Using Network Analyst to Improve Government Efficiency Lisa Morrison Agency GIS Coordinator...

Using Network Analyst to Improve Government Efficiency

Lisa MorrisonAgency GIS CoordinatorWisconsin Department of Agriculture, Trade & Consumer Protection Lisa.Morrison@wi.gov

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... 14 (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-AllocationAssigns “Demand

Points” (12,008 facilities) to “Facilities” (34 HQs)

Works way out from facility

IdentifyPoints not on

networkBeginnings 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

Contract City

Roads

Garbe (J)

Nickel

Rivers

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 ProblemCreate inspection

“circuits”6 territories x 6

circuits = 366 year rotationUpdate annually

OOB deletedNew highlighted

Identifyregular vehicle scale

inspection schedule

Web Mapping Application

Web Mapping Application

Web Mapping Application

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 CountyPBFI due June (26)

Frequency

!( 12 months

!( 6 months

!( 4 months

PBFI due July (16)

Other PBFI Schedule

") 12 months

") 6 months

") 4 months

PBFI due August (35)

#* 12 months

#* 6 months

#* 4 months

Frequency

Frequency

! Other Grade A

Possible “Existing” Routes

" Inspector HQ

! PBFI due June (26 farms)

! PBFI due July (16 farms)

! PBFI due August (35 farms)

June Routes (3)

July Routes (2)

August Routes (4)

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

NA1 - 8 farms

NA2 - 9 farms

NA3 - 10 farms

NA4 - 10 farms

NA5 - 10 farms

NA6 - 10 farms

NA7 - 10 farms

NA8 - 10 farms

" Inspector HQ

Town-based Proposed Routes

" Inspection HQ

Route 1 - 11 farms

Route 2 - 9 farms

Route 3 - 10 farms

Route 4 - 9 farms

Route 5 - 10 farms

Route 6 - 9 farms

Route 7 - 9 farms

Route 8 - 10 farms

Route Statistics

Existing#

Routes#

Days#

FarmsFarm Time* (Total Hr)

Route Distance (Total Mi)

Route Drive Time (Total Hr)

Mileage Costs** (Total)

June 3 3 26 19.50 345 10.27 $228.39July 2 2 16 12.00 230 6.83 $152.26August 4 4 35 26.25 442 13.22 $292.60

9 9 77 57.75 1017 30.32 $673.25

NA Proposed 8 8 77 57.75 837 23.92 $554.10 Savings 1 1 day 0 0 180 miles 6.4hr $119.16

Town-based Proposed 8 8 77 57.75 842 24.08 $557.44 Savings 1 1 day 0 0 175 miles 6.24 hr $115.81

* 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!