Supply chain analytics essentials

Supply Chain Analytics - Essentials
Dheenathayalan.R

Objective
To share the learnings I had from the course –
Supply Chain Analytics Essentials
by
Dr.Yao Zhao,
Professor in Supply Chain Management
Rutgers Business School
(Rutgers the State University of New Jersey)
Offered through Coursera.
Thanks to TamilNadu Skill Development Corporation
2Dheenathayalan.R Hosur

Flow of Presentation
• Introduction – Supply chain management
• Definition – Supply chain management
• Difficulties – Supply chain management
• Supply and demand
• Supply chain analytics
• Examples
• Types of analytics in supply chain management
• Supply chain domains
• Job opportunity analysis
• In addition to the contents from the original course, I had added some more
details for better understanding.
• Thanks to authors of the book- Designing and Managing the Supply
Chain,concepts,strategies and case studies by David Simchi – Levi, Philip
Kaminsky,Edith Simchi – Levi, Ravi Sankar , Investopedia, Wikipedia etc

Introduction
Global markets, products with shorter life cycles, heightenend
expectations of customers
Together with
Continuing advances in communication and
transportation technologies
(For example, Mobile communication, Internet and overnight delivery)
Forced business enterprises to focus on Supply Chain.

Introduction
• Product life cycle: Product life cycle refers to the length of time, a
product is introduced to consumers into the market until it's
removed from the shelves.
• The life cycle of a product is broken into four stages—introduction,
growth, maturity, and decline.

Introduction
• Raw materials are procured – items are produced at one or more
factories – shipped to warehouses for intermediate storage – shipped
to retailers or customers.
• So, to reduce cost and improve service levels effective supply chain strategies are
needed.
• Supply chain is also referred as logistics network.
Strategy:
• A general direction set for the company and its various components to achieve a desired state
in the future. Strategy results from the detailed strategic planning process.
• Strategy is a general plan to achieve one or more long-term or overall goals under conditions of
uncertainty.

Introduction
Supply:
• Supply is a fundamental economic concept that describes the total
amount of a specific good or service that is available to consumers.
Chain:
• A series of connected elements.
Management:
• Management is the coordination of all resources through the
process of planning, organizing, staffing, directing and controlling
in order to attain stated goals.

Definition - Supply Chain Management
Supply chain management is a set of approaches
utilized to efficiently integrate suppliers,
manufacturers, warehouses and stores, so that
merchandise is produced and distributed at the right
quantities to the right locations and at the right time in
order to minimize system wide costs while satisfying
service level requirements.
• Merchandise: goods that are for sale.
• Efficiently: in a well-organized and competent way.
• Effective – Adequate to accomplish a purpose; producing the intended or expected
result.
• Efficient – Performing or functioning in the best possible manner with the least
waste of time and effort.
• The difference between effectiveness and efficiency – Being effective is about doing
the right things, while being efficient is about doing things right.

Supply chain Management

Difficulties in supply chain management
• Supply chain strategies cannot be determined in isolation. They are
directly affected by another chain that most organization have, the
development chain that includes set of activities associated with new
product introduction.
• It is challenging to design and operate a supply chain so that total system
wide costs are minimized and system wide service levels are
maintained.
• The process of finding the best system wide strategy is known as global
optimization.

Difficulties in supply chain management
• Uncertainty and risk are inherent in every supply chain.
• Customer demand can never be forecast exactly.
• Travel times will never be certain.
• Machines and vehicles will breakdown.
• Industry trends ,outsourcing ,offshoring,lean manufacturing that focus on
reducing supply chain costs significantly increases the level of risk in the
supply chain.
“Thus supply chain needs to be designed and managed to
eliminate as much uncertainty and risk as possible, as well as
deal effectively with uncertainty and risk that remain.”
• The development chain and supply chain intersect at the production
point.
• Optimization: The action of making the best or most effective use of a situation or resource.
• Uncertainty: It refers to situations involving imperfect or unknown information.
• Risk: It is simply effect of uncertainty. It is the possibility of something happening bad.

Supply and Demand
Supply and demand form the most fundamental
concepts of economics.
Whether you are an academic, farmer, pharmaceutical
manufacturer, or simply a consumer, the basic premise
of supply and demand equilibrium is integrated into
your daily actions.
Only after understanding the basics of these models can
the more complicated aspects of economics be mastered.

Demand
As the
• Price of a good
increase, the demand
for the product will
decrease.
(except for a few
obscure situations).

Supply
When
prices of a product
increase,
producers are willing
to manufacture more
of the product
to realize greater
profits.

Supply & Demand
Finding an equilibrium
 Consumers look for lowest cost.
 Producers look for increasing output
only at highest costs.
 When prices become unreasonable,
consumers will change their
preferences and move away from the
product.
 A proper balance must be achieved
whereby both parties are able to
engage in ongoing business
transactions to the benefit of
consumers and producers.
 Theoretically, the optimal price that
results in producers and consumers
achieving the maximum level of
combined utility occurs at the price
where the supply and demand lines
intersect.
 The price of a commodity is
determined by the interaction of
supply and demand in a market.

Supply Chain Analytics
• Supply chain analytics - is where analytics meets supply
chain management.
• It is an emerging area that aims to apply data analytics to
supply chain management to generate a significant social
and/or economic impact.
• Analytics:
Analytics is the method of logical analysis. Analytics is the systematic
computational analysis of data or statistics. It is used for the discovery,
interpretation, and communication of meaningful patterns in data. It
also entails applying data patterns towards effective decision making.
 Analysis is focused on understanding the past; what happened and
why it happened.
 Analytics focuses on why it happened and what will happen in the
future.

Supply Chain Analytics
• Data analytics: Data analytics is the science of analyzing raw data
in order to make conclusions about that information.
• The supply chain is a complex network of companies that meets
demand by supply through many stages from factories or plants to
distribution centers or warehouses and to stores or demand
fulfillment centers.
• It largely determines customer satisfaction, thus revenue, cost of
goods sold, and operating cost for a company.
• Supply chain is always data-rich.
• The complex flows of materials and money through the network
often generate a large amount of data every day.
• The analysis and effective use of this data can significantly
improve revenue and reduce cost, and thus provide companies a
long-term competitive advantage.

Supply Chain Management
• Lower cost leads to improved profit and reduced price, which
increase profit and market share.
• Improved customer satisfaction leads to better relationships with
customers which increase sales.
• However, lower cost and higher customer satisfaction are often
conflicting objectives.
• Cost reduction may hurt customer service levels.
• To improve satisfaction, you may have to spend more. So it is
difficult to achieve both in the same time.
• But if you do, you can build a long-term competitive advantage.

Lesson
In the long run, Cost
Efficiency and Customer
Satisfaction beat pure
marketing plays.
Example 1: Wal-Mart Vs K-Mart
Wal-Mart
• Wal-Mart in 1979 was a small
discounted chain store with 229 stores,
and a revenue per store around $3.5
million.
• Wal-Mart invested in supply chain
technologies.
• The supply chain technology enabled
Wal-Mart to provide customers with
access to goods when and where they
wanted them.
• This is customer satisfaction. This is
high service level.
• So customers visiting Wal-Mart can
always get what they want.
• At the same time, Wal-Mart developed
a competitive cost structure and this is
cost reduction.
• After 24 years, in year 2003, Wal-Mart
grew into the number one company on
Fortune 500 list with 4688 stores and a
total revenue of $245 billion.
K-Mart
• K-Mart at that time, which had 1,891
stores and a revenue per store $7.2
million.
• K-Mart focused on flashy marketing
and advertising.
• After 24 years, in year 2003, K-Mart
declared bankruptcy.

Example 2 – Computer Industry
• Computer companies have the same technologies, such as CPU from Intel and
operating systems from Microsoft.
• So they're not really competing on technologies but on customer services and
cost structure.
• On one hand, technology advances fast, which means product life-cycle is
short and inventory cost is high due to obsolescence so they cannot hold
inventory.
• On the other hand, demand is highly unpredictable and customers expect high
availability of products and fast delivery. So you must provide high service
levels.
• Obsolescence :
It is the state of being no longer needed because something newer or
more efficient has been invented.
• Inventory :
In common it refers to all the items, goods, merchandise, and materials held by
a business for selling in the market to earn a profit. The four types of inventory
most commonly used are Raw Materials, Work-In-Progress (WIP), Finished
Goods, and Maintenance, Repair, and Overhaul (MRO).

Compaq
• Compaq's strategy focused on the
economies of scale by producing
the product in batches and
selling them by retailers.
• This resulted in high inventory
cost but lower production and
shipping costs.
• Compaq has a higher gross
margin than Dell but also a higher
days of inventory and a higher
operating cost over sales.
Dell
• Dell's strategy is the complete
opposite. It focused on inventory
cost and speed to market by
configure to order in production
and direct sales to end customers.
• This resulted in a lower
inventory cost but high
production and shipping costs.
• Dell has about 10% lower selling
price than Compaq. So here is the
key point. Even with a lower
price, Dell can make more money.
• Dell outperformed Compaq by
about 1% in operating margin.
Dheenathayalan.R Hosur 22

Company C
• Inventory = 80days
• Intel came out with a new
450-megahertz chip.
• Going to get the market
later based on the
decision related to
inventory cost.
Company D
• Inventory = 11days
• Intel came out with a new
450-megahertz chip.
• Going to get the market
69days sooner than
company C.
Lesson:
In the computer industry, inventory can be a pretty massive risk
because if the cost of materials is going down 50% a year and you got
two or three months inventories versus eleven days, you've got a
pretty big cost disadvantage.

Example 3 – Wal-Mart Vs Amazon
Wal-Mart
• Wal-Mart is the world's largest
retailer, mainly offline. It sells
anything.
Amazon
• Amazon is the world's leading
online seller. It sells anything
including those of third-party
sellers.
This is the combat between the best offline retailer and the best
online seller.
The outcome will determine the future of retailing in specific
countries of presence and around the world.

Analytics & Supply chain
Analytics is critical to supply chain management –Why?
1) Supply chain often involves a complex network of facilities and
products, and thus, it's hard to optimize.
2) Supply chain evolves over time. It is dynamic with often seasonal
and random demand and supply, and thus, it's hard to predict.
3) Supply chain is composed of many self-interested partners with
conflict of interest, and thus, hard to coordinate.
• In addition to the complex network and uncertainty, supply chain is
also hard to manage because trading partners may have a conflict of
interest.
• As a supplier, you always want from your retailer a stable volume,
slow delivery, meaning the retailer can wait, small variety, and a
high price.
• As a retailer, you want the exact opposite. You want your supplier
to be flexible in volume, can provide quick and flexible delivery.
You also want large variety and lower cost.
• This conflict of interest together with uncertainty can cause huge
problems.

Analytics & Supply chain
 Analytics are also critical because of the rich data available in
today's supply chains, such as demand data, shipping, and
delivery data, inventory data, production and outsourcing
data, and so on, as well as more unstructured data from
external sources, such as blogs and news, weather and traffic,
Twitter, and so on and so forth.
 An effective use of such data can help firms to respond
quicker and better to the changing environment.
 Analytics focus on qualitative insights and solutions based on
the data. They are different from qualitative guesswork.
 Output of analytics can answer questions such as which
strategy is the best, by how much, under what conditions?
As such, decisions can be much more precise and
actionable.

Types of Analytics
There are four types of analytics in supply chain management.
1) Descriptive analytics – It helps find out what happened and
so provide a clear assessment of the current situation.
2) Diagnostic analytics – It aims to discover why it happened,
and thus, the root causes.
3) Predictive analytics – It makes predictions for the future.
4)Prescriptive analytics - It provides decision support to
generate the desired outcome.

Supply chain domains
• A domain is functional areas of a supply chain.
In a typical manufacturing firm, the primary activities can be
classified into five categories:
Source, Make, Move, Sell, and Service
1) Source refers to purchasing and procurement.
2) Make refers to production and packaging.
3) Move refers to transportation and logistics.
4) Sell is about pricing, promotion, and retailing.
5) Service refers to customer services such as maintenance and
support.
Human resources, technology, and finance, accountings are
supporting activities.

Source Analytics
• Source analytics is applied to procurement, sourcing,
and ordering.
Key Performance Indicators(KPI):
1) Purchasing cost.
2) Quality or the defects.
3) Delivery in terms of lead time and on-time
performance.
4) Flexibility and security of the supplier.
Objective
To maximize the value and minimize the risk of supplies.

Source Analytics
Typical problems:
a) Strategic sourcing by spend analysis.
b) Supplier performance management.
c) Order management.
Strategic sourcing by spend analysis
 Spend analysis can identify opportunities for cost saving and risk
reduction.
 Spend analysis can provide important and real-time information of
the total spend by factory or facility, by material category, by the
type of contract, by vendor, and also over time in terms of the dollar
value and the percentage.

Source Analytics
Supplier performance management:
 To monitor quarter to quarter supplier performance scores to ensure
that the suppliers have a constant good performance.
 The pain points are the contracts compliance issues, supplier
bankruptcy risk, inconsistent supplier performance over time, and a
non contracted maverick spending going un-noticed.
 Analytics can help monitoring and tracking these abnormalities and
provide early signals before the company runs into troubles.
Maverick spending - Purchases made outside of agreed contracts.

Source Analytics
Order management:
Order Management is a common problem in purchasing.
Pain points
a) Too many small orders
b) Few large orders
• Too many small orders :The purchasing department may be
flooded by many small orders. It will slow the buyers by increasing
their workload.
• Few large orders :Large orders, although may enjoy a discount,
may result in high inventory cost due to limited shelf-lives.

Make Analytics
Make analytics is applied to production and inventory
systems.
Key performance indicators
1) Cost.
2) Time( such a cycle time, response time).
3) Variety.
4) Quality.
Objective
To manage machines, workforce and materials to meet
the demand in the most productive way.

Make Analytics
Typical problems :
a) Production planning and scheduling.
b) Workforce management.
c) Inventory management.
Production planning and scheduling:
 Production plan and schedule is made to increase the utilization of
the machines, reduce cost, and improve productivity.
 Analytics helps to determine the optimal way to utilize the
resources such as workforce, materials and machines to meet the
demand in the most efficient way.
Pain Points
a) Complexities generated by seasonal demand.
b) Complex bill of materials.
c) Varying raw material cost.
d) Varying capacity limits.

Make Analytics
Workforce management
Pain point:
Match between the workforce size and demand.
 Workforce should be adjusted over time.
 The problem is multiple types of workforce such as full-time
employees and consultants, with different pay rates and flexibility.
 Full-time employees, who have a small hourly wage but a high
training and let go cost.
 Consultants are the opposite, Their hourly wage is twice as much as
a full-time employees but they do not have a hiring and firing cost.
Analytics can determine optimal hiring plan and staffing schedule to
meet a demand at a minimal cost.

Make Analytics
Inventory management
Inventory is a critical component to almost every supply
chain.
Pain point:
1)Excessive inventory for some products - It is a waste of investment
and space.
2)Shortage for some other products – It hurts customer satisfaction
and reduces their willingness to buy.
Sales loss and high inventory cost in the same time. The
excessive inventories also occupy valuable space which could have been
used to sell other products.
Analytics can help reducing the excessive inventory and
preventing stock-out and thus improve service level and reduce cost.

Move Analytics
Move Analytics is applied to distribution and logistics.
Key performance indicators :
1) Cost (shipping cost, inventory cost, warehousing cost).
2) Time (fulfillment time, and on-time performance).
Objective
It is to fulfill demand timely and cost efficiently.
Typical problems
a) Fulfillment diagnosis.
b) Distribution and logistics planning.
c) Transportation management and Logistics network design.

Move Analytics
Fulfillment diagnosis
Pain Points:
a) Logistics systems are susceptible to many disruptions.
b) Logistics systems can perform poorly or even break down from
time to time.
 Logistics systems are typically very complex.
 It is hard to identify the root causes, manage, stabilize, and improve
the system performance.
 Analytics can analyze the fulfillment data in connection to various
factors, and can quickly identify and pinpoint the most likely
causes.
 Without checking up each step of the system physically, which may
take years, analysis of the performance data can quickly identify the
most likely causes.

Move Analytics
Distribution and logistics planning
Pain Points:
1) Conflicting needs of inventory and transportation.
2) High cost and low service levels.
 More frequent shipping can reduce inventory but increase
shipping cost.
 Failing to balance shipping and inventory, may lead to a higher
logistics cost together with a poor customer service level.
 Analytics can help balance the needs of shipping and inventory
optimally, and achieve the global optimal with reduced cost and
improved service levels.

Move Analytics
Transportation management and logistics network design
Pain Points:
1) Small load factor - trucks are not as full as expected - Empty spaces
in truck means a waste of shipping capacity.
2) The use of smaller and less economical trucks - Less economical
trucks means a higher shipping cost.
3) Inefficient routes - Inefficient routes mean poor customer services
and higher shipping cost.
Analytics can help improving the usage of bigger and more
economical vehicles, and a chance of full load and thus reduce the
transporting cost.

Sell Analytics
Key Performance Indicators
1) Revenue.
2) Customer satisfaction.
3) Cost.
Objective
To increase revenue and reduce cost.
Typical problems
a) Demand planning.
b) Product selection.
c) Pricing and promotion.

Sell Analytics
Demand planning
One important challenge in selling is demand planning for new
products .
Pain points
a) New product launch.
b) Demand is hardly predictable.
 Forecast errors can be high, thus it is hard to plan for capacity,
supply and workforce.
 It is also impossible to make wise decisions on product features,
distribution channels, advertising budget, and so on.
 Analytics can help to make more accurate forecast for demand, and
assess the impact of various factors on demand.

Sell Analytics
Product selection
Pain Points
a) A significant portion of a company's products may not sell well
and thus holding these items in inventory is a waste of money. (It
is a waste of money to carry products that do not sell.)
b) The non-productive items occupy space which could have been
used to sell other more productive items. (The non-productive
items also waste the opportunity of selling other more productive
items.)
Analytics can help optimizing product offerings by identifying and
replacing less productive items with more productive ones.

Sell Analytics
Pricing and promotion
Pain Points
a) The price discount significantly increases demand beyond expectation, and so
the firm stocks out and loses sales and customers' good faith. (You can lose
sales and customers' good will if you do price promotion but stock out.)
b) The price discount has no impact on the demand, so the firm just loses profit.
(You just lose the profit due to the discount if the discount does not increase
the demand.)
Analytics can make more accurate forecast on how price discounts may affect
the demand. That is the price elasticity. So, the company can select the right
product and timing for price promotion to increase profit and customer
satisfaction.
The responses of demand to price discounts are actually hidden in the historical
data.
Price elasticity of demand is an economic measure of the change in the quantity
demanded or purchased of a product in relation to its price change.

Supply chain analytics –
Job opportunity analysis
 Job: It is the work that we do regularly to earn money. It is a
specific task done as part of the routine of one's occupation or
for an agreed price.
 Opportunity: It is a chance to do something that we would
like to do; a situation or a time in which it is possible to do
something that we would like to do.
 Analysis: It is the process of breaking a complex topic or
substance into smaller parts in order to gain a better
understanding of it.
 Job opportunity analysis: It is the analysis process done to
find the best suited job/dream job to earn money among the
lot of opportunities available in front of us.

 The greatest shortages of professionals in area of supply chain
management are at the intersection of process and analytical
mastery.
 It shows that demand and supply planning, data science, and
sales and operations planning tops the list of positions in
greatest demand.
 It is also found that more than 50% of the survey respondents
selected problem solving and analytical skills as the most
important skills.
 In preparation, one need to have both supply chain domain
knowledge and data analytics skills.
 One also need to learn how to apply data analytics to
supply chains to generate an economic impact.
 Additional Skills required include good computer skills,
organisational skills, communication skills etc.

How to find out dream job?

Supply chain analytics essentials

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