1. APPLICATIONS FOR STRATEGIC ASSESSMENT,
POLICY AND DECISION SUPPORT,
MONITORING AND EVALUATION
IN URBAN PLANNING
Case Study
City of Baltimore, Maryland,
USA

2. STANDARDS
The purposes of assessing performance are: a) to identify, problems, directions and policies to increase the general performance over time, and b) to increase equity and/or equality, by bringing lower performers to the level of better performers. The user can: - set benchmarks and standards of performance according to sector policies; - change them dynamically on the screen to respond to immediate priorities; - compare performance against standards for several time periods.

3. Standards Indicator: population density
per square kilometer (Census 2010)
Indicator: population over 75 years of age (Census 2010)
Minimum
3.88
Census Tract 2506
Maximum
Census Tract 1003
Average
Minimum
0.00
Census Tract 1003
Maximum
15.07
Census Tract
Average
3.519

4. Standards
Indicator: percentage of population below poverty level (ACS 2014)
Indicator: percentage of households with more than 5 members (ACS 2014)
Minimum
0.00
Census Tract 402
Maximum
35.40
Census Tract 701
Average
8.356
Minimum
3.10
Census Tract
Maximum
73.80
Census Tract 2805
Average
25.401

5. RANKING COMPOSITE INDICES
The system allows the user to describe an entire aspect or problem by developing indices or composites, as weighted sums of standardized values of selected indicators.

6. RANKING COMPOSITE INDICES
By ranking, grouping and plotting the municipalities, neighborhoods, statistical areas, census tracts on the map, MapDecision allows the user to identify problems. Individual report cards produced for each case show the specific sector problems of the cases in point.
Units (municipalities, neighborhoods, statistical areas, census tracts) are ranked and grouped according to the values of the composite index. The groups are color coded like traffic lights: green is good, red is bad, and yellow is an intermediary situation.

7. Population education level index – ranking and mapping
Variable
Description
Weight
EDUC<9TH_GR
Percentage of population with less than 9th grade -2
EDUC_9-12_GR
Percentage of pop, with 9-12 Grade, no diploma -1
EDUC_HS_GRAD
Percentage of population graduating High School 1
EDUC_ASSOC_DEGREE
Percentage of population with associate degree
EDUC_BACHELOR_DEGREE
Percentage of population with bachelor degree
EDUC_GRADUATE_PROFESSIONAL
Percentage of population with graduate/professional degree 2
Index
composition:
ACS 2014
Legend:
Green and light green – census tracts with higher values of the index (population with higer education level)
Yellow – census tracts with average values of the index (population with average education level)
Brown and red – census tracts with lower values of the index (population with lower education level)

8. Ranking the spatial units - report cards
Report cards are generated for each census tract. They allow the user to compare the territorial units (in this case census tracts) in a SWOT (strength, weaknesses, opportunities and threats) strategic assessment approach.

9. Population education index – Report card
Legend:
The values displayed in green or red on each card are standardized, so the card shows for each variable selected whether the case has a value above or under the mean for all cases.
Green shows a relative strength of a case in comparison with the other cases for the respective variable.
Red shows a relative weakness of a case in comparison with all the other cases.

10. Population education index
Comparing report cards – Baltimore census tracts
Comparing 3 neighboring census tracts in Baltimore: the first ranking 7 in the index hierarchy (green on the map), the second ranking 87(yellow on the map) and the last one ranking 183 (brown on the map).
The length and the color of the bars in the report cards bars suggests explanations for the position in the hierarchy, highlighting the strengths and weaknesses of each territorial unit.

11. Dwellings and housing index – ranking and mapping
composition:
Variable
Description
Weight
%DWELL_OWNER
Percentage of private property dwellings 1
LACK_PLUMBING
% of housing units lacking complete plumbing facilities -1
LACK_KITCHEN
% of housing units lacking complete kitchen facilities
POP/DWELL
Average number of population per dwelling
%DWELL_HIGH_VAL
% high value housing units (over 1,000,000 USD)
%RENT>1000
% of housing units with rent value over 1,000 USD
ACS 2014
Legend:
Green and light green– census tracts with higher values of the index (better housing conditions)
Yellow – census tracts with average values of the index (average housing conditions)
Brown and red – census tracts with lower values of the index (poor housing conditions)

12. Dwellings and housing index
Comparing report cards – Baltimore census tracts
Comparing 3 neighboring census tracts in Baltimore: the first ranking 33 in the index hierarchy (green on the map), the second ranking 109 (yellow on the map) and the last one ranking 191 (brown on the map).
The length and the color of the report cards bars suggests explanations for the position in the hierarchy, highlighting the strengths and weaknesses of each territorial unit.

13. Income /earnings index – ranking and mapping
Variable
Description
Weight
MEDIAN_HH_INCOME
Median households income (dollars) 1
MEDIAN_EARNINGS_WORKERS
Median earnings for workers (dollars)
PER_CAPITA_INCOME
Per capita income (dollars)
ACS 2014
Index
composition:
Legend:
Green and light green – census tracts with higher values of the index (higher earnings)
Yellow - census tracts with average values of the index (average earnings)
Brown and red - census tracts with lower values of the index (lower earnings)

14. Buildings situation index
Comparing report cards – Baltimore census tracts
Comparing 3 neighboring census tracts in Baltimore: the first ranking 27 in the index hierarchy (green on the map), the second ranking 81 (yellow on the map) and the last one ranking 197 (brown on the map).
The length and the color of the report cards bars suggests explanations for the position in the hierarchy, highlighting the strengths and weaknesses of each territorial unit.

15. Vulnerability index – ranking and mapping
Variable
Description
Weight
%POP>75Y
Percentage of population with age over 75 years -1
EDUC<9TH_GR
Percentage of population with less than 9th grade
PER_CAPITA_INCOME
Per capita income (dollars) 1
UNEMPLOYED
Percentage of unemployed population
POP_BELOW_POVERTY_LVL
Percentage of population below poverty level
%HH>5
Percentage of households with more than 5 members
CHILD_DEPEND_RATIO
Child dependency ratio (younger population/active population)
Index
composition:
Census
2010 & ACS 2014
Legend:
Green and light green – census tracts with higher values of the index (areas with the lowest level of vulnerability)
Yellow – census tracts with average values of the index (areas with average level of vulnerability)
Brown and red – census tracts with lower values of the index (areas with the higher level of vulnerability)

16. Vulnerability index Comparing report cards – Baltimore census tracts
Comparing 3 neighboring census tracts in Baltimore: the first ranking 6 in the index hierarchy (green on the map), the second ranking 41 (yellow on the map) and the last one ranking 193 (brown on the map).
The length and the color of the report cards bars suggests explanations for the position in the hierarchy, highlighting the strengths and weaknesses of each territorial unit.

17. ANALYZING RELATIONSHIPS
MapDecision helps the user understand the relationships between inputs and outcomes. The RELATE procedure computes and displays the simple correlation between selected variables.

18. CORRELATION PLOT
Clicking on one cell in the correlation matrix displays the Correlation Plot of percentage of population with bachelor's degrees or above and per capita income (dollars).

19. EVALUATING PERFORMANCE
MapDecision allows the user to evaluate performance against inputs (human and financial resources) in the specific socioeconomic and demographic environment. The concept is that of a “black box” where inputs and outputs shed light on the process. The system identifies over-performers and under-performers.
If a census tract ranks low in social environment (education) or housing, yet it ranks high in achievement (lower percentages of population below poverty level), it is an over-performer.

20. EVALUATING PERFORMANCE
Example of over-performer census tract: high ranking according to poverty rate (low percentage of population under the poverty level) and lower ranks in education, housing and age dependency ratio

21. INDICATORS RELATIONSHIPS ANALYSIS
A multiple regression model provides insight into the relationships between various indicators.
Explained variable: Percentage of population below poverty level
Explaining variables: child dependency ratio, percentage of population with bachelor’s degree or above, percentage of unemployed population, percentage of inactive population and per capita income.

22. PLAYING WHAT-IF SCENARIOS
MapDecision supports the development of action plans for improving system performance by developing “what-if” scenarios based on the multiple regression model.
For example, changing various inputs of the model can indicate the impact on lowering the value of percentage of population below poverty level.

23. TARGETING
The analytical framework supports targeting of scarce resources at the units where the needs are greatest in the respective municipality. Quadrant analysis is used for targeting based on two criteria, and a more general query procedure allows targeting based on any number of criteria.
Quadrant analysis can also be used in identifying the under-performing and over-performing territorial units (e.g. territorial units with “local conditions” below average but results above average)

24. Targeting interventions - Baltimore
According to percentage of population below the poverty level and child dependancy ratio
Targeting the most disadvantaged areas
Highlighted on the map in magenta are the census tracts with both indicators, percentage of population below the poverty level and child dependency ratio, above the average

25. INDEX-BASED RESOURCE ALLOCATION
MapDecision helps address equity issues by supporting index-based resource allocation to direct resources to the territorial units where the needs are highest. The procedure allows an initial “proportional allocation” (e.g. per capita) to be adjusted in accordance to an index of need developed in consensus by the stakeholders.
For example, in the next scenario census tracts receive between 200 USD and USD per inhabitant. The resulting allocations are shown in the next slide.

26. Procedure
RESOURCE ALLOCATION

27. If a different range of per inhabitant allocations is agreed on, a new allocation scenario develops automatically.

28. The resource allocation procedure in MapDecision allows playing realistic allocation scenarios, including set-aside amounts for discretionary allocations, and manually changing the computed amounts for census tracts where other resources have been made available, etc.

29. EXPLORING LOCAL TRADE-OFFS
Several procedures allow the user to identify possible local trade-offs of strengths between neighboring census tracts. The purpose of this function is to promote local dialogue and transparency, to empower local units, tap local resources and decrease their dependency on the center.

30. EXPLORING LOCAL TRADE-OFFS
Green – census tracts that can be potential donors of resources
Red – census tracts that can be potential receivers of resources
Legend: