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Assignment Four - Big Data & Marketing Analytics MKT563

Student No : 94040609

Trish Anderson


The Maranguka Justice Reinvestment (JR) project is a community led program that demonstrates how the redirection of government funding into community programs can address underlying issues which lead to crime in the community (KPMG, 2018). This interactive model shows how the redirection of funding from the Justice System into Community Programs improves the rate of year 12 graduates, reduces the number of incidents of domestic violence whilst reducing the number of days spent in custody. This model also shows how investment in Community Programs leads to positive economic impacts for the Community as well as cost savings for the Justice System over time.

 

One of the key findings of the Maranguka JP project found that redirecting funding from the Justice system into the Community has multiple benefits. This model begins with NSW government funding on a scale from 0 to 1000 which can be adjusted using the sliders based on available funding, sliding the scale to the right increases the available funding. The % Community Funding and % Justice System Funding variables can then be adjusted in the sliders to determine how much of the funding goes to the community as a percentage and how much of the available funding gets allocated to the justice system.  

 

Investment into Community Programs is made available by the investments into the Bourke community.  Community Leaders in the Bourke Community develop programs and each program has shown to have a positive impact on the number of students graduating year 12 in the community, the number of domestic violence incidents and the number of days spent in custody.

 

Variables

The current number of Year 12 graduates, the current number of domestic violence incidents and the current number of days in Custody are input into the sliders on the hand panel and the model simulation will show how these figures are impacted through investment in the community over time. These variables also contribute to the growth of Youth Development, Family Strength and Adult Empowerment in the community. These factors result in reinvestment opportunities, which have positive economic impacts on the community. Savings are also passed back to the justice system as underlying issues in the community are addressed over time.

 

The slider scale on the right hand panel uses six adjustable variables to model how the rate of investment in the community can impact the rate of positive impacts in the community and the rate of reinvestment opportunities that can be achieved. Running the simulation will show the larger the % of Community Funding, the faster the results can be seen over time and the greater the economic impact and justice system savings will be. The smaller the % Community Funding will show how impacts are still positive but occur over a longer period of time.

 

% Community Funding and % Justice System are a percentage of funding whereas NSW Government Funding is represented in dollars ($). NSW Government Funding is on a scale from 0 to 1000 but the assumed scale is $000’s, where 1,000 equals $1,000,000.

 

 

Parameter Settings

With community funding, the amount of Year 12 graduates increases by 31% (KPMG, 2018)

With community funding, the number of Domestic Violence incidents decreases by 23% (KPMG, 2018) (KPMG, 2018)

With community funding, the number of days spent in custody decreases by 42% KPMG, 2018)

Reinvestment opportunities contribute to 1/3 of economic impacts back the community where 2/3 of the reinvestment opportunities contribute to savings within the Justice System KPMG, 2018).

 

Assumptions

The rate of impact on year 12 graduating students, Domestic Violence Incidents and Days spent in custody changes at the same rate of % Community Funding available to the community.

 

References

 

Backing Bourke: How a radical new approach is saving young people from a life of crime. (Thompson, G). abc.net.au.

KPMG. (2018). Maranguka Justice Reinvestment Project Impact Assessment. Retrieved from https://www.justreinvest.org.au/wp-content/uploads/2018/11/Maranguka-Justice-Reinvestment-Project-KPMG-Impact-Assessment-FINAL-REPORT.pdf

Impacts of Community Funding and Reinvestment in Bourke
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A systems model of the relationships amongst economic situation, health situations and Covid-19 in Burnie, Tasmania.

Health situation 
According to exposed and go out population decreases, the population of infected decreases after a stable   high cases period.  

Economic situation
When the infected population decreases, the population economic recovery increases over time, then become stable after a period of time. 
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Green lines: positive relationships
Red lines: negative relationships

Spill
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Simulation of MTBF with controls

F(t) = 1 - e ^ -λt 
Where  
• F(t) is the probability of failure  
• λ is the failure rate in 1/time unit (1/h, for example) 
• t is the observed service life (h, for example)

The inverse curve is the trust time
On the right the increase in failures brings its inverse which is loss of trust and move into suspicion and lack of confidence.
This can be seen in strategic social applications with those who put economy before providing the priorities of the basic living infrastructures for all.

This applies to policies and strategic decisions as well as physical equipment.
A) Equipment wears out through friction and preventive maintenance can increase the useful lifetime, 
B) Policies/working practices/guidelines have to be updated to reflect changes in the external environment and eventually be replaced when for instance a population rises too large (constitutional changes are required to keep pace with evolution, e.g. the concepts of the ancient Greeks, 3000 years ago, who based their thoughts on a small population cannot be applied in 2013 except where populations can be contained into productive working communities with balanced profit and loss centers to ensure sustainability)

Early Life
If we follow the slope from the leftmost start to where it begins to flatten out this can be considered the first period. The first period is characterized by a decreasing failure rate. It is what occurs during the “early life” of a population of units. The weaker units fail leaving a population that is more rigorous.

Useful Life
The next period is the flat bottom portion of the graph. It is called the “useful life” period. Failures occur more in a random sequence during this time. It is difficult to predict which failure mode will occur, but the rate of failures is predictable. Notice the constant slope.  

Wearout
The third period begins at the point where the slope begins to increase and extends to the rightmost end of the graph. This is what happens when units become old and begin to fail at an increasing rate. It is called the “wearout” period. 
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Introduction:
This model demonstrates the COVID-19 outbreak in Burnie, Tasmania. It shows how the government policy tries to reduce the spread of COVID-19 whilst also impacting the local economy.

Assumptions:
This model has four variables that influence the number of COVID-19 cases: infection rate, immunity loss rate, recovery rate and death rate.

In order to reduce the pandemic spread, in this model, assume the government released six policies when Burnie COVID-19 cases are equal or over 10 cases. Policies are vaccination promotion, travel restriction to Burnie, quarantine, social distance, lockdown and testing rate.

Government policies would reduce the pandemic. However, it decreases economic growth at the same time. In this model, only list three variable that influence local economic activities. 
Travel restrictions and quarantine will reduce Burnie tourism and decrease the local economy. On the other hand, quarantine, social distance, lockdown allow people to stay at home, increasing E-commerce business.
As a result, policies that cause fewer COVID-19 cases also cause more considerable negative damage to the economy.

Interesting insights:
One of the interesting findings is that the government policy would reduce the COVID-19 spread significantly if I adjust the total government policies are over 20% (vaccine promotion, travel restriction, quarantine, social distance, lockdown), 3560 people will die, then no more people get COVID-19.
However, if I change the total government policy to less than 5%, the whole Burnie people will die according to the model. Therefore, we need to follow the polices, which saves our lives.
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