What is the percentage change in the labor partial productivity measure for SunPath

Productivity is a catch-all term describing the amounts of work done in an organization, whether by employees, work groups, departments or the company as a whole. Depending on the job or industry, various work units measure productivity. For example, a sales department may measure sales visits per week, a hotel housekeeper may be ranked on rooms cleaned per shift and a manufacturing business may look at output compared with the labor hours required to produce that output.

Basic Productivity Calculation

The base concept for any productivity measure compares output to input. As a formula, it looks like this:

Productivity = output divided by input

The result generally compares units of work per units of time. These units change, based on factors such as industry or department, and individual businesses may analyze their productivity differently than others in the same sector. Productivity may even be calculated on sections within processes, such as the operations a machine can perform in a given time. In this example, productivity becomes a measure of throughput.

The Limits of Productivity Measurements

Productivity is a measure of quantity, so it serves only as a starting point for analysis. Considering the examples above, the sales department may have a high call volume but low purchase response; the housekeeper could increase her room count while complaints from arriving guests climb; the manufacturer may see both record output and record waste, reducing the number of pieces it can sell. Effective measures of efficiency require adjustment to the gross output amount or an output unit that factors out poor quality or wasted effort.

Common Outputs and Inputs

Because key productivity measures vary widely across enterprises, outputs and inputs change as needed to pinpoint the key analytics. Outputs may include sales amounts, units produced or activities performed, while typical inputs are often time-based, usually labor hours.

Calculating Productivity Percentage Change 

Comparative analysis of productivity requires a consistent calculation of productivity gathered for two or more periods. For example, consider a manufacturing plant that produces 50 units of a product per shift on Monday, using 10 employees, each working eight hours. Productivity can be expressed the following ways:

• 50 units per shift
  
• 50 units per 80 man-hours 
  
• 5 units per employee
  
• 0.625 units per man-hour.
  

On Tuesday, the same workers produce 55 units in the same time frame. Productivity changes to:

• 55 units per shift
  
• 55 units per 80 man-hours
• 5.5 units per employee
• 0.6875 units per man-hour.

Calculating the productivity percentage uses the formula:

Period 2 Result ÷ Period 1 Result x 100

In this example, any of the productivity numbers from Tuesday divided by the same number from Monday, and multiplied by 100, gives the value of 110 percent, so Tuesday was 10 percent more productive than Monday. This analytical process can be compared between any two periods, such as the previous period or the same period the previous year. As long as the productivity values are derived the same way, the productivity percentage change is a valid calculation.

Video Transcript

Hello. Let's find the energy partial productivity In 2019 and 2000 12. So energy Productivity in 2019 it was. We divide sales over energy or input of energy which is 10. It's 30 the same for 2020 would be equal to sale's over and then drink which is nine. Let me write clear. It's nine. It will be 36 point 67. And now we need to find what is the percentage change in the energy personal productivity. So 36 point 67 minus 30 over 30. It's 22 point 22 percent. So we have an increase in productivity. My 22 0.22 percent. This is the answer to our question. Okay, thank you very much for your attention.

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Sensitivity analysis of the base case financial model is

all of the above are correct

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customer requirements

importance to customer

competitive evaluation

technical characteristices

correlation

relations between

techincal evaluation

importance weigh

seeing the value in the end product

seeing the value in the design stage

all of the above are correct

Which of the following models uses a schematic model of the sequence of steps in a problem and the conditions and consequences of each step?

Compared with a service operation, a manufacturing operations capacity is which of the following?

demand can be smoothed by inventory policies

What is an important difference between capacity planning in services as contrasted to capacity planning in manufacturing operations?

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Which of the following is a partial measure of productivity?

Which of the following is the total measure of productivity?

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