PROJECT REPORT
ON
A STUDY ON SUPPLY CHAIN ANALYTICS AT MILMA
BY
SITARA K
1NZ19MBA53
Submitted to
DEPARTMENT OF MANAGEMENT STUDIES
NEW HORIZON COLLEGE OF ENGINEERING,
OUTER RING ROAD, MARATHALLI,
BENGALURU
In partial fulfilment of the requirements for the award of the degree of
MASTER OF BUSINESS ADMINISTRATION
Under the guidance of
Dr. PRIYAMEET KAUR KEER
ASSOCIATE PROFESSOR
2019 - 2021
CERTIFICATE
This is to certify that SITARA K bearing USN 1NZ19MBA53, is a bonafide student of Master
of Business Administration course of the Institute 2019-21, autonomous program, affiliated to
Visvesvaraya Technological University, Belgaum. The project report on “A Study on Supply
Chain Analytics at Milma” is prepared by her under the guidance of Dr. PRIYAMEET
KAUR KEER, in partial fulfilment of requirements for the award of the degree of Master of
Business Administration of Visvesvaraya Technological University, Belgaum Karnataka.
Signature of Internal Guide Signature of HOD Signature of principal
Name of the Examiners with affiliation Signature with date
1. External Examiner
2. Internal Examiner
Date: 19th April 2021
TO WHOM SO EVER IT MAY CONCERN
This is to certify that Ms. SITARA K (1NZ19MBA53), a student of MBA, New Horizon
College of Engineering, Bangalore has successfully completed 2 months (22 Feb 2021 to 16
April 2021) internship program at Milma.
The project that she worked was on “A STUDY ON SUPPLY CHAIN ANALYTICS AT
MILMA”. During her internship, Ms. SITARA K has been meticulous, diligent, inquisitive
and has shown leadership qualities.
We wish her all the best in her future endeavors.
Sincerely,
Shalini Jose
Business Associate
MILMA Kerala Co-operative Milk Marketing Federation Ltd., "Milma Bhavan", Pattom Palace P.O, Thiruvananthapuram-695 004. Kerala – India Email: [email protected]
Phone: +91-471- 2786400-448
DECLARATION
I, SITARA K, hereby declare that the project report on “A Study on Supply Chain Analytics at
Milma” prepared by me under the guidance of Dr. PRIYAMEET KAUR KEER, faculty of
M.B.A Department, New Horizon College of Engineering.
I also declare that this project report is towards the partial fulfilment of the university
regulations for the award of the degree of Master of Business Administration by Visvesvaraya
Technological University, Belgaum.
I have undergone an industry project for a period of Twelve weeks. I further declare that this
report is based on the original study undertaken by me and has not been submitted for the award
of a degree/diploma from any other University / Institution.
Signature of Student
Place:
Date
ACKNOWLEDGEMENT
The successful completion of the project would not have been possible without the guidance
and support of many people. I express my sincere gratitude to SHALINI, BUSINESS
ASSOCIATE, MILMA for allowing to do my project at MILMA.
I thank the staff of MILMA, Kerala for their support and guidance and helping me in
completion of the report.
I am thankful to my internal guide Dr. PRIYAMEET KAUR KEER, for her constant support
and inspiration throughout the project and invaluable suggestions, guidance and also for
providing valuable information.
Finally, I express my gratitude towards my parents and family for their continuous support
during the study.
SITARA K
1NZ19MBA53
TABLE OF CONTENTS
SL. NUMBER CONTENTS PAGE
NUMBERS
1
Executive summary 1
2
Chapter 1- Theoretical Background of The
Study 2 - 29
3
Chapter 2- Industry Profile & Company Profile 30 - 50
4
Chapter 3- Research Methodology 51 - 56
5
Chapter 4- Data Analysis and Interpretation 57 - 73
6
Chapter 5 - Summary of Findings, Suggestion
and Conclusion
74 - 90
7
Bibliography
8
Annexure
1 | P a g e
Executive Summary
This report is a study of Supply Chain Analytics at Milma based on a project that I have
successfully completed as a Business Analyst from 22.02.2021 to 16.04.2021.
The objective of the research is the applicability of supply chain analytics to the logistics at
Milma and using the data from it to create simple and dynamic dashboards to help the company
take necessary steps needed to improve the efficiencies in logistics. Thus, leading to faster and
leaner logistics processes at Milma. It also improves the trackability and clarity related to the
movement of the products.
Supply chain data was analyzed to produce powerful dashboards for procurement and sales at
Milma using Power BI. The dashboards consist of procurement and sales information of Milma
in the three main regions. Milma can make use of this model to find data points where sales
are less, find solutions for it using better marketing strategies and methods to increase sales in
that particular region. Milma can ensure that the products are tracked in a timely manner by
utilizing this model extensively, with live updates reflected on the dashboards.
This project work gave me an opportunity to learn Power BI and other aspects related to
logistics. The models created can be used for data visualization by offering highly interactive
and personalized views according to the needs of Milma.
Some of the study's recommendations include training Milma employees through workshops
on how to handle the newly implemented technologies with ease, making it easier for them to
understand the actual working and troubleshoot problems efficiently. Right management of the
dashboards that are created can be used to take rational decisions, to redesign the chain to
increase the value in logistics and to improve the overall supply chain at Milma, which in turn
can increase the profitability.
3 | P a g e
Introduction
A supply chain is said to be a system of entities, events, services, people, and technology
associated with the manufacture and distribution of a good. Anything from the shipment of raw
materials from a supplier to the manufacturer to the final delivery to the end consumer is
included in a supply chain. The supply chain sets out all facets of the manufacturing process,
such as the tasks that take place at each point, knowledge that is shared, raw materials that are
converted into useful products, personnel, and other factors that go into the end product.
Analytics refers to processing data to draw important conclusions, to better make decisions.
The information age consists of data that is well provided for and aligned to our needs. About
all that a business does today is determined in one way or another by data and analytics.
Advanced analytics methods are used by businesses to expand limits of operations, reduce
costs, find various advancement opportunities, and devise competent budgets. Analytics uses
data and mathematics to address business questions, to identify associations, to forecast
unpredictable effects, and to simplify decision making. Based on applied mathematics,
analytics, statistical modelling, and machine learning methods, this broad field of computer
science is used to discover concrete data correlations and uncover new insights.
Supply Chain
Supply chain consists of the tasks that is needed by an enterprise to distribute services and
products to the customers. It concentrates on the functional areas within a company necessary
to transform unprocessed resources to end products and services.
Supply chain can be a product-based supply chain or service-based supply chain. When the
supply chain of a company links with the supply chain of vendors and distributors it leads to
the formation of a supply chain network. This network helps to get a better understand and
monitor the movement of resources and expertise.
The need for a company to figure out its supply chain is necessary during the external review
in the pre planning stage. It helps the company to understand its business and where it would
like to see itself in future.
The basic steps of supply chain are procurement of raw materials, conversion into primary
portions, assembling the parts to create the final product and delivery of the goods to the
customer.
4 | P a g e
Supply Chain Challenges
Insufficient clarity
The supply chain is often complex and tough to comprehend. Thus, making it difficult
to record and arrange for the shifting of products. Without achieving clarity in this the
demand forecasting will be problematic. Excess of products produced leads to
increased amounts of waste and deficit of products produced causes failure to meet the
demands.
Lag or misplacement of products
Lack of proper follow up and traceability of the products leads to unnecessary lags and
misplacement of products. Thus, in turn affecting the delivery of the products to the
end user. Leading to unhappy customers due to badly maintained relationships with
them.
5 | P a g e
Optimization of Supply Chain
Optimization of supply chain increases the ability and efficacy of the supply chain network
using the technical knowledge from Artificial Intelligence, Blockchain and Internet of Things.
Supply chain is an important aspect in any business as it helps to attain good customer relations.
Optimization can be achieved in 3 steps:
Designing of SC
In this step the main job is to develop an efficient supply chain network which involves
deciding the locations at which the warehouses can be so that the logistics process
works smoothly.
Planning of SC
It involves creation of an effective supply chain routing protocol, stock storage planning
and easy flow of information between all parties involved in the supply chain so as to
achieve a symmetry between supply and demand.
Execution of SC
It involves the administration of the warehouses, procurement centers and timely
delivery of the products so as to satisfy the customer needs and wants.
Importance of SC Optimization
Agile
Due to the ever-changing customer needs and demands, to match a competitor’s level of
production or to deal with supply disturbances, there is a need for the supply chain to be agile
to keep up to such requirements.
Competitive Edge
Optimization of supply chain acts as one of the main aspects to achieve competitive edge as it
helps to align many processes which helps in making the overall process of supply chain easier.
Sustainability of SC
As customers are becoming more cautious about the environment and the impacts of supply
chain on the environment. The customers are interested to know if the product are produced in
a vital and ethical manner.
6 | P a g e
Supply Chain Management
Supply chain management is the management of movement of products or services beginning
from the procurement of raw materials to the distribution to the customer. A business has a grid
of contacts which include providers of raw resources to those who sell the products directly to
the end consumers. A good supply chain decreases producers and vendors excess stock pile up
and it also results in reduction of cost in terms loss due to excess produce, warehousing costs
and so on. An effective supply chain can be achieved by implementing lean processes. The
time involved in the supply chain process can be reduced by taking necessary steps to make or
buy products, or by outsourcing certain tasks to professional companies.
7 | P a g e
Segments of SCM
Planning the process
The first step in supply chain management is planning, it is considered as one of the most
crucial steps in supply chain management. A company needs to decide the number of resources
that would be needed to meet the demands. For a company to have a good supply chain it has
to do proper planning so as to meet the objectives.
Sourcing of raw resources
Businesses need to establish relationships with the providers of raw resources which are needed
to make the end product or service that has to be provided. This step involves many actions
like placing order for the materials, obtaining the materials, managing the stock and handling
the financial transactions with these vendors.
Making the end product
During this step the products are produced from the raw materials. The goods are then put
thought various quality checks to make sure it satisfies all the quality standards that are
mentioned. On successful completion of the checks the products are packaged and sent out for
delivery.
Delivery of the goods
The delivery of the finished goods is usually carried out by the logistics section of supply chain
management. The main duties include organizing the goods that should be heading out for
deliveries, sending out the products, handing out of bill of sale to customers and collecting the
payments for the goods sold. Delivery of products can also be outsourced to other professional
logistics companies. Different means of transport can be used for delivery of goods.
Return of products
This in step the product is sent back to the company from the customers end due to some errors,
imperfections which leads to the customer not being satisfied with the received product. A
company should have a good back logistics network for the smooth working of the return
process.
8 | P a g e
Analytics life cycle
The first prerequisite for any analytics project is data, no matter what you want to do with
analytics. Next, you need to evaluate the data until you have information. And then you need
to execute the findings of the research to guide decision making. Each process is ready for a
change in the analytics process. The quicker companies can progress across the analytical life
cycle, the quicker their investments in analytics can acquire real profit.
The steps of the analytics life cycle are: Data, Discovery and Deployment
Data
Data today is large, agile and complicated. Analytics applications, including conventional
standardized data and new technologies, such as streaming sensor information, pictures and
videos, have to process data of any type. Data management technique is required to access,
plan, clean and control the data. An advanced analytics framework streamlines data processing
with native access engines, built-in data consistency and data preparation tools that simplify
time-consuming activities with Artificial Intelligence. Data governance means that the data can
be reliable, since you know the origins and content and can track the accuracy of the data. It is
also possible to safeguard information where it is necessary.
9 | P a g e
Discovery
Discovery is about experimentation, visualization, and the creation of models. Finding a
suitable algorithm is always a trial-and-error operation. Selecting the perfect algorithm is based
on a number of facts like data size, business requirements, training period, variables, data
points, and more. Even the most professional data scientists, before testing with several
methods, cannot tell you which algorithm would work the best. In reality, comparing various
models coded in a different programming language with different data properties is normal in
the discovery process. This collaboration method works well where data scientists with diverse
skill sets are able to write programs in the language of their choice and non-programmers can
use a simple point-and-click interface to test the effects of various analytics approaches.
10 | P a g e
Deployment
Analytics efforts will be fruitful only if you execute and use the results of your observations.
Machine learning and other models are intended to be used accurately to get the right market
value. But the process of deployment is where most companies are suffering the most.
Designing a single model or thousands, it takes model management to switch from choosing
models to deploying models. Model management allows you to register, test, and maintain your
models centrally. The aim should be to develop models and deploy them everywhere, to
executive dashboards, straight into operating systems, or embedded into other software using
APIs.
11 | P a g e
Classification of Analytics
Descriptive
Descriptive analytics is a category of analysis focused on capturing and summarizing raw data
for simple understanding. In general, historical data is the subject of descriptive analytics,
including the framework which is important for interpreting facts and statistics. The area is
applied in a multitude of sectors, and uses, from inventory management to benchmarking
annual earnings and sales, and can serve a wide range of purposes. In the business intelligence
method, the field typically serves as a preliminary stage, providing a framework, for further
study and understanding. Descriptive analytics usually finds answers to what occurred, without
doing the more complicated analysis involved in diagnostics and predictive models.
Descriptive analytics is typically the first step in business intelligence, which can result in
visualizations such as pie charts, line diagrams, bar charts, and other simplified graphical
displays.
12 | P a g e
Predictive
Predictive analytics is a type of analytics that predicts events, actions, and patterns using both
recent and historical data. It requires the application of data sets of mathematical analysis
methods, descriptive queries, and automatic machine learning algorithms to develop models
that are predictive which tells the feasibility of the happening of an event by giving a
quantitative value. It has large search engines and online service providers which is widely
adopted by marketing, financial services, and insurance companies. Industries such as
healthcare, retail, and manufacturing also commonly use predictive analytics. Uses of
predictive analytics include analyzing online advertisements, monitoring consumer behaviour
to assess purchase habits, flagging potentially irregular financial purchases, recognizing
patients at risk of contracting specific medical problems, and predicting imminent system
defects before they occur in industrial machinery.
Prescriptive
Beyond the past insights of descriptive analytics and the probable future results of predictive
analytics, prescriptive analytics offer suggestions for the next steps that can be taken. Based on
the effects that come from simulating multiple future situations, businesses will analyze and
settle on a variety of alternatives. It takes the predictive analytics predictions and possibilities
a step forward by developing informed strategies that will still comply with the primary
elements of the company’s objective. Every enterprise wants to be efficient and prescriptive
analytics provides the potential to seize resources and have an upper hand in successful
decision making. It offers greater insights into whether such events can arise such that as new
steps are taken, associated causes can be tracked.
13 | P a g e
Business Analytics
Data related to organizations are gathered, organized, stored and studied about by utilizing
repetitive methods and calculation systems to convert the information into useful content for
businesses, this is what business analytics deals with. To increase effectiveness, determine
which information has value, find ways to resolve problems and so on can be considered as the
purposes of business analytics. Business intelligence is a part of analytics that is associated
with the need to find suitable content.
Business analysts all use precise data, technical analyses, and statistical modelling to create
solutions for data-driven challenges. Analytics, science that deals with calculations, content
models and transactional study are used by deep learning, composite group of data and artificial
intelligence to find out the tendencies that data follows. In order to reliably forecast potential
events linked to customer action or industry patterns, the accessible data and trends can be
leveraged to suggest measures that will direct consumers towards the desired target.
Components of Business Analytics
Data Aggregation
In order to prevent replication, data must be collected, organized, and cleaned until it can be
analyzed, and screened to delete incorrect, missing, and obsolete information. Sales,
transportation, finance and other data of business comes under business records. Data collected
from the customers or mediators directly through hard copies or soft copies, this is known as
volunteer information. Thus data is accumulated using volunteer and business records.
Data Mining
Sequence and flow that was not identifiable before can be found by drilling through data using
models. Data mining utilizes many computational methods like classification, regression, and
clustering. Classification is a process used to sort and group data when parameters like
demographics are known. Regression is a feature used, based on interpreting historical trends,
to forecast continuous statistical values. Clustering is a system in which unlabeled data is used,
14 | P a g e
and it is the technique of grouping together identical objects and then creating groups with the
clustered data.
Association and Sequence
Consumers execute identical practices at the same time or sequentially perform similar
activities. Patterns such as association and sequencing may be revealed by data.
Text Mining
Companies accumulate textual content to derive useful relationship metrics from community
channels, journal put ups and written information from tech support teams. This knowledge
will be used to produce new goods on demand, enhance customer service and experience, and
review the success of competitors. This method of obtaining data is called text mining.
Forecasting
Through evaluating processes that occur over a given time or season, a prediction of potential
events or activities based on historical data may be generated.
Predictive Analytics
Predictive business analytics employs a number of computational approaches to construct
predictive models that collect data from databases, detect trends, and offer a predictive value
for a spectrum of operational performance.
Optimization
When patterns have been recognized and forecasts have been developed, organizations will use
modelling tools to assess best-case scenarios.
15 | P a g e
Data Visualization
For simple and fast data processing, it provides visual representations such as charts and
graphs. These elements of data visualization empower companies to utilize their data to educate
and achieve future business priorities, improve sales, and deepen customer relationships.
Challenges Presented by Business Analytics
Managerial Distrust
It can be hard to convince everyone in upper management to join in for Business Analytics
introduction. While most companies have accepted a type of Business Intelligence and are able
to successfully handle data warehousing, analytics is still an environment regarded with
skepticism by higher authorities. People should be certain about it to get the best results.
Providing analytics along with the present existing business methods will assist to gain
confidence by the ones who are skeptical about it.
Lacking Collaboration
The assessment and execution of analytics-driven programs can be crippled by the inability to
achieve coordination within a cross-section of departments. For an analytics plan to thrive,
business and IT workers must be in harmony. Lack of cooperation poses the possibility that the
details offered will not be generated by analytics, leading to more mistrust and possible
abandonment of valuable advancement in technology.
Poor Commitment
While several analytics product bundles are advertised as a simple to use pre-engineered
service, prices would be high and the returns are gradual. During the beginning half of analytics
it requires a lot of effort as many people get worked up and give up the thought. Managers must
provide an environment that supports the process and conduct regular performance checks. The
models develop during the course of time and provide insights for the future.
16 | P a g e
Gradual Content Advancement
Owing to the unavailability or poor quality of usable data, Business Analytics implementations
frequently fail. An evaluation of maturity can often be carried out on the information
architecture and databases of the organization based on analytical specifications. Analysis,
clearing and obtaining data is done during the improvement phase. The condition of
categorized and practical data should be rated, the integration framework must have the
capacity to handle the recent updates of content that comes up.
Trends in Business Analytics
Artificial Intelligence
Artificial Intelligence is becoming more resourceful by tutoring itself and is being introduced
in many industries like investment, fabrication and trade.
Big Data
In every field of life with a growing focus on digitization, databases grow at an exponential
pace. More knowledge implies more future observations, but the sheer volume can be daunting.
This growth is both an advantage and a drawback.
Deep Learning
Deep learning processes huge amount information that can be used to figure out trends and
outputs that were difficult to analyze before. Machine learning is usually followed by deep
learning.
Micro-Segmentation
Companies categorize their customers into small groups based on the data related to their
buying behavior, this helps the company to better understand their focus group better and make
improvements to satisfy customers based on their specific needs.
17 | P a g e
Neural Networks
Accurate forecasts are given by this method using significant past trends by proper processing
and classification of data. Neural networks are trained so as to have the ability to analyze
information like how an individual would.
Power Business Intelligence (BI)
Power BI is an application software that is used to create data visualization reports of different
types of data like organized, disorganized and mixed data. Power BI is preferred over Excel
spreadsheets as it can handle enormous amount of data as compared to Excel. The reports that
are created using Power BI are dynamic and can be easily sent to others.
Desktop version of Power BI
It is an unpaid software that assists to transform and picturize information by running it on your
systems. It has the ability to associate information from many places and collate them into an
information system. Dynamic reports with visuals that can be easily understood by clients or
end users who is in need of the report which can be created using this software. End users who
use business knowledge can take the help of this software to build reports.
Some of the applications are as follows:
Link to data
To build a data model, transform and clean the data,
Build visuals that include graphical representations of the results, such as charts or
graphs.
Develop reports on one or more report sections, which are visual databases.
Share reports using the Power BI service with others
18 | P a g e
Data researchers or business intelligence experts (report creators) are sometimes considered
the individuals most commonly responsible for the above activities. Many individuals who do
not consider themselves to be an analyst or a report maker, however, use Power BI Desktop to
produce persuasive reports or to collect data from multiple sources and construct data models
so they can exchange these reports with their colleagues and organizations.
In the Power BI Desktop, there are three views:
Report: Reports and graphics are produced in this view, a majority portion of the
development phase is used up for this.
Data: This vision displays the information used in the report-associated information
system, and converts the data into the report format for best use.
Model: You see and control the relationships between tables in your data model in this
view.
19 | P a g e
Supply Chain Analytics
Supply chain analytics is the application of analytics to supply chain. It helps to run through
large amount of data which help a company to take better decisions, enhances the forecasting
capabilities increasing the profitability for the company. Supply chain analytics leads to a good
return of invest for a business that applies it. It helps to figure out the risks prior so as to take
corrective actions to prevent the risks from occurring. Use of analytics on supply chain data
helps to take better planning actions so as to reduce the wastes that are caused due to over
estimation of productions of goods. Lena processes are implemented by the use of supply chain
analytics. Supply chain analytics helps to understand the sequence and tendency that data
would follow based on the previous analysis of similar data, this helps to better predict what
would happen in future and take appropriate actions to reduce the errors that can occur.
Kinds of Supply Chain Analytics
Descriptive SC analytics
It compares supply chain old data and current data to understand the operations that is currently
being followed by the company.
For example, it helps to see what are the similar trends and patterns that is occurring currently
and that has happened before in the past records of the company.
Predictive SC analytics
It deals with understanding what can be done to prepare and prevent faults that can happen in
future before it actually affects the working of the company.
For example, based on the sequence that the data follows actions can be taken as precautionary
measures.
Diagnostic SC analytics
It helps to understand the errors that have occurred in past and what were the reasons that
caused them to occur.
For example, analysis of the data is conducted to figure out why the anomalies occurred in the
past.
20 | P a g e
Perspective SC analytics
It helps businesses resolve issues and boost enterprise value. Assists to reduce the disturbances
in operations that can occur by joining hands with right partners.
For example, a company coming up with best strategies to improve on its overall operations to
increase the profitability.
21 | P a g e
Five C’s of SC Analytics
The five C’s of SC analytics can be used for optimization of the supply chain which helps to
maintain the company’s position and turns out feasible for a long period.
The five C’s are as follows:
Connections of data
The capability of supply chain analytics to retrieve of the same form
or of different forms of data from social communication platforms
or online network of things using business resource planning and
enterprise to enterprise assimilation tools.
Collaborations with providers
To boost better collaborations with providers it is necessary to adopt
cloud-based business connections to allow numerous business
collaborations and pacts.
Cyber awareness in supply chain
One of the main responsibilities of supply chain analytics is to make sure
that all the components within the network are secure from cyber
intervention and meddling which would affect the efficient working of
all operations with the supply chain.
22 | P a g e
Cognitively enabled supply chain
The activities and judgements of the recent supply chains are regulated
by Artificial Intelligence platforms, this helps to make many supply
chains programmed and self-automated to carry out the necessary tasks
with the supervision of humans.
Comprehensible information from SC analytics
The information received from supply chain analytics must be easy to
understand, so that the implementations can happen fast by reducing the
latency occurring during the various supply chain operations.
Supply Chain
Analytics
Collaboartive
Connected
CognitiveCyber aware
Comprehensible
23 | P a g e
Emanating trends in SC analytics
Optimization of Inventory in SC analytics
The use of supply chain analytics helps to plan properly before purchasing materials so that
there is no over purchasing which would require a lot of inventory space which will lead to
unnecessary increase in the overall cost involved. Thus with the help of proper planning the
inventories can be made simple with minimum storage of material.
Analytics of Demand in SC analytics
Supply chain analytics helps to understand the patterns and trends to be able to judge when the
demand would be more or less. A proper understanding of demand analysis has a lot of benefits
like overproduction can be minimized, only required quantity of raw materials can be acquired,
more man power can be hired based on the increase of demand and so on.
Inventory Optimization
Demand Analytics
Replenishment Planning Analytics
SC Metrics Measurement and Reporting
Networking Planning and Optimization
24 | P a g e
Analysis of Replenishment Decision in SC analytics
Supply chain analytics can be useful to decide the right amount that is needed to be purchased
for the restocking of raw materials required by the business for the production of the end
products.
Network Decision and Enhancement in SC analytics
Supply chain analytics helps to make sure the network in which the operations are carried out
is planned properly so that there is not much time wasted in travelling long distances between
the components of the chain. This help to maintain the customer relationships by timely
satisfaction of demands.
Supply chain parameter analysis and documentation in SC analytics
All operations of the supply chain are assessed and if any deviations are found from the normal
then corrective actions are taken. These actions are taken based on the “SMART” goals. The
changes that are made need to be documented properly so that it can be useful for future
references.
25 | P a g e
Advantages of Supply Chain Analytics
Improved demand forecasting
Demand forecasting is considered as one of the most important aspects of supply chain as
incorrect forecasting can lead to a lot of problems involving cost and time. Supply chain
analytics helps to better understand the demand by analyzing the previous data and predicting
similar demands of products.
Hike in Return on Investment
Supply chain analytics helps to analysis data better and to take the right decisions. These steps
lead to a better return on investment than enterprises which fail to perform analysis on the data
they possess.
26 | P a g e
Improved receptiveness
Supply chain analytics helps to track the needs and requirements on regular basis this helps to
comprehend the need for more or less materials to be acquired so as to avoid unnecessary
disruption in the flow of goods. Thus, supply chain analytics allows the chain to be agile.
Increased clarity across the Supply Chain
Supply chain analytics allows real time tracking of orders with the use of technologies like
“Blockchain, IoT and Artificial Intelligence”. This helps to increase the clarity of the supply
chain and to take necessary actions. Without the application of analytics, it makes it very
difficult to track the orders and understand the reasons for delay.
Improved rapport with providers
Supply chain analytics has a very well-connected network of partners, providers and
distributors this helps to improve the relationship among them as there is constant
communication within the about the requirements.
Improved Disruption Handling
Supply chain analytics helps to handle disruptions that can occur in future by providing signs
and warnings of what can tend to occur thus giving the supply chain managers time in advance
the tackle the situation than waiting till the last minute when happens.
27 | P a g e
Blockchain
Blockchain is a form of structure which is used to store collection of data. In blockchain as the
name suggests the data is stored in blocks and when a block reaches its maximum capacity the
data is then carried over to the next block. The blocks are connected like a chain so that the
order remains intact.
Blockchain technology has 3 parts:
Blocks
It is a structure that is used to store data.
Nodes
In blockchain the data is not all stored at one place or controlled by just one person. The data
in blockchain is distributed at many places known as nodes. Each node in the network contains
copies of the data on the blockchain. Any actions taking place on the chain can be easily tracked
cause of the transparency property that blockchain possess.
Miners
It is used to make new blocks on the existing chain, this phenomenon is known as mining in
blockchain.
28 | P a g e
Advantages
Security of data
It is very difficult to hamper the data that is stored in a blockchain. This is because each block
on the blockchain has a unique hash code to itself. If there is any attempt to hamper data only
that block is changed which causes the has code of that block also to change, but the hash codes
of the other blocks remain the same.
Transparency of data
The data in blockchain is distributed at many places known as nodes. Each node in the network
contains copies of the data on the blockchain. Any actions taking place on the chain can be
easily tracked cause of the transparency property that blockchain possess.
29 | P a g e
Reliable Business
In blockchain the all parties involved in a network are properly verified and only authentic ones
are allowed to remain in the network. So, all the businesses that take place are reliable and safe.
Decrement in money involved
The cost associated in blockchain is reduced as the presence of third parties is eliminated, most
of the documentation involved in the trade is carried out online thus reducing the paperwork
tremendously and leaner processes replace the old processes which involve a lot of money.
Live tracking of products
Due to the transparency in the processes, it allows live tracking of the products using
blockchain. This helps to take corrective actions when there are delays in the delivery of
consignment. Live tracking also helps improve relationships with customers as they are given
all information about the products status and not keeping them in the dark, this in turn increases
profitability of the enterprise.
31 | P a g e
Dairy Industry in India
India is known as one of the biggest producers of milk on a global scale. After liberalization
this industry has grown swiftly. The main purpose of this industry is to increase the production
of milk and promote the use of technologies for processing milk. Most of India’s milk yield
comes from rural areas who are small scale producers. Farmers who are into farming are usually
into the dairy business also because crop farming is seasonal whereas dairy production happens
all through the year.
The Indian Dairy Industry structure consists of two main categories:
Organised Sector
This category is made up of co - operatives and companies that are run privately.
Unorganised Sector
This category is made up of local dealers, milkmen and milk that is used for self-consumption.
32 | P a g e
The main movement in this industry in India started off in a small village in Gujarat where the
farmers protested against the unethical trade methods that were followed. The solution to this
problem was to take control of acquirement, transformation and commerce by removing the
intermediators. This was adopted by few villages in Gujarat under the leadership of Dr.
Verghese Kurien. This grew to become one of the best dairy producers in the country what we
today know as AMUL.
This led to the setup of National Dairy Development Board with the main goal of duplicating
the Amul model nationwide. The Amul model consists of three levels which are as follows:
Cooperative dairy societies at village level
Milk unions at district level
Member unions at state level
33 | P a g e
In this model it can be seen that the villagers themselves control the dairies. The farmer groups
use the state milk federation to directly sell the products the end users. Thus, the intermediators
are eliminated which helps the farmers to get a good price. The involvement of intermediators
leads to huge amounts being taken away by them and the farmers hardly getting anything in
return. This model helps to poor farmers to get good profitability even when the business in
low.
34 | P a g e
Milma
Milma is one of the famous organizations in the dairy industry in Kerala. It was founded in the
year 1980. Milma deals with the supply and delivery of milk and milk-based products
throughout Kerala. The main aim of Milma is to produce ample amount of milk for the whole
state. According to “Operation Flood” which was a dairy project started by “National Dairy
Development Board” whose main goal was to connect the milk producers to satisfy the
demands of urban regions. It was during the second phone of this project that Kerala was
included in it. Thus, the birth of Milma took place and its head office is in Thiruvananthapuram.
It is an organization which consists of three levels. The three levels are:
At the village level is the cooperative dairy societies
At the district level is the area milk producing unions
At the state level is “Kerala Cooperative Milk Marketing Federation”
Milma has three main regional operation centers in Ernakulam, Malabar and
Thiruvananthapuram.
35 | P a g e
Board of Directors
Mr. P A Balan Master (Chairman of KCMMF)
Mr. Rajeshkumar Singh IAS (Additional Secretary, Govt. of Kerala)
Mr. Kallada Ramesh (Chairman of TRCMPU)
Mr. John Theruvath (Chairman of ERCMPU)
Mr. Mani K S (Chairman of MRCMPU)
Mr. Karumadi Murali (Representative of TRCMPU)
Adv. S Gireesh Kumar (Representative of TRCMPU)
Mr. E M Paily (Representative of ERCMPU)
Mr. K K Johnson (Representative of ERCMPU)
Mrs. Lissy Xavier (Representative of ERCMPU)
Mr. P Sreenivasan (Representative of MRCMPU)
Mrs. K K Anitha (Representative of MRCMPU)
Mr. P P Narayanan (Representative of MRCMPU)
Mr. S Rajeev (Regional Head of National Dairy Development Board)
Mr. S Sreekumar (Director of Dairy Development Department)
Mr. O B Suresh Kumar (Deputy Secretary of Finance Department Government of Kerala)
Dr. Patil Suyog Subhash Rao IFS (Managing Director)
36 | P a g e
Vision
To continuously seek to produce superior quality milk and milk-based items to the end
consumers with prime benchmarks. The items are produced by spirited and fixated employees
by making use of the best and latest technologies that is available leading to the growth and
profitability for the producers.
Mission
The mission of Milma is to assist in the growth of milk producers through the contentment
experienced by the end consumers on using the products made at Milma.
Objectives of Milma
To develop a feasible dairy corporation in Kerala.
To offer a steady retail place and even amount for the yield given by the milk producers.
To direct excess milk supply from smaller regions to larger regions where there is a
shortage of supply, this also helps the producers to get returns for their yield.
Performing tasks to boost manufacturing, acquisition, transforming and selling, milk
and other milk-based products that are produced by the farmers so as to help them grow
financially.
37 | P a g e
Societies
Each of the three regional operating centers have societies within them.
In Thiruvananthapuram union there are four districts with operating societies under it:
Trivandrum which has 220 operating societies
Pathanamthitta which has 112 operating societies
Kollam which has 169 operating societies
Alapuzha which has 167 operating societies
In Ernakulam union there are four districts with operating societies under it:
Ernakulam which has 304 operating societies
Idduki which has 174 operating societies
Kottayam which has 203 operating societies
Thrissur which has 198 operating societies
In Malabar union there are six districts with operating societies under it:
Kannur which has 173 operating societies
Palakkad which has 316 operating societies
Kasaragod which has 129 operating societies
Malappuram which has 215 operating societies
Kozhikode which has 232 operating societies
Wayanad which has 57 operating societies
38 | P a g e
Dairies
Each of the three regional operating centers have dairies within them.
In Thiruvananthapuram union there are three dairies:
Kollam Dairy
Pathanamthitta Dairy
Thiruvananthapuram Dairy
In Ernakulam union there are four dairies:
Kattapana Dairy
Kottayam Dairy
Thrissur Dairy
Ernakulam Dairy
In Malabar union there are seven dairies:
Kozhikode Dairy
Palakkad Dairy
Kannur Dairy
Wayanad Dairy
Kasaragod Dairy
Malayora Dairy
Naduvattam Central Product Dairy
39 | P a g e
Kerala Co-operative Milk Marketing Federation units
KCMMF is considered as the main body of Milma that takes care and controls the working of
all the other bodies. The main goal of the body is to provide profitable revenue to the producers
and superior quality items for the end customers. It handles mainly three units under it.
Central Dairy Products center at Alappuzah
Center for Cattle Feed at Malapuzah, Palakkad
Center for Cattle Feed at Pattanakkad, Alappuzha
40 | P a g e
Center for Cattle Feed at Malapuzah, Palakkad
This center was established by the Department of Animal Management, Kerala in the year
1972. After which it was transferred to KCMMF in 1982 by the National Dairy Development
Board and Government of Kerala for the operation of the second “Operation Flood” project in
the state. Feeds that are produced in this center are “Milma Gomathi Pellet” and “Milma
Gomathi Rich Pellet”.
41 | P a g e
Center for Cattle Feed at Pattanakkad, Alappuzha
This center was set up in 1985, it was a small center with a competency of 100 metric tons per
day. In 1993 the center was expanded to provide a competency of 300 metric tons per day and
the plant was also renovated with latest equipment. The feed from this center is given to milk
producers in many districts. Feeds that are produced in this center are “Milma Gomathi Pellet’
and “Milma Gomathi Rich Pellet”. Recently “Milma Gomathi Gold Feed” was introduced.
Another variety of feed is the “Milma Bypro Feed” which is highly nutritional for milking
cows.
42 | P a g e
Central Dairy Products center at Alappuzah
Central Dairy Products center is controlled by KCMMF. This center mainly caters to the other
products that are produced at Milma like “curd, ghee, flavoured milk, milk powder, fruit juices,
milkshakes, buttermilk and packaged drinking water”. This center has a Quality Checking
Laboratory where chemical and microbiology tests are carried out.
43 | P a g e
Products
The main product of Milma company is milk. The company has now ventured out to producing
of different kinds of products which can be made with milk.
Milma Milk
Milma produces many kinds of milk to satisfy the needs of the end consumers. Milma produces
seven varieties of milk.
Milma Long Life Milk
Milma Homogenised Toned Milk
Milma Pasteurised Standardised Milk
Milma Pasteurised Homogenised Toned Milk
Milma Pasteurised Toned Special Milk
Milma Pasteurised Toned Milk
Milma Pasteurised Double Toned Milk
44 | P a g e
Fermented Milk Products
Milma produces three varieties in fermented products.
Milma Skimmed Curd
Milma Sambharam
Milma Set Curd
Dairy Products which are Rich of Fat
Milma produces two products under this category.
Butter
Ghee
45 | P a g e
Other Milk Based Products
Milma has a wide range of milk-based products that it produces.
Frozen Milk Products
Milma Sip up
Milma Ice cream
Milma Kulfi
Energizing Drinks
Flavoured Milk
Mango Drink
Chocolate and Strawberry Milkshake
46 | P a g e
Milk Products
Milma Milma Powder
Milma Paneer
Milma Milk based Sweets
Milk Peda
Palada Mix
Gulab Jamun
Chocolate
47 | P a g e
SWOT Analysis of Milma
Strengths
Milma is one of the main dairy industries in Kerala with many societies and dairies
under it.
Milma has its own cattle feed production units also thus there is no need to relay on
external sources for feed.
Milma has a very well-connected network as the three main regional units work closely
with all the units that come under it.
Milma does not only focus on one range of product like milk which is its main product.
It has also come up with many milk-based products that have gained the interest of end
consumers.
Milma has gained the confidence of the milk producers by giving them the best returns
for their yield and by making sure their yield does not go waste by directing it to regions
where there are shortages.
Weakness
Lack of proper tracking of products.
Inadequacy to handle the supply of milk.
Opportunities
Incorporating of latest technologies like “AI, Blockchain and IoT” for overall
improvement of supply chain activities.
Creation of dynamic dashboards for better inventory control and demand forecasting
with the help of analytics.
Implementation of “Instant Integrated Management Information System” this will help
in better decision making.
Threats
With the increase in Veganism there may be a hit in the sales of product if more
customers convert to vegans.
Customers with lactose intolerance will go for substitute products which are not dairy
based.
Competitor companies who have better supply chain analytics.
48 | P a g e
Porter’s Model of Five Force
Suppliers’ Potential to Bargain
The supplier’s potential to bargain is low as the milk producers who provide their yield to
Milma are given the best of profits or returns as the number of intermediators are reduced
cause of the structure followed at Milma.
Buyers’ Potential to Bargain
The buyers’ potential to bargain is low, as Milma is one of the most trusted brands when it
comes to dairy products in the state of Kerala. The organization has many loyal customers
who have been using their products from generations and so they have never felt the need
to bargain.
49 | P a g e
Risk of New Entry
The risk of new entrants is quite low as the companies venturing into this field will know
the history of Milma and its connection to the people of the state. To break through all the
offerings given by Milma and trying to gain a customer base would be a task.
Risk of Alternative Products
The risk of alternative products is medium cause of the adaptation of veganism by some
people. Few customers with lactose intolerance also tend to look out for products that are
not diary based so as to satisfy their needs. This can turn out to be a bigger problem if it
converts many of Milma’s customers to non-dairy product consumers.
Conflicts Among Existing Rivals
The conflicts among rivals are less as Milma has been is this industry for the longest time
as compared to the other rivals. Milma has ventured out into making of other dairy based
products, showing that it’s not stagnant focusing on just one product but has been growing
by creating new products to satisfy the needs for their customers. Milma has its own quality
checking laboratories and its own cattle feed centers also thus giving it an upper hand
compared to the other players in this market.
50 | P a g e
Future Growth and Prospects
Incorporating of latest technologies like “AI, Blockchain and IoT” for overall
improvement of supply chain activities.
Creation of dynamic dashboards for better inventory control and demand forecasting
with the help of analytics.
An email structure to make communication smoother with all the components in the
supply chain.
Implementation of “Instant Integrated Management Information System” this will help
in better decision making.
Usage of cloud technology to interchange information easily and make processes
happen faster by usage of latest technologies.
52 | P a g e
Literature Review
Incorporation of Blockchain in supply chain helps to better track the products that are being
shipped to different parts by providing better visibility. Blockchain helps to keep data
decentralized than all data stored at one place and controlled by one entity. With this technology
comes with a few challenges like extendibility, collaboration issues which has to be addressed
properly to get maximum results from blockchain. (Sohail Jabbar et al., 2020)
Blockchain usage in supply chain provides an immense degree of protection to important
reports, analysis assessments and remedial operation methods that are usually prone to being
exploited by people who want to get insights about the company. It also helps to reduce the
expenses involved which may arise by inappropriate charging made by callous providers, the
transparency in blockchain leads to decrease in such costs. It also aids to increase the
information exchanged among different units of a company by proper coordination with each
other thus leading to a reduction in the number of issues arising. (V.G. Venkatesh et al.,2020)
Supply Chain with analytics provides immense support when it comes decision making, it helps
to analyze the past data and present conditions to predict demand for the future, optimization
of resources involved in the operations and makes the organization agile. (Tino T. Herden et
al., 2020)
Food Supply Chain has many crucial functions as it needs to make sure all the perishable
products are delivered correctly to the end consumer. The has been a arise in technology
integrations in this industry. In a dairy industry the utmost importance is to maintain the quality
of the products. The integration of Blockchain technologies in dairy industry can help to
maintain authentic information about the quality of the products. (Joseph Kasten, 2019)
Technologies like blockchain helps to decrease deal costs by eliminating intermediators by
gaining partners confidence through proper clarity and security provided to all the information
that is exchanged. The two types of ambiguities that deals to deal costs are circumstantial and
observable. (C.G. Schmidt and S.M. Wagner, 2019)
53 | P a g e
Blockchain can be used to provide flexibility in supply chain that assists to deal with
disturbances that occur suddenly in the operations which can be easily resolved by coordinating
efficiently with all the partners in the network to make sure the delay that has occurred can be
minimized as much as possible and not miss the deadline by a huge amount of time. (Hokey
Min, 2018)
Application of analytics to supply chain can lead to many benefits like choosing the best route
for transportation, sustainable logistics, shelf space optimization, reverse logistics process can
be made easier by proper tracking of the consignments as most of the time this process is
usually not handled in an efficient way. Analytics helps to automate logistics; self-arranging
logistics makes use of Radio Frequency IDs to track the items. (Anitha P and Malini M. Patil,
2018).
Application of analytics in supply chain is being adapted at a fast pace by many companies.
Analytics on supply chain helps to better understand the data which makes to take better
decisions, predict scenarios, make forecasts about need for products. It leads to the growth of
the company, increase in the revenues earned and ability to stand out from other competitors.
(Prashanth R Nair, 2014)
Analytics application in supply chain has many benefits few of them being “in marketing it can
be used for sentiment analysis to know about the demand for new trends, in procurement it can
be used for supplier negotiations, in warehouse operations it can be used to manage inventory
space and predict demands and in transportation it can be used to optimize the routes for the
transport of products.” (Ivan V R and Benny T, 2014)
54 | P a g e
Research Gap
There is a lot of research happening in the field of supply chain analytics to create efficient
supply chains for companies by the implementation of various technologies. According to
current research it can be found that much light has not been thrown in the direction related to
the use of data from these technologies being incorporated with data visualization tools to make
dashboard that would help an organization to make better decisions related to supply and need
of materials, transportation details and so on which in turn improves the overall supply chain
related processes.
Statement of the Issue
In any company we know that logistics is considered as the heart of the business. A huge
amount of world business is solely dependent on logistics. Supply chain is considered the most
intricate part of a business as in includes many entities of differing views and preferences. To
achieve an efficiency in the supply chain process it includes all entities functioning in a
synergic and harmonious manner so that the transaction of goods, messages and so on happen
smoothly. One of the major issues in supply chain is that there is not proper clarity about the
processes that are taking place, this turns out to be quite a problem for many businesses.
Cohesion of items and procedures in a multi entity chain is considered as a big challenge. These
problems make it hard to figure out at which stage of supply chain the item is at, thus leading
to many issues like delay in deliveries, cancellation costs, bad reputation and unsatisfied
customers.
Necessity for the Study
Application of Supply Chain Analytics at Milma helps to provide many benefits like:
By analyzing the previous data to better understand the sequence and tendency of risks
that has been occurring over the past years at Milma.
Proper analysis of need and supply can help make better decisions related to
procurement of materials and inventory management.
55 | P a g e
Application of analytics to supply chain helps to give better insights related to the
decisions that are to be taken.
“Lean Supply Chain” helps to reduce the overall cost and risks related to supply chain,
therefore improving the whole process.
Objective of the Study
The objective of the research is the applicability of supply chain analytics to the logistics at
Milma and using the data from it to creative simple and dynamic dashboards to help the
company take necessary steps needed to improve the efficiencies in logistics. Thus, leading to
faster and leaner logistics processes at Milma. It also improves the trackability and clarity
related to the movement of the products.
Scope of the Study
Milma is a powerful and influential dairy company in Kerala which has many competitors. The
logistics of the company is considered as one of the important aspects of the business which
can be improved by incorporating new methods and technologies. This research helps to focus
on the benefits Milma can achieve with the implementation of supply chain analytics. The
proper analysis of data helps to predict the future scenarios and take better precautions to deal
with risks and reduce the wastes generated leading to a sustainable chain. Leveraging the
benefits from the dashboards created helps Milma to have a competitive edge.
Sample Size
The sample size used for this research is 110 responses. The participants who took part in this
research are employees who work at Milma.
56 | P a g e
Sampling Technique
Sampling technique that is used for this study is simple random sampling. This method is
chosen as it is simple to implement, also it saves time and cost involved. It is a legitimate
sampling method that helps to reduce unfairness.
Data Collection tools
Data was collected for this study by conducting personal interviews with the employees who
are working at Milma to get a better understanding of the supply chain process which involves
planning and execution of tasks.
Another method that was used to collect data is an online questionnaire which acted as a survey
tool to get opinions of the employees related to the application of analytics to the logistics of
Milma.
Statistical Tools
The statistical tools used for this study are Microsoft Power BI to create dynamic dashboards.
Python and Microsoft Excel are used for data visualization.
Limitations of the Study
Some of the limitations of this study are as follows:
For a big company like Milma to implement analytics as a whole would require time
and it is not something that can happen overnight.
For technologies to be adapted also there must be people who can handle them and
work with the data that is generated from it, the employees must be well versed in the
latest technologies.
Climatic, financial, communal, legislative, constitutional and technological aspects can
influence the business.
58 | P a g e
Data Collection
No. "How
important
is logistics
at Milma?
"
"Is
Milma
taking
steps to
improv
e the
logistic
s? "
"Should
logistics
be a part
of the
company
's
strategy
? "
"How often
is logistics
critically
reviewed at
Milma?"
"What are the
quality metrics
used in logistics
at Milma? "
"Problems
that
influence
logistics at
Milma? "
1 Important Yes Yes Monthly Timely Delivery Tracking
2 Important Yes Yes Monthly Timely Delivery Tracking
3 Important Yes Yes Monthly Timely Delivery Tracking
4 Important Yes Yes Monthly Timely Delivery Tracking
5 Important Yes Yes Monthly Timely Delivery Tracking
6 Important Yes Yes Quarterly Timely Delivery Tracking
7 Important Yes Yes Quarterly Timely Delivery Tracking
8 Indifferent Yes No Quarterly Timely Delivery Tracking
9 Important Yes Yes Quarterly Timely Delivery Tracking
10 Important Yes Yes Quarterly Timely Delivery Tracking
11 Important Yes Yes Yearly Cost Leadtime
12 Important Yes Yes Yearly Quality Reliability
13 Important Yes Yes Yearly Quality Reliability
14 Important Yes Yes Yearly Quality Reliability
15 Important Yes Yes Yearly Quality Tracking
16 Important Yes Yes Yearly Error - free Tracking
17 Important Yes Yes Yearly Timely Delivery Tracking
18 Important Yes Yes Yearly Timely Delivery Tracking
19 Indifferent Yes No Yearly Timely Delivery Tracking
20 Important Yes Yes Yearly Timely Delivery Tracking
21 Important No Yes More than a
year
Timely Delivery Tracking
22 Important No Yes Monthly Timely Delivery Tracking
59 | P a g e
23 Important Yes Yes Monthly Timely Delivery Tracking
24 Important Yes Yes Monthly Timely Delivery Tracking
25 Important Yes Yes Monthly Timely Delivery Cost
26 Not
important
Yes Yes Monthly Timely Delivery Reliability
27 Important Yes No Quarterly Quality Reliability
28 Important Yes Yes Quarterly Quality Reliability
29 Important Yes Yes Quarterly Quality Tracking
30 Important Yes Yes Quarterly Timely Delivery Tracking
31 Important Yes Yes Quarterly Timely Delivery Tracking
32 Important Yes Yes Yearly Timely Delivery Tracking
33 Important Yes Yes Yearly Timely Delivery Tracking
34 Important Yes Yes Yearly Timely Delivery Tracking
35 Important Yes Yes Yearly Timely Delivery Tracking
36 Important Yes Yes Yearly Timely Delivery Tracking
37 Important Yes Yes Yearly Timely Delivery Tracking
38 Important Yes Yes Yearly Timely Delivery Tracking
39 Not
important
Yes Yes Yearly Timely Delivery Reliability
40 Important Yes No Yearly Cost Cost
41 Important Yes Yes Yearly Quality Reliability
42 Important Yes Yes More than a
year
Quality Reliability
43 Important No Yes Monthly Quality Tracking
44 Important No Yes Monthly Error - free Tracking
45 Important Yes Yes Monthly Timely Delivery Tracking
46 Important Yes Yes Monthly Timely Delivery Tracking
47 Important Yes Yes Monthly Timely Delivery Tracking
48 Important Yes Yes Quarterly Timely Delivery Tracking
49 Important Yes Yes Quarterly Timely Delivery Tracking
50 Not
important
Yes Yes Quarterly Timely Delivery Tracking
60 | P a g e
51 Important Yes Yes Quarterly Timely Delivery Tracking
52 Important Yes Yes Quarterly Timely Delivery Tracking
53 Important Yes Yes Yearly Timely Delivery Reliability
54 Important Yes Yes Yearly Timely Delivery Tracking
55 Important Yes Yes Yearly Error - free Tracking
56 Important Yes No Yearly Timely Delivery Tracking
57 Important Yes Yes Yearly Timely Delivery Tracking
58 Important Yes Yes Yearly Timely Delivery Tracking
59 Important Yes Yes Yearly Timely Delivery Tracking
60 Important Yes Yes Yearly Timely Delivery Tracking
61 Important Yes Yes Yearly Timely Delivery Tracking
62 Important Yes Yes Yearly Timely Delivery Tracking
63 Not
important
Yes Yes More than a
year
Timely Delivery Tracking
64 Not
important
Yes Yes Monthly Timely Delivery Reliability
65 Important No Yes Monthly Timely Delivery Reliability
66 Important No Yes Monthly Error - free Cost
67 Important Yes Yes Monthly Timely Delivery Tracking
68 Important Yes Yes Monthly Timely Delivery Tracking
69 Important Yes Yes Quarterly Timely Delivery Tracking
70 Important Yes Yes Quarterly Timely Delivery Tracking
71 Important Yes Yes Quarterly Timely Delivery Tracking
72 Important Yes Yes Quarterly Timely Delivery Tracking
73 Important Yes No Quarterly Timely Delivery Tracking
74 Important Yes Yes Yearly Timely Delivery Tracking
75 Not
important
Yes Yes Yearly Timely Delivery Tracking
76 Important Yes Yes Yearly Timely Delivery Tracking
77 Important Yes Yes Yearly Quality Cost
78 Important Yes Yes Yearly Timely Delivery Tracking
79 Important Yes Yes Yearly Timely Delivery Tracking
61 | P a g e
80 Important Yes Yes Yearly Timely Delivery Tracking
81 Important Yes No Yearly Timely Delivery Tracking
82 Important Yes Yes Yearly Timely Delivery Tracking
83 Important Yes Yes Yearly Error - free Tracking
84 Important Yes Yes More than a
year
Timely Delivery Tracking
85 Important Yes Yes Monthly Timely Delivery Tracking
86 Important Yes Yes Monthly Timely Delivery Tracking
87 Important No Yes Monthly Timely Delivery Tracking
88 Important No Yes Monthly Timely Delivery Reliability
89 Important Yes Yes Monthly Quality Tracking
90 Important Yes Yes Quarterly Timely Delivery Tracking
91 Important Yes Yes Quarterly Timely Delivery Tracking
92 Indifferent Yes Yes Quarterly Timely Delivery Tracking
93 Important Yes Yes Quarterly Timely Delivery Tracking
94 Indifferent Yes Yes Quarterly Timely Delivery Tracking
95 Not
important
Yes Yes Yearly Quality Tracking
96 Not
important
Yes No Yearly Timely Delivery Tracking
97 Important Yes Yes Yearly Timely Delivery Tracking
98 Not
important
Yes No Yearly Timely Delivery Tracking
99 Important Yes Yes Yearly Timely Delivery Reliability
100 Not
important
Yes No Yearly Timely Delivery Tracking
101 Not
important
Yes No Yearly Timely Delivery Tracking
102 Not
important
Yes Yes Yearly Timely Delivery Tracking
103 Indifferent Yes No Yearly Timely Delivery Tracking
104 Not
important
Yes Yes Yearly Timely Delivery Tracking
62 | P a g e
105 Important Yes No Quarterly Timely Delivery Reliability
106 Important Yes Yes Quarterly Timely Delivery Tracking
107 Important Yes No Quarterly Timely Delivery Tracking
108 Not
important
Yes Yes Quarterly Timely Delivery Tracking
109 Important No No Quarterly Timely Delivery Tracking
110 Not
important
No Yes More than a
year
Timely Delivery Tracking
No. "Will
implementatio
n of technology
solve the
problems
related to
logistics? "
"What effects will
technology have
on logistics? "
"Do you
think use
of
technology
in logistics
will
increase
the cost
involved? "
"Which logistic activity
at Milma requires
improvement? "
1 May be Competitive edge Yes Transportation and
delivery
2 Yes Competitive edge Yes Transportation and
delivery
3 Yes Competitive edge Yes Transportation and
delivery
4 Yes Competitive edge Yes Transportation and
delivery
5 Yes Competitive edge Yes Transportation and
delivery
6 Yes Cost saving Yes Inventory management
7 Yes Competitive edge Yes Inventory management
8 Yes Competitive edge Yes Inventory management
63 | P a g e
9 Yes Competitive edge Yes Transportation and
delivery
10 Yes Competitive edge Yes Transportation and
delivery
11 Yes Competitive edge May be Transportation and
delivery
12 No Competitive edge Yes Transportation and
delivery
13 Yes Competitive edge Yes Transportation and
delivery
14 Yes Competitive edge Yes Packaging
15 Yes Competitive edge Yes Transportation and
delivery
16 Yes Competitive edge Yes Transportation and
delivery
17 Yes Time saving Yes Transportation and
delivery
18 Yes Time saving Yes Transportation and
delivery
19 Yes Time saving Yes Transportation and
delivery
20 Yes Competitive edge Yes Transportation and
delivery
21 Yes Competitive edge Yes Transportation and
delivery
22 Yes Competitive edge No Transportation and
delivery
23 No Competitive edge No Transportation and
delivery
24 No Competitive edge No Transportation and
delivery
25 Yes Time saving No Overall process
26 Yes Time saving No Overall process
64 | P a g e
27 Yes Competitive edge Yes Overall process
28 Yes Competitive edge Yes Overall process
29 Yes Competitive edge Yes Overall process
30 Yes Competitive edge Yes Inventory management
31 Yes Competitive edge Yes Inventory management
32 Yes Increase
traceability
May be Inventory management
33 Yes Increase
traceability
Yes Transportation and
delivery
34 Yes Competitive edge Yes Transportation and
delivery
35 No Competitive edge Yes Transportation and
delivery
36 Yes Competitive edge Yes Transportation and
delivery
37 Yes Competitive edge Yes Transportation and
delivery
38 Yes Competitive edge No Inventory management
39 Yes Competitive edge No Overall process
40 Yes Competitive edge No Transportation and
delivery
41 Yes Competitive edge No Transportation and
delivery
42 Yes Competitive edge No Transportation and
delivery
43 Yes Competitive edge Yes Transportation and
delivery
44 Yes Cost saving Yes Transportation and
delivery
45 Yes Increase
traceability
Yes Overall process
46 No Increase
traceability
Yes Overall process
65 | P a g e
47 Yes Competitive edge Yes Inventory management
48 Yes Competitive edge Yes Overall process
49 Yes Competitive edge Yes Overall process
50 Yes Competitive edge Yes Transportation and
delivery
51 Yes Competitive edge Yes Transportation and
delivery
52 Yes Time saving Yes Transportation and
delivery
53 Yes Time saving May be Transportation and
delivery
54 Yes Competitive edge Yes Transportation and
delivery
55 Yes Competitive edge Yes Transportation and
delivery
56 Yes Competitive edge Yes Transportation and
delivery
57 No Competitive edge Yes Transportation and
delivery
58 Yes Competitive edge Yes Transportation and
delivery
59 Yes Time saving Yes Transportation and
delivery
60 Yes Time saving Yes Inventory management
61 Yes Time saving Yes Inventory management
62 Yes Competitive edge Yes Inventory management
63 Yes Competitive edge Yes Packaging
64 Yes Competitive edge No Transportation and
delivery
65 Yes Competitive edge No Transportation and
delivery
66 Yes Competitive edge No Transportation and
delivery
66 | P a g e
67 Yes Competitive edge No Transportation and
delivery
68 No Competitive edge No Transportation and
delivery
69 Yes Competitive edge Yes Overall process
70 Yes Competitive edge Yes Overall process
71 Yes Competitive edge Yes Overall process
72 Yes Increase
traceability
Yes Overall process
73 Yes Increase
traceability
Yes Overall process
74 Yes Competitive edge May be Transportation and
delivery
75 Yes Competitive edge Yes Transportation and
delivery
76 Yes Competitive edge Yes Transportation and
delivery
77 Yes Competitive edge Yes Transportation and
delivery
78 Yes Competitive edge Yes Transportation and
delivery
79 May be Competitive edge Yes Inventory management
80 No Competitive edge No Inventory management
81 Yes Competitive edge No Transportation and
delivery
82 Yes Competitive edge No Transportation and
delivery
83 Yes Competitive edge Yes Transportation and
delivery
84 Yes Time saving Yes Transportation and
delivery
85 Yes Time saving Yes Transportation and
delivery
67 | P a g e
86 Yes Competitive edge Yes Packaging
87 Yes Competitive edge Yes Transportation and
delivery
88 Yes Competitive edge No Transportation and
delivery
89 Yes Competitive edge No Transportation and
delivery
90 Yes Competitive edge Yes Transportation and
delivery
91 No Competitive edge Yes Transportation and
delivery
92 Yes Competitive edge Yes Inventory management
93 Yes Competitive edge Yes Inventory management
94 Yes Competitive edge Yes Overall process
95 Yes Competitive edge May be Overall process
96 Yes Increase
traceability
Yes Transportation and
delivery
97 Yes Increase
traceability
Yes Transportation and
delivery
98 Yes Competitive edge Yes Transportation and
delivery
99 Yes Competitive edge Yes Transportation and
delivery
100 Yes Competitive edge Yes Transportation and
delivery
101 Yes Competitive edge No Overall process
102 No Competitive edge No Overall process
103 No Competitive edge Yes Overall process
104 Yes Competitive edge Yes Transportation and
delivery
105 Yes Competitive edge Yes Transportation and
delivery
68 | P a g e
106 Yes Competitive edge Yes Transportation and
delivery
107 Yes Competitive edge Yes Transportation and
delivery
108 Yes Time saving No Transportation and
delivery
109 No Time saving No Inventory management
110 No Time saving No Inventory management
The above data are the responses that were compiled from the survey that was carried out. It
consists of 10 questions and a total of 110 responses were collected. The respondents for this
survey are the employees at Milma to know what is their take on application of analytics to
supply chain and other information related to logistics process.
Data Interpretation
From the above graph it can be comprehended that logistics is an essential process at Milma.
The products at Milma are perishable and thus needs an efficient supply chain to make sure the
products are delivered to the customers according to proper quality standards.
69 | P a g e
Milma in its future prospects has a lot of this lined up to improve the logistics which includes
the implementation of blockchain technology, IoT.
It is seen that the logistics at Milma is reviewed mostly on a yearly basis, this can be worked
upon by having implementing half yearly reviews and gradually making it a monthly reviewing
system which will help to scale up the logistics to much better level with changes made
according to the needs.
70 | P a g e
There is a need for logistics to be part of the company strategies as we know these strategies
are considered a very essential for helping mold the company’s future. It involves a lot of
brainstorming to decide how to increase customer satisfaction.
One of the most important metrics in logistics is the timely delivery of the products to satisfy
the needs and requirements of the customers. Timely delivery also helps to maintain the
freshness of the products.
71 | P a g e
It is noticed that the problem that is reported the most in logistics in the lack to be able to track
the items. This affects the overall process as the delivery time cannot be estimated leading to
many problems in turn leading to let-down customers. The use of blockchain can help to resolve
this issue as it provides easy traceability of the goods with timely updates.
Technology can help solve many issues as well as to predict the future in a better way,
understand the risks that are likely to occur and also provide an accuracy when in comes to the
planning of resources.
72 | P a g e
The effects of technology are many, with proper insights about the applications of technology
we understand it leads to cost cutting, time saving and traceability. As the employees are not
much aware of the latest technologies and their benefits, they failed to point these as the major
effects.
The main activity that requires improvement is transportation and delivery with the use of
technologies like “blockchain and internet of things” helps to increase traceability of goods and
have an agile supply chain.
73 | P a g e
Most of the respondents think that incorporation of technology to logistics would increase the
cost involved, but there are many other benefits which can be achieved by the use of technology
which in turn would actually reduce the cost involved.
75 | P a g e
Findings
Power BI one of the latest business analytical tools is used in this project to show procurement
and sales at Milma. Power BI represents the data as visual reports and dynamic dashboards that
can be used by Milma improve their supply chain.
Data models of procurement and sales data
Data models are used to find the connections among the different data present in different
tables. The properties of the connections vary from one to one and one to many.
The above is the data model for procurement data. There exists a one to many (1: *) relationship
between the tables Dim_Category, Dim_Date to Fact-Data. Single cross filter from
Dim_Category to Fact-Data and Dim_Date to Fact-Data means that only one table in the
relationship can be used to filter the data.
76 | P a g e
The above is the data model for sales data. There exists a one to many (1: *) relationship
between the tables Dim_Category, Dim_Date to Fact-Regionwise, Dim_Category, Dim_Date
to Fact-Productwise and Dim_SubCategory to Fact-Productwise. Single cross filter from
Dim_Category, Dim_Date to Fact-Regionwise and Dim_Date to Fact_Productwise means that
only one table in the relationship can be used to filter the data. Bi-directional cross filter from
Dim_Category, Dim_SubCategory to Fact-Productwise means that both tables in the
relationship can be used to filter the data.
77 | P a g e
Dashboard of Procurement data
The dashboard consists of the products procured each year and the procurement from each of
the regions like Malabar, Ernakulam and Thiruvananthapuram.
79 | P a g e
Dashboard of Sales data
The sales data consists of three dashboards – region wise sales, product wise sales and product
sales for each region.
Dashboard for Region wise sales at Milma
85 | P a g e
From the analysis of data, we can see that there is a 0.44% increase in sales between 2018 and
2019. CC03(MRCMPU) accounted for the majority of the increase among the other regions,
offsetting the decrease of CC01(TRCMPU). There were no significant changes to the relative
contributions.
86 | P a g e
There is a 2.54% increase in sales between 2019 and 2020. CC01 (TRCMPU) had the largest
increase among other regions. There were no significant changes to the relative contribution.
87 | P a g e
The product wise sales across the three regions in the year 2020. CC01 refers to TRCMPU,
CC02 refers to ERCMPU and CC03 refers to MRCMPU.
TRCMPU
ERCMPU
88 | P a g e
MRCMPU
CC01(TRCMPU) consist of 20% of the records, CC02(ERCMPU) consists of 17.14% of the
records and CC03(MRCMPU) consist of 62.85% of the records, most affects the distribution.
89 | P a g e
Suggestions
Implementation of blockchain technology can help to lighten the disharmony in the
logistics at Milma. It also helps to reduce the cost and time of organizational processing.
A mix of a many technologies can be used to provide better of materials which in turn
leads to exceptional relationships with customers.
Right management of the dashboards that are created can be used to take rational
decisions, to redesign the chain to increase the value in logistics and to improve the
overall supply chain at Milma which in turn can increase the profitability.
Training the employees of Milma by conducting workshops to figure out handle the
new implemented technologies with ease, making it simpler for them to understand the
actual working and trouble shoot efficiently.
90 | P a g e
Conclusion
This study is based on Supply Chain Analytics at Milma, the application of analytics to supply
chain and the data from the analytical technologies can be reported using Power BI, which is a
business analytics tool used to make powerful dashboards. The reports created using Power BI
provides a multidimensional view of the datasets of Milma. The visualizations are not fixed, it
is highly interactive and can be personalized according to the needs of the company. The model
created can discover insights and get solutions when data is added or deleted. Milma can make
use of this model to find data points where the sales are less, finding solutions for it using better
marketing strategies and ways to increase the sales in that particular region. By using this model
intensively Milma can make sure that the products are being tracked timely with live updates
being reflected in the dashboards. This will help to increase customer satisfaction with proper
clarity on the delivery of products which in turn will increase the profits flowing into the
company.
91 | P a g e
Bibliography
milma.com
https://www.jigsawacademy.com
https://www.sas.com
https://searchbusinessanalytics.techtarget.com
https://scm.ncsu.edu
https://www.cips.org
04/04/2021 Questionnaire on Logistics at Milma
https://docs.google.com/forms/d/1YWK070sfkblf-vcuSQWwLoDxK3y1S1f8KCqnPnfR2Q4/edit 1/4
1.
Mark only one oval.
Not important
Indifferent
Important
2.
Mark only one oval.
Yes
No
3.
Mark only one oval.
Yes
No
Questionnaire on Logistics at MilmaThis questionnaire is used to get more in sights about the supply chain at Milma
*Required
How important is logistics at Milma? *
Is Milma taking steps to improve the logistics? *
Should logistics be a part of the company's strategy? *
04/04/2021 Questionnaire on Logistics at Milma
https://docs.google.com/forms/d/1YWK070sfkblf-vcuSQWwLoDxK3y1S1f8KCqnPnfR2Q4/edit 2/4
4.
Mark only one oval.
Monthly
Quaterly
Yearly
More than a year
5.
Mark only one oval.
Quality
Timely Delivery
Error - free
Cost
6.
Mark only one oval.
Tracking
Lead time
Cost
Reliability
How often is logistics critically reviewed at Milma? *
What are the quality metrics used in logistics at Milma? *
Problems that influence logistics at Milma? *
04/04/2021 Questionnaire on Logistics at Milma
https://docs.google.com/forms/d/1YWK070sfkblf-vcuSQWwLoDxK3y1S1f8KCqnPnfR2Q4/edit 3/4
7.
Mark only one oval.
Yes
No
Maybe
8.
Mark only one oval.
Time saving
Cost saving
Increase traceability
Competitive edge
9.
Mark only one oval.
Yes
No
May be
10.
Mark only one oval.
Transportation and delivery
Inventory management
Packaging
Overall process
Will implementation of technology solve the problems related to logistics? *
What effects will technology have on logistics? *
Do you think use of technology in logistics will increase the cost involved? *
Which logistic activity at Milma requires improvement? *
0%SIMILARITY INDEX
%INTERNET SOURCES
0%PUBLICATIONS
%STUDENT PAPERS
1 <1%
Exclude quotes Off
Exclude bibliography On
Exclude matches Off
A Study on Supply Chain Analytics At MilmaORIGINALITY REPORT
PRIMARY SOURCES
I. H. Yigin, H. Taşkin, I. H. Cedİmoglu, B. Topal."Supplier selection: an expert systemapproach", Production Planning & Control,2007Publication
Top Related