Using Network Analyst to Improve Government Efficiency Lisa Morrison Agency GIS Coordinator Wisconsin Department of Agriculture, Trade & Consumer Protection WLIA Annual Conference – February 14, 2014

About DATCP Divisions Food Safety Trade and Consumer Protection Animal Health Agricultural Resource Management Agricultural Development Management Services & Office of the Secretary Field Staff ~ 1/3 agency staff HQs in field or home offices Work at facility + drive time = total workload

ESRI Network Analyst (NA) NA extension provides network-based spatial analysis Drive time along network Drive distance along network (not “as crow flies”) ESRI StreetMap network data Options New Route New Service Area New Closest Facility New OD Cost Matrix New Vehicle Routing Problem New Location/Allocation

Case Studies Weights and Measures and Petroleum Inspections Gaps in coverage New inspector HQ Inspection territories Overnight stay Inspection “circuits” PBFI Dairy Inspections More efficient inspection routes? Animal Health Investigations Routing investigators during emergencies

W&M and Petroleum Inspections DATCP W&M acquired DSPS petroleum inspectors DATCP: scales, scanners, meters, tanks, gas pumps DSPS: petroleum storage tanks, fuel quality Existing inspectors (DATCP) + 21 (DSPS) Visited the same petroleum facilities Goals Cross train DATCP and DSPS staff Create 35 new inspector territories Provide maps to field inspectors and supervisors Efficiently cover the state Efficiently move equipment around the state

NA New OD Cost Matrix Multiple “Origins” (HQs) to multiple “Destinations” (inspection locations) True travel time along network Identify HQ clusters Gaps in coverage New HQ sites

NA New Location-Allocation Assigns “Demand Points” (12,008 facilities) to “Facilities” (34 HQs) Works way out from facility Identify Points not on network Beginnings of inspection territories

Inspectors need… Easy to follow boundaries in the field HQ to be within 15 miles of territory boundary (if HQ outside territory) Territories that do not overlap

All inspected facilities within a “contract city” wholly contained within one inspection territory

NA New Service Area Buffer around HQ True travel distance along network (could also use true travel time) Identify Eligible for overnight stay if more than 70 miles from HQ

NA New Vehicle Routing Problem Create inspection “circuits” 6 territories x 6 circuits = 36 6 year rotation Update annually OOB deleted New highlighted Identify regular vehicle scale inspection schedule

Web Mapping Application

Photo: Wisconsin Milk Marketing Board

PBFI Dairy Inspections Current System Performance Based Farm Inspection (PBFI) Each Grade A dairy farm inspected 1 to 4 times a year Frequency based on inspection history and milk quality test results in prior 12 month rolling period Inspection frequency re-categorized every 3 months Issues Neighboring farms have different frequencies Inspector passes by the same farms multiple times a year Farmers, inspectors and managers ask about efficiency...

Existing Situation – Green County

Possible “Existing” Routes

Proposed Route Parameters What if...all farms inspected 2 times a year? Neighboring farms put on same inspection schedule Any signficant time and cost savings? Assumptions 1 route per day No more than 10 farms per route 45 minutes per farm inspection (10 x 45 = 7.5 hr at farms max) Minimize driving by same farm multiple times Town-based approach? Routes begin and end at HQ

NA Proposed Routes

Town-based Proposed Routes

Route Statistics Existing # Routes # Days # Farms Farm Time* (Total Hr) Route Distance (Total Mi) Route Drive Time (Total Hr) Mileage Costs** (Total) June $ July $ August $ $ NA Proposed $ Savings11 day00180 miles6.4hr$ Town-based Proposed $ Savings11 day00175 miles6.24 hr$ * FARM TIME assumes 45 minutes inspection work per farm work (i.e., does not include travel time). ** MILEAGE COST assumes $0.195/mile for fuel $3.90/gal) + $0.467/ mile for vehicle maintenance costs = $0.662/mile.

Animal Health Investigations Positive Sample at Index Farm Initiates Concentrated sampling of all individual animal (of potentially affected species) at premises within a 10 kilometer radius of the index farm Potential sampling of animals at other premises that purchased stock from the same supplier or index farm.

NA – New Route Create routes for closest investigators Routes may be outside normal inspection territories Identify Most efficient sampling routes

NA Issues Bad locations Points not on the network must be manually corrected or they will be ignored (or may cause analysis to fail) GPS HQs not in optimal locations Manually deal with overlaps when HQs clustered Accounting for unique workload at each facility Must assume workload the same at all facilities or spend lots of time manually entering information for each facility Difficulty dealing with “special circumstances” Assign complex facility to staff outside normal territory

NA Issues Bias toward “marketing” and “package delivery” Difficult to figure out which option/parameters to use Creating territory boundaries Manual process to create “realistic” understandable boundaries Problems with multiple variables (e.g., contract city, 15 mile limit) Linking NA results back to data Difficult to figure out how to link NA results back to source data Vehicle scale route maintenance

Questions? Thanks!