Business Decision Analytics: An ERP Case Study for Torrens University

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MGT602 Business Decision Analytics

Contents
Introduction....................................................................................................................................3
Research Analysis..........................................................................................................................4
Sources of data and the use of data analytics to identify trends forming the evidence for
decision making...........................................................................................................................4
Visualisation of the decision-making process.............................................................................6
Select three decision-making tools and techniques for the project..............................................7
Conclusion....................................................................................................................................10
References.....................................................................................................................................11

Introduction
The following essay provides the sources of data and the use of data analytics to identify the
trends forming evidence for decision making. Visualisation of the decision-making process is
also provided. Further three decision-making tools and techniques to be used for the project are
also studied.
The project taken for the report is Enterprise Resource Planning at Torrens University which
is a private university in Australia.

Research Analysis
Enterprise resource planning is a software of business process management allowing the
organisation to use the system of integrated applications for managing the business and
automating other function such as human resources, services and technology. Enterprise resource
planning requires a large dedicated team for customizing and analysing the data.
Sources of data and the use of data analytics to identify trends forming the evidence for
decision making
There are numerous sources of data n ERP system. The source of data chosen should meet the
needs of the project. However, the needs can change with the growth in business and in that case,
the source of data chosen for ERP system should be expandable so as to meet the new business
needs. This means that the source or the ERP system should support plugins or have an
additional module. Some of the sources for the ERP system are as follows:
 ADempiere: ADempiere targets at small and midsized businesses. The multidimensional
features of ADempiere focus on helping the businesses to satisfy its wide range needs. For
helping ERP in the process of purchasing, sales, accounting and inventory processes ADempiere
add the supply chain management and customer relationship management feature.
 Apache OFBiz: Apache OFBiz is built on a common architecture and helps the business
in customising the ERP as per their needs. Apache OFBiz is mostly suitable for midsized and
large enterprises having the resources for internal development for the purpose of adapting to the
existing IT and business processes. Its available modules are for HR, manufacturing, accounting,
catalogue management, e-commerce, inventory management and CRM (Thumburmung et al.
2016).
 Dolibarr: Dolibarr is useful for the purpose of end-to-end management for small-sized
and mid-sized businesses. It focuses on keeping track of inventory, contracts, payment and
orders for supporting and managing an electronic point-of-sale system in an interface providing
clear information. It also provides additional add-ons extending its features.
 ERPNext: ERPNext is a classic source of data for Enterprise resource planning. The
purpose of creating ERPNext was to replace the expensive ERP implementation. The purpose of
developing ERPNext was meant to be used in small-sized and mid-sized businesses. IT provides
various modules including the ones for project management, purchase, sales, managing inventory

and accounting. It is the easiest source to be used which includes entering some information and
it provides does rest of the details by itself.
 Metasfresh: As the name suggests, Metasfresh focuses on keeping its data fresh. It is
also an open source which is focused on businesses of small and medium size. It has gained quite
a lot of attention even being the latest source from other sources discussed.
 Odoo: Odoo is an integrated source of application including various modules for
purchasing, manufacturing, inventory management, accounting, billing and project management.
All the provided modules are helpful in properly communicating the data and share of
information efficiently and in an effective manner.
 Opentaps: Opentaps is among some of the few open sources of information developed
for use within large businesses, providing a high level of power and flexibility. It provides the
majorly required modules which include the modules for manufacturing, purchasing, financing
and managing inventory. Another feature being provided by Opentaps is that it helps in
analysing all the aspects present in the business. All this information can be used for better
planning in future. Further, it allows add-ons and additional modules, expanding its features.
 WebERP: WebERP is an ERP source module operating through the web, as its name
suggests. It is focused on distribution, manufacturing and wholesale businesses. Further, it allows
integration with other third-party sources expanding the business knowledge base. It aims to be
an efficient, platform-independent and fast source, easy to be used for general businesses
(Thomas et al. 2018).
 xTuple PostBooks: xTuple PostBooks is useful for the small businesses having
outgrown their roots in e-commerce, distribution and manufacturing businesses. The
comprehensive source is built around accounting, ERP and CRM features add distribution,
vendor reporting abilities, purchasing and inventory.

Visualisation of the decision-making process
In the modern developed era, the art of visualisation is making the decision-making process more
sensible. Visualisation of the decision-making process is the process of graphically presenting
the process of decision. The need for visualisation of the decision-making process is that it helps
in making the whole process look very simple and attractive and also assists in easily
understanding the whole process so that it can be carried out effectively (Moore, 2017).
Indentification
of the decision
Gathering the
information
Identifying
alternatives
Weighing the
Evidences
Choosing
among the
alternatives
Taking action
Reviwing the
decision

Select three decision-making tools and techniques for the project
ERP system is mainly needed for the purpose of meeting the functional requirements which are
as follows:
 An easy to use system and interface working seamlessly across various departments,
having controlled access.
 Having a common database that can be accessed through multiple applications.
 Customisation and integration of add-ons as per necessity.
 Using various parameters, for searching and reporting utilities to generate reports.
All the above-mentioned needs and requirements of ERP can be fulfilled using specific and
perfect tools and techniques. The decision-making tools and techniques to be used for Enterprise
resource planning are group decision support system, knowledge-based decision support system,
decisions support system. A brief discussion of all three above mentioned tools and techniques is
as follows:
1. Group decision support system:
Group decision support system is a technology which provides support for the collaboration of
the project by enhancing digital communication using numerous tools and techniques. These
programs are useful for supporting the customised projects which require various types of
protocols of meetings, group work and providing input in the group. Group decision support
system can be used in numerous ways as the developers make more sophisticated and versatile
resources for helping the group in promoting their work. The aspects of a group decision support
system include features of brainstorming, scheduling and documenting meeting, local elements,
distance participation and auxiliary support. Group decision support system is mostly with a
decision support system as both support human decision making. The group decision support
system is generally developed for the purpose of supporting either a group or a team. The use of
group decision support system in Enterprise resource planning is because of its various
characteristics which help and supports the group in their process of decision making (Kar,
2015). Some of the characteristics of the group decision success system used in ERP are as
follows:
 The group decision support system is specially designed for supporting decision-making
techniques, effective communications and creative thinking.

 It is very easy to use and the members of the group having different backgrounds can also
take part effectively.
 It is very flexible and can be used in different perspectives and different decision-making
processes.
 The existence of parallel communication allows numerous members to participate and
contribute towards the group performance simultaneously (Lolli, 2017).
The application of group decision support system in Enterprise resource planning consists of
three major components which are as follows:
 Hardware: Hardware includes the hardware equipment that is having physical existence
such as audio-visual tools, computers, networking equipment and electronic displays etc. It also
includes the physical setup made for the group meeting including the chairs, tables etc.
 Software: Software includes the tools which do not have a physical existence but
contribute to the project. Electronic tools for brainstorming, tools of forming policies, idea
organisers, electronic questionnaires, priority setting tools etc. are some of the software
components assisting the project of Enterprise resource planning.
 People: People comprises of the members of the group working on the project. It
includes the experienced and cooperating staff members focused on meeting the needs and
requirements of the project.
All these components of a group decision support system help in arranging and maintaining all
the resources required for completing the project and successfully carry out the project.
2. Knowledge-based decision support system:
The knowledge-based decision support system is the systems which are designed for the purpose
of ensuring more precision in the process of the decision-making process with the appropriate
and timely use of the information, knowledge management and data for the project. This
particular system of decision making is referred to as a decision support system based on
knowledge, which includes the use of knowledge and the perfect application of the knowledge
and communication techniques necessary for the completion of the project. The knowledge-
based decision support system is useful in the efficient and successful completion of the project
as in the current modern era multiple decisions are made, thus it helps in making choice for
choosing the perfect decision for the project which depicts proper use of the knowledge and
resources (Alyoubi, 2015). Knowledge-based decision support system evolved a new generation

of the decision supporting system. However, along with the benefits provided by the knowledge-
based decision support system, various complication also arises in the development and use of
the knowledge-based support system. The knowledge-based decision support system is
developed and implemented in the project by using the following steps which include gathering
the knowledge, engineering the gathered knowledge, representation of the knowledge, reasoning,
knowledge base system’s construction, finding out alternatives of the knowledge gathered and
the last step consists of making the perfect decision for using the most appropriate knowledge for
the project (Kwan, 2015).
3. Decisions support system:
The decision support system is an information system which is used for the purpose of
supporting the decision-making process involved in the project. The decision support system
helps the project managers to analyse all the data collected and all the other information involved
in the project for the purpose of solving problems and making perfect decisions. The decision
support system helps in perfect decision making, solving the problem on time and improving the
efficiency of dealing with problems (Arnott & Pervan, 2016). The effective implication of the
decision support system is made in the project for successfully choosing the perfect decision
which is required for the completion of the project. The decision support system is focused on
underspecified and less structured problems faced by the management. It tries to combine the use
of various models and techniques with the data access functions. It also makes the features to be
used easily by the person without knowledge of computers. It makes the decision-making
process and adaption to the environmental changes very flexible and adaptable (Beşikçi et al.
2016).
Implementation and the use of the above-mentioned decision-making tools and techniques in the
project of Enterprise resource planning in Torrens university, helps in successful completion of
the project with collecting the perfect required knowledge, making the best decision regarding
the selection of most appropriate knowledge for the project and making efficient use and analysis
of the knowledge.

Conclusion
The following report focused on the decision making the process and the tools and techniques
used in a project with reference to the project taken Enterprise resource planning in Torrens
University. It involves focusing on the sources of data collection and their use in the decision-
making the process which involved the study of decision-making tools for Enterprise resource
planning. The visualisation of the decision-making process is provided along with the benefits of
visualising the decision-making the process. Three tools of the decision-making process are
studied and analysed which includes a brief discussion made on the group decision support
system, knowledge-based decision support system, decision support system.

References
 Alyoubi, B. A. (2015). Decision support system and knowledge-based strategic
management. Procedia Computer Science, 65, 278-284.
 Arnott, D., & Pervan, G. (2016). A critical analysis of decision support systems research
revisited: the rise of design science. In Enacting Research Methods in Information Systems (pp.
43-103). Palgrave Macmillan, Cham.
 Beşikçi, E. B., Arslan, O., Turan, O., & Ölçer, A. I. (2016). An artificial neural network-
based decision support system for energy efficient ship operations. Computers & Operations
Research, 66, 393-401.
 Kar, A. K. (2015). A hybrid group decision support system for supplier selection using
analytic hierarchy process, fuzzy set theory and neural network. Journal of Computational
Science, 6, 23-33.
 Kwan, P. W., Welch, M. C., & Foley, J. J. (2015). A knowledge-based Decision Support
System for adaptive fingerprint identification that uses relevance feedback. Knowledge-Based
Systems, 73, 236-253.
 Lolli, F., Ishizaka, A., Gamberini, R., Rimini, B., Balugani, E., & Prandini, L. (2017).
Requalifying public buildings and utilities using a group decision support system. Journal of
Cleaner Production, 164, 1081-1092.
 Moore, J. (2017). Data visualization in support of executive decision making.
Interdisciplinary Journal of Information, Knowledge, and Management, 12, 125-138.
 Thomas, P., Welsh, R., Folla, K., Laiou, A., Mavromatis, S., Yannis, G., ... & Persia, L.
(2018). FOR A COMMON DATA COLLECTION SYSTEM AND DEFINITIONS.
 Thumburmung, T., Vasconcelos, A. C., & Cox, A. (2016). Integrating qualitative data
collection methods to examine knowledge management across disciplinary boundaries. In
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