A Framework for using Business Intelligence for Learning Decision

Making with Business Simulation Games

Waranya Poonnawat

1,2

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.

1 INTRODUCTION

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).

Recently,

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:

283

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

Framework.

2 BI GAME

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

support.

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

Century

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

strategy.

Later, during the game play before going on each

step (step 3 to 6), business problems - which are

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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.

The

advantages of our BI game are as follows:

(1) the implementation with modern technology

(e.g., cloud computing); (2) the flexibility in

the

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.

3 DATA WAREHOUSE SYSTEM

“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

framework.

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.

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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.

4 SELF-SERVICE BUSINESS

INTELLIGENCE

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.

5 LEARNING ASSESSMENT

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,

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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,

2013).

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.

6 CONCLUSIONS

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

Century

skills through their learning process and have better

understanding how to use BI to support decision

making.

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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