Using Self-service Business Intelligence for Learning Decision Making
with Business Simulation Games
Waranya Poonnawat
1,2
and Peter Lehmann
1
1
Faculty of Information and Communication, Stuttgart Media University, Stuttgart, Germany
2
School of Computing, University of the West of Scotland, Paisley, U.K.
Keywords: Self-service Business Intelligence, Business Simulation Games, Decision Support Systems, Business
Intelligence, Management Process, Decision Making.
Abstract: This position paper presents, firstly, the evolution of decision support systems (DSS) and the challenges in
teaching in the field of DSS. Secondly, the concepts of management process, decision support technology,
self-service business intelligence (SSBI), business simulation games and literature search results on business
games associated with DSS are presented. Lastly, we suggest a conceptual framework of using DSS/SSBI
on top of business simulation games to support better decision making.
1 INTRODUCTION
Information systems for supporting management
decision making, known as Decision Support
Systems, or DSS, have been evolving since the mid-
1960s (Power, 2007). The evolution of DSS
concepts remains an important research topic in both
industries and universities (e.g., DSS 2.0
Conference, 2014).
Over the last decades, DSS were utilized with
some limitations and difficulties, such as
heterogeneous data source extraction, multi-
dimensional modelling, business analytics,
information workers’ collaboration, multi-channel
user interfaces and massive data visualisation.
Meanwhile, the high demand for managing the
corporate’s information factory (Inmon, Imhoff and
Sousa, 2001) brought the modern and powerful DSS
concepts and methods onto the DSS stage, which are
compromised under the term “Business
Intelligence”, or BI. Starting in the late 90s, Gartner
coined the term BI to describe “a set of concepts and
methods to improve business decision making by
using fact-based support systems” (Power, 2007, p.
11-12). This enables BI applications to function for a
wider group of end users and move from the
management-focused decision support to the easy-
to-use decision support to users at all levels of a
company – strategic, tactical and operational.
Decision making in companies is necessary for
operating and managing highly optimised business
processes. Using BI applications with less support
from the information technology (IT) departments is
called “Self-Service Business Intelligence”, or SSBI
(Imhoff and White, 2011, p. 5). SSBI is a new BI
generation beyond traditional BI technology which
needs more IT contribution. Using SSBI tools, users
have a variety of personal decision support features
and functions, for instance creating, searching,
exploring, modelling, analysing, visualising, sharing
and collaborating to develop their own ad-hoc BI
solutions. The complexity of BI functionalities,
therefore, is far more powerful than ever and users
are able to use SSBI technology within their
desktops or spreadsheet applications with a higher
degree of independency from the IT departments.
Nevertheless, the BI-related subjects are typical
in the field of Information System (IS) and have
been taught for many years (Power, 2007). They are
still very popular in the academic world. Subjects
such as Information Analytics, Management
Information System, Business Intelligence and
Business Analytics, are based on DSS/BI concepts.
Moreover, Wixom’s survey about the BI status in
academia (Wixom, Ariyachandra and Mooney,
2013), had a base of 319 professors from 257
universities in 43 countries around the world. There
were many BI-related subjects that have been taught
in various academic disciplines, for instance
Information System, Decision Science, Statistics,
Computer Science, Management Information
System, Business Analytics, Operations Research,
235
Poonnawat W. and Lehmann P..
Using Self-service Business Intelligence for Learning Decision Making with Business Simulation Games.
DOI: 10.5220/0004941202350240
In Proceedings of the 6th International Conference on Computer Supported Education (CSEDU-2014), pages 235-240
ISBN: 978-989-758-021-5
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
Supply Chain Management, Economics, Marketing
and Accounting.
In the survey’s top message, the question about
teaching and learning BI was listed as the most
challenging issue. Challenges mentioned included:
access to data sets, finding a suitable textbook,
finding suitable cases and providing realistic
experiences (Wixom et al., 2013).
Consequently, the questions about how to teach
and learn BI have arised as follows:
(1) “How can students be taught not only the
basic concepts about BI and the handling of a BI
tool, but also to select the “right” BI tool for making
good decisions in the decision making process?”
Since BI/SSBI tools are diverse and often overlap
each other, as a consequence they are difficult to use
for some users or with a high risk to be overused by
other users (Eckerson, 2012).
(2) “What kind of educational platform can be
used to teach the effective and efficient usage of BI
tools?” Business simulation games are popular and
known as one of the most effective education
methods, which are widely used for teaching and
learning managerial skills, such as making decisions,
using management techniques, integrating ideas,
applying theory to practice and giving the
experiential learning to students (e.g., Ben-Zvi,
2010; Faria, Hutchison, Wellington and Gold, 2009;
Lin and Tu, 2012; Wawer, Miloz, Muryjas and
Rzemieniak, 2013; Williams, 2011).
In this position paper we suggest a framework to
teach and learn BI concepts as a decision supporting
method on top of business simulation games. The
framework focuses on using SSBI which is a new
and powerful BI technology generation for a wide
range of decision making by users or information
workers. We will focus on SSBI because it gives the
opportunities to all kind of users to design DSS/BI
models with less IT-technical background needed.
2 MANAGEMENT PROCESS AND
DECISION MAKING
DSS/BI technologies are used increasingly to
support the management processes, which can be
seen as a systematic series of different phases. As
an example for management process the following
schema will be used to explain the typical
management tasks in four phases: Business
Analysis, Decision Taking, Organisation & Steering
and Success Controlling (Gluchowski, Gabriel and
Dittmar, 2008) (see Figure 1).
Strategic
Goals
Marketing
Environment
Enterprise
Environment
Solution
Alternatives
Alternatives
Evaluation
Decision
Business Analysis
Decision Taking
Success
Controlling
Organisation
& Steering
(Adapted from Gluchowski et al., 2008, p. 21)
Figure 1: Phase diagram for management process.
Phase 1 Business Analysis: the managerial decisions
always occur along the business processes, which
depend on the context of business objectives,
internal and external environment. This initial phase
focuses on the (permanent) analysis of situations
based on three pillars: (1) Strategic Goals – all
objectives from all levels of company should be
harmonised, not be in conflict and used as a strategic
framework to influence and balance with the other
two pillars; (2) Marketing Environment – such as
competition, economic growth and stability and
technological advancements, and (3) Enterprise
Environment – such as availability of resources,
organisational culture and structure. All activities,
that have an impact or influence on the stability of
this system have to be observed, analysed and
validated.
Phase 2 Decision Taking: this phase emphasizes
the planning for taking decisions and consists of
three steps: (1) Solution Alternatives – any possible,
realistic and relevant alternatives are formulated and
collected under a given assumption for any expected
future actions; (2) Alternatives Evaluation – all
collected alternatives have to be evaluated and
compared based on the possible risks, feasibility and
implications of each alternative, and (3) Decision –
an alternative is selected out from others which has
an acceptable risk and is suitable for a specific
business situation for further implementations.
Phase 3 Organisation & Steering: the selected
alternative has to be implemented and a course of
actions has to be undertaken. Therefore, the
organisational structure and project management
have to be designed and developed in order to
transfer any accountabilities, responsibilities and
communication through all hierarchical management
CSEDU2014-6thInternationalConferenceonComputerSupportedEducation
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levels during the implementation period.
Phase 4 Success Controlling: the selected
alternative is used as the baseline and the actual
results are used to measure and compare with the
baseline. The variances have to be analysed, which
leads to any new actions and restarts the next cycle
of the management process.
The business value, which can be gained from
management process, depends on the decision
making latency or action distance – the distance
between the starting point that the business event
occurs and the action is taken. The action distance
consists of three factors as follows: (1) data latency
– the time starting from the point that a business
event occurs, relevant data are captured, prepared
and stored; (2) analysis latency – the time for data
analysis, information generation and delivery to the
proper persons, and (3) decision latency – the time
to consider and understand all relevant information,
make decisions to take the course of action and
respond with an intelligent manner (Hackathorn,
2003).
Figure 2 shows the value-time curve – the
relationship between the (business) value and time to
take the action – which represents as a decay
function. The business value decreases rapidly after
the business event happens, therefore, the faster to
take action, the higher to save business value.
(Adapted from Hackathorn, 2003)
Figure 2: The value-time curve.
3 DECISION SUPPORT
TECHNOLOGY
Shim, Warkentin, Courtney, Power, Sharda and
Carlsson (2002) stated that computer technology
solutions have been used to support complex
decision making and problem solving since the late
1950s in terms of DSS and become more significant
since the early 1970s. Classical DSS tools have been
designed with three main components: (1) the
capabilities to access internal and external data,
information and knowledge; (2) the functions for
modelling and analysing, and (3) the simplified user
interfaces to enable interactive queries, reporting and
graphing functions. In addition, the research areas of
DSS technology typically focus on how to improve
the “efficiency” of users’ decision making and the
“effectiveness” of decisions.
DSS applications can be used to describe any
analytical applications that help managers in
planning and optimising business goals and
objectives, such as production planning, investment
portfolio optimisation, Executive Information
System, expert system and Online Analytical
Processing (OLAP) (Wixom and Watson, 2010). In
addition, data warehouse technology has emerged to
handle massive data, operate OLAP and implement
dashboard or scorecard applications for DSS (Power,
2007). DSS remain popular in corporate and
academic research publications due to the
contribution of the four powerful DSS technologies:
data warehouse, OLAP, data mining and World
Wide Web (WWW) (Shim et al., 2002).
Since the early 1990s, Gartner coined the term
BI and the term BI also has been used to describe the
analytical and decision support applications. Wixom
et al. (2010, p. 14) also defined BI as “a broad
category of technology, applications and processes
for gathering, storing, accessing and analysing data
to help its users make better decisions”. The authors
also stated that BI plays a critical role, impacts to
organisational success, is required to compete in the
marketplace and changes from being used by a few
specialists to many workers.
In today’s economic environment, BI solutions
become more important and essential for managing
the company intelligently. However, many decisions
still are not based on BI because of the limitations to
access information and to use suitable BI tools for
business analytics. A new development of BI
technology called Self-Service BI, or SSBI, offers an
environment to support and empower users to create
their own ad-hoc BI solutions and making decision
faster. The development of SSBI technology is
highly growing and the new SSBI functionalities
will be launched more into the marketplace
(Evelson, 2012; Howson, 2013).
UsingSelf-serviceBusinessIntelligenceforLearningDecisionMakingwithBusinessSimulationGames
237
4 SELF-SERVICE BUSINESS
INTELLIGENCE
The concept of personal decision support systems is
the oldest form of DSS (Arnott, 2008), and the
concept of SSBI has been attempted to integrate in
BI systems for many years (Mundy, 2013).
Originally, the objective of both concepts is
supporting personal decision making. In recent
years, however, the development of SSBI emerged
as a new advanced BI technology in the marketplace
in order to fulfil this objective. Some significant
drivers for SSBI requirement are as follows: the
business needs change constantly and rapidly, the IT
departments are unable to satisfy the business users’
requirements in timely manner, the slow access to
information provided by the IT departments, the
business users need to do more analytics and the
limitation of IT budget (e.g., Eckerson, 2012; Imhoff
and White, 2011; Kulkarni, 2012).
SSBI is defined as “the facilities within the BI
environment that enable BI users to become more
self-reliant and less dependent on the IT
organisation” (Imhoff and White, 2011, p. 5). These
facilities focus on four main objectives: (1) to make
BI results easy to consume and enhance; (2) to make
BI tools easy to use; (3) to make data warehouse
solutions fast to deploy and easy to manage, and (4)
to make data sources easy to access (Imhoff and
White, 2011).
Since SSBI tools are diverse, an appropriate self-
service environment can be provided by knowing the
types of information workers, the skill levels of
different information workers and the tools or
fuctions of SSBI they need (Imhoff and White,
2011). Moreover, Imhoff and White (2011) found
that business users’ skills and the lack of business
users’ training are two of the top five inhibitors for
SSBI.
5 BUSINESS SIMULATION
GAMES
Business simulation game is a subset of simulation
games which focuses on business content, whereas,
the broader definition of simulation game underlying
of two concepts: simulation and game. The term
“simulation” generally refers to “a representation of
a real system, an abstract system, an environment or
a process that is electronically generated” (Hainey,
2010, p. 44). The term “game”, is defined by Hay as
“an artificially constructed, competitive activity with
a specific goal, a set of rules and constraints that is
located in a specific context” (as cited in Wilson,
Bedwell, Lazzara, Salas, Burke, Estock, Orvis and
Conkey, 2009, p. 2). Cruickshank stated that the
term simulation game is used as “one in which
participants are provided with simulated
environment in which to play” (as cited in Connolly
and Stansfield, 2006, p. 466).
Faria et al. (2009) stated that business simulation
games have been developed and used as the vehicles
for teaching the business concepts for more than 40
years in universities and companies. The major
reasons of using business simulation games were as
follows: gained experience, strategy aspects,
decision-making, learning outcomes and teamwork
experience. The advancement of IT provided more
opportunities to improve the learning experience and
the way to use business simulation games and also to
develop a more complex environment. In addition,
business simulation games have moved from being a
supplemental tool to a central tool and have become
a major form of pedagogy for business education.
Several studies stated that business simulation
games enable students to learn how to make
decisions, manage the business process in a modern
enterprise, link between abstract concepts and real
world problems and improve quantitative skills (e.g.,
Ben-Zvi, 2010; Lin and Tu, 2012; Wawer, 2013;
Williams, 2011). Furthermore, the new concept of
business simulation games, which combines with
case-based approaches and experience-based
learning theories, results in business simulation
games being one of the popular and effective way of
education methods (Wawer, 2013).
6 LITERATURE SEARCH
The literature search has been performed to find the
empirical studies about business games associated
with DSS. The literature search has been done using
several online databases – Google Scholar,
ScienceDirect, EBSCO, IEEE, Springer, Wiley
Online, ACM and Emerald. The terms used for
searching from abstracts, titles and keywords, as
follows:
(“serious games” OR “business games” OR
“games-based learning”) AND (“decision support
system” OR “management information system”)
The initial search returned 1,362 results, of
which ten articles met the criteria - business games
associated with using DSS for making decision –
and two added articles were found in the references.
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The studies showed that some business simulation
games provided decision support tools inside the
games and some others used the external decision
support tools. The reporting in the business
simulation games was often based on pre-defined
queries with little flexibilities in using ad-hoc
queries. Analytical modules for prediction were
restricted to the database of the games. The
flexibility for tactical queries and automated
decisions were not foreseen. Moreover, business
simulation games in the studies were not designed
with regard to teaching and learning BI concepts.
However, the strength was on teaching business
scenario.
7 PROPOSED SOLUTION
This position paper suggests a conceptual
framework of using DSS on top of business
simulation games to teach and learn decision making
(see Figure 3).
In the research project, business simulation
games will be used as an educational platform to
Business Analysis
Decision Taking
Success
Controlling
Organisation
& Steering
Business Analysis
Decision Taking
Success
Controlling
Organisation
& Steering
Business Analysis
Decision Taking
Success
Controlling
Organisation
& Steering
Business Analysis
Decision Taking
Success
Controlling
Organisation
& Steering
Figure 3: A conceptual framework of using DSS on top of
business simulation games.
simulate the business scenario. During the business
processes, the DSS tools – SSBI – will be applied
for each business activity to support the decision
making process.
We will select business simulation games which
support the representative business processes,
evaluate a software platform for DSS provided SSBI
functionalities and then attach with the business
simulation games, lastly, create criteria for
measuring the learning outcomes.
The framework will be used for experiments to
prove that whether it is able to support learning and
teaching BI, provide a better understanding of using
SSBI tools and applications and SSBI technology
will help end users to make better
(valuable/actionable) decisions.
Furthermore, this framework will integrate an
instrument for students and teachers to measure the
learning outcomes based on the concept of “learning
analytics” (Siemens, Gasevic, Haythornthwaite,
Dawson, Shum, Ferguson, Duval, Verbert and
Baker, 2011).
8 CONCLUSIONS
For many years, DSS have been used to improve the
quality of managerial decisions. DSS applications
have changed over the last decades, moving from
Enterprise Reporting System to Management
Information System and nowadays to Business
Intelligence Solutions. The issue of teaching and
learning DSS is still a big challenge in the academic
world, since the DSS- or BI-related subjects are still
difficult, complex and challenging. Moreover, the
demand for well-educated students in the field of
DSS is still growing.
We are working on a framework using business
simulation games to overcome the restrictions and
limitations of the existing DSS teaching solutions.
We will embed a SSBI solution into business
simulation games in order to learn and teach DSS/BI
in a modern, integrated and fun-to-use environment.
We also believe that the integration of SSBI into
business simulation games will increase the learning
outcomes. We will provide a platform to measure
and manage students’ learning in the field of
DSS/BI. Our platform will also be used for
experiments to measure learning behaviour, with a
strong focus on the 21st century skills defined by the
European Community (Redecker, Leis, Leendertse,
Punie, Gijsbers, Kirschner, Stoyanov and Hoogveld,
2011).
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239
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