2020 – Sem 2 - MGT3SMG – Assessment Task 2 Guide

This small guide is designed to assist you with the completion of MGT3SMG Assessment Task 2. The task is designed to test your ability to employ Fermi logic, as well as strategic management concepts, in helping a client choose a strategic direction and achieve above average returns.

This guide is a guide only; the data used is artificial and not accurate. Your data must be based on actual market research. You are free to structure the report how you wish, however it must have:

•       1,200 words (+/- 10%)

• An introduction

•       A main body

• A conclusion

Additionally,   tables   and

diagrams   are   essential   to   this   assessment.

There   are   no   required

academic/scholarly references for this assignment, however if you do choose to use any, they must be correctly cited.

Per the instructions of the LMS, the report requires the following:

• Research from com.au and AirBNB
• Systematic research identifying an anticipated efficiency figure* for your client's AirBNB listed properties
• An assumed efficiency figure* for agency managed properties of 90%
• The weekly rate of return for properties, based on your efficiency figure*, in the suburbs of Kingsbury, Preston, Bundoora, and West Heidelberg found on both com.au and AirBnB
• Calculations showing the weekly rate of return over 12 months for your client's properties, derived from your research into realestate.com.au and AirBnB, based on the mode of tenancy which may be either whole-of-property or per room rentals
• The weekly agency costs and fees of properties managed by real estate agents or AirBNB
• Tables showing projected rental income from both realestate.com.au and AirBNB for your client's thirty (30) properties on both whole-of-property and per room base also showing deductions for agency and AirBNB fees
• A final recommendation for both the distribution of your client's properties and their mode of tenancy, between real estate agents and AirBnB, based on your calculations

In the next section, we will illustrate a possible way of structuring the assignment. Again, this is only one such way of structuring the assignment, and provided you have met the above requirements, other structures are permitted.

Section 1: Introduction

Here, you will introduce the report. What is the document that the reader is reading? What is its purposes? You must provide a commentary on what each of the following sections will contain (like a roadmap), so that your reader knows where they are in the report at all times.

Section 2: Market research and efficiency figure of our properties

In this section, you will perform some market research and develop the efficiency figure of any properties listed on AirBnB.

Market research might involve describing things such as the median house price, median rental price, and other important information about the areas studied. This will require some research (realestate.com, Airbnb.com).

You will also define your AirBnB efficiency figure here. It is unreasonable to expect that every single AirBnB property will be booked 100% of the time; thus, we need a number which represents a likely scenario for AirBnB managed properties. You could come up with your own formula, or try something like this:

•       If our client’s AirBnB properties are occupied 4 days out of every 7, then they have an

efficiency figure of 57.14%

o   [ (4 / 7) x 100 ] = 57.14

The efficiency figure for AirBnB properties is a number that you will create, based on a reasonable best guess and some research. How many days do you think that these properties will be occupied per week (or per year?)

This number will be important when it comes to determining revenues.

The efficiency figure for agency managed properties (non-AirBnB) is a static 90% (as stated on the task LMS page).

Section 3: Your client’s portfolio

Here, you might illustrate what your client’s portfolio looks like. Your client has 30 houses, each of which are 4 bedroom 2 bathroom homes in the following suburbs:

•       Bundoora

• Kingsbury

•       Preston

• Heidelberg West

You must demonstrate how many houses are in the client’s portfolio and where they are located. There should be fairly even representation among each suburb (data permitting). Diagrammatic representation can be useful here: e.g:

Further, this is where you will split them among AirBnB & agency rentals. It is up to you to decide how you wish to do this; there is no right or wrong answer. You could split them 50-50, 60-40 or even 90-10! E.g:

You must also decide what the mode of tenancy will be. Will you charge per room, or charge per house? If you prefer simplicity, per house is easiest. If you would like to engineer maximum profits or can see a particular strategic advantage, per room may be better. You can split the portfolio across per house and per room if you would like:

Section 4: Demonstration of revenues

Here, you will calculate and demonstrate revenues. Importantly, this section requires tables, but cannot simply be a table; you must walk your reader through what it is they are reading. In this instance, I opt to charge per house, and have a 50-50 split between agency and AirBnB (I was also unable to locate any current Heidelberg West data, so I have split my portfolio across Bundoora, Kingsbury and Preston). A rough example looks like this:

15 agency properties
	Me ian rent per week for a single property (realestate.com)	Median rent per week x 5 properties	Median rent per week @ 90% efficiency
Bundoora	$440	$2,200	$1,980.0
Kingsbury	$360	$1,800	$1,620.0
Preston	$500	$2,500	$2,250.0
Heidelberg West	n/a	n/a	n/a
Total	$1,300	$6,500	$5,850.0

 

15 AirBnB properties
		Median rent per week for a single property (airbnb.com)		Median rent per week x 5 pro erties		Median rent per week @ 57% efficiency
Bundoora	$800		$4,000		$2,280.0
Kingsbury	$750		$3,750		$2,137.5
Preston	$750		$3,750		$2,137.5
Heidelberg West	n/a		n/a		n/a
Total	$2,300		$11,500		$6,555.0

The data illustrates that while AirBnB houses seem to potentially generate significantly more median rent per week, their lower efficiency figure brings them back in line with agency managed properties. Thus, we

now know that boosting management.

the efficiency figure is critical for houses which

are assigned to AirBnB

The tables should be clearly labelled, and the logic of the tables must be readily apparent to the reader. Do not make your reader try and interpret meaning from the tables.

Section 5: Demonstration of costs

Here, you will continue by demonstrating costs. You will need to find out how much money real estate agents typically charge for managing rental properties, as well as the percentage that AirBnB takes from users (hosts). This information is freely available on the internet.

You should also think about other potential / hidden costs that have the capacity to lower the client’s returns. Be imaginative.

Section 6: Overall net position

Here, you will have another set of tables which demonstrates your client’s final net position (total revenues after costs have been deducted). Again; do not assume your reader is a data-analyst. You must walk them through any tables involved.

Section 7: Conclusions & Recommendations to the client

Finally, you must make some recommendations to the client. After analysing your data, you might decide that they should instead move some of their properties, or some properties in certain areas from AirBnB to real-estate agents, or vice versa. Perhaps you uncover particular costs with one mode or the other, and this will influence your decision on how the client should structure the management of their portfolio.

Final notes

Being able to clearly and beautifully express data is an essential skill in strategic management. If you are going to convince important stakeholders of the value of an important strategic move, you must be able to use data-driven analysis to reinforce your argument, as well as present that analysis in a compelling way. Find ways to make your report easier for a lay-person to read, so that they can clearly follow the logic of your argument.