Decision Making in Supply Chain: Business Intelligence Analysis

This essay delves into the critical role of decision-making within supply chain management, emphasizing the integration of business intelligence (BI) tools and technologies. The essay explores the evolution of supply chain functionalities in response to globalization and technological advancements, including the implementation of RFID. It examines the challenges organizations face in making informed decisions, supported by a literature review that highlights the impact of BI on various supply chain domains such as demand forecasting, inventory management, and performance benchmarking. The analysis covers key articles and research gaps, particularly the need for more quantitative and practical data, while also acknowledging the benefits of BI in optimizing processes like lean manufacturing. The essay concludes with recommendations aimed at enhancing decision-making effectiveness, advocating for the strategic use of BI and data-driven insights to improve efficiency and responsiveness within the supply chain.

Decision Making in Supply Chain
Assessment Item 2: Essay
Student Name:
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Subject Name: Business Intelligence and Decision Support
Subject Code: 32567
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Abstract
Supply chain functionality has emerged to a be key functionality that has been developed
tremendously in recent centuries. With advent of globalisation and technology, there are a
number of technologies that have been integrated across supply chain for making it effective and
efficient. Recent developments in RFID have impounded further complexity in functions of the
supply chain. Involvement of a number of participants along with tools, techniques make it
relevant to take various decisions. Decision making has emerged to be an integral functionality
across supply chain management domains. Organisations hence are integrating various business
intelligence (BI) tools and functionalities to extend scope of decision-making endeavors such as
to solve complex problems. The scope of this essay analyses pertinent literature in decision
making related to supply chain that can provide an organisation wide impact. Analysis of
relevant tools and recommendations from the same has also been integrated to increase
effectiveness of such.
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Table of Contents
Abstract............................................................................................................................................2
Introduction......................................................................................................................................4
Statement of Problem......................................................................................................................4
Literature Review............................................................................................................................5
Research Gap and Critical Analysis................................................................................................7
Recommendations and Conclusion..................................................................................................9
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Introduction
Supply chain comprises of an integral functionality within organisations, which deal in
variety of products (Vercellis, 2011). Organisations derive tremendous synergies from
integration of supply chain functionalities. Supply chain can become value-chain for the
organisation generating more revenues and opportunities for it. With globalisation and
technological advent, supply chain has increasingly become an integral functionality that provide
competitive advantages to the organisation. However, functionalities involving the supply chain
is increasingly complex due to presence of large number of functions and participants in it. There
needs to be tremendous transfer of information throughout the chain of supply chain such that it
can function in an appropriate manner. At every step of information flow there is decision
involvement that allows organisation to select amongst diversified strategies, costs, prices, tools
and so on. Technological advancement has led to integration of RFID (radio frequency
identification devices) into supply chain to enhance its efficiency and effectiveness. Hence, it can
be identified that there are a number of decision making criteria’s that are involved in supply
chain framework. The scope of this essay examines from various literatures, decision making
with business intelligence criteria’s that are integrated into supply chain with analysis of the
same (Popovič, 2012). In the end certain recommendations are provided that can allow catering
to effectiveness and efficient decision making as being a form of business intelligence into
supply chain.
Statement of Problem
Organisations are faced with diversified range of challenges in the domain of decision
making in supply chain. Business intelligence framework developed in recent years has made
tremendous contributions to decision making in supply chain. This essay examines key
challenges related to decision making in supply chain.
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Literature Review
Business Intelligence has created immense impact in various domain of business
functionality. Especially in the domain of supply chain business intelligence scope extends to
multiple domain also allowing for development of decision making (Ballou, 2007). This
literature review has incorporated and evaluated pertinent journals from business intelligence
framework to understand challenges faced in the domain related to supply chain. BI in supply
chain framework allows for identification of computing technologies for analysis and discovery
of business supply chain related data such as inventory levels, production pave, manufacturing
capabilities and so on, that can driver profitability. Z. R. Jourdan (2008) article, Business
intelligence: An analysis of the literature 1. In the journal Information Systems Management,
pages 121 to 131 (Jourdan, 2008). The scope of this article identifies scope related to BI that can
be applied in decision making in supply chain that can drive processes. As entire services related
to supply chain in connected with customer delivery of products, demand forecast is an integral
BI tool that are used by companies. Companies integrate supply chain BI tool for creating imapct
on their seamless array of data that is available to them from warehouse management systems
(WMS), TMS along with supply chain execution systems.
C. M. Olszak (2007) article, Approach to building and implementing business
intelligence systems. In the journal Interdisciplinary Journal of Information, Knowledge &
Management, page 2 (Olszak, 2007). This article integrates ways in which companies are able to
turn their integral data into key information which can be effectively be used by them. BI tools in
decsion makign support for supply chain can be divided into three categories as reporting, real-
time dashboards and benchmarking. Reporting is an integral functionality that allows the
business to track its development and growth through various processes by obtaining data
regarding Key Performance Indicators (KPIs) from the market. On-time delivery, customer
acceptance rates, meeting committed capacity are all integral in makign crucial decisions in the
supply chain framework (Turban, 2011). Real-time dashboards on the other hand allows
interractive overview of daily happenings in transport, warehouse and other facilities that are
related to supply chain. Benchmarking is another crucial functionality that weights company’s
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performance against market scenarios regarding on-time deliveries, customer satisfaction rates,
freigth rates and so on. Such comformance to standards allows benchmarking of the company
allowing higher performance.
P. M. Trkman (2010) article, The impact of business analytics on supply chain
performance. In the journal Decision Support Systems, pages 318 to 327 (Trkman, 2010). This
article analyses potential of BI to contribute in the doamin of supply chain in various fields as
transportation, warehousing, deliveries and so on. Through integration of BI certain key
functions in supply chain can greatly be enhanced and incorporated. BI has capability to analyse
smallest of mistakes in supply chain functionalities by integrating in lean logistics methodology.
Application of BI tools and techniques in supply chain management framework is discussed in
relation to supply chain management. An additional advantage from research in supply chain that
has been added to BI proceses includes RFID tool. RFID tool acts as an additional BI tool
providing data flow, which are further used for analysis at every point in supply chain processes.
M. A.Waller (2013) article, Data science, predictive analytics, and big data: a revolution
that will transform supply chain design and management. In the Journal of Business Logistics,
pages 77 to 84 (Waller, 2013). The scope of this article reviews decision criteria’s through
integration of BI into supply chain network. BI allows better decision by analysis of data,
optimising performance with respect to various systems. Thus, BI tool is integral in case
management wants to extend its capabilities with respect to supply chain decision making
capabilities. There are wide number of journals that provides relevant insights into concpets and
theories of BI that can be used in supply chain processes in decision making. The main
functionality however prevails is to create a dynamic response for each step of the movemnent
for the product. A challenge in respect to integrating BI for catering to decision making criteria
in business is its capability to proces information. Each type of organisation makes use of its own
BI tool for generating effectiveness in its supply chain procedure. While goal for such integration
is crucial to develop competency within the industry, its procedure still remains to be a
challenge. Method of application of BI tools in business highly vary and differ across various
domain of businesses. Hence, businesses needs to learn from their competitors regarding the
various processes in BI they have integrated. Such application will allow creation of core
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competency and brand development in the market. Thus, BI tool is integral to success of supply
chain processes.
Research Gap and Critical Analysis
The analysis of literatures and analysis related to business intelligence with its application
in supply chain framework has been conducted in the previous section. In spite of thorough
evaluation of various literatures there remains a pertinent gap in research analysis. The research
has been conducted with evaluation of literatures from journal articles, hence mostly secondary
analysis of data and concepts have been undertaken. Qualitative analysis has been done for the
purpose of this study and quantitative analysis has mostly been rejected in this. The research is
mostly theoretical in nature and practical related data has not been undertaken for this study. The
scope of the study however can easily be extended in the future with further addition of
quantitative research and first had data extraction.
Business Intelligence is bent optimization of their performance for better decision making
in supply chain framework. BI tools are used to create visible transportation, warehousing,
inventory and other component integration. Supply chain requires randomness with which
components of the each part of the network needs to respond, such fast response creates
compatibility to provide system based functionality. While product within an organisation moves
form one point to another starting with supplier of raw material, it undergoes transformations. At
each stage a value addition is done to the product then it goes to its warehouse or inventory,
which stores the product for final delivery to its customers (Sahay, 2008). Products moves from
one point to another based on customer demands of such products, hence customer demand
forecasting plays an integral in supply chain functionalities.
Attaining competency through processes in supply chain is fairly easier now compared to
the past. Earlier in absence of BI mechanisms and tools several products used to suffer damage,
there had also been incidence of products misplacements and other mishaps. Such delays with
products have not only hampered organisational brand name but also deterred expansion of
businesses. Earlier instead of BI tools, data mining techniques used to be adopted that led to
storing of high volumes of data. Such high volumes of data often led to confusion and
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misinterpretation, which resulted in nearly no effectiveness. Hence, researchers along with
industrialists developed tools that techniques that allowed integrating their components of supply
chain processes such that they are easily able to track products. Tracking products has been of
foremost importance in this domain of supply chain that creates efficiency of processes. Along
with data mining, a tool was required within industries that allowed them to make prediction
regarding their business processes and outcomes, preventing potential losses. Thus, emergence of
BI allowed immense effectiveness to existing systems prevailing in supply chain processes. BI
not only gathered and processed data but also provided critical information that could value add
to the organisation. Through BI processes, organisations could easily decide what to produce,
how much to produce, what quantities to produce and when to produce (Ranjan, 2009). Such
critical information was required to ensure organisations success and sustainability for the future.
RFID formed an integral tool in SCM processes that let them integrate BI systems to products
directly. Now, organisations were capable of ascertaining reasons for failure or success of their
various products. They could take more prudent decisions, which were integral especially in fast
moving goods. Any type of fast moving industry faces immense threats from extinction of its
demand related to particular products.
Products related to FMCG, fast fashion, trends related businesses are often faced with
threats from large volumes of products lying unutilized in their inventory over long periods of
time. In these industries specifically information needs to be passed rapidly throughout supply
chain such that logistics managers can respond to them fast and make integral decisions related
to them. Such response or decisions are not possible in case they are not sourced from authentic
and reliable analysis of data from sources. Data from storage are compiled and analysed utilizing
BI technologies that have capabilities to recognize key integral information. With BI systems
integrated into business systems, an organisation can not only have control over their resources,
financial primarily rather they can take useful decisions regarding their inventory. The most
useful invention of dynamic responsive supply chain system is lean manufacturing processes,
that only triggers production once needed to. Lean manufacturing can deliver efficiency and high
profitability to business by reducing amounts of working capital that gets blocked due to
inventory. RFID techniques are similar that creates a response system that triggers information
once a product gets exhausted. This can allow SCM processes in backward integration.
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At every point in supply chain a decision has to be made as to whether to transport or
hold inventory. SCM processes that integrates BI often includes ERP (Enterprise Resources
Planning) systems as well. ERP system can provide information regarding resource facility that
are present with the organisation, such that SCM can trigger its procurement. Another integral
aspect of SCM is its transportation systems. An ineffective transportation system can claim
significant amount of resources and put burden on the business. It is the liability of SCM to plan
its transportation management processes as well such that it can function in cost reductions.
Transportations for the organisation uses diesel which needs to be optimized such that it does not
become burdensome on the business. While every business is aware regarding the multiple
benefits that can incur from BI integration into supply chain, there prevails confusion regarding
its application capability. A methodology for application of BI tools for obtaining a procedural
decision making needs to be devised. Such strategies for integration of decision making
capabilities according to industry standards will help create competency and leadership position
for the organisations.
Recommendations and Conclusion
Analysis of framework related to BI integration into SCM processes for decision making
can enable development of better and more efficient framework. With globalisation, corporations
now needs to reach out to global customer bases with their products hence SCM forms a key to
their sustenance. Certain recommendations, which will allow corporations to gain maximum
advantage from integration of BI into SCM framework, includes the following;
 Organisations in order to have a responsive supply chain system needs to integrate BI
tools to transform data into information for the organisation. Once data transforms into
information and is passed onto layers of supply chain delivery then it can act as useful
data for taking integral decisions.
 Decision making in supply chain is restricted to comprehending analytical data available
through BI systems. While BI functionality acts as a key component in providing
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information, scope related to such information needs to be carefully evaluated prior to
their application as they are purely mechanically computed.
 BI systems might provide information that are integral for taking decisions but it is not
able to provide filtered information, which it user’s needs to. While BI might be a
mechanical process, decision support systems are not hence makers of decisions needs to
carefully evaluate such data and information prior to arriving at decisions.
 Customer demand is a highly dynamic field that changes continuously and is affected by
a plethora of variables. With new trends and corporations catering to similar products, it
might be nearly impossible to arrive at decision regarding customer demand. Thus, in
customer demand forecast, decision makers has to carefully evaluate the various
variables in connection to past trends prior to instructing their production processes.
 BI might be capable of generating information from wide variety of data, but its
implications has to be attempted physically with such information. Meaning movement
of goods in an efficient manner is possible only in case information is passed on rapidly
throughout such supply chain systems. An integrated framework of supply chain systems
is more effective compared to one that is dependent on external systems. Thus,
organisations needs to integrate their crucial functions with respect to their product
delivery at each and every point of the supply chain including transportation to derive
efficiency from the process.
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Reference Lists
Ballou, R. H. 2007. Business logistics/supply chain management: planning, organizing, and
controlling the supply chain. Pearson Education India.
Jourdan, Z. R. 2008. Business intelligence: An analysis of the literature 1. Information Systems
Management, 121-131.
Olszak, C. M. 2007. Approach to building and implementing business intelligence systems.
Interdisciplinary Journal of Information, Knowledge & Management, 2.
Popovič, A. H. 2012. Towards business intelligence systems success: Effects of maturity and
culture on analytical decision making. Decision Support Systems, 729-739.
Ranjan, J. 2009. Business intelligence: Concepts, components, techniques and benefits. Journal
of Theoretical and Applied Information Technology, 60-70.
Sahay, B. S. 2008. Real time business intelligence in supply chain analytics. Information
Management & Computer Security, 28-48.
Trkman, P. M. 2010. The impact of business analytics on supply chain performance. Decision
Support Systems, 318-327.
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Turban, E. S. 2011. Decision support and business intelligence systems. Pearson Education
India.
Vercellis, C. 2011. Business intelligence: data mining and optimization for decision making.
John Wiley & Sons.
Waller, M. A. 2013. Data science, predictive analytics, and big data: a revolution that will
transform supply chain design and management. Journal of Business Logistics, 77-84.
Appendix
Figure 1: Supply Chain Decision-Making Framework
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