City of Surrey Fire Service: Reducing Uncertainty for Annual Staffing Costs

Background

City of Surrey, British Columbia, Canada.

Surrey

Background

Len Garis

• Fire Chief, 2001-Present• Assistant Chief, 1998-2001

Surrey, BC, Canada

Pitt Meadows, BC, Canada• Fire Chief/Director of Protective Services, 1992-1998• Volunteer/Contract Fire Chief, 1984-1992

Justice Institute of BC• Program Coordinator, 1988-1992

Background

Frederick G. Culbert, P. Eng.

• 37 years of experience in the international development, trade, transportation and energy sectors in Canada, the United States, Asia and South America

• M. Sc. (Stanford), Engineering-Economic Planning

• Focus on the implementation and development of economic and financial planning models to evaluate public and private sector business cases

Motivators and ApproachMotivators and Approach

Problem Statement

1. Inability to predict annual operating costs

2. Inability to dynamically measure:• new regulations and policies• new staffing techniques• modifications to existing practices

Ineffective management and allocation of resources

Resulting in:

Drivers

Number of Shifts Lost to Sickness and WCB by Month: 1998 - 2001

125

150

175

200

225

250

275

300

325

J an Feb Mar Apr May J un J ul Aug Sep Oct Nov Dec

1998 1999 2000 2001

Unpredictable staffing levels cause difficulties in planning.

Drivers

Staff Count

50

51

52

53

54

55

56

57

58

59

60

61

62

Shift / Date

A Reg A SP B Reg B SP C Reg C SP D Reg D SP

FRC in service for training on C Shift, Apr 21 & 22

Under or over-staffing is common.

Methodology

Modeling must be systematic and inclusive

Model Development Process and Inputs

MANAGEMENT

Info

rmat

ion

flo

w

Da

tafl

ow

Ÿ Source information input

Ÿ IntegrationŸ Analysis, forecastingŸ Planning, modeling

Ÿ

ŸStrategyDecision-making

OPERATIONAL

ANALYSIS and PLANNING

Model Types

Model development is iterative, where results must be validated.

1. Deterministic approach enables situational analysis.

2. Probabilistic approach enables projected analysis.

Two approaches to test the model:

Inputs, Outputs and ProcessThe model calculates the probability of achieving consistent four-person staffing under various scenarios.

MODELINGMODELING

CONSTRAINTSCONSTRAINTS• Standards• Policies• Budget

MODIFY until objectives met

RESULTSRESULTSFULL TEAMFULL TEAM

Case StudiesCase Studies

Simulation 1Input Parameters (simplified):

Incremental Staff Added

Personnel Required by Shift

Staff Absence Adjustment

Staffing Offset by Shift

0

57

No

No

Simulation 1 - Results

5%

15%

25%

35%

45%

55%

65%

75%

85%

95%

$30,000 $50,000 $70,000 $90,000 $110,000 $130,000 $150,000 $170,000

Cu

mu

lati

ve

Fre

qu

en

cy

A M ean of A B M ean of B C M ean of C D M ean of D

*Note: Shift A and B are almost coincident, and the averages for both Shift A and B are similar in this iteration.

Simulation 1 - Observations

• Teams A and B most inefficient (average C $94,000 annually)

• Team D most efficient (average C $49,000 annually)

• Variable performance direct result of historically low absences

• Average annual cost C $300,000

Simulation 2Input Parameters (simplified):

Incremental Staff Added

Personnel Required by Shift

Staff Absence Adjustment

Staffing Offset by Shift

0

57

Yes

Yes

Simulation 2 - Results

5%

15%

25%

35%

45%

55%

65%

75%

85%

95%

$30,000 $50,000 $70,000 $90,000 $110,000 $130,000 $150,000 $170,000

Cu

mu

lati

ve

Fre

qu

en

cy

A M ean of A B M ean of B C M ean of C D M ean of D

Simulation 2 - Observations

• Spread between teams decreasing

• Variance between individual team performance decreasing

• Average annual cost C $266,000

Simulation 3Input Parameters (simplified):

Incremental Staff Added

Personnel Required by Shift

Staff Absence Adjustment

Staffing Offset by Shift

0

57 + 2 = 59

Yes

Yes

Simulation 3 - Results

5%

15%

25%

35%

45%

55%

65%

75%

85%

95%

$30,000 $50,000 $70,000 $90,000 $110,000 $130,000 $150,000 $170,000

Cu

mu

lati

ve

Fre

qu

en

cy

A M ean of A B M ean of B C M ean of C D M ean of D

Simulation 3

• Enormous shift in average annual cost (from C $266,000 to C $516,000 annually)

• Addition of 2 staff not cost-effective

• Currently under-utilized resources in shifts

Changes Modeled• Just-in-time Staff Replacement - no gapping• Fill long-term absences with temporary staff• Staffing pools for WCB and special leave• Intershift transfers for dynamic scheduling• 56-day cycle• Add FR truck unit when shift is overstaffed• Balance scheduled absences based on historic patterns• Stabilization of scheduled absences, using “City Days”

Conclusion

Projected callback cost at straight time = C $30/hr

Where:Minimum = C $172,630 Average = C $250,103Maximum = C $276,063 Budget = C $425,000

Assumes:• Suggested techniques applied• Absence conditions stable• No extreme events occur

Contingency Plans

• Reduce on-duty staff to 55 prior to budget running out to maintain 4-person staffing

• Simulation indicates that if average absence/shift reduced by 0.6, then 55 on-duty staff (with addition of FR unit), can be realized within budget.