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Understanding the various sources of flying hour program (FHP) variance is key to crafting policy solutions to the causes.

• Simple planning error is one source of uncertainty in predicting flying hours in a given year. Another is external causes, such as congressional action. A third source involves Air Force decisions made after the original flying hour program is set; this issue appears to be the most problematic and frustrating for supply chain managers. Examples of this are wide-scale flying hour cuts and combat aircraft reductions. Such changes in course are among the most disruptive examples identified and are sometimes large enough to register in enterprise-wide error metrics.

FHP variance causes negative, though usually modest, downstream effects on the supply chain.

• Underflying, for example, can incur opportunity costs (leaving money on the table in the budget process). It can also incur financial costs (around $2–4 million annually in holding costs for unneeded inventory). Overflying, on the other hand, can contribute to readiness problems.

Some individual programs do experience large FHP variance and downstream effects.

• Planners can be caught off guard when sudden, radical changes to a fleet's flying hour forecast appear, with little or no communication as to why, and with little opportunity to communicate the downstream effects, such as canceled contracts.

Improved flying hour planning would not significantly improve enterprise-level spare parts forecasting.

• Flying hours are generally poor predictors of actual removals, and the Air Force bases its flying-driven parts forecasts primarily on that single variable. Better coordination and communication could help avoid many of the program-level perturbations experienced recently, but further efforts to reduce FHP variance may not have an observable effect on enterprise-level forecast accuracy because of the inherent underlying uncertainty.

The Air Force spends about $4 billion annually to buy and repair spare parts for aircraft. One way to reduce these costs is to improve the accuracy of demand forecasts: Demand that runs lower than forecast levels results in excess parts; demand that runs higher results in shortages and reduced readiness. One way to improve spare part demand forecasts is to reduce the flying hour variance — the difference between the number of flying hours that are forecast and the number that are actually flown. RAND researchers were asked to gauge the potential effect of flying hour variance on cost and readiness and identify policy options to rectify problems identified. They determined that although flying hour program variance resulted in a substantial opportunity cost, its effect on enterprise-level financial cost and readiness was relatively small. The Air Force is taking steps to reduce variance in the flying hour program, and researchers endorsed that effort. However, they indicated that other factors had much greater influence and should be dealt with to make significant reductions in the overall variance.

• Chapter One

  Introduction

• Chapter Two

  Background

• Chapter Three

  Quantifying the Negative Effects of Flying Hour Program Variance

• Chapter Four

  Conclusions and Recommendations

• Appendix A

  Simulation Tool for DLR Decisions

• Appendix B

  Additional Data on Flying Hours and Removals