Ch1 Evans BA1e

8/10/2019 Ch1 Evans BA1e

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We can first use descriptive statistics by examining historical data on customer flow

Examine the number of customers based on different days of the week, month (perhaps even year).

Also examine the number of customers at different times of the day.

By summarizing the common traits of busy times/days, we can develop a strategy on when to open

The most important data would be the number of customers per time period (hour, or 15-minutes,


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up more cash registers.

epending on how flexible the work force scheduling is).


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Arrival Day of The Week (Month/Year)

Length of Stay

Use of Mini Bar

Cash or Credit Customer

Use of Extra Hotel Services (such as Wi-Fi, Room Service, On Demand Movies etc.)

Using these data measurements, the hotel can decide which customers are likely to spend more mo

For example, if a certain group of customers are likely to spend a lot of money on room service, tho

Or, using the arrival day and length of stay, one can identify whether a customer is a business travell

These business travellers might spend more money if their company is paying for the trip and identi


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ney within the hotel.

e customers may be offered discounts at nightly stay prices.

ler or not (we can assume that they tend to arrive weekdays and don't stay the weekend)

ying them may prove to be lucrative.


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Customer Arrival Date

Customer Arrival Time

Customer Service Time

Purchase Type

Revenue Generated

Just using these basic types of data, a fast food restaurant will be able to identify rush hours in a giv

Using this information, they can decide how many registers to open at different times of the day.

Also looking at the purchase patterns, they can decide on how to stock up on different food items o


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n day.

different days of the week.


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Cust ID Region Payment Transaction C Source Amount Product

10001 East Paypal 93816545 Web $20.19 DVD

Ordinal Categorical Categorical Ordinal Categorical Ratio Categorical


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Time Of Day

22:19

Interval


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Homeowner Credit Score rs of Credit His volving Balan volving Utilizati Decision

Y 725 20 11,320$ 25% Approve

Categorical Interval Interval Ratio Ratio Categorical


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Gender Age Ethnicity

Length of

Residency Satisfaction

Quality of

Schools

Categorical Interval Categorical Interval Ordinal Ordinal


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MODEL:

BALANCE = -17,732 + 367 x AGE + 1300 x YEARS EDUCATION + 0.116 x HOUSEHOLD WEALTH

a. 367 The average account balance increases by approximatel

1300 The average account balance increases by approximatel

0.116 The average account balance increases by approximatel

b. AGE 36 years old

EDUCATION 16 years

WEALTH 175,000.00$

PREDICTED BALANCE 36,580.00$


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ly $367 for each year increase in AGE

ly $1300 for each year increase in EDUCATION

ly $0.116 for each $1 increase in WEALTH


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MODEL:

D = k - pP + aA + tT + qQ

a. P: As Price increases, Demand goes down.

A: As Advertising increases, Demand goes up.

T: As Transportation increases, Demand goes up.

Q: As Product Quality increases, Demand goes up.

b. The variables do not influence each other.

c. The relationship of D to P is overly simplistic. If P is too high, the model predicts negative

The variables might influence each other as well. For example, high production quality m


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D, in fact D will be at least ZERO.

ay cost more and hence may have a higher price tag.


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Variable Cost 9.00$ /unit Variable Cost 12.00$ /unit

Fixed Cost 4,000.00$ Fixed Cost -$

a. VOLUME 1000 units

Cost of Manufacturing 13,000.00$

Cost of Outsourcing 12,000.00$


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E: Earnings

T: Turnover

S: Sales

C: Cost of Sales

TI: Total Investment

CA: Current AssetsFA: Fixed Assets T = S / TI

MC: Mill Cost of Sales

SC: Sales Expense

FC: Freight and Delivery

AC: Admin Costs

TI = CA + FA

Turn

Total Investment

Current Assets Fixed Assets


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ROI = T * E / S

E = S - C

ROI

over Earnings

SALES Cost of Sales

Mill Cost ofSales

SellingExpense


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C = MC + SC + FC + AC

Freight &Delivery

AdminCosts


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a 10

x -0.25 0 0.5 1 1.5

0.25 14.14 10.00 5.00 2.50 1.25

0.50 11.89 10.00 7.07 5.00 3.54

0.75 10.75 10.00 8.66 7.50 6.50

1.00 10.00 10.00 10.00 10.00 10.001.25 9.46 10.00 11.18 12.50 13.98

1.50 9.04 10.00 12.25 15.00 18.37

1.75 8.69 10.00 13.23 17.50 23.15

2.00 8.41 10.00 14.14 20.00 28.28

2.25 8.16 10.00 15.00 22.50 33.75

2.50 7.95 10.00 15.81 25.00 39.53

When b


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-

5.00

10.00

15.00

20.00

25.00

30.00

35.00

40.00

45.00

- 0.50 1.00 1.50 2.00 2.50 3.00

SAMPLE SKETCHES

b


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MODEL:

G = (m x d ) / vf

m 24 miles

d 20 days

480 total miles per month

vf 30 mpg

G 16 gallons used per month


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DEMAND MODEL

D = 2000 - 3P

COST MODEL

C = 5000 + 4D = 5000 + 4 x ( 2000 - 3P) = 13000 - 12P

TOTAL REVENUE

TR = D x P = ( 2000 - 3P) x P = 2000P - 3 P^2

TOTAL COST

TC = 13000 - 12P

TOTAL PROFIT

TP = TR - TC

= 2000P - 3 P^2 - (13000 - 12P)

= -13,000 + 2012 P - 3 P^2


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P D

600.00$ 500

300.00$ 1200

Revenue = P x D= P x (-2.333 P + 1900 )

= -2.333 P^2 + 1900 P

P Revenue

1.00$ 1,898$

10.00$ 18,767$

100.00$ 166,670$

1,000.00$ (433,000)$

500.00$ 366,750$

750.00$ 112,688$

250.00$ 329,188$

375.00$ 384,422$

425.00$ 386,102$


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P + 1900

0.00 $400.00 $500.00 $600.00 $700.00

vs Demand

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Ch1 Evans BA1e