John Deere Financing and Operation

Optimization Strategy by

Rameez Rosul

Introduction

Hi I am Rameez , I am an Analyst with John Deere .We make agricultural machinery. My manager John is worried lately

It turns out that that he has been given a task to find a road map for underwriting strategies and reducing operation costs .

John Deere's revenue by region 2008-2016

John Deere's (Deere & Company's) revenue from 2008 to 2016, by region

(in million U.S. dollars)

Source: Deere & Company ID 271864

Note: United States; 2008 to 2016

17,065

14,823

16,611

19,214

22,737

23,852

22,391

18,750

16,742

11,008

7,961

9,036

12,41512,999

13,495 13,147

9,616 9,339

0

5000

10000

15000

20000

25000

30000

2008 2009 2010 2011 2012 2013 2014 2015 2016

Revenue in

mill

ion U

.S. dolla

rs

U.S. and Canada Outside U.S. and Canada

Further information regarding this statistic can be found on page 8.

http://www.statista.com/statistics/271864/revenues-of-john-deere-by-region-since-2008/

John shares

some insight :

Low prices for major

crops

Over production of

crops

Preference for

Leasing of machinery

Farmers refuse loans

and thus sales suffer

Used vehicle market

increase

Possible

reasons for

decline

Problem statement

Which region will be most profitable for the underwriters to provide financial options ?

Solution

Using past data of crop value, we will find crops that are most probable to be of high value .

The crop prices and harvest size will determine value of crops

Following up with its regions they are grown in .

John “how are you defining High/low

value “

BY Creating two engines in our model

Weather Engine :BY using the weather data to decide the value of harvest next year. We are taking 50/50 probability for this model.

Value Engine :This contains the data of the prices ,harvest size and other market forces to determine the value .

We use the max ,min and average values for determining the value .

Assumptions in the model

Our Model is taking overall country averages to

distinguish our target crops .

The weather engine has been kept at 50 %

good

It is assumed that good weather will give good

crops

Using past data for analysis is a good indicator

Rameez to John

Rameez ”John, As our initial analysis

clearly shows that field crops are doing

well , we should proceed further analyzing

field crops .

John” Yes you are right . Our majority

products also deal with field crops “

Simulations results using 1000 Trails

Adding uncertainty with respect to weather and

market forces

model gave us

• Wheat

• Rice

• Hay

• Cotton

• Soybean

• Corn

Probability of corn 51% being high value

49% being low value crop

Probability of Hay 45% being high value

55% being low value crop

Probability of Rice 05% being high value

95% being low value crop

Probability of Wheat 40% being high value

60% being low value crop

Probability of Soybean 51% being high value

49% being low value crop

Probability of Cotton 11% being high value

89% being low value crop

John asks:

“Now that we have found the crops to concentrate on ,

Which regions do you suggest for the crops in question

?.”

Solution :”By finding the expenditure , the area under

harvest and the history of growing patterns for the

crops ,we come up with the common states”

Rameez to John

Finding probable high value crops

and regions with favorable aspects we

can make our operation lean in terms

of inventory and assets

States with large cultivated area

States with most expenditure

Common states for wheat

Common states for Hay

Common States for Rice

Common States for Soybean

Common States for Corn

Common States for Cotton

John to Rameez

“Great Job Rameez ,you truly are a asset to the team and

the company ,where will we be without you .you are God

send”

Rameez replies”But wait John! there is more .What if you

wanted to further rank the states for crops like Wheat.

John”You read my mind .do tell”

Rameez ”we ranked the states further on bases of

1)Forecast Machinery expenditure growth%

2)Forecast area under cultivation growth%

Recomndation

John Summarizing

So Rameez you suggest that we should lend

to farmers next year who plan to grow

Corn

Hay

Soybean

Wheat

John Summarizing :Ranking for States

Corn: Michigan, Indiana, Missouri, Wisconsin,

Ohio, Illinois, Iowa

Hay: Michigan ,Missouri, Wisconsin, Ohio, Illinois,

Iowa

Wheat: Michigan, Indiana, Missouri ,Ohio, Illinois

Soybean: Michigan, Indiana, Missouri, Wisconsin,

Ohio, Illinois, Iowa

Ok John I am leaving for the day .

Thank you Does any one other than john have any question?