Economies of scale in police air operations

1. Economies of scale in police air operations Daniel Livingstone, Home Office 04/03/2013

2. Overview • NPAS need to understand the reason underlying variations in relative costs per flight at each base; • A flight is defined as an operational or training mission. It is expressed in terms of duration (hours) and variable cost (of fuel and some maintenance); • Base costs are fixed in the short term but variable in the long term; • Costs per flight for each base are then compared. These are proxies for unit costs; • Any evidence of unit costs decreasing with flight hours point to economies of scale.

3. However.. • Some bases may be situated far away from demand which will artificially increase flying hours and costs; • Endogeneity bias: some airframes may be tasked for missions to retrospectively justify their purchase in pre-NPAS days; and • Training hours are a legal requirement which means that training flights could be viewed as a fixed cost.

4. Assumptions formatting1 • Costs per period for a starting date are shown; • Where costs vary per period they are profiled; • Requires all costs to be classified identically at each base; • No more than 4 operating categories of airframe per base; • Each airframe category must have identical cost profiles

5. Assumptions formatting 2 • 20 different categories of staff; • 20 different categories of operating cost;

6. Training and tasking assumptions • Precise details critical to analysis of scale economies; • 2 years split into monthly periods; • Training costs behave as both fixed and variable costs. The volume of missions and their length/duration will determine the impact of training costs on the effects of scale; • Inputs comprise: - total training flights; - total mission flights; - hours/distance in take off, cruise and landing; - Base location and mission centroid geo co- ordinates; • Differences in tasking allow demand to be normalised which can better illustrate cost differences between bases;

7. Profiling • This sub model shows the periodic rate of increase/decrease in costs; • It is inferred from monthly data for each cost line; • Each profile can then be compared; • Profile normalisation can also be accomplished if bases post differing one off costs over the 2 year period;

8. Outputs • Comprise: - capital costs (Which comprise airframe lease costs plus routine maintenance); - staff costs; - operating costs which includes maintenance costs associated with flying; and - spares; - flying/training hours and flying/training distances travelled; - total number of missions/training flights • Together these permit measures of efficiency such as costs per flight etc to be calculated.

9. Application • Measures of efficiency can be analysed to understand the potential for scale economies; • Normalisation permits the model to be run in scenario mode with the identical missions and distances across bases; • Easy identification of cost differences between bases; • Can be used for decision making by projecting costs forward and examining the incremental consequences of expenditure decisions; • The effects of consolidating/relocating bases can also be appraised, although this would require a base location model to be added on;

10. Additional functionality • Base location model; • Demand model.