Managing Performance Based Logistics Success for a Multibillion-Dollar Aeronautics Company
Global sustainment – PBL portfolio management
This aeronautics company, specializing in products of military aircraft, wanted to improve its current performance based logistics (PBL) strategies. Long–term objectives of this ongoing project included:
Change from issue management to risk mitigation
Reduce analysts’ non value-added time
Better understand what’s driving PBL performance
Improve strategic decision making
Key PBL challenges included:
Lack of common and consistent PBL metrics across the entire portfolio of contracts
Lack of understanding of the correlation between contract performance and related cost
Limited visibility into drivers of poor performance
Profitability buried in the programs
Inefficient use of analyst time
How We Helped
To tackle the PBL challenges, we deployed an ongoing approach. The process included five key steps:
Isolate key performance indicators (KPIs) – Determine which KPIs are critical to understanding PBL financial and operational performance. Define a common set of KPIs across the programs.
Define correlation between operational and financial metrics – Determine which integrated logistics support elements contribute to supporting the overall contractual metrics (e.g., mission capable status) and how they are weighted.
Build a financial hierarchy to capture the data – Provide a financial and operational hierarchy for each PBL program such that complete drill-down to the event level can be achieved when analyzing PBL performance drivers. This involves extending the current financial work breakdown structure from three to seven levels.
Provide portal access to the results – Design and implement a presentation layer, with appropriate security, to provide access to the results and drill-down capability to various levels in the organization.
Change the reporting philosophy of the programs – Today, the programs use a combination of earned value model and data extracts to create their combined metrics. The end users will need to be coached to understand the need to shift their efforts from data mining and manipulation to have more focus on analysis.
Instead of analysts using non-value added time for mining data, they are analyzing the data and developing creative solutions to business problems. The new paradigm is more effective because:
Valuable analyst time is freed up, allowing for companies to understand key financial correlations
Analysts analyze the results looking for the best risk mitigation approach
A single set of metrics and KPIs are implemented across the programs, which includes an integrated view with drill-down to identify source of risk