The document discusses how the USDA leveraged graph databases and Neo4j to help modernize and streamline its conservation programs. It captured business processes using Blueworks Live during stakeholder interviews. This data was then modeled as a graph in Neo4j to enable more comprehensive analysis than traditional tools. Graph queries and visualizations provided insights that identified redundancies and opportunities for improvement. The USDA stakeholders found the graph views from Neo4j helpful for strategic planning. Future applications may include exporting processes as BPMN files and developing additional algorithms.

1. Graph Intelligence for Business
Process Re-engineering (BPR)
at USDA
Leveraging graphs to drive business process
reengineering
Michael Dimant | Data Analyst
Washington, DC | 5 Mar 2020

2. 22
Agenda
USDA Context
Impact of Graphs on Solutions
Future Applications
Neo4j Government Graph Day

3. 3
USDA Context

4. 44
USDA sought to modernize and enhance its conservation financial
assistance programs
Three agencies executing
conservation financial assistance
efforts across 20+ programs
Neo4j Government Graph Day
A new mission area (FPAC) was
established consolidating all
three agencies
Sought to streamline and
modernize into a singular
common conservation approach

5. 55
Project began with a traditional business process re-engineering
(BPR) approach
A business management strategy
focused on capturing an
organization’s As-Is processes,
analyzing them, and using that
analysis to design and implement
To-Be processes.
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6. 66
Leveraging this approach, the BPR team mapped 210 processes
across 18 conservation programs for USDA FPAC
• Breadth and granularity of As-Is data
captured allowed the team to
conduct comprehensive data
analysis on its findings
• Laid the groundwork for a data
driven approach in the team’s
recommendations for improvement
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7. 77
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Utilized Blueworks Live during stakeholder interviews to document
As-Is processes

8. 88
Capturing processes in Blueworks Live allowed data to be
structured
• Basic unit of process maps were considered
“Activities”
• Metadata within each Activity included:
- Participant
- Systems
- Cycle Time
- Cost
- Inputs
- Outputs
- Execution Method
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9. 99
The team amassed a large amount of useful process data but
lacked capability to analyze in aggregate
• Existing analysis capabilities in Blueworks
Live were limited
• Captured As-Is data had features that favored
a graph approach
• Graphs facilitated quantitative analysis and
data visualization effectively
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Sample USDA Neo4j Graph

10. 10
Impact of Graphs
on Solutions

11. 1111
Neo4j Query Results
Developed queries to traverse graph for tactical business
intelligence recommendations for USDA stakeholders
• Queries enabled rapid, responsive
answers to business intelligence
questions
• Insights helped identify areas of
redundancy, overlap, and consistent
bottlenecks across programs
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12. 1212
Allowed team to identify opportunities for automation, gaps between As-Is and To-
Be processes, and consolidate areas for improvement
Created various queries tailored to suit BPR efforts
EXAMPLE: How many "swivel chair" activities exist for all processes in the Conservation
Reserve Program (CRP)?
• "Swivel chair" activities are:
• Manually executed
• Involves >= 2 systems
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IMPACT

13. 1313
Query Visualization Example
Queries tailored to suit BPR efforts were translated into data
visualizations to better illustrate findings
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14. 1414
Bloom Visualization of Activities (Red) and Systems (Green)
for USDA Conservation Program
Visualization of data revealed powerful story for stakeholders
• In May 2019, USDA stakeholders
participated in a 3-day Design
Thinking session
• Presenting graph views in Neo4j
Bloom uncovered simple but
impactful insights for stakeholders
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15. 1515
Tableau Dashboard
(Connected to Neo4j Process Data)
Graph data powered multiple client deliverables to include a
comprehensive Tableau dashboard
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16. 1616
Linked Processes Across 18 Conservation Programs
Experimental use of algorithms opened the door to further strategic
insights
CENTRALITY ALGORITHMS
• Identified critical processes in
comprehensive network of
processes
SIMILARITY ALGORITHMS
• Highlighted overlap between
programs in terms of systems,
inputs, and stakeholders
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17. 17
Future Applications

18. 1818
BPMN Export for Process
Developing solution that transforms BPMN (XML) into Neo4j graphs
BPMN has multiple advantages
over JSON:
• Software agnostic
• Richer data
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19. 1919
Continue to develop algorithms for strategic insights
Leverage power of algorithms to
drive more powerful analysis
• Overlap algorithms
• Shortest path algorithms
Neo4j Government Graph Day