Q.1 what is the difference between matrix organization and functional organizati
ID: 2754017 • Letter: Q
Question
Q.1 what is the difference between matrix organization and functional organization ? if you are dealing in projects then which organsation will be better and why please compare between the two?
Q.2 What is decision making ? what are routine decisions and non routine decisions? What are the fundamental assumptions of Break even analysis which should be known to the person who is going to use it? How you can extend the forumula for break even analysis in the following situation:
If company wants to assess what will be the profit or loss if X quantities will be sold.
How many units will be required to sell if the manager wants to make a profit of Y.
What are the limitations of break even analysis. Derive the formula also for break even analysis with clearly drawing diagrams. Can you use this tool when
The cost and price are not changing linearly.
When you are dealing with 6 products situations instead of one.
Q.3 How regression method of forecasting is different than moving average and exponential forecasting methods?
If you do not have a lot of data then which method you will prefer and why ?
What are the special advantages of regression method of forecasting over others and how it works. Concepts only along with mathematical formulaes.
Explanation / Answer
Question 1: A functional organization is one where each employee has a clear/single line of reporting. The teams are organized according to specialities like HR, Sales, Production, Finance, Engineering etc. Each team works on its own tasks independently.
A matrix organization has a project team which crosses organization functional boundaries. Team members cut across various departments. Functional team members report to members of the project team when involved in a project but also retain reporting to their functional head. Hence the matrix style of reporting.
When dealing in projects a matrix organization will be better suited as
1. Projects typically cut across multiple departments. Matrix organizations have prior experience in such circumstances
2. Barriers to communication are often lower in matrix structures and issues are identified early and addressed in a more effective manner
3. Project control is more centralized which ensures that sticking to project timelines is more easier. A functional structure may have difficulty in coordinating effectively and will rarely have experience of independently running the project management function
Question 3: Let us consider each of these methods in detail using a simple example. Let us assume we want to forecast daily variations (price change / day open - day close) of the Dow Jones Index.
Moving Average: Is based on a lookback period and we assign equal weight to each data point. Lets assume 50 days. So forecasted value will equal the simple average of the last 50 days recorded value. The benefit is that this is very easy to calculate but this method gives equal importance to each and every observation. The disadvantage is a very volatile day continues to have equal importance till it goes out of the sample considered for averaging.
Exponential average: Very similar to moving averages with the major difference being that recent data points are given more weight and importance of older data points decays over time till it goes out of the sample. They give more importance to recent data points.
Regression Analysis: Regression analysis is a statistical model which tries to explain the relationship amongst variables. In our example, the dependent (explained) variable is the value of the variation in price of Dow Jones Index and the independent variable could be say (just an example) trading volume. Regression analysis attempts to estimate the value of the dependent variable given the independent variable. You can visually think of it as drawing a graph with the dependent variable on the Y axis and the independent variable on X axis. A point would indicate the value (combination of X & Y). Once you plot all the dots, you can think of regression as drawing the line which comes closest to all of the data points. Regression is also different from averages in its predicting power. Regression will give us a value for a dependent variable under any value of the indpendent variable. A regression Averages on the other hand are severely limited here. If we do not have a lot of data then regression analysis may not be the best choice.
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