Using Decision Analysis Maps for Planning and Managing Spares in the Aviation Industry
Pierre Kacha
The US Coast Guard maintains a fleet of about 220 aircraft of four different types. These aircraft, including helicopters and fixed wing airplanes, are deployed to 26 air
stations around the country and must be ready to take off at a moment's notice. Keeping the right number of spare parts in the right location within a tight budget is a complex and dynamic problem.
To keep the system in balance, spare parts must be purchased or repaired well in advance of the expected demand for parts dictated by mission tempo and fleet conditions. Some
of these spare parts, manufactured overseas, require a two-year ordering and production lead time. At the same time, the fleet, often exposed to corroding sea water, is aging and requiring maintenance in new
areas.
Item planners at the US Coast Guard's Aircraft Repair and Supply Center in Elizabeth City, NC are responsible for maintaining spare part supply chain balance. They have to make
monthly and daily management decisions that will maximize aircraft fleet availability and stay within budget.
A critical set of decisions to item planners is to determine whether to buy new or to repair certain parts, and when to take such actions given possible demand, budget constraints
and administrative and production lead time.
To make good decisions consistently, items planners require (i) total pipeline visibility and (ii) the ability to determine what set of actions will yield the best results. To
accomplish these tasks with thousands and thousands of parts requires decision support tools than can address all key supply chain management processes, including planning and procuring repairs and new buys,
managing the repair cycle and the return of defective spares, fulfilling demand by the stations, and managing budgets.
A Unique Approach
Decisions, such as the ones taken by spares item managers on a daily basis, are the heart of any business. Improving organizational decision-making is one of the most critical
and productive way to improve business. decision/analysis partners uses a unique methodology to help identify decision support needs and to create effective programs to improve decisions in organizations.
The heart of this methodology is a decision map which captures the decision-making process in the form of a network of nodes and links, where a node represents a decision, and a
link between two nodes represents the inter-dependency between two decisions. The value of decisions is represented by the weight of the outbound link. An interconnected network of decision nodes is called
a decision path.
The value of a decision is measured by its 'doability' – a measure that includes qualitative criteria, such as the 'ease' of making the decision, and measurable criteria, such
as the availability of supporting transactional or historic data, and its payoff – a measure of the 'return on decision' reflecting the decision's impact on achieving stated business goals. Payoff is
estimated in terms of qualitative (e.g., customer satisfaction) and quantitative criteria (e.g., inventory reduction).
Decision analysis maps are different from process flows in that a decision may spawn downstream decisions of varied value. As a result, decision paths of lesser value can be
ignored (or relegated), unlike process flows that require that all paths be 'traveled'.
Decision analysis mapping is part of an overall series of steps as depicted below:
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