A one-day survey course of data analytics tools, techniques, and best practices aimed at managers and supervisors. The class involves a hands-on exercise with open data and is intended to build data literacy and familiarity with the analytics process, while also addressing the challenges and opportunities of doing more and better analysis in the context of city operations.
Managers, supervisors, and team leaders with a need to better understand the analytics process, as well as the key tools and techniques to to bring data-driven insights to city operations.
This course introduces participants, especially managers and executives, to the concept of data-driven decision-making and management. Participants will learn how to better use data for setting goals and defining objectives, while identifying the proper metrics for those objectives and the elements of meaningful management dashboards. Participants will also learn how to assess the right analytical tools to manage projects, processes, and analytic staff within their departments.
- Discuss the data-driven decision making process
- Explore the role of managers and analysts in the decision making process
- Introduce useful terminology around data and the data analytics process
- Get some hands-on experience analyzing data
- Participants will better understand using data in the decision-making process
- Participants will better understand the analytics process
- Participants will better understand the value of data, particularly open data
- Participants will better understand the role of analysts and managers in the decision-making process
- Introduction to Analysis and Problem Formulation (9:00 – 9:50)
- 5 primary types of analysis
- Quantifying needs
- Operational analysis
- Performance metrics
- Prioritization
- Data sharing/empowering stakeholders
- Group discussion: "What type of analysis does your office do?"
- 4 main concerns in government analytics
- Technical
- Legal
- Cultural
- Political
- Benefits of good analytics
- Group discussion: "What challenges and opportunities have you experienced with analysis in your office?"
- 5 primary types of analysis
- Analytic Management in Practice (10:00 – 10:50)
- Overview of Statistics (11:00 – 12:00)
- Why statistics?
- Data distributions
- Measures of central tendency
- Mean
- Median
- Mode
- Measures of variability
- Range
- Quartiles
- Inter-quartile range
- Standard deviation
- Correlations
- Causation
- Discussion: "How are statistical measures used in your office?"
- Lunch (12:00 – 1:00)
- The Analytical Process and Designing Data Visualizations (1:00 – 1:55)
- The 6 steps in the analytical process
- Problem formulation
- Data gathering/preliminary analysis
- Data cleaning
- Hypothesis testing
- Verification
- Visualization
- Designing data visualizations
- Selecting the appropriate type of chart
- Effective use of color
- The 6 steps in the analytical process
- Break (1:55 - 2:00)
- Introduction to Open Data (2:00 – 2:20)
- Group discussion: "What is open data?"
- Definition of open data
- Benefits of open data
- Concerns with open data
- Open Data Portal Live Demo (2:20 - 2:30)
- Practical session in Exploratory Data Analysis (2:30 – 2:50)
- Introduction to exploratory data analysis
- Exercise 2: Exploring 311 Noise Complaints
- Break (2:50 - 3:00)
- Practical session in Question-driven Analysis (3:00 - 3:50)
- Introduction to question-driven analysis
- Exercise 3: Vision 0 (dB)
- Group presentations (3:50 - 4:20)
- Analytics resources for the busy city manager (4:20 – 4:40)
- Wrap-up discussion and course evaluations (4:40 – 5:00)
- Dismissal (5:00)
- Task to participants
- Given a background in the expansion of Universal Prekindergarten in New York City, discuss in your groups what kind of analysis would be useful to the assigned area of concern (capacity, outreach, enrollment, monitoring, and evaluation), what concerns must be navigated, and how the management of the process can be best supported with data
- Present the work of the group to the class
- Desired outcomes
- Participants will practice applying the fundamentals of problem formulation for data-driven decision making around a particular policy program issue
- Participants will gain experience articulating business problems as they relate to policy programs with data
- Task to Participants
- Follow along in a guided exercise exploring 311 Service Requests related to noise compliants in New York City
- Desired outcomes
- Participants will have practice performing simple analysis with open data
- Participants will gain experience manipulating data in Excel, including formatting spreadsheets, using Pivottables, creating charts, and writing formulas
- Task to Participants
- Given 311 noise complaint data, assist enforcement efforts by identifying NYC community districts that have a high volume of noise complaints and the time frame enforcement resources should be deployed to combat the noise issue at its peak
- Identify the prevalent types of noise complaints in these areas to guide enforcement in each community district
- Desired outcomes
- Participants will be familiar with the analytics process, using city data to make policy and program decisions
- Participants will be more familiar with the tools of basic data analysis and understand the types of questions that can be answered with data