Based on this module's readings and your own independent research, develop a listing of what you believe are the most important metrics for operations managers. How does each metric support the overall financial performance of the organization

The definition becomes defined in the clarification section below, as per the particular circumstance.

Explanation:

Meeting customer expectation:

This metric of success would reflect just how much the clients are represented. It will represent the quality of the service of the business and will provide them with crucial input. This metric would help the organization address the trouble areas. If the degree of customer loyalty rises, sales will also rise because more and more clients enjoy the company’s products or services.This would also show the pattern of clients as well during the company's measures to handle the issue.

Productivity:

This is a significant parameter that indicates how much is expended on activities and whether the business gets in exchange. It extends from financial return with the introduction of new goods from marketing and distribution activities to return on invested capital. Productivity is closely linked to organizational financial efficiency.When productivity rises, profits rise as well. In terms of their historical and present performance, data analytics can help to decide how and why the multiple fields work.

Cash flow:

It explains how well the cash flows within and without the organization. If the business later collects reimbursement from consumers but earlier pays its vendors, then it suggests significant operating inefficiency.These efficiencies should be worked out by the organization to minimize operational expenses and preserve favorable cash flow to boost the company's financial well-being.

A)  both functions are linear

B) f(x) = 7446.4x + 178713.6 and f(x) = 11000x + 179000

C) House 2 will value $106894.4 more than house 1.

Step-by-step explanation:

A) Value Increase from year 1 to year 2:

House 1: 193,606.40 - 186,160 = 7446.4

House 2: 201,000 - 190,000 = 11000

Value Increase from year 2 to year 3:

House 1: 201,350.66 - 193,606.40 = 7744.26

House 2: 212,000 - 201,000 = 11000  

This means that a constant increament in x variable gives a constant increament in both houses vales. Then, both functions are linear.

B) The slope is the same as the value increment from one year to the next one.

slope (m) of House 1: 7446.4

slope (m) of House 2: 11000

General formula of a line:

f(x) = mx+b

Replacing with a known point:

House 1

186,160 = 7446.4(1) + b

b = 186,160 - 7446.4 = 178713.6

equation: f(x) = 7446.4x + 178713.6

House 2

190,000 = 11000(1) + b

b = 190,000 - 11000 = 179000

equation: f(x) = 11000x + 179000

C) Replacing x = 30 into each equaiton:

Value of House 1 after 30 years

f(x) = 7446.4(30) + 178713.6 = 402105.6

Value of House 2 after 30 years

f(30) = 11000(30) + 179000 = 509000

Then, house 2 will value 509000 - 402105.6 = $106894.4  more than house 1.