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STRATEGIC INFORMATION REQUIREMENTS ELICITATION:
A NORMATIVE MODEL OF INFORMATION DOMAINS AND
INFORMATION TYPES
Gianmario Motta,
Information and Systems Department, University of Pavia
Via Ferrata n.1 I-27100 Pavia Italy
Giovanni Pignatelli
Information and Systems Department, University of Pavia
Via Ferrata n.1 I-27100 Pavia Italy
ABSTRACT
This paper presents a method for Strategic Information Requirements Elicitation
(SIRE). It defines information requirements for the Enterprise, and it includes (a) a
metamodel (b) a series of design steps and (c) a software tool. The metamodel creates
normative information models, since it defines the information domains a given
enterprise should have. The design steps cover the process that goes from the
metamodel down to a ER schema of databases, by a sequence of breakdown and
specializations. The software tool helps the analyst in designing well formed schemas.
The approach is founded on some key ideas. First, an enterprise processes information
on a set of universal domain families, which include stakeholders, products, process
and contexts. By specializing these domain families the analyst identifies domains
specific to an individual enterprise. Second, any information domain includes
different information types, namely master information, that defines structural
properties, transaction information, performance / analytical indicators. By crossing
information domains and information types the analyst identifies Strategic
Information Entities (SIE). A case study on Healthcare shows how powerful the
method is. The method is simple and elegant, for it requires a minimal amount of
definitions and is readily understood by management and users. In information
systems planning, it can be used to define the overall domains of a given service
system, e.g. healthcare, to assess the coverage of current systems and the gap to fill.
The tool also allows to store high level models that can be mapped against real
database schemas of commercial software platforms to understand their coverage
Finally it can be used for a green field design of new systems.
Keyword: Strategic Information Requirements, Aggregated Business Entities,
Systems Requirements Engineering, Requirements Analysis, Systems Analysis, IT
Strategic Planning, IT Strategy
INTRODUCTION : APPROACHES TO STRATEGIC ANALYSIS OF
INFORMATION REQUIREMENTS
Since the heydays of information systems, an evergreen issue is the structure and
semantic of the enterprise information. In short, the issue can be summarized by two
questions:
• What information our business needs?
• How far is actual information from the information we need?
The issue can be at high or low level. At low level you have the detail typical to the
analysis of elementary activities and transactions. There, the solution is simple: the
analyst collects and models the requirements of the user or of processes and maps
them versus the computer databases. At high level you need to work with the
aggregation typical to IT strategic planning or to the analysis of the enterprise process
architecture. At this level, the analyst should elicit the structure and semantics of
information from the characteristics of the enterprise. Analysis of high level and
strategic information requirements is precisely the scope of this work. Our purpose is
a model that has normative power, generality and completeness. With this model, the
analyst would get a list of the potential contents of the data base of the enterprise and
compare actual information with the ideal information classes. .
The need of a structured approach to identify information emerged since Seventies. A
champion of this early methods is Business Systems Planning (BSP), very popular in
Eighties (IBM, 1975). BSP associates data classes and processes in a grid, that shows
which process uses which data. The oversimplified example given below (Table 1)
shows how information classes IC1, …, ICn are used by processes P1, .., Pn. The X
sign indicates that the information is used; the empty box means the information is
not used.
Table 1 Information to business process grid : a simple case
Information Classes Business
Processes IC1 - Materials
Master
IC2- Inventory
Level
IC3 - Receiving Transactions
IC4- Inspection Transactions
P1 X - X X
P2 ... X ... ...
... ... ... ... ...
Pn X X - X
From our viewpoint, the robustness of this approach is questionable. First, neither
completeness nor granularity nor homogeneity of information classes are certified.
Indeed, the information classes reflect the experience of users being interviewed, but
the analyst does not know if all potential information has been considered or not.
Second, the aggregation level of information classes can be heterogeneous. “Materials
Master” is much more comprehensive information class than “Receiving
Transactions”, “Inspection Transactions”, “Inventory Level”. The subsequent
champion, Information Strategy Planning (ISP (Martin, 1990) integrates different
information models, such as BSP, Entity Relationships and Data Flow Diagrams
(DFD), but does not complies with granularity, completeness and homogeneity
requirements. With the advent of Enterprise Resource Planning suites, a new family of
information systems analysis methodologies emerged. Among them, the highly
successful ARIS (Architecture of Integrated Information Systems) provides some
normative definition of high level information, but it mirrors SAP (Scheer 2000) and,
therefore, does not provide a really universal view.
Another methodological family is given by business processes reference frameworks.
Among them SCOR (Supply Chain Organization and Reference Model) gives a
comprehensive and widely accepted framework of business process in manufacturing
industry (Bolstorff 2007, SCOR 2001). The framework supports the analyst to design
and /or assess a map of business processes to plan and operate sourcing, making and
delivering operations of a supply chain. A similar framework for the domain of
telecommunications is proposed by eTOM (Enhanced Telecom Operations Map®)
eTOM contains also the Shared Information Data Model (SID), that offers a
normative framework for shared information / data, based on the concepts of Business
Entities and Attributes (TMForum 2003, 2005). A Business Entity is a thing of
interest to the business, while Attributes are facts that describe the entity. In short “an
Aggregate Business Entity (ABE) is a well-defined set of information and operations
that characterize a highly cohesive, loosely coupled set of business entities”
(TMForum, 2003). By defining ABEs in telecommunications domain, SID is a
normative framework for information but it lacks universality, since it is oriented to
telecommunications nor it provides an axiomatic approach to identify Entities.
A third family of framework concerns management information. For instance, the
worldwide known Balanced Score Card (BSC) (Kaplan and Norton, 1996, 2006) and
6Sigma (Gupta, 2006) define also normative frameworks of management information.
BSC proposes a list of indicators for strategic control (financial performance,
performance of internal processes, performance on learning and growth) and 6 Sigma
provides a method to identify quality performance data. However, these frameworks
not comprehensive, since they consider management and not operations information.
Furthermore, they lack a formal method.
The focus of these three families of framework can be described on three axes (Figure
1). The axis of generality represents the universality of an approach on industries: the
wider the range the higher the universality. The axis of normative capacity measures
the ability of suggesting the “right” information requirements. The axis of
completeness of represents the capacity of considering all information realms, namely
management, analysis, operations. Different approaches excel on different axis, but no
one has a comprehensive coverage. BSP is universal but it is not normative at all.
BSC is general and normative but not complete. Finally, SID is normative, but not
general nor complete. Figure 2 also positions our purpose. Our purpose is a normative
model that fills the three axes of normative capacity, generality and completeness.
With such model, the analyst will get a list of the potential contents of the data base of
the enterprise that can be further validated and expanded.
Generality
Normative capacityCompleteness of
domains
BSP/ISP
BSC
eTOM
Figure 1 : Comparison of frameworks for enterprise information analysis
THE ENTERPRISE INFORMATION CATALOGUE
The first step of a normative model is to define a catalogue. The catalogue lists
information domains and also defines their structure. Now the catalogue should be
universal, i.e. generally valid for whatever enterprise. The method will therefore
consist in the specialization of the types of the universal catalogue (super-type) into
the specific catalogues of individual enterprises (sub-types).
The catalogue should be comprehensive, thus reflecting a reasonable requirement of
completeness. Therefore information in catalogue should address all the potential
domains of structure/actors and of operations. Finally a catalogue should be
reasonably and not mix apples and oranges.
However, the key point is to identify are candidate SIEs of enterprises. As we have
said at the very beginning of our paper, the catalogue of candidate SIEs result from
crossing two main categories, information domains and information types.
INFORMATION DOMAINS
The concept of information domain is already used in the SID model. We assume an
enterprise processes information on the domains where it operates. Our first level is
nothing else but a generalization of the SID semantics and it includes stakeholders,
resources, context and output. Let us consider each of these domains.
Our vision of stakeholders reflect Freeman’s concept (1984), where “a stakeholder in
an organization is (by definition) any group or individual who can affect or is affected
by the achievement of the organization’s objectives”. In our catalogue stakeholders
include Law, Competitor, Customer, Supplier, Broker, Shareholder. In short,
stakeholders are the who’s of the enterprise.
The domain of output reflects the operations of the enterprise and includes Process,
Product and Service information.
Resource domains reflect classic economics and includes Personnel (as Human
Resources), Plants and equipments (as Technological Assets), Materials, Cash (as
Monetary Resources). In short, resources are input used by enterprise to produce its
outputs.
Finally, the domains of context reflect the environment where the enterprise operate
and include and its structure and include Structure, Project and Region.
INFORMATION TYPES
From countless years, analysts classify information in database in three classes,
namely master data, transactions data, analytical / calculated data. This intuitive
taxonomy is very valuable when generalized.
Master Data represent structural entity properties and are typically related to “strong
entities”. Transaction Data describe the properties of events a given strong entity is
generating or receiving, (as orders, state changes and alike) and are typically related
to “weak entities”. Finally Analysis Data are indicators that are calculated from
Transaction and Master Data, and provide information for management and
governance e.g. profitability of a plant, a customer or quality of a supplier.
THE STRUCTURE OF THE CATALOGUE OF SIRS
The result of the combination of information types and information domain is a grid
that contains the SIE of “level zero” (Table 2). Each cell represents a SIE that could
be seen as a couple (D, E) where D is the Information Domain and E is the
Information type.
CUSTOMIZATION, REFINEMENT AND VALIDATION OF THE
CATALOGUE OF SIES
The simple grid is of course useless. To get real data the analyst customizes SIEs that
are specific to the individual enterprise within the analysis scope. An example of such
customization is Table 3 where the aggregate domain “Customer” is specialized in the
sub-domains “private” and “enterprise”. Similarly, master data are specialized into
“Identification and “Social” and the same happens with Transaction data.
In short the customization is obtained by well known primitives of Creation,
Specialization, Decomposition used on aggregate information domains and
information types. Actually, the customization is iterative, with refinement and
validation sessions with key business representatives. In this process, the analyst will
also identify attributes, e.g. key and attributes of customer identification information.
Of course the information requirements can be also expressed by using standard ER
notation. In this case, you can track the process of specialization and decomposition,
but you loose the double dimension of information types and domains.
Table 2: The SIE standard catalogue
INFORMATION TYPE
Master Data
Transaction
Data
Analysis
Data
Law LAM LAT LAA
Competitor COM COT COA
Customer CUM CUT CUA
Supplier SUM SUT SUA
Broker BRM BRT BRA
Stakeholders
Shareholder SHM SHT SHA
Personnel PEM PET PEA
Plants PLM PLT PLA
Raw materials RAM RAT RAA
Resources
Cash CAM CAT CAA
Structure STM STT STA
Project PJM PJT PJA Context
Region REM RET REA
Process PRM PRT PRA
Product PDM PDT PDA
IINFORMATION
DOMAIN
Output
Service SEM SET SEA
Table 3: An example of specialization of “Customer”
INFORMATION TYPES
Master Data Transaction Data
Identifica
tion Social
Man-Machine
transaction
Machine-Machine
transaction
Analysis
Data
Private Customer
Enterprise
AGGREGATED ENTITIES AND IT STRATEGIC PLANNING
The main use of strategic information requirements is in IT strategic planning. An IT
strategic plan will summarize (a) the architecture of applications, data and
infrastructure and (b) assess the impact of technology and business discontinuities
(Motta 2007; Nolan 2005).
The architecture of data is obtained by customizing the general catalogue of SIEs.
Also, by crossing the catalogue and the actual database the analyst can assess the
current information support.
In a similar way, the analyst can do some form of sensitivity analysis of technology
and business discontinuities. Technology discontinuities, e.g. Service Oriented
Architecture, may impact on a wide span of elements of the enterprise architecture.
Business discontinuities are strategic business moves of the enterprise, e.g. the
convergence between telecom and media business, or change of the whole business,
e.g. the switch from analogical to digital TV.
ASSESSMENT OF INFORMATION SUPPORT
To assess to what extent SIEs are supported and / or used, SIEs are crossed with
business processes, organizational structures, IT applications and IT architecture. The
grids describe relations G information classes I to information users U (business
processes, organizational structures, IT applications and IT architectural elements):
G = {U,I,A} (1)
The SIE meta-model (Figure 2) may be used to assess both AS-IS and TO-BE
scenarios from a variety of perspectives:
• Information and Databases grid: assesses the databases coverage by qualitative
metrics
• Information and Application grid: assesses the use of information by
applications in terms of information lifecycle and/or qualitative metrics
• Information and Organizational structure grid: it identifies information
ownership;
• Information and processing levels: it identifies how information is distributed
on and used by the processing architecture (client, server, mobile devices)
Figure 2: relationships between Aggregated Business Entities and other SIE Relations of IT
Strategic Planning
SENSITIVITY ANALYSIS
Sensitivity analysis identifies information domains impacted by strategic
discontinuities, e.g.:
• Business Discontinuity: the impact of enterprise strategies e.g. mergers,
acquisitions, new products, new services is assessed (which SIEs will be
affected and how much?)
• Technology Discontinuity: the impact of technology changes on information is
considered (which SIEs will be affected by emerging technologies e.g. Service
Oriented Architecture and how much?)
• Normative Discontinuity: the impact of regulations e.g. privacy, security etc.
is identified and possibly described (which SIEs will be affected by privacy
restrictions etc?)
POSITION OF THE SIRE METHOD IN ZACHMAN’S FRAMEWORK
The method as described here has a rather good coverage in the Zachman’s
framework (Inmon, 1997), a popular reference to position what really a method does.
are a semi-structured model, that gives something more than a “List of things
important to the business”.
STRATEGIC ENTITIES AND DATABASES DESIGN
Strategic information Design has a very high level scope that is independent from (a)
Business Processes and (b) Information and Communication Technology.
The model offers a strategic view of an enterprise and defines macro contents of the
Enterprise Databases. We have defined an algorithm that starting from the SIE model
enables the analyst in design the Entity Relationship Diagram in-the-large of the
databases. This first schema could be furthermore refined to obtain all the data
specification we are interested in (i.e. in a Request for Proposal in a ERP project).
The SIE-to-ER mapping algorithm is composed by three steps, namely:
1. Mapping, that takes in input the SIE model and converts it into a preliminary ER
model. The mapping is applied for each domain in the model and could be
summarized by the following table. Through this step you delete the “horizontal
discontinuities”, in other words you link master information and transaction
within the same information domain. Please note that the use of ER Composite
pattern or use of Composite/Complex attribute depends on the recursion structure
of the decomposition (e.g. Bill of Material of a material good instead of the
decomposition of Master Data in personal data and in residence data).
2. Link of Informative Islands. The first step is domain-centered so the preliminary
ER schema is composed by several low-coupled “Informative Islands”. With this
step we identify common entities, attributes and relation between domains and
merge them in order to obtain a more cohesive ER schema. Through this step you
delete the “vertical discontinuities”, in other words you link master information
belonging different information domains and transaction information belonging
different domains and “diagonal discontinuities” by linking master information
and transaction information belonging different information domains
3. Model refinement, that inserts new relations between entities, specializes or
decomposes entities and attributes and aggregates or generalizes entities. The last
step enhances the ER schema by inserting deeper domain competences.
Table 4: Coverage of the SIRE method over Zachman’s Framework
Layer
What
(Data)
How
(Function)
Where
(Network)
Who
(People)
When
(Time)
Why
(Motivation)
Scope
(Contextual)
Planner
List of things
important to the
business
List of processes
the business
performs
List of locations in
which the business
operates
List of
organizations
important to the
business
List of events
significant to
the business
List of business
goals/strategies
Business Model
(Conceptual)
Owner
Semantic or
ER Model
Business Process
Model
Business Logistics
System Work Flow Model
Master
Schedule Business Plan
System Model
(Logical)
Designer
Logical Data
Model
Application
Architecture
Distributed System
Architecture
Human Interface
Architecture
Processing
Structure
Business Rule
Model
Technology
Model
(Physical)
Builder
Physical Data
Model System Design
Technology
Architecture
Presentation
Architecture
Control
Structure Rule Design
Component
Configuration
Implementer
Data Definition Program Network
Architecture Architecture
Timing
Definition
Rule
Specification
Functioning
Enterprise
Worker
Data Function Network Organization Schedule Strategy
Table 5: Summary of mapping algorithm between SIE and ER model
SIRE Model ER Model
Specialization Enhanced ER Specialization
(Overlap or Disjoint)
Decomposition ER Composite pattern or use of
Composite/Complex attribute
Property of Master Data Entity Type or Attributes
Property of Transaction Data Entity Type and Relationship
Type
Property of Analysis Data Calculated attributes
Figure 3: ER Composite Pattern
SIRE IN GOVERNMENT: A CASE STUDY
Comune di Milano outsourced the real estate management to several enterprises (Real
Estate Manager - REM). Each REM manages a part of the real estate with a different
Information System. A new local law (Legge Regionale 8 novembre 2007, N. 27) has
defined new criteria to compute the lease fee and new policies for the valorization and
rationalization of public real estate. Lease rents are computed both on the value of the
apartments as on the base of Index of Equivalent Economic Situation (IEES) an
indicator that summarize the Financial Situation of the tenents.
Comune di Milano wants to know the impact of new law on existing REM’s IS in
terms of functional requirements and related costs. Functional requirements define
what the IS must to do in order to comply with law policies.
The law has a deep impact on REM’s systems because:
• Defines a Transitory period (3 years ) for the lease computation due by the
eldest tenants. During this period the lease is subject to variations (raises or
abatements, modification in parameters, etc...) that bring it to reach the quote
defined by the law at the end of temporary state.
• involves the end-to-end processes as for units allocation as for the customer
appeals
• changes the computation of lease rent because it must reflect the house value
and the socio-economic state of the tenents
• changes the DB schema with the creation of new information (master,
dynamic and historical)
• Creates a new interface beetween Comune and Managers in order to enable
Comune di Milano to certify IEES declared by tenents
• Changes the reporting and the billing processes in term of templates and data
reported
• Needs a complex User-test in order to fit the whole range of instances (that
crosse three dimensions: User classes, Events and Transitions) defined by the
law
The evaluation of the impact on the software is based on an SIRE analysis. In this
case SIEs have been used to (a) define the DB structure and (b) to evaluate the costs
through the Function Points Analysis (FPA).
SIR DESIGN
The first step is to customize the standard grid as shown in Table 6.
Table 6 – Customized SIR grid for public apartments of Comune di Milano
Transactions Data
Master Data
Events Certifications
Law
o Allocation criteria
o Safety
o Social contribution
o Periodic Check
o Conformity / Non Conformity
state
Tenant
o Master Data o Other
Information
o Lease deal o Leases
o Payment Delays
o Breaches o Lease Renewals
o Adjustments
o Lease abatements o Lease raises
o Appeal
Customer
Household
o Master Data
o Declared IEES
o Other Information
o Certified ISEE
Stakeholder
Broker REM
o REM Master
Data
Unit
Resources Plants
Garage
o Master Data
o Ordinary Maintenance
o Extraordinary Maintenance
o Valorization and Rationalization Actions o Renovation Actions
o Architectural Barrier-Free Design and
Environmental improvements actions o Utilities
o Services
DATABASES DESIGN
Now we can use the customized grid to define the would-be-DB schema with the
mapping algorithm discussed above. For simplicity we will consider only Customer
and Plants Domains. By applying the mapping algorithm we obtain two informative
Islands shown in next figures respectively the Customer and the Unit Dbs.
Figure 4: Informative island related to Cutomer Domain
Figure 5: Informative island related to Unit Domain
The second step is to link obtained Information Islands master data belonging
different information domains i.e. each tenant rents a unit, a deal involves a unit and
so on. Through this step we could see the ER schema raising from informative islands
as shown in figure (please note that in the figure we have inserted only three cross-
island relationships to make the diagram understandable).
Figure 6: Link between Informative islands
The third step is to add / delete or transform relations identified in the second step i.e
the two relations Tenent-perform-deal and deal-involves-unit become the ternary
relation User-Deal-Unit, etc…
Figure 7: Ultimate ER Schema
IMPACT OF THE LAW ON PROCESSES AND ON THE INFORMATION
SYSTEM.
According with the interviews the overall schema of processes for the house
management is shown in next figure.
Figure 8: Structure of Business Processes affected by the law
Now we can use the ER schema designed above to compute the function points. The
REMs’ IS provides several functions related to the real estate management.
Particularly the IS supports three macro-processes heavily involved by the law:
1. Lease computation.
2. Billing
3. Reporting
Table 7 – CRUD Table that crosses SIE with Business Processes
Lease
Computation
Billing
Appeals
Management
Parameters
Management
Reporting
Unit R R R R,U R
Tenant R R R R,U R
Household R R R R,U R
Deal R R R R,U R
Lease Rent R,U R R R R
Modification C R R R,U R
Bill - R,U - - -
Certified IEES R - - R R
Appeal - - R,U R
Declared IEES - - - R,U R
To define the use cases and then the function points (so the costs) we use Assembly
Lines Diagrams and CRUD table that explode the Business Process / SIE table. In this
way we you are able to Information assess the use of information by applications in
terms of information lifecycle and to define the FP needed for each function. The next
picture shows the information needed by the Lease Comupation while the table shows
the CRUD details about each Use Case.
Figure 9: Assembly Lines and related Use cases for the process “Lease Computation”
Table 8: CRUD Table that crosses SIE with Use Cases
Lease Computation
Sustainable lease
computation
Economic Data Check
IEES Check Special clauses evaluation
Lease Abatement
Computation
Lease Variation
Computation
Unit R R R
Household R R R R R
Deal R R R R R R
Tenant R R R R R R
Lease U R R
Modification C C
Bill
Certified IEES R
Function Points
TOOL
In order to support the analysts in identifying as much as possible Strategic
Information requirements, we have designed a visio-based tool that enable the
creation of well-formed SIRE models. The tool follows the three steps methodology
we discussed above to get SIEs:
• Selection of in-the-large SIE from the Standard Grid
• Specialization/Decomposition od selected SIEs
• Refinement of each SIE by the definition of properties
The tool is based on the SIE metamodel discussed above and implements it trough the
following ER schema
Figure 10: Entity relationship schema used by the SIRE tool
Furthermore, to simplify the work of the analyst, the tool implements a set of APIs for
the exportation of the SIE models in different format (HTML code, Word, Powerpoint
presentation, etc...). In the next picture is shown a screen shot of the tool that shows
the editing features.
CONCLUSIONS
We have illustrated a strategic information model, based on a normative framework
with numerous advantages:
• It assists the analyst in identifying “right” information requirements
• It is cross-industry and can be specialized as needed
• It is strategic and it can stop at the detail levels defined by the planning
process, by zooming critical areas and summarizing non critical ones
• It easy to understand for management and supports a what-if analysis of
business strategic alternatives
• It can be linked to detailed information requirements analysis.
The framework has been used in government to design databases and to compute
costs, has been partially used in a strategic planning of a very large telecom
corporation and has been successfully tested in healthcare to identify the information
strategy. On going work includes the further development of the application to
customize the overall catalogue and of a Knowledge Base (KB) where the analyst can
find and modify predefined information models. The navigation on this KB supports
the design of best-fit models through the integration and the reuse of experiences (best
of breeds).
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