Powerpoint
Applied Managerial Decision-Making: U2 Individual Project XXXXXXXXXXX Colorado Technical University 4/18/18
Summarize & present data for client expansion feasibility
Prepared for big d management
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Analyzing Market Data
Lots of markets to choose from
Is this the right one?
How do we know?
Good question
Data driven decisions
Maximize opportunities for success
Welcome Big D management. Today we are trying to establish the feasibility of a new market for our client. Of course, with a world marketplace, business’s today have lots of choices. Where should they invest their time and energy? Of course, there is no way to know with 100% certainty but data can be a critical decision driver. Growing a new market is like growing a you seedling, you want to plant in the most fertile soil under the most advantageous moisture and sunlight conditions. This careful attention to the environment you start in maximizes your chances for success.
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Data Evaluation – Part I
Proposed new market – Chicago
“Control” population – US
Evaluated based on potential for outdoor sporting goods
Our client has proposed Chicago as a potential new market. We have evaluated US Census data for 2000 in this area and in the overall US population. For our purposes, the US serves as the control population. Compared to the “average” US population, how does this area compare for purposes of characteristics we may find beneficial for effective marketing and sales our target product, outdoor sporting goods. First data set we look at is gender. Our client could make a determination based on the outdoor sporting good categories they specialize in and the gender that prefers those products. While you can see there is not a significant variance between Chicago and the US, Chicago does have a slightly higher percentage of females when compares to the overall country (US Census).
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Gender
US Female Male 0.51100000000000001 0.48899999999999999 Chicago Female Male 0.50900000000000001 0.49099999999999999
Data Evaluation – Part I
Next we look at Marital Status. This is an indicator of lifestyle, available resources and priorities. Clearly this data set is not a driver in and of itself but it could be useful to correlate other data with that we evaluate. Chicago has roughly 20 percentage points more never married individuals than the US as a whole (US Census). What other data could we look at to determine if this is a good or a bad thing for our client?
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Marital Status
US Divorced Never Married Now Married Separated Widowed 9.7500000000000003E-2 0.27100000000000002 0.51129999999999998 5.3999999999999999E-2 6.6299999999999998E-2 Chicago Divorced Never Married Now Married Separated Widowed 7.5899999999999995E-2 0.54200000000000004 0.3095 3.7999999999999999E-2 3.4599999999999999E-2
Data Evaluation – Part 2
Employment information is added to what we know about our market. The big difference you notice in this chart is that Chicago has roughly 20% more individuals in the Labor Force vs Not in the Labor Force compared to the US (US Census). This indicates as you would expect that the never married individuals from the prior data set are in the labor force. This is a good indicator that these individuals have both the time and the resources for extra curricular activities. While this might not mean they would choose to spend money in a sporting good store, it would indicate that researching the market further is warranted. If the population is inclined to an outdoor lifestyle, they would not have resource nor familial constraints. Let’s explore further.
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Employment
US Not in Labor Force In Labor Force Employed Unemployed In Armed Forces 0.36099999999999999 0.63900000000000001 0.93400000000000005 5.7000000000000002E-2 8.0000000000000002E-3 Chicago Not in Labor Force In Labor Force Employed Unemployed In Armed Forces 0.189 0.81100000000000005 0.95599999999999996 4.3999999999999997E-2 0
Data Evaluation – Part 3
For me, this is the chart that sells the market. Chicago household income over $200,000 is a staggering 11 percentage points greater than the national average (US Census). Chicago has greater percentages of household income averages all the way down to $75,000 and greater (US Census). In simple terms of disposable income, this is a huge indicator. With a product that is purely optional such as outdoor sporting goods, your market has to have money to spend on nice to haves and this market has that.
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Household Income
US $ 0 - $9,999 $ 10,000 - $14,999 $ 15,000 - $19,999 $ 20,000 - $24,999 $ 25,000 - $29,999 $ 30,000 - $34,999 $ 35,000 - $39,999 $ 40,000 - $44,999 $ 45,000 - $49,999 $ 50,000 - $59,999 $ 60,000 - $74,999 $ 75,000 - $99,999 $100,000 - $124,999 $125,000 - $149,999 $150,000 - $199,999 $200,000 + 9.5399999999999999E-2 6.3100000000000003E-2 6.25E-2 6.5699999999999995E-2 6.4399999999999999E-2 6.3700000000000007E-2 5.91E-2 5.6500000000000002E-2 4.9700000000000001E-2 9.0399999999999994E-2 0.1043 0.1023 5.1999999999999998E-2 2.52E-2 2.1999999999999999E-2 2.3699999999999999E-2 Chicago $ 0 - $9,999 $ 10,000 - $14,999 $ 15,000 - $19,999 $ 20,000 - $24,999 $ 25,000 - $29,999 $ 30,000 - $34,999 $ 35,000 - $39,999 $ 40,000 - $44,999 $ 45,000 - $49,999 $ 50,000 - $59,999 $ 60,000 - $74,999 $ 75,000 - $99,999 $100,000 - $124,999 $125,000 - $149,999 $150,000 - $199,999 $200,000 + 7.1400000000000005E-2 3.15E-2 3.1300000000000001E-2 3.04E-2 3.1E-2 4.4200000000000003E-2 4.0800000000000003E-2 4.1799999999999997E-2 3.6600000000000001E- 2 7.9699999999999993E-2 9.4200000000000006E-2 0.1147 8.5900000000000004E-2 5.7099999999999998E-2 7.2099999999999997E-2 0.13730000000000001
What Else?
This is just the first step
Other questions:
What are the trends in disposable income expenditures?
What is the household makeup of the married households?
How much free time do the work force participants have?
While the market looks very viable, there are more questions about the data we have crunched.
Additionally, we should ask the client what other markets are being considered? How do those markets compare to this one?
In conclusion, we can offer our client value in their research.
Here at Big D, we have the experience sorting through extensive data to derive information and present it in a meaningful way to help our clients make excellent decisions. We can help them take this set of data on their suggested market and further refine it to focus in on the legitimacy of this option. We also have the experience to guide them to ask questions outside of this data set and pin point within the data set. While we are comparing to the entire US population data set here, that might not be the most useful comparison. An individual living outside of a major market for instance, might not matter as much to this client as individuals in major markets. I’m confident our whole team can help us turn this market expansion into a success for our client.
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References
Colorado Technical University. (2018). Visual Aids [MUSE]. Retrieved from Colorado Technical University Virtual Campus, MGMT600-1802A-02 : https://campus.ctuonline.edu
Colorado Technical University. (2018). Presenting Business Statistics [MUSE]. Retrieved from Colorado Technical University Virtual Campus, MGMT600-1802A-02 : https://campus.ctuonline.edu
Colorado Technical University. (2018). Summarizing and Presenting Data [MUSE]. Retrieved from Colorado Technical University Virtual Campus, MGMT600-1802A-02 : https://campus.ctuonline.edu
Scott, M. (2018). MGMT600 Unit 2 live chat [Multimedia presentation]. Retrieved from Colorado Technical University Virtual Campus, MGMT600-1802A-02: https://campus.ctuonline.edu
US Census Data
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