A Framework for using Business Intelligence for Learning Decision
Making with Business Simulation Games
Waranya Poonnawat
and Peter Lehmann
Faculty of Information and Communication, Stuttgart Media University, Stuttgart, Germany
School of Computing, University of the West of Scotland, Paisley, U.K.
Keywords: Business Intelligence, Decision Support Systems, Decision Making, BI Skills, 21
Century Skills, Business
Simulation Games, Data Warehouse, Self-Service Business Intelligence, Learning Assessment.
Abstract: This position paper will give an overview of the Business Intelligence (BI) learning framework which
includes: (1) BI game; (2) data warehouse system; (3) self-service BI tools, and (4) learning assessment.
The BI game is used as an educational platform to simulate business scenarios and business processes. The
data warehouse system integrates all of the business transactions and results from the BI game and provides
a single point of truth for analytical information. During the business processes, self-service BI tools are
used to access data marts for business analytics by both students and instructors. The learning assessment
component is used to evaluate students’ knowledge and skills in BI and 21
Century skills.
The evolution of modern Business Intelligence (BI)
is from Decision Support Systems (DSS) which has
emerged since the mid-1960s (Power, 2007). This
decision support technology is still an important
research topic in the realms of both industry and
universities (e.g., DSS2.0 Conference 2014).
Gartner (2013) published a survey result
reported that BI has been in the top rank of CIO
global technological priorities for several years –
2009, 2012 and 2013. However, the skill gap in the
BI field was still significantly up to 60% of reponses
from 2,053 CIOs of 36 industries across 41
countries. This skill gap has both a negative and
short-term impact on business (Gartner, 2013).
Based on the survey from BI Congress 2012
regarding the status of BI in academia, there were
several significant challenges in teaching and
learning BI, for instance, access to data sets, finding
suitable cases, providing realistic and meaningful
experiences (Wixom et al., 2013). Several BI
instructors have attempted to improve their BI
teaching and learning methods and have considered
alternative methods, for instance, proposing course
components and learning objectives to teach data
warehousing and data mining (Fang et al., 2006),
teaching data warehousing and data mining using
case projects (Rob et al., 2007), teaching BI using
cloud computing technology (Mrdalj, 2011),
teaching BI with puzzle-based concept (Presthus et
al., 2012), proposing a pedagogical design and
method for a practical technical module for a
nontechnically oriented BI course (Wang et al.,
2013), concerning an experiential learning concept
in teaching BI (Podeschi, 2014).
As well as this, the labour market will need more
new skills and more new ways of learning (Redecker
et al., 2011). Thus, it is not only BI skills that are
needed for the next-generation BI workforce
(Wixom et al., 2010), but also the 21
Century skills
for European Community.
Game is one aspect of the technology trend that
will be able to support the future of learning to build
up new skills (Redecker et al., 2011). Game
characteristics, for instance, competition and goals,
choice, rules, fantasy and challenges, can contribute
and sustain 21
Century skills (Romero et al., 2014).
Moreover, business simulation games have been
known as one of the most effective education
methods for teaching and learning managerial skills
(e.g., Faria et al., 2009; Wawer et al., 2013;
Williams, 2011).
Therefore, the BI learning framework (see Figure
1) is proposed to contribute learning and teaching BI
for the next-generation BI workforce concerning
both BI skills and 21
Century skills. The
framework consists of four components as follows:
Poonnawat W. and Lehmann P..
A Framework for using Business Intelligence for Learning Decision Making with Business Simulation Games.
DOI: 10.5220/0005474902830288
In Proceedings of the 7th International Conference on Computer Supported Education (CSEDU-2015), pages 283-288
ISBN: 978-989-758-108-3
2015 SCITEPRESS (Science and Technology Publications, Lda.)
(1) BI game – an educational platform to provide
simulation realistic business scenarios, data sets,
suitable cases with meaningful experiences; (2) Data
Warehouse (DW) system – an information service to
support business managerial decision making; (3)
Self-Service BI (SSBI) tools – a personal business
analytical tool to analyse and monitor business
performance management, and (4) learning
assessment a set of evaluation methods for
students’ learning outcomes.
Figure 1: The four components of the BI Learning
BI game is a kind of computerised business
simulation game for teaching and learning BI. Since
there have been several empirical studies indicating
that business simulation games enable students to
learn how to make a decision, 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; Wawer et
al., 2013; Williams, 2011). Most of business
simulation games were developed based on different
learning objectives, for instance, inventory
management, strategic management, marketing
management, business terms. However, the learning
objective of BI game focuses on the BI concept,
knowledge and skills for managerial decision
BI game has been developed by the research
team of BI Academy (BIA) – the learning portal and
community for teaching and learning BI (www.bi-
academy.eu). The prototype was launched since
February 2014 and has been tested with students in
several European universities.
BI game is based on the conceptual framework
(see Figure 2). In each business activity students
implement the management process cycle to make a
decision (Gluchowski et al., 2008).
The objectives or competence goals of the game
focus on students’ learning for both (1) 21
skills and (2) BI skills – which are about using
OnLine Analytical Processing (OLAP) tools for
decision support, creating OLAP-based business
Figure 2: A conceptual framework for the BI game.
planning, designing a multi-dimensional model,
designing an ETL process, appling data mining
concepts and running business based on BI concepts
by using SSBI tools as a business analytical tool.
The organisational or event format of BI game
has six steps (see Figure 3). Firstly, students are
assigned into groups randomly and each group
represents a city opening a new bike shop. Then,
they have been introduced to BI game and the bike
marketing situation based on the city. Students have
to present their business plan to get an initial market
share for starting their business. Secondly, students
book the initial settings for a store location, product
mix, required employees and marketing campaigns.
After the initial settings (step 2), the data generator
with an embedded simulation algorithm generates
the revenue based on the input business parameters.
Next, students can access the data access layer of the
ERP system, learn how to apply SSBI tools, analyse
the data and make a decision to refine their business
Later, during the game play before going on each
step (step 3 to 6), business problems - which are
based on the learning objectives - are given to
students. The business problems should lead
students to use SSBI tools to generate OLAP reports,
OLAP-based business planning models, data mining
models, what-if scenarios or Balanced Scorecard
(BSC) dashboards.
Figure 3: The organizational format of the BI Game.
advantages of our BI game are as follows:
(1) the implementation with modern technology
(e.g., cloud computing); (2) the flexibility in
number of BI teaching modules (e.g., multi-
dimensional modelling, ETL process, OLAP reports,
business planning, data mining, what-if analysis,
dashboard); (3) the flexibility of the duration for
running the game (e.g., three days, one week, one
semester); (4) the contribution for international
students; (5) the usage of BI vendor university
alliance programs (e.g., Microsoft MSDN Academic
Alliance, SAP University Alliances); (6) the system
scalability which can handle large amount of players
at a time, and (7) the learning assessment to analyse
learning outcomes.
“A data warehouse is a subject-oriented, integrated,
non-volatile and time-variant collection of data in
support of management’s decision making process”
(Inmon et al., 2008, p.7). It integrates heterogenous
and distributed data sources. Users, therefore, are
able to have access to the same sources of analytical
information, gain insights of their business
performance and can make better decisions which
will help them to balance all levels of their business
strategies (Poe, 1996). The major advantange of data
warehousing is to support the vertical integration
(Oehler, 2006) between different management levels
– operational, tactical, and strategic – and provide a
single point of truth for enterprise information
(Inmon et al., 2001). Moreover, a data warehouse is
a good practice solution for information logistics and
is considered as a reference architecture to underpin
a successful BI project.
With the data warehouse system component, BI
learning framework can handle data from the
business simulation game and learning process. Its
development is based on the technical framework
(see Figure 4).
Figure 4: A technical framework for the BI learning
Data sources originate from business game
application and the data generator engine simulates
the revenues and costs. All are based on the initial
settings, initial market share and proposed business
plan. The game data is stored in a game server and
later will be extracted, transformed and loaded
(ETL) into
the data warehouse system. All
transactional and master data from game are stored
as a relational model in Operational Data Store
(ODS) layer of the data warehouse system (see
Figure 5).
Figure 5: The relational model in ODS layer.
Later, students are assigned to design an
information model for their data mart, design an
ETL process and create an ETL package to populate
data into data marts. Consequently, students can use
SSBI tools to carry out business analytics and
improve their business performance
in accordance
with the rights to access their data only.
Self-Service Business Intelligence or SSBI is a new
advanced BI technology. It provides an environment
whereby users can easily create their own data
models and analyse data by themselves (Imhoff et
al., 2011). There are several types of information
workers that are involved in using SSBI. These are:
information producers, information consumers,
information collaborators and Data Warehouse
(DW) or BI builders (Imhoff et al., 2011).
SSBI tools cover the front-end applications of BI
landscape as follows: (1) presentation tools, for
instance, reporting and dashboards; (2) analysis
tools, for instance, OLAP analysis and data mining;
(3) visualisation tools, for instance, displaying data
with maps or various types of charts and graphics;
(4) integration tools, for instance, adding external
data into the BI data model, and (5) data discovery
or exploration tools, for instance, using ad-hac query
(Aziz, 2014). OLAP is considered as a core
technology of BI for decision makers to view data
from a variety of perspectives and visualise
summarised information with respect to business
performance from various analysis with scorecards
and dashboards (Richards et al., 2014). Moreover,
modern SSBI tools will be able to access various
data sources from different providers and more data
mart structures (e.g., relational model, multi-
dimensional model, flat files).
Students will be the next-generation BI
workforce for the (business) community. They need
to have more analytical skill and make faster and
better decisions based on information they have in-
hand. So, the faster they make a decision, the more
they can save the business value (Hackathorn, 2003).
In the BI learning framework environment,
students learn in a short period how to use SSBI
functionalities in a tool – such as an electronic
spreadsheet – to conduct business analytics
concerning the business problems and learn to use
SSBI tools improving their decisions based on fact.
The usage of BI tools are, for instance, applying data
mining concept to analyse the prospective customers
for a mailing list, creating OLAP-based business
planning for the next years procurement, designing a
dashboard to monitor the sales performance by using
Key Performance Indicators (KPIs), etc.
Instructors also can monitor how students run
their business and solve the business problems, for
instance, using OLAP-based reports to assess the
overview of profit for each group of students (see
Figure 6) and a dashboard to see the revenue for
each store by price segment (see Figure 7).
Figure 6: Sample of an OLAP-based report.
Figure 7: Sample of a dashboard.
There are at least three groups of skills that are
needed for today’s BI users as follows: (1)
analytical skills – e.g., data mining, statistical
analysis; (2) IT skills – e.g., data mart model, ETL
process, and (3) business knowledge and
communication skills – e.g., business functions,
ability to explain what is being analysed (Andoh-
Baidoo et al., 2014). However, the diversity of SSBI
tools and features are not trivial to use. As most of
users focus on consuming the information, while
others focus on producing the information.
Consequently, SSBI tools could be difficult to use
for some users or with a high risk to be overused by
other users (Eckerson, 2012).
The next-generation BI workforce needs also to
have 21
Century skills – collaboration or
teamwork, communication, ICT literacy, social or
cultural skills, creativity, critical thinking, problem
solving, productivity, learning to learn, self-
direction, planning, flexibility, risk taking, manage
conflicts and sense of initiative (Romero et al.,
2014). Additionally, there are two methods that are
primarily used for the competency assessment: (1)
self-assessment, and (2) evaluation of results from
business simulation game by the instructors (Karl,
Therefore, the learning assessment for the BI
learning framework will be categorised into three
parts as follows:
(1) self-assessment – students are requested to
complete the questionnaires before and after playing
BI game. They evaluate themselves for BI skills and
Century skills.
(2) game results – students should pass the
course or get a certificate, as and when they are able
to run a business well. The game results also will be
used to compare between each group for discussion
or debriefing (Crookall, 2010).
(3) SSBI usage – students’ level of BI skills
depend on how advance they are able to use SSBI
tools for data analysis as shown in the organisational
format of BI game.
Our BI learning framework provides a closed-loop
model started from the initial settings of business
parameters based on business strategy. All business
settings are stored in the ERP server, information
requirements and data marts are modelled,
developed and deployed in the data warehouse
server. Business analytics are performed in order to
make reasonable decisions and later students are
able refine their business model for the next cycle.
This closed-loop approach helps students to learn
to manage the performance of the business processes
and is able to align business goals and processes
consistently (Martin, 2014). Additionally, students
are able to understand the impact between each
business process because it involves human
intervention to improve the way decisions are made
(Kerremans et al., 2012).
We believe that the BI learning framework
provides a modern, integrated and easy-to-use
platform which will overcome the limitations and
challenges in learning and teaching BI. Moreover,
students will improve their BI skills and 21
skills through their learning process and have better
understanding how to use BI to support decision
Furthermore, we are working on the integration
of more business scenarios into the framework, in
order to leverage BI maturity and improve 21
Century skills for students.
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