PowerBI Visualization: Community takes Commitment, Pt. 1

| Ivoire Morrell, MSFT Chicago Civic Tech Fellow

This is the first in a three-part series of Detroit Crime statistics, causes and potential solutions. Microsoft’s Civic Tech Fellow Ivoire Morrell shares a powerful story of the history, economic impact and future narratives of Detroit’s most economically depressed communities. It is our hope that by shining a spotlight on the raw data, and illustrating the impact on Detroiters, that we can together build a stronger future.

You are a product of your environment. So choose the environment that will best develop you toward your objective. Analyze your life in terms of its environment. Are the things around you helping you toward success — or are they holding you back?” (W. Clement Stone).

There is truth to this statement spoken by the late Chicagoan and philanthropist/businessman William Clement Stone. Environment has a huge impact on who we become. While the environment we live in does not fully guarantee our success or failure in life, it plays a significant factor on the outcome. Sadly, we do not get to choose the environments we are born into. In Detroit, Michigan, many citizens live in some of the most poverty-stricken and crime -ridden communities in the United States. It would be astonishing if everyone could live in enriching environments where the landscape is beautiful, employment opportunities are plentiful, security is nearly guaranteed, and crime is close to obsolete.

How do we change an environment from one riddled with crime and poverty, to a flourishing environment with economic growth and declining crime? This question led to the development of my first PowerBI visualization titled: Community Takes Commitment. Using Microsoft’s powerful data analyzation and visualization tool PowerBI, I extracted data from Data Driven Detroit’s (D3) vault of information, creating visuals that detail information about crime in Detroit. The goal of this visualization was to analyze the crime in the city, determine how economic factors influence crime, and to consider what solution(s) should be applied that could lead to positive change.



The visualization above, titled Crime in Detroit, displays detailed information about all of the reported crimes committed in the city from January 2009 to June 24, 2016 (minus sexual crimes, which are not included in the data, and excluding miscellaneous crime in all figures). Figure 1.1 (Top-Left) displays a tree-map showing the total amount crime by category. Categories include aggravated assault, burglary, homicide, and stolen vehicle to name a few. According to the data, the top five offense types over the past 7 years were:

  1. Assault (141,129)
  2. Larceny (133,272)
  3. Burglary (108,862)
  4. Damage to property (93,528)
  5. Stolen Vehicle (89,243).

Figure 1.2 (Top-Right) displays the rate of crime (total crime divided by total population) by year from 2009 – 2015 (2016 not measured due to incomplete data). The highest rate of crime was in the year 2010, which measured at 20%. Figure 1.3 (Bottom) displays a bar chart of the total amount of crime committed by neighborhood over the 7-year span. The neighborhoods with the most offenses were:

  1. State Fair-Nolan (33,258)
  2. Burbank (30,184)
  3. Greenfield(28,584)
  4. Warrendale (27,129)
  5. Denby (26,404).

One of my biggest takeaways from the data was that three of the top five categories were related to some form of theft (larceny, burglary, and stolen vehicle). Another big take away was the fact that three of the top five communities with the most offenses occurred are on the eastside of Detroit (State Fair-Nolan, Burbank, and Denby).


The second visual above is a continuation of the first; with a focal point on the 2015 offenses (minus sexual crimes, which are not included in the data, and excluding miscellaneous crimes in all tables). Table 2.1 (Top-Left) shows the total offenses committed by month in 2015. February (6,465) had the fewest crimes while August (9,423) had the greatest number. Table 2.2 (Top-Right), displays the sum of crimes by precinct. Precinct 8, at 12,404, reported the most crimes in 2015. Figure 2.3 (Bottom-Left) contains information about the time frames when most crimes occur in Detroit. The data shows that in 2015, the greatest number of crimes were committed between 12pm – 1pm, with approximately 5,905 reported offenses. The least amount of crimes were committed between 6am – 7am, with approximately 14,848 reported offenses.  Table 2.4 (Bottom-Middle) displays the neighborhoods with 2,000 crimes or more committed in 2015. Greenfield reported the most offenses in 2015, with 3,542. The last Table 2.5 (Bottom –Right) contains information about the communities displayed in Table 2.4 and the percentage of household in the community living under the median household income ($25,000).

The information displayed on this figure, particularly Tables 2.4 and 2.5, shows that crime occurs most strongly in high-poverty neighborhoods. Nearly half of the population for each neighborhood where the most offenses occurred is living in poverty. Each of the neighborhoods exceeds the city average of citizens living in poverty by at least six percentage points. These statistics indicate to me that there may be inadequate development in these communities, which leads to fewer employment opportunities for individuals to earn substantial income.

When you are living in a community that lacks the opportunity to excel beyond the constraints of impoverished living, it places citizens in a state of economic oppression. When citizens are lodged into this environment, the notion of crime as a method to earn revenue is reinforced. Impoverished environments breed criminals; criminals do not breed impoverished environments. If I am living in an environment where the damaged school system is set up to prepare me for a scarce factory job, instead of preparing me for higher education; if the primary opportunities for employment in my community are minimum wage paying jobs that lack the likelihood of growth pertaining to wage increase; when there is acute neglect from the city in regards to development of community infrastructure to help me advance; crime becomes a feasible option to generate revenue. When survival is dependent upon earning revenue and the environment hinders chances at financial growth, crime becomes a way of making a living, resulting in higher crime rates in impoverished communities.

Stay tuned for the second part of the series, where I will compare Detroit’s Crime statistics to similarly-sized US cities.

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