MSS Report: Business Intelligence Systems in UK Milk Industry Overview

This report provides an analysis of business intelligence systems within the UK milk industry, focusing on content management and data mining applications. The report begins with an introduction to management principles and the role of technology in enhancing efficiency, specifically within the context of Muller Milk and Ingredients. The findings section examines the use of content management in the UK milk industry, highlighting its role in milk testing, quality control, and streamlining digital content. The report also explores the implementation of data mining in Muller Milk, detailing its positive impact on cost reduction, supply chain management, and the detection of trends. The conclusion summarizes the benefits of business intelligence in the industry, and recommendations are provided, including the adoption of advanced technologies such as vacuum systems, membrane technology, and sustainable practices. The report emphasizes the importance of monitoring milk temperature and leveraging drone technology and AI to improve operations, animal care, and product quality.

MSS – Report assessment
1

Abstract
The report has described about different types of business intelligence system that are been
used by companies operating in UK milk industry. Also, it has been analysed that how those
systems have eased its operations. Besides that, what changes have occurred due to use of
system. In addition, the e of content management in UK milk industry is explained. Along with
it, in report it has been described about use of data mining as business intelligence system in
Muller milk organization. This has impacted in positive way by increasing its efficiency and
production. Furthermore, it has enabled in providing real time data and info easily.
2

Table of Contents
Abstract............................................................................................................................................2
INTRODUCTION...........................................................................................................................4
FINDINGS.......................................................................................................................................4
Question 1........................................................................................................................................4
How content management is used in UK milk industry..............................................................4
Question 2........................................................................................................................................5
Use of data mining in Muller milk and ingredients organization................................................5
CONCLUSION................................................................................................................................6
RECOMMENDATIONS.................................................................................................................7
REFERENCES................................................................................................................................9
3

INTRODUCTION
Management is termed out as an art of getting thing done effectively and efficiently. Thus, this is
defined as set of principles that relates with function of planning, organising, directing and
controlling the things in effective manner (Roiger, 2017). To enhance managerial efficient,
technical advancement has huge role as this enables to improve working efficiency.
The present report is based on business activities of Milk industry and chosen entity is
Muller Milk and Ingredients in UK. Henceforth, report will outline analysis on content
management to analyse the working. Also, assignment will cover data mining in Muller milk and
ingredients organization.
FINDINGS
Question 1
How content management is used in UK milk industry
Content management is process that undertakes its procedures as collection, delivery, retrieval,
governance and overall management of information (Torgo, 2016). Thus, core function of the
Milk industry is to manage day to day production of milk. With help of analysis, this can be
conducted that content management aids to focus on milk testing and quality control as these
both are crucial components of milk processing industry. Hence, milk industry uses this
approach as this aids to gather, store, utilise, preserve and process the information with better
managerial activities (Leskovec, Rajaraman and Ullman, 2020). Hence, it has been also analysed
that effectiveness, efficiency, compliance and continuity all are combine in different proportion
to drive the business activities successfully.
Thus, milk industry uses the Enterprise content management as this aids to keep all electronic
files organised, enhancing collaboration and sharing. Also, this can be stated that dairy Roadmap
is a cross-industry initiative that helps to brings out together participants from entire dairy supply
chain and this is inclusive of farmers, dairy manufacturers and industry partners (Olajire, 2020).
In addition to this, British dairy industry has taken wide range of initiatives to make commitment
to set targets and to produce regular reports on the progress as this assist to reduce its
environmental footprint.
4

From the analysis, this has been identified that Around 79% of milk processed in the UK
from the 9 companies that undertakes the steps to take processing over 300 thousand tonnes per
annum (Abdulgader and Rahimi, 2020.). There are number of the milk industry in the UK that is
using the content management as this assist to undertake dairy activities in cost effective manner
and also have ease of use as this are the principles allows the business to streamline the digital
content and authoring process (Coimbra, Bathazar and Cruz, 2020). Number of the milk industry
has used content management approach in the beginning as this aids to reduce paper and
streamline filing. In this, it has been identified that Milk industries are making the use of content
management process as this assist to provide business users with procedure such as automation
capabilities that assist to reduce IT resources and costs.
Herein, Milk industries uses content management as this has wide range of several that
monitors the contribution with help of using content management system. Also, this assist to
streamlines business process. In addition to this, this has been analysed that it improves
productivity and profitability of dairy business from existing level and also assist to facilitate
unique innovative system of controlling costs and improving revenue. It has been analysed that
the use of content management aids to undertake the hygienic milking techniques and adopts
cold pressure methods by keeping bottles of milk in under enormous water pressure
(Saboyainsta, and Maubois, 2020). This is technique that aids to remove the harmful
microorganisms.
Question 2
Use of data mining in Muller milk and ingredients organization
In milk industry there are many companies that is using different types of business
intelligence system in their operations (Dual and Du, 2016). The use of system depends on needs
of companies. Data mining is a new way of extraction data from large dataset. It has enabled in
providing new info which is utilized in business decision making. However, there are large data
been stored. The data consists of customer details, product sales, operational expenses, etc. This
new tool is having various applications such as AI, machine learning and statistics.
In Muller milk and ingredients data mining is used to extract large dataset and obtain useful info.
Here, the new info is generated and then according changes are made in those areas. In this
business data mining has benefited in finding out patterns in production of milk products. With
help of it they are able to reduce almost 8- 13% cost. Apart from it, the cost incurred in SCM has
5

also decreased to 6- 8% (Dutt, Ismail and Herawan, 2017). The manager of company is able to
understand flow of data and what is relevant for business. Also, outcomes generated from it are
analysed and on basis of that quick decision are taken. Furthermore, data mining is used to detect
conception in dairy cows. Thus, they are able to find out good and poor dairy cows. It is also
useful in finding out quantity of milk produced by them, protein content in it, etc so, on basis of
it company have changed their diet. Similarly, it is analysed that MMI use data mining to
enhance revenue as well (Eldén, 2019). The data related to demand of different markets is
obtained and then evaluated. Through it, they have developed many new dairy products by
combination of various taste and flavors. It has been useful to increase profits. Along with it,
data mining is also used by company to extract large customer base data. They access data of
customer to find out change in their buying patterns and trends. By this the manager have taken
quick decision to develop new dairy products. Hence, it has helped them to retain them and
increase customer base. Basically, the organization is using data mining to increase revenue and
reduce costs within production. So, this has resulted in increasing return on investment. The new
info obtained from it is used by management in making various changes in producing bread,
butter, cheese, etc. Furthermore, use of this intelligence tool has allowed them to make effective
strategies of marketing products (Ivezić, Connolly and Gray, 2019). Also, they are able to
estimate demand and supply of various dairy products in different markets. Thus, on basis of it
organization do produce units of each product. The raw data of customer has benefited MMI to
get more about them such as needs, taste and preference, demographics and other data.
Additionally, along with data mining company is using artificial intelligence in certain areas.
Now, for complex tasks like in fragmentation, saturation, process of milk AI systems are used. It
has enabled in maintaining quality of milk. In AI systems default criteria are set on basis of
which quality of milk is measured. This has made it easy to analyse protein content in milk and
on basis of it segregating it for producing of dairy products. Alongside, AI is integrated with data
mining that has resulted in converting raw data into useful info with this it manager are able to
analyse data is more easier and effective way (Leskovec, Rajaraman and Ullman, 2020). They
are able to take more effective decision in less time and implement it without process or method.
Generally, in organization statistics related to daily operations are accessed like expenses, sales,
etc then by comparing it those stats new data is obtained. It helps in finding out area where cost
6

incurred is high and then taking decision to make changes in it. Thus, in this way almost 7- 9%
cost is decreased by Muller milk company.
CONCLUSION
From report it can be concluded that business intelligence system has enabled in bringing
ease in overall business operations. It is useful in storing lareg data in database and servers.
Moreover, the data is analysed is easier way providing useful outcomes. In milk industry content
management has provided crucial info about demand and supply of milk products in various
areas. Furthermore, all data is stored in segregated way. This has benefited in decision making.
Likewise, in Muller milk data mining is used to access data of customer and products. With help
of it they are able to reduce almost 8- 13% cost. Apart from it, the cost incurred in SCM has also
decreased to 6- 8%. Furthermore, data mining is used to detect conception in dairy cows. Thus,
they are able to find out good and poor dairy cows.
RECOMMENDATIONS
Advancement in technology assist to dairy farmers to improve quality of services. On the
basis of above report, the suggestive measure given that aids to facilitate working of Milk dairy
industry in proficient aspect. Henceforth, these are outlined in following ways as are-:
 Milk industry in the UK should have the use of vacuum system to milk their cows.
Hence, vacuums are contained in machines form in the parlour to have ease in service. It
is system that allows multiple cows to milked at the same time. These are the machines
that made with soft rubber that aids to ensure comfort of cows during milking. Therefore,
this can be stated that each cow must be milked, eat grain and have her udder cleaned and
dried while she leaves on rest.
 The milk industry should have the use of advances such as membrane technology,
techniques as microbiological and analytics testing that assist the dairy industry to
produce the new commodities and also helps to improve processing efficiency and aids to
gain greater control over manufacturing process. This has been analysed that the
analytical techniques are also continually changing as new technologies become available
in market.
 The dairy industry should adopt the sustainability as this leads to have the use of
renewable resources that allows the dairy operations to give energy to back to the grid
and have enough power to have effective use of it.
7

Henceforth, this can be stated that the technical advancement helps to dairy industry to
continually evolving with it. Therefore, the future of the technical advancement in the dairy
industry echoes the present trend. To make this use effective there is needs to have the use of
drone to scan fields, fatal recognition software and number of the cell phone application that
assist to monitor herd health’s. therefore, the farmers of Milk industry are taking continual
steps to promote a quality product, better animal care and sustainable practices as these all
plays crucial role to drive out business performance in effective and efficient mode. In
addition to this, it also can be stated that Regular monitoring and recording of milk
temperature needs to be undertaken as this is crucial for all dairy farms, Therefore, mostly
this simplified with the use of a Time Temperature Recorder that is termed out as the
automatic temperature check within the interval of each 15 minutes.
8

REFERENCES
Books and journals
Dua, S. and Du, X., 2016. Data mining and machine learning in cybersecurity. CRC press.
Dutt, A., Ismail, M.A. and Herawan, T., 2017. A systematic review on educational data
mining. Ieee Access, 5, pp.15991-16005.
Eldén, L., 2019. Matrix methods in data mining and pattern recognition (Vol. 15). Siam.
Ivezić, Ž., Connolly, A.J. and Gray, A., 2019. Statistics, data mining, and machine learning in
astronomy: a practical Python guide for the analysis of survey data. Princeton University
Press.
Leskovec, J., Rajaraman, A. and Ullman, J.D., 2020. Mining of massive data sets. Cambridge
university press.
Olajire, A.A., 2020. The brewing industry and environmental challenges. Journal of Cleaner
Production, 256, p.102817.
Abdulgader, M. and Rahimi, Z., 2020. Performance and kinetics analysis of an aerobic
sequencing batch flexible fibre biofilm reactor for milk processing wastewater
treatment. Journal of Environmental Management, 255, p.109793.
Coimbra, P.T., Bathazar, C.F. and Cruz, A.G., 2020. Detection of formaldehyde in raw milk by
time domain nuclear magnetic resonance and chemometrics. Food Control, 110,
p.107006.
Saboyainsta, L.V. and Maubois, J.L., 2000. Current developments of microfiltration technology
in the dairy industry. Le Lait, 80(6), pp.541-553.
Roiger, 2017 Torgo, 2016Leskovec, Rajaraman and Ullman, 2020 Olajire, 2020 Abdulgader and
Rahimi, 2020 Coimbra, Bathazar and Cruz, 2020 Saboyainsta, and Maubois, 2020.
9