Description
Business Intelligence (BI) is playing a major role in most Enterprise Information Systems (EIS) architectures providing strategic and tactical management information on selected issues.
Organisational Dynamics and Ambiguity of Business
Intelligence in Context of Enterprise Information
Systems – a case study
Torben Tambo
1
, Ole Dahl Gabel
2
, Martin Olsen
1
and Lars Bækgård
1
,
1
AU Herning, Aarhus University, Birk Centerpark 15,
7400 Herning, Denmark
{torbento, martino, larsb}@hih.au.dk
2
Independent Business Intelligence Professional, Gyldenvang Alle 19,
2770 Kastrup, Denmark
{ole.dahl}@hotmail.com
Abstract. Business Intelligence (BI) is playing a major role in most Enterprise
Information Systems (EIS) architectures providing strategic and tactical
management information on selected issues. BI is typically detached from
mainstream transaction systems and provides a translated view of the business
with high ranking executives as key audience. BI has as such a number of
distinctive characteristics proposing that management of BI need more
attention. This paper is based on an in-depth, longitudinal qualitative case study
using an interpretivistic and sociologically inspired methodology. This study
present findings within the relationship between technology and business in BI
is particularly complex as operational issues are secondary to the desired
systems outcome?s character of a management construct. A management
framework is proposed for BI related to its special characteristics involving
enterprise communication between operational and tactical/strategic levels,
inexact data, representation of historical consensus, and intrinsic translation
between management culture and technology. BI should be viewed as
integrated in and mutually interacting with corporate EIS. This paper
contributes to a dualistic understanding of BI as both a technological and a
social system. The originality of this paper is in its augmentation of IS
management with a better comprehension of the BI aspect intended to
contribute to a distinct management framework for BI.
Keywords: Enterprise Information Systems, Business Intelligence, Information
Systems Architecture, Social Construct, Datawarehouse.
1 Introduction
Business Intelligence (BI) is the overall term for high-level reporting and analysis
[1][2][3] in an Enterprise Information Systems (EIS) context [4]. BI emerged during
the 1980ies [5] as a combined understanding of information system extracting and
aggregating data from production systems and presenting this in an enriched form
typically directed toward tactical and strategic management users[6]. BI is a critical
component in the overall EIS landscape of most large businesses [7] and worldwide
BI software spending in 2011 were 12,2 billion USD [8].
BI is continuously evolving [9][10] with new features introduced such as fraud
detection, advanced user front-ends, easier and faster data repositories, and master
data management (MDM) system [11]. Dynamic business environments with
mergers, divestures, and ongoing strategic business re-alignment [12] are putting
strong demands on BI with redesign, timeliness of reporting, and operational changes
[13]. BI is often the most important IS in strategic decision making [14][15][16][17].
With the linking of BI to top-level business management and the dynamics of both
technology and application of technology [16], BI projects tend to be positioned in a
techno-political cross-fire. This is an ideal situation for at least technology to gain
attention, but also a risk in making up requirements more of perceived top-level
management that a broader organizational usefulness.
In the following it is assumed that BI broadly represent an ongoing process for
meeting ever-changing top-level management requirements – dynamics - with BI
practitioners at risk for making large systems for ad hoc purposes, as the intended
users only have lasting interest in few KPIs (Key Performance Indicators) and
requested one-off analysis. The remainder of the organization might then be left with
less useful BI systems. Subsequently it is claimed that BI systems represent a more
ambiguous and socially determined set of translations and communications than a
specific linear aggregation of the transactional base. BI has to deal with a co-existence
of other reporting structures, e.g. accounting, operational reports from ERP systems,
supplier?s and customer?s reporting. E.g. accounting is by law not allowed to
transform data, but still tends to have important strategic validity. Tactical
management, analytical specialists, and in some cases even of operational interest
could generally be more in the focal point as key stakeholders of corporate BI. With
BI clinging senior management as information receivers, it is interesting to study,
how BI projects navigate within this organizational complexity.
IS and EIS research approaches emphasize the understanding of BI as a technology
in an organization setting; in this paper it assumed the important differences exist
between regular IS and BI. Subsequent the general claim is that these differences
relate to issues like (1) lack of active transactions, (2) extraction (distancing, dis-
location) and transformation of the original operational data, (3) the lack of interactive
use case (CRUD absence), (4) the lack of business cases, and (5) the lack of
integration in operational business processes and activities. BI is however integrated
in EIS when it comes to infrastructure, operations management, MDM quality,
[17][18][19] and probably most important: management attention.
Management of BI is a relatively overlooked discipline with either technology or
strategic requirements dominating, and not more holistic considerations as generally
associated with EIS and transactional oriented systems. The outcome of BI projects
tends to be cost-driven compromises of business and technology.
BI projects and governance thus tend to overlook the broader organizational
context in which to obtain usefulness and business value [20] in favour of perceived
or short-term management objectives. This leads to the following research question
for the subsequent study: Can a broader organizational contextualization of BI in
direction of corporate tactical and operational levels, better provide value especially
by considering the intrinsic properties of BI of ambiguity, translation and
communication? Besides this question this paper is to serve as a substantiated position
paper employing an extensive literature review and in in-depth case study.
2 Theoretical considerations
BI is a regularly found component in most EIS landscapes. BI?s prime role is to
provide information for strategic and tactical (human) decision making. Management
Information Systems (MIS) [21] are here seen separately from BI as MIS relates to
execution and control in an integrated operational context whereas BI relates trailing-
edge reporting. In IS and EIS literature, BI is rarely seen distinctively, however
O?Brien & Marakas [4] suggest BI as positioned exclusively in the two upper layers
of the corporate organizational and information hierarchy and suggest BI as the
overarching notion for a set of technologies comprising among others Management
Information Systems (MIS), Decision Support Systems (DSS), Data Mining and
Online Analytical Processing (OLAP). Clark et al. [16] suggest a super-class of
management support systems (MSS) whereof DSS, executive information systems
(EIS), knowledge management systems (KMS) [21], and business intelligence (BI)
are a part. However, BI is in the following understood as the portfolio of systems
extracting, aggregating and presenting data from any operational system of the
enterprise. The theoretical considerations below go to the technology of BI and the
organisational issues of BI.
2.1 The technology of BI
Data completeness and consistency is a major topic across information sources and
silos, [22] suggest implementing a cross-cutting Enterprise Information management
framework o.a. including meta-data and MDM consideration across silos.
Characteristically BI works on data extracted from the general transaction systems
of the corporate IS landscape. The Extract, Transform and Load (ETL) system [23]
[7] ensure relevance, consistency, integrity and purpose of the BI-data; but the ETL
process do at the same time change data, leaves out data decided not to be included,
and adapt to scope of further utilization of data. Classic compromises exist with e.g.
currency values, week/month comparisons, stable/new business, re-grouping of items,
unclear stock ownership, linking of data and business processes.
On user front-ends, data accessibility and presentation, Lee and Noah [25] suggest
embedding BI into general information portal of the enterprise.
BI is occasionally suggested as a technological solution to overcoming reporting of
internal IS / IT processes [26], also „BI on BI? is discussed by Lin et al. [27] in
making of analytic network process (ANP) based assessment model to assess the
effectiveness of BI systems.
Information management is dealing with collecting, understanding, filtering,
transforming and conveying data from sources to BI repositories [28][29][22]. Data
sources might not only be company-internal, but also external data sources of
business partners and 3
rd
party information providers can play an important role [30].
BI is typically context dependent in the sense that it must give meaning to the
design and purpose [31] of the specific business and business unit, e.g. sales,
purchase, B2B, B2C. BI might also reflect other specialized demands and
requirements, e.g. BI in support of business processes [32].
Ramakrishnan et al. [33] emphasize data collection strategies in datawarehouse
construction highlighting insight, consistency and organizational transformation as
main purposes of BI. Data collection is viewed either to be problem driven or
comprehensive; consistency is linking to institutional isomorphism. This also support
the idea of BI as preservant of the organization.
2.2 Organisational issues of BI
There is a broad understanding that BI is about complex technology in an
organisational and business environment [4][14][15]. There seem to be less
understanding on the drivers, motivators and impact of BI. Elbashir et al. [34] present
a host of BI-induced successes in enterprises but also make reservations on validity of
BI-success measurement. Learning is the key organisational issue in [13]. Viaene et
al. [35] exemplifies BI for organisational transformation at operational level in police
work. Finnie and Barker [36] propose a framework for developing supply chain
organisations using real time BI. IBM [37] propose a framework inspired by Gartner
looking at People, Processes and Applications&Tools; it is also suggested to give
equal considerations to these three areas.
The literature on regular BI implementation is relatively rich [38][39][40] however
several of these tend to draw a straight line from BI project governance to usefulness
and BI as competitive factor [41]. BI is different between enterprises, high initial
costs are widely recognized [13][42], and special low cost measures are suggested for
SME [40][43]. As whole, BI for SME is drawing attention of its own [44].
Alter?s work system method (WSM) [45] relates to general IS understanding using
a assessment frame of simplicity, clarity, scope, systematic power, explanatory power,
validity, reliability, and fruitfulness. It is expected that general IS research
methodology can contribute both in capturing the identical features of BI and IS and
the differences.
The management orientation of BI is in risk of overlooking the importance of other
factors, and misinterpret BI as a “universal truth” instead of a best-possible translation
of measurable factors from the business operations. Senior level management only
managing from BI is rarely seen and management processes normally also include
substantial qualitative reasoning.
BI is expected to move from a strategic, de-coupled perspective into more
operational usefulness requiring faster conveying of data from operational platforms
to reporting platforms [46][43][36][47]. Operational systems based on BI feedback
has drawn research interest of its own [14][35].
Fernandes [48] propose to see BI using an Enterprise Architecture lens projected
into a so-called Entrepeneurial Information Architectue comprising mission, prospects
and business success factors, thereby calling for a more holistic understanding.
Clark et al. [16] highlight the gap between technologies available in the
marketplace and organisational capability to acquire and leverage this technology as a
construct of technology gap. BI failures are thus tied to organizational issues such as
(lack of) organizational readiness [49], inappropriately managing the technology or
use of an inappropriate technology.
2.3 Theoretical frame of research
Key theoretical issues of BI in the subsequent analysis are centred on ambiguity,
translation and communication to understand management challenges of projects and
systems. Ambiguity relates to the filtered and aggregated character of data extracted
from the original operational context. Translation relates to adaption of original
operational data into staging of data for the use in various front-end systems.
Communication relates to data in form of analytical systems and reports directed
towards corporate management with the management?s requirements for insight,
oversight, abstraction and distance from operational contexts.
3 Method
This study is qualitative, cross-disciplinary and inspired by interpretivism [50][51].
Critical is the positioning of BI within an IS research methodology [52]. The basic
platform of BI is viewed as both a technological system and a social system.
Information conveyed by the IS platform includes disciplines such as sales, customer
relationship management, branding and an array of socio-technical issues which each
has research traditions of its own [53]. This relates to Taylor [54] identifying IS
research as issues of balancing focus and diversity by applying a polycentric view.
This paper stretch from business strategy into IS strategy [55]. A critical issue
within BI is that various receivers relate to different foci: all challenging a clear cut
methodological stance. Bryant [55] states that communication is always prevalent in
IS research and that communication convey social constructs, i.e. aiming at
maintaining the view on the techno-social construct around BI; the context of the
system, more than the system itself, is critical Avgerou [56]. Smithson & Hirscheim
[57] have in their contribution(s) underlined IS as a research discipline of
comprehension through evaluation of technological and business factors.
Baskerville & Myers [58] have described the “danger” of IS research working in
waves of fashion with rising and declining interest for certain topics. In this study we
“suffer” from the majority of BI contributions are technological and BI in a social
context is more an empirical notion than a scientific construct. We therefore join
Baskerville & Myers by conducting this study in close collaboration with IS
practitioners and as Benbasat & Zmud [59], we emphasize relevance in practice. The
idea of engaged scholarship from Van de Ven [61] and Mathiassen & Nielsen [60]
focuses the research agenda on finding reason and provide practitioners, as well as
research communities, with insight from the matured use of BI. The IS method and its
cross-disciplinary nature include elements of technology and business research [52].
4 Case
The following case is a study of Company B?s BI systems with a starting point in
1997 and a preliminary end-point somewhere in 2012. Company B is a privately
owned Northern European fashion company selling clothes out of around 2500
concept stores and 8.000 independent stores.
4.1 15 years of BI in Company B
In 1997 Company B was in an early but rapid growth phase. With just over 100
stores, there was no clear information exchange strategy between the central office
and the stores. The company had initiated collaboration with several vendors of Point-
of-Sale (POS) systems and central office systems, but all of the projects were
terminated prematurely. Finally NCR took up the challenge and succeeded in
supplying a POS, a simplistic data exchange based of copying of flat files, and a
central datawarehouse based on Teradata?s server and analytical front-end products.
The Teradata system remained until around 2004 were Company B raised increased
criticism of issues of infrastructural management. It was decided to switch the full
retail platform to Microsofts portfolio of servers and POS-systems. During 2005
dataload from the simplistic file share was established loading data in Microsoft SQL
Server using SQL Server Integration Services (SSIS). A front-end was established
using SQL Server Reporting Services (SSRS) with Targit®. The POS conversion to
Microsoft suffered from lack of cost-efficiency and were winded down during 2007.
Teradata and SSRS/Targit remained concurrently for some years until a sufficient
amount of features had been ported away from Teradata.
Early 2006, after less than a year of operation, there came increased criticism of the
SSRS. A newly established business development function suggested a redesign
based on a different technology. Mid-2006 they made a Request for Information (RFI)
and invited vendors to present their suggestions for solution; invited vendors were
Oracle/Discoverer, Oracle/SiebelAnalytics, Oracle/Hyperion, Business Objects, SAS.
Business Objects were chosen together with a large Indian consultant company
(“Ivor”) for implementation. Soon after, Business Objects was acquired by SAP.
Under project management by the business development team, Ivor continued to fail
deadlines for acceptance of the delivery. Ivor suggested issues within Company B to
be determining, and reduced the project team mostly to provide support. Problems
were mostly centered around getting the same figures out of the Targit system as the
Business Object system even if dataload and masterdata were left unchanged from the
SSIS system. Users remained with Targit. Late 2010 a new Business Objects team
(“TLA”) was brought in and Ivor was dismissed; meanwhile the technology was
rebranded to SAP Business Warehouse (BW). The TLA team came out of SAP BI
experience. The project was restarted together with a general strategic realignment
towards general use of solutions from SAP. The TLA team defined an acceptable
subset of masterdata to be supported. Furthermore are team defined a minimum subset
of reports to be offered to users even though the users still had Teradata?s richness of
functionality in mind. The SAP BW project was relatively quickly completed, but
most retail operations groups stopped to use the system and relied afterwards on local,
manually updated Excel reporting.
4.2 Critical issues of learning
In several of the critical phases over the years the process has been far more
technology-centred than centred on business requirements. The later projects have had
difficulties in remaking well-accepted reports and functionalities of the first system.
Given the organisations distributed character with more than 2000 data collection
points (shops), a certain degree of „contamination? of data will happen, this is
removed in the ETL processes, but happen to change data too far away from the
transactional basis and therefore nurturing organizational scepticism. Up until 2003
there was one POS system with one software version. After this the number of
different POS has now grown to around 8 distinctive systems/versions. Each system
has slight differences that add up in the ETL process.
Ambiguity of data has been prevalent during the projects from 2003 – 2011.
Ambiguity resulted in consultants repeatedly failed to validate new reports against
older reports and led to scepticism. Ambiguity could e.g. be “a troubled store got a
marketing support payment made as a credit note against an invoice making the value
of goods a large negative number”, “ongoing change of product categories made
certain categories incomparable”, “damaged price tags in stores were replaced with
stores own tags and prices unrelated to master data”.
The direct system management responsibility was shifting around over the years
between teams with very distinctive focus and little attention to cross-organisational
issues. When the systems were more stable, operations and infrastructure teams were
in charge with little business insight. When changes were to happen, the business
development team took charge with little technology insight. Collaboration and
distinction of responsibilities largely failed. External consultants were often in critical
positions as manpower, change agents or technologists. The external consultants were
often stuck between the organisation?s lack of clarity of roles: to rely on business
developers as technology resources or vice versa to rely on operations associates
when asking business questions. The consultants were actively used in blame games
and continuously being sacked and re-hired.
BI is by the business organization regarded as an independent reporting regime.
Beside this the most operational parts of the organization also has organizational units
for supply chain management and financial reporting. Both of these units has during
the most of the period relied on parallel reporting systems, typically transactions
(sales orders, purchase orders, etc.), invoices and bookkeeping. This has created a
referential situation continuously challenging the BI systems and offering the
organization a personalized and agreed reporting scheme. The different organizational
units have obviously personalized each in its direction making these local reporting
systems incomparable. The centralized, generally accepted BI has during the years
been a shared vision.
5 Discussion
BI projects and systems are no more complex than other IS and EIS, but also no less
prone to failure. BI has the thankless role on putting together data from potentially
massive numbers of operational databases, and displaying this in a useful and
meaningful way. It is here claimed that BI systems must be viewed differently than
general transactional EIS to ensure project and system success. The differences are
bound to
- the absence of operational criticality and integration,
- the transformed and henceforth ambiguous character of data – with the risk
of losing business transparency, and
- the strategic (mis-) interpretation where BI is communication-wise directed
towards the corporate top-level, but has more clear usefulness in tactical,
analytical and operational areas
Particularly the strategic direction leads to several deeper issues on the
managements need for “ad hoc, unscheduled, summarized, infrequent, forward
looking, external, wide scope” information [4], which is difficult to obtain in any IS.
This need is prioritised and interpreted above the lower part of the organisations much
more mundane information requirements. Much is this can be condensed into that
alignment of BI with business [35][33][40][46] is more difficult than general IS and
EIS because of the missing rooting of BI in operational practice and subsequently the
definition of the BI outcome as a social construct rather than a business or technology
construct.
BI needs to deal with complex requirements in presenting the actual state of the
enterprise with filtered and aggregated data. Nowhere else in the enterprise would it
be acceptable to communicate with a reduced set of data. The definition of the
acceptable would in any enterprise be rooted in management directives, quasi-
consensus among the involved, and the technological potentials or limitations. As
mentioned before, BI lack some characteristics of IS, but inexact data and definition
by culture could be added. The risk is that BI defining a perceived version of the
corporate truth as technology idealize top management wants it, and thereby risk
misleading critical enterprise insight.
Case learning: BI needs a balanced and dualistic approach to technology and
business; several of the incidents in the case failed due to unbalance. The
ambidextrous character of IS [20] and IS organisations seem important particularly
stretching both beyond the narrow technologist and analyst view provided in the case:
Analysts must be able to get insight and represent even highly simplistic and low-
skilled on-the-floor business processes, e.g. purchasing and sales assistants work
processes. Likewise must technologists not only address infrastructure and narrow
information flow, but also be able to take broader view into the fuller EIS landscape
potentially including external business partners and dis-joint IS platform.
The case study methodology is here giving a possibility of moving very close to a
single case. The case has a longitudinal perspective were repeated patterns are found;
this perspective is furthermore interesting in the found growth scenario were the lack
of well-functioning BI didn?t stop growth and also reflected strategic managements
use of a multitude of sources in decision making. The case provided a critical view on
BI. The case obviously also needs a critical distance on organisational and
management immaturity, projects being pushed despite lack of readiness, and absence
of a capable internal project organisation on both business and technology side.
A management of BI framework should be building upon a dualistic business –
technology management thinking and obviously moving forward to more complex
multi-process and multi-stage approach as suggested in [37]. Time must be a part of
the framework as technology and business are expected to follow some roadmaps that
must be included in planning to maintain relevance. Alignment with business strategy
but also operational practice seems critical. This is furthermore leading to suggestions
of organisational and technological embeddedness where BI must be able to provide
an account of data, data flow, data remediation, and rooting in business processes and
use cases. Readiness and maturity are by some authors suggested but could probably
also depend business and technology.
Summary: Management of BI must aim at avoiding „islanding? of BI and seek to
make BI data more reflecting on the business foundations of the enterprise, and along
with this create an environment for less strategy and more tactics and operations of
corporate BI.
6 Conclusions
The arm?s length between production systems and BI can be beneficial in having
more refined, cleansed, consistent data for strategic business control and decision
making. This establishes an information repository of general corporate benefit
particularly if it is incorporated into EIS environment with a broad operational
orientation.
Suggestions for further research include a more holistic understanding of success
criteria of BI where technology, business characteristics, and BI process assessment is
taking part. Also the suggested management framework of dualistic thinking, time,
alignment and embeddedness would be interesting to research further. As the case
describes, even failed BI projects can have secondary effects of significant business
value. So future research is in the line of finding the more determining factors in
creating BI success or turning little used BI systems into assets of the general EIS.
The general rhetoric in BI satisfying the very need of the senior management seem
disputable in the light of (1) BI is intentional translations done before senior
management get insight, (2) BI do probably have its core users among tactical
management and analysts, (3) BI is by many authors expected to move closer to
operational requirements and need adaptions to this, (4) BI is one besides more
quantitative reporting systems that together with qualitative reporting strongly
compete on senior management?s attention.
In terms of IS research a more inclusive view on BI would strengthen the holistic
understanding of EIS and could support BI with better organisational support,
relevance and value-orientation.
From the discussions in this study it seem questionable that BI can succeed in its
predominant strategic role, much more important is it to conclude BI as a tactically
oriented information system with strong operational potentials – in line with [34]. A
more distinctive approach to BI within the EIS frame as suggested in this paper could
help both BI research and BI systems and projects in succeeding.
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doc_222488854.pdf
Business Intelligence (BI) is playing a major role in most Enterprise Information Systems (EIS) architectures providing strategic and tactical management information on selected issues.
Organisational Dynamics and Ambiguity of Business
Intelligence in Context of Enterprise Information
Systems – a case study
Torben Tambo
1
, Ole Dahl Gabel
2
, Martin Olsen
1
and Lars Bækgård
1
,
1
AU Herning, Aarhus University, Birk Centerpark 15,
7400 Herning, Denmark
{torbento, martino, larsb}@hih.au.dk
2
Independent Business Intelligence Professional, Gyldenvang Alle 19,
2770 Kastrup, Denmark
{ole.dahl}@hotmail.com
Abstract. Business Intelligence (BI) is playing a major role in most Enterprise
Information Systems (EIS) architectures providing strategic and tactical
management information on selected issues. BI is typically detached from
mainstream transaction systems and provides a translated view of the business
with high ranking executives as key audience. BI has as such a number of
distinctive characteristics proposing that management of BI need more
attention. This paper is based on an in-depth, longitudinal qualitative case study
using an interpretivistic and sociologically inspired methodology. This study
present findings within the relationship between technology and business in BI
is particularly complex as operational issues are secondary to the desired
systems outcome?s character of a management construct. A management
framework is proposed for BI related to its special characteristics involving
enterprise communication between operational and tactical/strategic levels,
inexact data, representation of historical consensus, and intrinsic translation
between management culture and technology. BI should be viewed as
integrated in and mutually interacting with corporate EIS. This paper
contributes to a dualistic understanding of BI as both a technological and a
social system. The originality of this paper is in its augmentation of IS
management with a better comprehension of the BI aspect intended to
contribute to a distinct management framework for BI.
Keywords: Enterprise Information Systems, Business Intelligence, Information
Systems Architecture, Social Construct, Datawarehouse.
1 Introduction
Business Intelligence (BI) is the overall term for high-level reporting and analysis
[1][2][3] in an Enterprise Information Systems (EIS) context [4]. BI emerged during
the 1980ies [5] as a combined understanding of information system extracting and
aggregating data from production systems and presenting this in an enriched form
typically directed toward tactical and strategic management users[6]. BI is a critical
component in the overall EIS landscape of most large businesses [7] and worldwide
BI software spending in 2011 were 12,2 billion USD [8].
BI is continuously evolving [9][10] with new features introduced such as fraud
detection, advanced user front-ends, easier and faster data repositories, and master
data management (MDM) system [11]. Dynamic business environments with
mergers, divestures, and ongoing strategic business re-alignment [12] are putting
strong demands on BI with redesign, timeliness of reporting, and operational changes
[13]. BI is often the most important IS in strategic decision making [14][15][16][17].
With the linking of BI to top-level business management and the dynamics of both
technology and application of technology [16], BI projects tend to be positioned in a
techno-political cross-fire. This is an ideal situation for at least technology to gain
attention, but also a risk in making up requirements more of perceived top-level
management that a broader organizational usefulness.
In the following it is assumed that BI broadly represent an ongoing process for
meeting ever-changing top-level management requirements – dynamics - with BI
practitioners at risk for making large systems for ad hoc purposes, as the intended
users only have lasting interest in few KPIs (Key Performance Indicators) and
requested one-off analysis. The remainder of the organization might then be left with
less useful BI systems. Subsequently it is claimed that BI systems represent a more
ambiguous and socially determined set of translations and communications than a
specific linear aggregation of the transactional base. BI has to deal with a co-existence
of other reporting structures, e.g. accounting, operational reports from ERP systems,
supplier?s and customer?s reporting. E.g. accounting is by law not allowed to
transform data, but still tends to have important strategic validity. Tactical
management, analytical specialists, and in some cases even of operational interest
could generally be more in the focal point as key stakeholders of corporate BI. With
BI clinging senior management as information receivers, it is interesting to study,
how BI projects navigate within this organizational complexity.
IS and EIS research approaches emphasize the understanding of BI as a technology
in an organization setting; in this paper it assumed the important differences exist
between regular IS and BI. Subsequent the general claim is that these differences
relate to issues like (1) lack of active transactions, (2) extraction (distancing, dis-
location) and transformation of the original operational data, (3) the lack of interactive
use case (CRUD absence), (4) the lack of business cases, and (5) the lack of
integration in operational business processes and activities. BI is however integrated
in EIS when it comes to infrastructure, operations management, MDM quality,
[17][18][19] and probably most important: management attention.
Management of BI is a relatively overlooked discipline with either technology or
strategic requirements dominating, and not more holistic considerations as generally
associated with EIS and transactional oriented systems. The outcome of BI projects
tends to be cost-driven compromises of business and technology.
BI projects and governance thus tend to overlook the broader organizational
context in which to obtain usefulness and business value [20] in favour of perceived
or short-term management objectives. This leads to the following research question
for the subsequent study: Can a broader organizational contextualization of BI in
direction of corporate tactical and operational levels, better provide value especially
by considering the intrinsic properties of BI of ambiguity, translation and
communication? Besides this question this paper is to serve as a substantiated position
paper employing an extensive literature review and in in-depth case study.
2 Theoretical considerations
BI is a regularly found component in most EIS landscapes. BI?s prime role is to
provide information for strategic and tactical (human) decision making. Management
Information Systems (MIS) [21] are here seen separately from BI as MIS relates to
execution and control in an integrated operational context whereas BI relates trailing-
edge reporting. In IS and EIS literature, BI is rarely seen distinctively, however
O?Brien & Marakas [4] suggest BI as positioned exclusively in the two upper layers
of the corporate organizational and information hierarchy and suggest BI as the
overarching notion for a set of technologies comprising among others Management
Information Systems (MIS), Decision Support Systems (DSS), Data Mining and
Online Analytical Processing (OLAP). Clark et al. [16] suggest a super-class of
management support systems (MSS) whereof DSS, executive information systems
(EIS), knowledge management systems (KMS) [21], and business intelligence (BI)
are a part. However, BI is in the following understood as the portfolio of systems
extracting, aggregating and presenting data from any operational system of the
enterprise. The theoretical considerations below go to the technology of BI and the
organisational issues of BI.
2.1 The technology of BI
Data completeness and consistency is a major topic across information sources and
silos, [22] suggest implementing a cross-cutting Enterprise Information management
framework o.a. including meta-data and MDM consideration across silos.
Characteristically BI works on data extracted from the general transaction systems
of the corporate IS landscape. The Extract, Transform and Load (ETL) system [23]
[7] ensure relevance, consistency, integrity and purpose of the BI-data; but the ETL
process do at the same time change data, leaves out data decided not to be included,
and adapt to scope of further utilization of data. Classic compromises exist with e.g.
currency values, week/month comparisons, stable/new business, re-grouping of items,
unclear stock ownership, linking of data and business processes.
On user front-ends, data accessibility and presentation, Lee and Noah [25] suggest
embedding BI into general information portal of the enterprise.
BI is occasionally suggested as a technological solution to overcoming reporting of
internal IS / IT processes [26], also „BI on BI? is discussed by Lin et al. [27] in
making of analytic network process (ANP) based assessment model to assess the
effectiveness of BI systems.
Information management is dealing with collecting, understanding, filtering,
transforming and conveying data from sources to BI repositories [28][29][22]. Data
sources might not only be company-internal, but also external data sources of
business partners and 3
rd
party information providers can play an important role [30].
BI is typically context dependent in the sense that it must give meaning to the
design and purpose [31] of the specific business and business unit, e.g. sales,
purchase, B2B, B2C. BI might also reflect other specialized demands and
requirements, e.g. BI in support of business processes [32].
Ramakrishnan et al. [33] emphasize data collection strategies in datawarehouse
construction highlighting insight, consistency and organizational transformation as
main purposes of BI. Data collection is viewed either to be problem driven or
comprehensive; consistency is linking to institutional isomorphism. This also support
the idea of BI as preservant of the organization.
2.2 Organisational issues of BI
There is a broad understanding that BI is about complex technology in an
organisational and business environment [4][14][15]. There seem to be less
understanding on the drivers, motivators and impact of BI. Elbashir et al. [34] present
a host of BI-induced successes in enterprises but also make reservations on validity of
BI-success measurement. Learning is the key organisational issue in [13]. Viaene et
al. [35] exemplifies BI for organisational transformation at operational level in police
work. Finnie and Barker [36] propose a framework for developing supply chain
organisations using real time BI. IBM [37] propose a framework inspired by Gartner
looking at People, Processes and Applications&Tools; it is also suggested to give
equal considerations to these three areas.
The literature on regular BI implementation is relatively rich [38][39][40] however
several of these tend to draw a straight line from BI project governance to usefulness
and BI as competitive factor [41]. BI is different between enterprises, high initial
costs are widely recognized [13][42], and special low cost measures are suggested for
SME [40][43]. As whole, BI for SME is drawing attention of its own [44].
Alter?s work system method (WSM) [45] relates to general IS understanding using
a assessment frame of simplicity, clarity, scope, systematic power, explanatory power,
validity, reliability, and fruitfulness. It is expected that general IS research
methodology can contribute both in capturing the identical features of BI and IS and
the differences.
The management orientation of BI is in risk of overlooking the importance of other
factors, and misinterpret BI as a “universal truth” instead of a best-possible translation
of measurable factors from the business operations. Senior level management only
managing from BI is rarely seen and management processes normally also include
substantial qualitative reasoning.
BI is expected to move from a strategic, de-coupled perspective into more
operational usefulness requiring faster conveying of data from operational platforms
to reporting platforms [46][43][36][47]. Operational systems based on BI feedback
has drawn research interest of its own [14][35].
Fernandes [48] propose to see BI using an Enterprise Architecture lens projected
into a so-called Entrepeneurial Information Architectue comprising mission, prospects
and business success factors, thereby calling for a more holistic understanding.
Clark et al. [16] highlight the gap between technologies available in the
marketplace and organisational capability to acquire and leverage this technology as a
construct of technology gap. BI failures are thus tied to organizational issues such as
(lack of) organizational readiness [49], inappropriately managing the technology or
use of an inappropriate technology.
2.3 Theoretical frame of research
Key theoretical issues of BI in the subsequent analysis are centred on ambiguity,
translation and communication to understand management challenges of projects and
systems. Ambiguity relates to the filtered and aggregated character of data extracted
from the original operational context. Translation relates to adaption of original
operational data into staging of data for the use in various front-end systems.
Communication relates to data in form of analytical systems and reports directed
towards corporate management with the management?s requirements for insight,
oversight, abstraction and distance from operational contexts.
3 Method
This study is qualitative, cross-disciplinary and inspired by interpretivism [50][51].
Critical is the positioning of BI within an IS research methodology [52]. The basic
platform of BI is viewed as both a technological system and a social system.
Information conveyed by the IS platform includes disciplines such as sales, customer
relationship management, branding and an array of socio-technical issues which each
has research traditions of its own [53]. This relates to Taylor [54] identifying IS
research as issues of balancing focus and diversity by applying a polycentric view.
This paper stretch from business strategy into IS strategy [55]. A critical issue
within BI is that various receivers relate to different foci: all challenging a clear cut
methodological stance. Bryant [55] states that communication is always prevalent in
IS research and that communication convey social constructs, i.e. aiming at
maintaining the view on the techno-social construct around BI; the context of the
system, more than the system itself, is critical Avgerou [56]. Smithson & Hirscheim
[57] have in their contribution(s) underlined IS as a research discipline of
comprehension through evaluation of technological and business factors.
Baskerville & Myers [58] have described the “danger” of IS research working in
waves of fashion with rising and declining interest for certain topics. In this study we
“suffer” from the majority of BI contributions are technological and BI in a social
context is more an empirical notion than a scientific construct. We therefore join
Baskerville & Myers by conducting this study in close collaboration with IS
practitioners and as Benbasat & Zmud [59], we emphasize relevance in practice. The
idea of engaged scholarship from Van de Ven [61] and Mathiassen & Nielsen [60]
focuses the research agenda on finding reason and provide practitioners, as well as
research communities, with insight from the matured use of BI. The IS method and its
cross-disciplinary nature include elements of technology and business research [52].
4 Case
The following case is a study of Company B?s BI systems with a starting point in
1997 and a preliminary end-point somewhere in 2012. Company B is a privately
owned Northern European fashion company selling clothes out of around 2500
concept stores and 8.000 independent stores.
4.1 15 years of BI in Company B
In 1997 Company B was in an early but rapid growth phase. With just over 100
stores, there was no clear information exchange strategy between the central office
and the stores. The company had initiated collaboration with several vendors of Point-
of-Sale (POS) systems and central office systems, but all of the projects were
terminated prematurely. Finally NCR took up the challenge and succeeded in
supplying a POS, a simplistic data exchange based of copying of flat files, and a
central datawarehouse based on Teradata?s server and analytical front-end products.
The Teradata system remained until around 2004 were Company B raised increased
criticism of issues of infrastructural management. It was decided to switch the full
retail platform to Microsofts portfolio of servers and POS-systems. During 2005
dataload from the simplistic file share was established loading data in Microsoft SQL
Server using SQL Server Integration Services (SSIS). A front-end was established
using SQL Server Reporting Services (SSRS) with Targit®. The POS conversion to
Microsoft suffered from lack of cost-efficiency and were winded down during 2007.
Teradata and SSRS/Targit remained concurrently for some years until a sufficient
amount of features had been ported away from Teradata.
Early 2006, after less than a year of operation, there came increased criticism of the
SSRS. A newly established business development function suggested a redesign
based on a different technology. Mid-2006 they made a Request for Information (RFI)
and invited vendors to present their suggestions for solution; invited vendors were
Oracle/Discoverer, Oracle/SiebelAnalytics, Oracle/Hyperion, Business Objects, SAS.
Business Objects were chosen together with a large Indian consultant company
(“Ivor”) for implementation. Soon after, Business Objects was acquired by SAP.
Under project management by the business development team, Ivor continued to fail
deadlines for acceptance of the delivery. Ivor suggested issues within Company B to
be determining, and reduced the project team mostly to provide support. Problems
were mostly centered around getting the same figures out of the Targit system as the
Business Object system even if dataload and masterdata were left unchanged from the
SSIS system. Users remained with Targit. Late 2010 a new Business Objects team
(“TLA”) was brought in and Ivor was dismissed; meanwhile the technology was
rebranded to SAP Business Warehouse (BW). The TLA team came out of SAP BI
experience. The project was restarted together with a general strategic realignment
towards general use of solutions from SAP. The TLA team defined an acceptable
subset of masterdata to be supported. Furthermore are team defined a minimum subset
of reports to be offered to users even though the users still had Teradata?s richness of
functionality in mind. The SAP BW project was relatively quickly completed, but
most retail operations groups stopped to use the system and relied afterwards on local,
manually updated Excel reporting.
4.2 Critical issues of learning
In several of the critical phases over the years the process has been far more
technology-centred than centred on business requirements. The later projects have had
difficulties in remaking well-accepted reports and functionalities of the first system.
Given the organisations distributed character with more than 2000 data collection
points (shops), a certain degree of „contamination? of data will happen, this is
removed in the ETL processes, but happen to change data too far away from the
transactional basis and therefore nurturing organizational scepticism. Up until 2003
there was one POS system with one software version. After this the number of
different POS has now grown to around 8 distinctive systems/versions. Each system
has slight differences that add up in the ETL process.
Ambiguity of data has been prevalent during the projects from 2003 – 2011.
Ambiguity resulted in consultants repeatedly failed to validate new reports against
older reports and led to scepticism. Ambiguity could e.g. be “a troubled store got a
marketing support payment made as a credit note against an invoice making the value
of goods a large negative number”, “ongoing change of product categories made
certain categories incomparable”, “damaged price tags in stores were replaced with
stores own tags and prices unrelated to master data”.
The direct system management responsibility was shifting around over the years
between teams with very distinctive focus and little attention to cross-organisational
issues. When the systems were more stable, operations and infrastructure teams were
in charge with little business insight. When changes were to happen, the business
development team took charge with little technology insight. Collaboration and
distinction of responsibilities largely failed. External consultants were often in critical
positions as manpower, change agents or technologists. The external consultants were
often stuck between the organisation?s lack of clarity of roles: to rely on business
developers as technology resources or vice versa to rely on operations associates
when asking business questions. The consultants were actively used in blame games
and continuously being sacked and re-hired.
BI is by the business organization regarded as an independent reporting regime.
Beside this the most operational parts of the organization also has organizational units
for supply chain management and financial reporting. Both of these units has during
the most of the period relied on parallel reporting systems, typically transactions
(sales orders, purchase orders, etc.), invoices and bookkeeping. This has created a
referential situation continuously challenging the BI systems and offering the
organization a personalized and agreed reporting scheme. The different organizational
units have obviously personalized each in its direction making these local reporting
systems incomparable. The centralized, generally accepted BI has during the years
been a shared vision.
5 Discussion
BI projects and systems are no more complex than other IS and EIS, but also no less
prone to failure. BI has the thankless role on putting together data from potentially
massive numbers of operational databases, and displaying this in a useful and
meaningful way. It is here claimed that BI systems must be viewed differently than
general transactional EIS to ensure project and system success. The differences are
bound to
- the absence of operational criticality and integration,
- the transformed and henceforth ambiguous character of data – with the risk
of losing business transparency, and
- the strategic (mis-) interpretation where BI is communication-wise directed
towards the corporate top-level, but has more clear usefulness in tactical,
analytical and operational areas
Particularly the strategic direction leads to several deeper issues on the
managements need for “ad hoc, unscheduled, summarized, infrequent, forward
looking, external, wide scope” information [4], which is difficult to obtain in any IS.
This need is prioritised and interpreted above the lower part of the organisations much
more mundane information requirements. Much is this can be condensed into that
alignment of BI with business [35][33][40][46] is more difficult than general IS and
EIS because of the missing rooting of BI in operational practice and subsequently the
definition of the BI outcome as a social construct rather than a business or technology
construct.
BI needs to deal with complex requirements in presenting the actual state of the
enterprise with filtered and aggregated data. Nowhere else in the enterprise would it
be acceptable to communicate with a reduced set of data. The definition of the
acceptable would in any enterprise be rooted in management directives, quasi-
consensus among the involved, and the technological potentials or limitations. As
mentioned before, BI lack some characteristics of IS, but inexact data and definition
by culture could be added. The risk is that BI defining a perceived version of the
corporate truth as technology idealize top management wants it, and thereby risk
misleading critical enterprise insight.
Case learning: BI needs a balanced and dualistic approach to technology and
business; several of the incidents in the case failed due to unbalance. The
ambidextrous character of IS [20] and IS organisations seem important particularly
stretching both beyond the narrow technologist and analyst view provided in the case:
Analysts must be able to get insight and represent even highly simplistic and low-
skilled on-the-floor business processes, e.g. purchasing and sales assistants work
processes. Likewise must technologists not only address infrastructure and narrow
information flow, but also be able to take broader view into the fuller EIS landscape
potentially including external business partners and dis-joint IS platform.
The case study methodology is here giving a possibility of moving very close to a
single case. The case has a longitudinal perspective were repeated patterns are found;
this perspective is furthermore interesting in the found growth scenario were the lack
of well-functioning BI didn?t stop growth and also reflected strategic managements
use of a multitude of sources in decision making. The case provided a critical view on
BI. The case obviously also needs a critical distance on organisational and
management immaturity, projects being pushed despite lack of readiness, and absence
of a capable internal project organisation on both business and technology side.
A management of BI framework should be building upon a dualistic business –
technology management thinking and obviously moving forward to more complex
multi-process and multi-stage approach as suggested in [37]. Time must be a part of
the framework as technology and business are expected to follow some roadmaps that
must be included in planning to maintain relevance. Alignment with business strategy
but also operational practice seems critical. This is furthermore leading to suggestions
of organisational and technological embeddedness where BI must be able to provide
an account of data, data flow, data remediation, and rooting in business processes and
use cases. Readiness and maturity are by some authors suggested but could probably
also depend business and technology.
Summary: Management of BI must aim at avoiding „islanding? of BI and seek to
make BI data more reflecting on the business foundations of the enterprise, and along
with this create an environment for less strategy and more tactics and operations of
corporate BI.
6 Conclusions
The arm?s length between production systems and BI can be beneficial in having
more refined, cleansed, consistent data for strategic business control and decision
making. This establishes an information repository of general corporate benefit
particularly if it is incorporated into EIS environment with a broad operational
orientation.
Suggestions for further research include a more holistic understanding of success
criteria of BI where technology, business characteristics, and BI process assessment is
taking part. Also the suggested management framework of dualistic thinking, time,
alignment and embeddedness would be interesting to research further. As the case
describes, even failed BI projects can have secondary effects of significant business
value. So future research is in the line of finding the more determining factors in
creating BI success or turning little used BI systems into assets of the general EIS.
The general rhetoric in BI satisfying the very need of the senior management seem
disputable in the light of (1) BI is intentional translations done before senior
management get insight, (2) BI do probably have its core users among tactical
management and analysts, (3) BI is by many authors expected to move closer to
operational requirements and need adaptions to this, (4) BI is one besides more
quantitative reporting systems that together with qualitative reporting strongly
compete on senior management?s attention.
In terms of IS research a more inclusive view on BI would strengthen the holistic
understanding of EIS and could support BI with better organisational support,
relevance and value-orientation.
From the discussions in this study it seem questionable that BI can succeed in its
predominant strategic role, much more important is it to conclude BI as a tactically
oriented information system with strong operational potentials – in line with [34]. A
more distinctive approach to BI within the EIS frame as suggested in this paper could
help both BI research and BI systems and projects in succeeding.
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