String
Reference value BLA all attributes from the Goal class
Target Double
Compensation
Type
ValueUnit String Suggested value BLA currency attribute from Compensation class
Value
Expression
String Reference value BLA compensation_value attribute from Compensation class
Count Count Integer Suggested value BLA
Value “1” [when the attribute check_on_BLA_due_date
from Goal class is ‘equal to false’]
TimeInterval Time Interval Integer Suggested value BLA
Difference (in days) between the due_date from BLA
class and the current date [when the attribute check_on_
BLA_due_date from Goal class is ‘equal to true’]
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Table 3: QoS attributes used by BLA2SLA, as proposed
by Garcia and Toledo (2006).
QoS
attributes
Unit
(metric)
Definition
Accuracy Percentage The service error rate over a
time interval
Capacity Integer The number of concurrent
requests a service allows
Reliability Time The time for continuity of
correct service and for transition
to correct state
Cost Double The calculation of the costs
incurred of using the service
Availability Percentage The time a service is operating
(in percentage terms)
Scalability Percentage The throughput increase rate in
a given time interval
Stability Percentage The rate of change of service
interface
Latency Time The time taken to start servicing
a service request
Robustness Integer The level of service resilience l
to incorrect inputs and
invocation sequences
Throughput Percentage The request processing rate a
service supports
Response
time
Time The time a service takes to
complete its task
The tool has a main screen, as illustrated in
Figure 8, which is split in: (i) the top, which contains
general information on the SLAs (i.e. those related
to Name, Context and Service Terms according to
Figures 5 and 6); and (ii) the bottom, which contains
the SLA details (i.e. those related to the Guarantee
Terms according to Figures 5 and 6).
The tool operation begins with importing the
XPDL file that represents the business process
model generated and exported by the BLA@BPMN,
which includes all possible BLAs linked with such a
model. Then, the list of BLAs present in the process
model is displayed in BLA List field. Thus, any
BLA listed may be chosen by the specialist so that
the SLAs are derived for it.
According to the derivation rules presented in
Table 1, the fields SLA Name, Expiration Time,
Agreement Initiator and Agreement Responder are
automatically filled with information from the
imported XPDL file, in line with each selected BLA.
This information is ready only in the tool.
The Services list is similarly filled with
information from the XPDL file: all activities that
have been selected as part of the sub-process under
jurisdiction of a BLA are presented as potential
services to be implemented as web services. The
processing of this type of information in the input
file needed to consider details of the language used
by the BLA@BPMN tool: for example, the BLAs
are linked to activities in the BPMN model using
graph coordinates X and Y. Once incorporated by
the BLA2SLA tool, these activities have the “WS-”
prefix added to their names.
Given that not all activities present in the process
model should be computationally executed via web
services, the specialist may disregard such activities
marking them as Not a service. This action can be
useful, for example, to disregard activities from the
process model that will be manually executed or via
Figure 8: BLA2SLA prototype tool – main screen with an illustrative example.
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222
script; since in this case this approach does not
assumes a SLA for them in terms of SOA context.
Activities marked as Not a service are not
considered by the tool during definition of the
Guarantee Terms. For purposes of SLA integrity
control, only activities not currently used to create
Guarantee Terms may be marked as Not a service.
For each BLA, it is expected that the specialist
defines a set of SLAs (i.e. a set of guarantee terms)
according to his or her knowledge about this BLA-
SLA mapping and the business-IT involved context.
The tool helps the specialist to find, in a visual and
systematic way, the best set of SLAs that together
will cover the respective BLA.
The tool presents a list of the GuaranteeTerms
already created for the selected BLA. The existing
ones can be edited or new ones can be created. For
both cases, a list of web services is presented in the
Scope list to be selected or unselected for the scope
of the GuaranteeTerm, which means for which web
services it applies. Activities marked as Not a
service are not presented in the Scope list.
For each Guarantee Term, and all services
selected as its scope, information related to the
Service Level Objective should be defined. Such
information includes: Guarantee Term Name, KPI
Name, Target and Metric. CustomServiceLevel
option is not available in this tool version. None of
this information is direct created by the tool, i.e. they
need to be defined by the specialist based on the
selected BLA, whose details can be viewed in this
tool for reference. For KPI Name, the tool allows the
specialist to choose one of those QoS attributes
presented in Table 3, and once it is chosen the
respective metric unit is presented in Metric. These
QoS attributes are physically stored in the structure
of the Variable class (see Figure 7). Target must be
defined by the specialist.
Also for each Guarantee Term, and the KPI
Target (Service Level Objective), a set of Rewards
and a set of Penalties can be defined by the
specialist. The tool lists all already defined rewards
and penalties, which can be viewed or deleted. To
add either new rewards or penalties, the specialist
must define their Value Unit and their Value
Expression. All currency values used in the selected
BLA are made available for selection for Value
Unit, although any other currency value can be used.
Moreover, the specialist must define the rules for the
Assessment Interval in terms of Count or Time
Interval. In this case, values are suggested according
to those proposed in Table 2, and can be changed
according to decision of the specialist. The derisions
being taken in these cases, by the specialists, should
be done considering the selected BLA, whose details
can be viewed anytime.
In the illustrative example showed in Figure 8,
there is a SLA (or Guarantee Term) is presented,
called “GuaranteeTerm1”. Moreover, a new SLA,
called “GuaranteeTerm2” is being added.
“GuaranteeTerm1” has the following associated data
(not presented in Figure 8):
Web service(s) in Scope: “WS-Send for
approval”;
KPI Target (Service Level Objective):
Response Time in 30 minutes;
Penalty: $ 5,000.00 [to be charged to each
service invocation].
“GuaranteeTerm2”, in turn, is being defined with
the following data (presented in Figure 8):
Web service(s) in Scope: “WS-Send positive
response” e “WS-Create contract”;
KPI Target (Service Level Objective):
Availability in 95,00%;
Penalty: $ 10,000.00 [to be charged to each
service invocation].
Still for this specific case of BLA, a third
example of SLA to be added could have the
following data (not presented in Figure 8):
Web service(s) in Scope: “WS-Send positive
response” e “WS-Create contract”;
KPI Target (Service Level Objective):
Availability in 99,00%;
Reward: $ 10,000.00 [to be charged to each
service invocation].
The tool allows that defined SLAs can be either
saved and loaded again or else exported in the WS-
Agreement format. If there are more than one BLA
in the process model imported via XPDL file, the
tool creates a WS-agreement for each BLA during
the export procedure.
The following attributes of WS-Agreement
language were not incorporated by the tool
BLA2SLA: Location (Variable class), Importance
(BusinessValueList class), ServiceTermReference e
and Utility (Preference class), as presented in
Section 5. Thus, these attributes are given the default
value "[to be defined]" at the time of SLA
generation in WS-Agreement specification.
Therefore, an XML file is created in accordance
with the official WS-Agreement scheme, which
allows the IT area subsequently specify this
information as needed.
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6 EVALUATION OF BLA2SLA
An experiment was conducted with specialists to
analyze the StrAli-BPM approach, including
BLA2SLA. According to Sánchez et al. (2010), an
experiment helps determine the effectiveness of
methods and approaches proposed in a previous
study, and by reducing uncertainties about the
associated theory. Travassos, Gurov and Amaral
(2002) state that an experiment should be supported
by measurements so that the initiative that is carried
out can be characterized, and that these can be both
qualitative and quantitative.
The Goal-Question-Metric (GQM) technique
was used to systematize the experiment: this is an
experimentation process based on the phases of
definition and interpretation (Travassos, Gurov and
Amaral, 2002). The definition phase adopted a top-
down approach: setting goals, formulating questions
and defining the metrics. The interpretation phase
used a bottom-up approach: measuring the results of
the experiment in terms of metrics, formulating
answers to the defined questions and grouping the
answers to demonstrate the success of the goals.
Six employees of a large scale Brazilian
financial institution were involved in the experiment.
Only specialists in the application field of StrAli-
BPM were chosen to take part in the experiment.
Moreover, these specialists represent different
management levels (strategic, tactical and
operational) as well as both of the different sides –
business and IT. The experiment involved a formal
introduction and a practical handling of StrAli-BPM
and associated tools, including BLA2SLA.
The goals were defined with the aim of
understanding the following, from the standpoint of
the specialists: level of contribution, practical
applicability, effectiveness, viability, usability of the
prototypes, and limitations. Questions and metrics
were defined to refine these goals so that a roadmap
could be derived with four qualitative questions and
six quantitative questions to conduct focused semi-
structured interviews (Yin, 2005).
As a result of the experiment, a series of data
from analyses were collected for StrAli-BPM in
general, as well as for BLA@BPMN and BLA2SLA
in particular. The results that are solely related to
BLA2SLA can be highlighted as follows:
In terms of how much BLA2SLA contributes
towards achieving SLAs that meet the goals
set up by business areas; the specialists stated
that it provided significant advantages over
ad-hoc approaches. On a scale from 1 to 5, the
average of their responses was 3.7;
In terms of the ease of creating SLAs from the
goals established in BLAs that are combined
with business process models; the specialists
thought that BLA2SLA has a good degree of
usability. On a scale from 1 to 5, the average
of their responses was 3.5;
The results of the qualitative questions, in
general, showed that: on the one hand,
BLA2SLA performed very well in the
evaluation, and the specialists pointed out that
it had a number of potential benefits and
advantages; on the other hand, the same
specialists also noted a number of limitations
since they thought that as the organizational
environment of a large-scale company is quite
complex, such an approach must be fully
mature to allow it to be used effectively.
7 CONCLUSIONS
The StrAli-BPM approach advances the state of the
art in the Strategic Alignment between business and
IT areas by suggesting that SLAs can be established
from BLAs. The BLA2SLA part outlined here was
carried out from the BLA@BPMN part, which was
previously discussed by Salles et al. (2013).
The StrAli-BPM approach is sufficiently general
to meet a wide range of needs in business areas and
IT infrastructure, since organizations have peculiar
features in terms of process modelling, SOA
paradigm implementation and KPIs with business-
aware capacities. In Salles et al. (2013), it has been
shown that the use of BLAs and KPIs essentially
makes it easier to identify NFPs in the context of
BPM, at the process level.
In addition to the mapping to BPMN elements,
the BLA structure was prepared to enable the
subsequent semi-automatic derivation of SLAs,
since the BLA@BPMN prototype tool exports the
BLA structure, with all its attributes and values, to
the XML format. In view of this, we decided to
move towards with this approach, by
accommodating the derivation of BLA in SLAs, as
well as by developing and evaluating its
computational support in greater depth.
The results of the experiment that was conducted
to evaluate the whole StrAli-BPM show that this
BLA2SLA part was well assessed by all the
specialists involved. In summary, they reported that
they ignore any approach similar to BLA2SLA and
considered it to be an important step towards
achieving strategic alignment in organizations.
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In future work, we would like to improve the
BLA2SLA approach by extending the direct
mapping between BLA and SLA attributes,
whenever possible. Moreover, we would like to test
it by carrying out a controlled experiment in which
users could try it out in a case study.
ACKNOWLEDGEMENTS
We thank the State of São Paulo Research
Foundation (Fapesp), Brazil, for its support.
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