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dem82 [27]
2 years ago
11

You are managing a project to build an urgent care clinic. Your company is expanding and has constructed 25 clinics so far. Whic

h estimating technique makes the most sense to use in this situation?
Business
1 answer:
Dmitry_Shevchenko [17]2 years ago
6 0

Answer:

Delphi technique

Explanation:

The Delphi model is a technique of group communication in which a panel of experts reach consensus on a set of questions and discussions. This is used to predict or to forecast. First, choose an effective facilitator and experts with relevant expertise, and ensure that the issue is well established after that they reach with a decision

Therefore in the given case, the delphi technique is used

You might be interested in
Ultra Co. uses a periodic inventory system. The following are inventory transactions for the month of January: 1/1 Beginning inv
creativ13 [48]

Answer:

$830,000

Explanation:

Ultra Co.'s inventory for January:

Date               Number of units   Unit balance      Unit cost     Total cost   

January 1             20,000                20,000               $13         $260,000       

January 20          30,000                50,000               $15         $710,000          

January 23          40,000                90,000               $17        $1,390,000      

<u>January 31          (50,000)                                       ($16.60)    ($830,000) </u>

Ending inventory                             40,000                              $560,000

Using the last-in, first-out (LIFO) method, the COGS = (40,000 units x $17 per unit) + (10,000 units x $15 per unit) = $680,000 + $150,000 = $830,000                                          

5 0
2 years ago
As part of a major plant renovation project, the industrial engineering department has been asked to balance a revised assembly
ioda

Answer:

A)Minimum = 0.2 minutes

Maximum = 4.6 minutes

Cycle time = = 2 minutes per unit

B) Number of Stations = 3

D) the percentage of idle time for the assignment in decimal = 0.43

Explanation:

A) Operating output = 240 units per 8hours.

Converting to per hour, we get; 240/8 = 30 units per hour.

Minimum cycle time = longest task time

Maximum cycle time = sum of task times

Minimum = 0.2 minutes

Maximum = 0.2 + 0.4 + 0.2 + 0.4 + 1.2 + 1.2 + 1.0 = 4.6 minutes

Now, operational time(OT) is 8 hours a day. Converting that to minutes, we have =60x8 = 480 minutes

Cycle time(CT) = OT (per day) /desired output

Therefore, calculated cycle time = 480/240

= 2 minutes per unit

B) Number of stations = Maximum time / CT

= 4.6/2 = 2.3 which is approximately 3 stations

C) The task diagram is drawn in image 1 attached. Therefore, we can assign tasks based in the greatest number of following tasks as follows;

Task Number of following tasks

a 4

b 3

c 2

d 2

e 1

f 1

g 0

D) for the idle time from the assigned tasks in "c" above, from the "image 2" attached; the percentage of the idle time will be=

Total remaining time of tasks without remaining feasibility tasks/ {(number of these tasks) x(CT)}

Which gives percentage of idle time = (0.8 + 0.8 + 0.8 + 1.0)/{(4)x(2)}

= 3.4/8 = 42.5%

Since we are to convert to decimal,

= 0.425 approximately 0.43

4 0
2 years ago
What is the most common function performed by electronic data interchanges?
Ad libitum [116K]
What is the most common function performed by electronic data interchanges? S<span>ending electronic equivalents of structured documents between different organizations. An electronic data interchange is an interchange between computers to other computers within the same type of business. These interchanges are used for the programs to communicate electronically. </span>
5 0
2 years ago
Neighborhood Insurance sells fire insurance policies to local homeowners. The premium is $270, the probability of a fire is 0.1%
Nonamiya [84]

Answer:

Explanation:

There are two possible payout scenarios - 1) There is a fire 2) There is no fire. So payout table will look like below:

Scenario 1 Scenario 2

Fire No-Fire

Payout 260,000 0

Probability 0.10% 99.90%

Answer B)

Expected Value of profit = Profit from scenario 1 * probability of scenario 1 + Profit from scenario 2 * probability of scenario 2

Profit from scenario 1 = Premium Collected - Insurance Payout = 270 - 260,000 = -259730

Profit from scenario 2 = Premium Collected

Scenario 1 Scenario 2

Fire No-Fire

Profit -259730 270 given

Probability 0.10% 99.90% given

Profit*Probability -259.73 269.73 10 =Expected Value

Variance

= (Profit from scenario 1)^2 * probability of scenario 1 + (Profit from scenario 2)^2 * probability of scenario 2 - (Expected Value)^2

Standard Deviation = Square root of variance

Scenario 1 Scenario 2

Variance Fire No-Fire

Profit^2 67,459,672,900.00 72,900.00

Probability 0.10% 99.90%

Profit^2 * Probability 67,459,672.90 72,827.10 67,532,400.00 =Variance

8,217.81 =Standard Deviation

So, the expected income is $10, with a variance of $8,217.81

Answer C)

Joint Probability of two independent events = probability of event 1*probability of event 2

Scenario Probability

Single Case - No fire 99.90%

Single Case - fire 0.10%

Scenario Join Probability Payouts

No Fire 99.8001% 0

One Fire 0.0999% 260,000

Two Fire 0.0001% 520,000

Answer D)

Scenario Join Probability (p) Payout (b) Premium (a) Profit (x) = (a-b) xp x2p

No Fire 99.8001% 0 540 540 538.92 291,017.09

One Fire 0.0999% 260000 540 (259,460) (259.20) 67,252,172.11

Two Fire 0.0001% 520000 540 (519,460) (0.52) 269,838.69

Summation 279.20 67,813,027.89

Expected Value (E)= Sum(XP)= 279.20

Variance (Var)= x2p-E2= 67,735,074.95

Standard Deviation = Sqrt(Var) 8,230

Answer E) From b & d, we can see that expected profits have increased drastically with increase in number of policies, though variance and S.D. of this expected profits remained similar

8 0
2 years ago
Now consider the case in which the manufacturer offers a marginal unit quantity discount for the plywood. The first 20,000 squar
Sindrei [870]

Answer:

Explanation:

We can use the following method to solve the given problem

We are given following

Annual demand,

D = 20000*12

D = 240,000 sqft

Fixed order cost, is given as

S = $ 400

Considering the unit cost, is given as

C = $ 1

Holding cost, H = 1*20% = $ 0.2

EOQ = sqrt(2DS/H)

= √(2*240000*400/0.2)

= 30,984 sq ft

This is higher than 20,000 and less than 40,000 sq ft. For this reason, the applicable price for this quantity is $ 0.98

For C = $ 0.98, holding cost, H = 0.98*20% = $ 0.196

Revised EOQ = sqrt(2*240000*400/0.196) = 31,298 sq ft

Total annual cost of EOQ policy = D*C + H*Q/2 + S*D/Q

= 240000*0.98 + 0.196*31298/2 + 400*240000/31298

= $ 241,334.5

Now consider the next level of price, C = $ 0.96

Holding cost, H = 0.96*20% = $ 0.192

EOQ = sqrt(2*240000*400/0.192)

= 31633 sqft

This amount is will not be feasible for this price, because it requires a minimum order of 40000 sqft.

Therefore, Q = 40,000

Total annual cost = 240000*0.96 + 0.192*40000/2 + 400*240000/40000

Total annual cost = $ 236,640

Total annual cost is lowest for order quantity of 40,000 sq ft.

1) Optimal lot size = 40,000 sq ft.

2) the annual cost of this policy

= $ 236,640

3) the cycle inventory of plywood at Prefab = Q/2 = 40000/2

At prefeb= 20,000 sq ft

4) let's assume the manufacturer sells all plywood at $ 0.96, then

Holding cost, H = 0.96*20%

H= $ 0.192

EOQ = sqrt(2*240000*400/0.192)

EOQ = 31633 sqft

Total annual cost = 240000*0.96 + 0.192*31633/2 + 400*240000/31633

Total annual cost = $ 236,471.6

Difference in total annual cost = 236640 - 236471.6 = $ 168.4

4 0
2 years ago
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