Importance of Information Flow in Supply Chain Management

This article discusses the importance of information flow in supply chain management, the five significant information flows in the supply chain, and how organizations can improve information gathering. It also covers the current trends and future practices in data analytics and ethical considerations in the use of customer data.

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Supply Chain
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Introduction
There are many different expressions that are used in defining supply chain management
(SCM). However, the best of these expressions define supply chain management as the
comprehensive systematic approach that is used in managing the flow of money, information, as
well as materials between the consumer and the supplier. Understanding supply chain
management is crucial in understanding how a business functions. Nonetheless, SCL also deals
with the coordination along with the integration of processes and among organizations. Supply
chains are dependent on accurate and timely flow of information. This helps in determining the
levels of raw materials and finished goods, production, and logistics positions, as well as the
positioning of products within the supply chain among other related things. Organizations are
considering the importance of information flow in a supply chain and are trying to improve it
using RFID and EDI. A deeper analysis of supply chain management will be conducted to
identify the importance of information flow in SCM.
Importance of Information Flow
Information flow is very critical to the performance of SCM since it offers a ground on
which managers can make decisions. Information Technology comprises of tools that are used in
analyzing information and executing on it with the intention of improving the supply chain’s
performance (Cannella, Framinan, Bruccoleri, Barbosa-Póvoa and Relvas, 2015, pp.122). Hence,
information is crucial in making wise decisions.
Nonetheless, information flow is important because it acts as a glue that facilitates the
working together of the supply chain drivers with the primary objective of developing a supply
chain that is integrated and coordinated. The SCM depends on information since it offers a firm

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foundation which facilitates the execution of transactions. Deficiency of this information makes
it impossible for managers to know what the customers want or the amount of inventory in stock
(Janvier-James, 2012, pp.196). Generally, information is important because it assists in making
wise decisions within the supply chain, both at the strategy, planning, and operations levels of
decision-making.
Information flows in a supply chain comprise of:
Production flow: It is important in operations planning because it helps manage the
movement of goods from supplier to consumer and deals with the needs of the customers.
Financial flow: it is important during operations planning because it includes credit terms
and payment schedules.
Information flow: It is important because it deals with transmitting orders as well as
updating the delivery status.
Value flow: Is important in assigning costs, revenues, and asset values on products.
Risk flow: Is important in determining the potential risk that might affect the supply
chain, both internal and external risks.
Improving Information Gathering
Globalization has impacted organizations and forced them to change their ways of
communication by implementing the technology. Organizations have also enhanced diversity
and shaped their business performance by improving their information technology application in
their supply chain management (Lotfi, Mukhtar, Sahran and Zadeh, 2013, pp.302). This has
improved through information gathering and exchange which has enabled them to forecast for

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future and improve accuracy. The first information technology that has been developed by
organizations to improve accuracy and forecast is the distribution requirement planning. This is a
management procedure that provides a connection between operations and transportation
requirements that makes sure that the supply chain will be able to meet demand (Prajogo and
Olhager, 2012, pp.516). This form of information technology applies the time-based logic to
restore inventories in warehousing systems. Moreover, DRP assists in planning major resources
in a distributions channel such as financial flaw and transport capacity. This form IT assists the
organization to forecast for the future needs and it also improves the accuracy of the supply
chain.
Another type of information system used by the organization to enhance accuracy is the
marketing information system. This system enables organizations to manage a large amount of
data that they have at hand. This information may be important to the managers in making
important decisions (Piotrowicz and Cuthbertson, 2014, pp.11). The marketing information
system records internally produced reports and data, gathers market intelligence on an ongoing
basis, records marketing research information, and assists managers in decisions making. An
organization generates a lot of information such as accounting, sales, and inventory (Chan, He
and Wang, 2012, pp.560). Therefore, organizations constantly gather treated to websites and the
number of people who visit and device ways to attract more.
Ethical Consideration
Marketing research has experienced a revival with the wide use of the internet and social
media networks. This has made it easier for an organization to connect with customers and
gather data which is fed into the computer database and be aligned with other pieces of

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information collected during unrelated transactions (Wu, Cegielski, Hazen and Hall, 2013,
pp.29). However, the way organizations conduct their market research comprises of many
serious ethical consequences hence affecting the lives of consumers in ways yet to be fully
understood. The first ethical consideration facing the organization is the use of deceptive
practices. The methods that most organizations use to gather and access data about its consumers
can result in deceptive practices and lack of honesty in the organization’s research methods. This
kind of ethical issue may affect the organization. The searchers have no right to coerce and
pressurize the consumer to respond to a particular answer (Brandenburg, Govindan, Sarkis and
Seuring, 2014, pp.301). On the other hand, the company might use deceptive techniques such as
sugging. This refers to the act of selling under the aspect of research. This happens where
salesperson approaches an individual and asks questions using the phone. As they do their
inquiries in the name of research, they will gain information about potential sales or influencing
the person to develop a bias about a certain product.
Another ethical consideration facing organization is the breaching of confidentiality.
Organizations often share information about customers with affiliates and partners. Besides,
some organizations sell data which they have collected on customers to outside form. This is
ethically wrong since it breaches the confidentiality of the consumer. Invasion of privacy is also
an ethical issue that companies are facing (Irizarry, Karan and Jalaei, 2013, pp.252). Most
organizations have an unrivaled ability to collect data, store, and match data relating to
customers that can violate an individual’s right to privacy. In many cases, the consumers or
customers do not have a clue the extent of the firm’s filtration into their lives. The organization
uses this data to reach out to the customer with targeted advertising. However, the process of the
target may pose a chilling impact on personal freedom.

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Current Trends and Future Practices
The manner in which data analytics is manifesting within organizations is undergoing a
lot of revolution. Hence, this is resulting in the development of new data analytics methods such
as DataOps as well as other hybrid solutions such as IoT analytics. Current trends in data
analytics include:
IoT Analytics: Internet of Things is among the most disruptive technology that is being
adopted in the modern workplace. The Internet of Things devices are capable of getting
connected via a network and may comprise of smart lighting and health monitors (Li, 2012,
pp.62). By 2020, it is estimated that there will be over 20.4 billion Internet of Things devices.
Augmented Analytics: Augmented analytics are expected to dominate in business
intelligence, embedded analytics, and analytics as well as data science. The technology is
disrupting the business intelligence industry because it seeks to lower the entry barriers into the
industry (Kambatla, Kollias, Kumar and Grama, 2014, pp.2564). Augmented analytics is
effective in assisting data scientists to automate processes associated with preparing and
analyzing data along with building models.
Data Ops Data Analytics: transformation in data analytics is not only changing the use of
data but also the methodology. DataOps methodology is being utilized in combining together
DevOps teams and software engineering (Chen, Shih, Shyur and Wu, 2012, pp.2548). Using
DataOps, organizations are able to build data analytics platforms with ease.
However, as the government steps in to monitor the use of customer data in
organizations, the new legislation will reduce the potential abuse of customer data, and will
decrease gathering of data (Nunan and Di Domenico, 2013, pp.509). The constant pursuit and

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use of data affect a person’s privacy and confidentiality. As a result, for instance, Europe’s
General Data Protection Regulation recognizes the dangers and attempts to control the
commercial use of sensitive as well as private data (Kshetri, 2013, pp.379). As a result,
organizations along with data analytics will be required to put in place processes, including
internal records to ensure that they comply with these regulations. In addition, organizations will
be entitled to inform their clients within 72 hours of any kind of breach that is likely to put their
individual rights and liberties in danger (Wixom, et al., 2014, pp.9). Nonetheless, companies will
only be required to gather data that is only necessary to their business (data minimization) as
well as limiting access to personal data only to individuals required to process it.
Conclusion
There have been many advances that have taken place in the supply chain of any
organization due to globalization. This has led current trends and future practices in the supply
chain such as IoT analytics, augmented analytics, and Data Ops Data Analytics. Many
organizations have advanced their technology to ease the complex procedure involved in
gathering data and exchanging information for accuracy and forecasting. Organizations have
incorporated IT systems such as distribution requirement planning and management information
system. This IT systems have improved speed and accuracy and assisted organizations to
anticipate future demands in the organization. Moreover, there are five significant information
flows in the supply chain which include production flow, information flow, financial flow, value
flow, and risk flow. Despite the current practices and many innovations in the supply chain, there
are various ethical considerations that are facing organizations in their use of customer data to
predict the behavior of customers and plan to future demand. The ethical consideration includes
the use of deceptive practices, invasion of privacy, and breaching of confidentiality.

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