Data Insight for Business Decisions: A Manufacturing Industry Analysis

This report examines the pivotal role of data insights in the manufacturing industry, emphasizing its impact on business decision-making. The introduction highlights the significance of data in understanding market trends and reducing business risks. The study explores the role of information in manufacturing, including its use in product tracking, understanding customer needs, and adapting to technological advancements. It delves into the types of data used, such as first, second, and third-party data, and how these are utilized in day-to-day operations. The report also covers data capture and storage methods, including DATAMARK and ERP systems, and provides examples of how data drives business decisions, such as in supply chain management and talent acquisition. Furthermore, it explores the use of primary and secondary market research in conjunction with Management Information Systems (MIS) and databases to enhance insights and inform strategic planning. The conclusion reinforces the importance of data as a critical element in the manufacturing sector, driving informed decision-making and overall business success. The report emphasizes the benefits of data-driven decision-making, including improved customer satisfaction, optimized operations, and a competitive edge in the market. This analysis provides a comprehensive overview of data insights in the manufacturing industry, demonstrating the value of data-driven strategies.

Data Insight for business
decisions

Table of Contents
INTRODUCTION......................................................................................................................2
Role of information and data within manufacturing industry................................................2
Type of data used by organization.........................................................................................3
Presenting how information is used within day to day operations.........................................4
How data is captured and stored............................................................................................4
Presenting example of how data is used to deliver insight for business decision making.....5
How market research secondary and primary studies used in conjunction with MIS...........6
CONCLUSION..........................................................................................................................6
REFERENCES...........................................................................................................................7

INTRODUCTION
Data insights are the knowledge which a firm gain by determine range of data within
specific situation. In the same way, current study main aim is to determine the importance of
data within an industry. With the help of this, reader provides an insights that assist business
to make decision and also reduce chances of risk. The entire study will based upon
manufacturing industry because it is a fastest and developing industry that keep coping with
new changes. Further study will determine the role of information within selected industry
and examine how data used to successfully implement day to day operations. Moreover,
study will provide different examples of how data is used to deliver insight for business
decision making and examine how market research primary and secondary studies used in
conjunction with MIS.
Role of information and data within manufacturing industry
Information play big role in manufacturing such that it assist to execute the operations
within industry successfully. Hence, the importance are as mention below:
Assist manufacturers to trace product: Information provides exact product details to
manufacture industry and an ability to track exact location of their product as well. Also, with
the help of correct information, industry manufacture the products and supply the same to
customers as well (Dubey and et.al., 2020). That is why, information plays an important role
in success of manufacturing industry. Beside this, data assist to identify the market needs and
this in turn satisfy the wants of users too.
Helps in determine the customer needs: Once the companies operate in
manufacturing industry identify the market needs, they tries to develop same product which
are needed by customers. Earlier there is no proper information provided to manufacturing
industry and that is why, companies are not successfully meet the needs. But with emerging
modern era, companies relies upon advance technology and collect information that assist to
examine demand. For example, most of the pharmaceutical companies are manufacturing
vaccine of COVID-19 because it’s a need of customers and they collect information through
news channel. Thus, it reflected that information play big role in manufacturing industry.
Aid manufacture to comply with advance technology: In modern era, companies are
trying to meet the demand of market and for that adhere advance technology which in turn
assist to measure quality (Chakphet and et.al., 2020). Such that big data analytics are useful

because it provides crucial information about any fluctuation within process of development
and ensure that produces developed by company are meet with quality metrics or not. Hence,
it is reflected that industry is transforming with the help of technologies and even business
realize the importance of innovation in their workplace.
Better insights: When manufacturing industry collect data, they easily access to
information and make improvements as well (Big data in manufacturing, 2020). Therefore, it
will assist to observe trend in production and labor time and minimize strategy as well as
business risk throughout operations.
Type of data used by organization
There are three type of data used by the organization operating in manufacturing
industry such that:
 1st party data: It means organization collect information by their own directly from
audience or customers. This further includes data from behavior, action or interest that
demonstrated across website. It further include non- online information like collect
customer feedback which will be stored in CRM database (Dubey and et.al., 2016). It
is consider the best source of information which provide correct insight to make better
decision for the business. This method is used by the company because it has less
chance of error and easy to collect information while others are not.
 2nd party data: It is similar to first party data, but it requires to seek out companies
with data which they need. For example, company falls under manufacturing industry
uses this data through activity on website, mobile app usage, social media etc. The
data collected from this source are more precise than others. So it can be stated that
with the help of this data, company reach to new audience and increase the scale of a
data as well.
 3rd party data: It is the information which company buy from other source but are not
original collectors of that data. Among all, The Lotame Data Exchange is one of the
largest 3rd party data exchange in world who support most of the company to collect
the information and make decision accordingly (Henning and et.al., 2020). This type
of data happens rapidly and at large scale, but the chances of accuracy and correctness
is lower in this type as compared to others. Through this organization enhance the
first party data and reach to new potential customers. Overall it assist to increase the
precision of targeting and leads to reach wide audience as well.

Presenting how information is used within day to day operations
Manufacturing companies are realizing the importance of data collection in order to
remain competitive within industry. As a result, it assist to improve the business process and
transform business models which rely on data collection. That is why, the companies
increases their investment and also shift their focus to solution providers in order to get best
solutions. Organization within manufacturing industry uses real time and shop floor data
along with sophisticated statistical assessment. In addition to this, data are also used to
improve the customer satisfaction (Cui, Kara and Chan, 2020). For that 1st party data are used
in which they make direct contact with audience and tries to identify the needs which will
further execute in operations. Beside this, 1st party data accuracy and relevance also allow to
predict future pattern which helps to perform operations successfully. On the other side, HR
of the company also uses this data type in which they offer personalize content and
advertisements that keep attract customers and meet the demand.
Therefore, these data type assist the companies to examine opportunities in order to
increase the production yield. For example, the biopharmaceutical manufacturing company
produces hormones, vaccines and blood components which in turn leads to final product. For
that, company needs accurate information which help to develop vaccine accordingly. Hence,
it can be stated that with the help of effective data type most of the companies improved their
day to day operations which in turn assist to meet the define aim of a company (Gunasekaran
and et.al., 2018). Also, some information show the cause of variable and change its process as
well in order to eliminate the waste and reduce production cost too.
How data is captured and stored
Capturing and storing the data in most of the companies are consider a difficult task.
But with emerging advance technology, there are numerous ways that provide new insights to
business. Also, data capture is crucial to improve customer product interaction by improving
brand and company profit (Fang and et.al., 2020). Therefore, in manufacturing industry,
DATAMARK offers technology solution for capturing data and secure customer information
as well. This also assist to stored necessary information and saves company from costly
impacts of data breaches which in turn provides customers a feeling of security as well.
Moreover from shipping order to inventory, many facets of manufacturing enterprise
creates lot of form. That is why, there is a need to have enough knowledge of database and
information system which in turn leads to handle sensitive data. So, with the help of installing

DATAMARK as a software and an experienced management helps to take a business at
success level (Li and Mao, 2020). In addition to this, Enterprise Resource Planning (ERP)
system is another information management system which help in stored data in
manufacturing industry, as most of the companies are uses the same. This system consist
functions like accounting, HR and financial system which in turn increase quality and
efficiency and support company to make decision.
Beside this with reference to database in manufacturing assist to manage the parts,
components and inventories. As it store large amount of information that is needed to provide
accurate data for efficiency, automation and quick decision making in manufacturing process.
Similarly, supply chain database is the ecosystem which is used to provide the information
with regards to manufacturing process. Also this database is used to maintain efficiencies in
order to grow and maintain competitive advantages as well.
Presenting example of how data is used to deliver insight for business decision making
Data assist companies to make better decision for the company and retain the
customers as well. Research also reflected that data centered organization are 23 times more
likely to acquire customers and retain their customers with an aim of profit generation (Tao
and et.al., 2018). For example, TVS, Honda Motors uses data in order to deliver for business
decision making because it helps to improve manufacturing and ensure that there is a better
quality assurance as well. Also with the help of correct information, company is able to
manage the supply chain and evaluate if they face any risk.
In addition to this, data also improve the way organization attract and retain talent and
this is possible if a company have enough information which in turn assist to make decision
better. For example, consulting group decided to undergo a major restructuring process in an
University. For that, company have to identify the best employees which is possible with the
help of data. The team of a firm begun by streamlining data point like professional history,
education background, age and demographics which help to identify the best employees who
suit in their roles (Chang and Lin, 2019). Thus, it is clearly reflected that data provides detail
insights to the company which help to make better decision for the welfare of a firm.
Moreover, with the help of this data, manufacturing company identify the unfold customer
trend and interpret the business performance as well which in turn assist to gain competitive
edge within market.

How market research secondary and primary studies used in conjunction with MIS
Both primary and secondary research assist to increase insights with the help of MIS
and database. Such that manufacturing industry uses 1st type data in which company collect
fresh information from customers and this data are stored with the help of MIS and database.
Also with the help of effective primary research, company determine exact information and
through secondary research, manufacturing company determine the how trend is changes
from last year and now company comply with advance technology in order to meet the
demand of customers (Lin and Chen, 2019). In the same way, with the help of MIS and
database system, company keep trying to store the data in confidential manner. Such that
there are range of software installed within companies which in turn lead to organize the data
in better manner. Like ERP that assist manufacturing industry to prevent the date from third
party.
In addition to this, with the help of MIS and database, both primary and secondary
research assist companies to make decision for the welfare of a firm. Also, by combining the
same with Management Information system, company’s manager determine the exact report
and plan accordingly to meet the define aim. Also both studies tries to increase insight and
provides a broader view to generate the best results which in turn leads a business towards
further level of success.
CONCLUSION
By summing up above report it has been concluded that data or information consider
important element within Manufacturing industry. Such that they keep connected overall
function and provide better insights to business in order to make decision better for the firm.
Further study concluded that there are three main type of data used by organization operating
within manufacturing industry such that 1st, 2nd and 3rd party data. Moreover it is also examine
that with reference to MIS and database, entire data are stored and captured in proper manner
that lead to generate best results. Apart from this, with the help of correct information,
company take business decision which in turn lead a business at further level of success
within manufacturing industry.

REFERENCES
Books and Journals
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Collaboration Types, Supply Chain Management and Market Performance of Thai
Manufacturing Firms. International Journal of Supply Chain Management. 9. pp.28-
36.
Chang, V.I. and Lin, W., 2019. How Big Data Transforms Manufacturing Industry: A
Review Paper. International Journal of Strategic Engineering (IJoSE). 2(1). pp.39-
51.
Cui, Y., Kara, S. and Chan, K. C., 2020. Manufacturing big data ecosystem: A systematic
literature review. Robotics and computer-integrated Manufacturing. 62. p.101861.
Dubey, R. and et.al., 2016. The impact of big data on world-class sustainable
manufacturing. The International Journal of Advanced Manufacturing
Technology. 84(1-4). pp.631-645.
Dubey, R. and et.al., 2020. Big data analytics and artificial intelligence pathway to
operational performance under the effects of entrepreneurial orientation and
environmental dynamism: A study of manufacturing organisations. International
Journal of Production Economics. 226. p.107599.
Fang, P. and et.al., 2020. Data analytics-enable production visibility for Cyber-Physical
Production Systems. Journal of Manufacturing Systems. 57. pp.242-253.
Gunasekaran, A. and et.al., 2018. Agile manufacturing practices: the role of big data and
business analytics with multiple case studies. International Journal of Production
Research. 56(1-2). pp.385-397.
Henning, S. and et.al., 2020. Goals and measures for analyzing power consumption data in
manufacturing enterprises. arXiv preprint arXiv:2009.10369.
Li, L. and Mao, C., 2020. Big data supported PSS evaluation decision in service-oriented
manufacturing. IEEE Access. 8. pp.154663-154670.
Lin, B. and Chen, Y., 2019. Will economic infrastructure development affect the energy
intensity of China's manufacturing industry?. Energy Policy. 132. pp.122-131.
Tao, F. and et.al., 2018. Data-driven smart manufacturing. Journal of Manufacturing
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Online
Big data in manufacturing. 2020. [Online]. Available through:
<https://www.mckinsey.com/business-functions/operations/our-insights/how-big-
data-can-improve-manufacturing>.