Using Lean Six Sigma and Predictive Modeling to Determine Optimal Sustainment Parameters for Systems in Theatre
In 2003, the Project Manager, Night Vision/Reconnaissance, Surveillance, and Target Acquisition (PM NV/RSTA) began fielding a much-needed, key quick reaction capability (QRC) in Afghanistan aptly named the Rapid Aerostat Initial Deployment (RAID). RAID comprises three key sensors which provide persistent day and nighttime targeting and surveillance data - - the RAID Tower (a sensor mounted on large towers), the mobile Eagle Eye (a sensor mounted on smaller, movable towers), and the RAID Aerostat (a sensor mounted on a large balloon). As the systems were fielded and in use, the PM's focus shifted to sustainment of the systems, and more specifically, how best to ensure the highest operational availability (Ao) and operational readiness (OR) rates of the systems within the various constraints of theatre to provide better protection for the warfighter. "We were rapidly fielding RAID systems, particularly in Iraq to meet theatre requirements and our Program Executive Officer, Brig. Gen. Thomas Cole, reviewed the sustainment of the RAID systems and requested that we take a closer look at the level of field service representative (FSR) support required to maintain an operational availability of 90% or better," said Col. Linda R. Herbert, project manager, NV/RSTA. Robin Whitworth, deputy project manager, NV/RSTA, added, "We needed to find the 'knee in the curve' particularly with regard to the number of FSRs required to maintain the systems at the 90% Ao level or above. We wanted to determine the point at which adding additional FSRs would have a negligible impact on overall Ao, so that we could then re-direct the dollars saved to other areas worthy of improvement, such as sparing processes and travel time." Unlocking the Power of Combining Lean Six Sigma and Modeling Determined to exceed an Ao target of 90%, PM NV/RSTA looked to the Lean Six Sigma (LSS) methodology and specifically, the Define, Measure, Analyze, Improve, and Control (DMAIC) approach to decompose the major sustainment issues and develop appropriate solutions in a cost-effective manner. In her former role as executive officer to Lt. Gen. N. Ross Thompson III, former Military Deputy to the Assistant Secretary of the Army for Acquisition, Logistics, and Technology ((ASA)ALT), Herbert saw the fruits of the LSS methodology first-hand. "During my time at ASA(ALT), I witnessed the power of LSS in solving complex issues, such as those that arise under any sustainment situation. As a PM, I was determined to use LSS, where appropriate, to continuously improve my processes and my organization so that we would be better positioned to serve the warfighter. When my Deputy and I reviewed sustainment of the RAID systems, we decided it was time to kick-off a LSS project to address head-on the issues negatively impacting Ao." In the spring of 2009, PM NV/RSTA launched a LSS project initially focused on determining the optimal number of FSRs to maintain the RAID systems at an Ao of at least 90%. The LSS Project Team represented a cross-functional mix of members spanning several organizations, including PM NV/RSTA personnel, PM Integrated Tactical Systems (PM ITS) personnel (formerly PD RAID), Communications and Electronics Command (CECOM) personnel, and Booz Allen Hamilton contractor support. The Team worked in a highly collaborative fashion to gather key historical data, conduct appropriate analyses, and develop and implement sound solutions. What resulted was a robust, predictive model capable of simulating myriad conditions in theatre that impact system sustainment, such as time waiting for spare parts, time waiting for travel to a system, mean time between maintenance (MTBM), percentage of help desk calls that resolve an issue, etc. In all, more than ten sustainment variables were incorporated into the model. Preparing the Model to Respond to PM NV/RSTA's Initial Research Question The first research question the team was tasked with answering was "How does the performance of the RAID Legacy OIF systems vary with the number of FSRs?" To answer this question, the team first gathered qualitative data from key stakeholders to build a detailed process map representing the FSR Repair Process. In addition to the process map, the team determined current, in-theatre hub alignments, as well as the various key assumptions, such as travel times, sufficiency of spares, and wait times of various types of transportation (e.g., helicopters versus convoys). Together, the FSR Repair Process Map and the hub structure became the "backbone" of the model. Once the backbone of the model was developed, the team gathered, prepared, and analyzed various types of quantitative, historical data available on the performance of the RAID Legacy systems in OIF, to determine key metrics such as mean down time (MDT), mean time between maintenance (MTBM), failure rates, and overall operational availability (Ao) and operational readiness (OR). Results of the historical data analysis were then compared to the initial results as simulated by the model to ensure that the model accurately represented reality/current conditions. "The Team exposed the model to various validation and verification exercises to ensure that it accurately represented reality," Herbert explained. Both the FSR Repair Process Map and the hub-alignment structure (the main backbones of the model) were validated through detailed stakeholder interviews, including personnel based in OIF. Furthermore, simulation results were compared to results based on the historical data analyses to ensure a "close match" (initial validation results matched historical Ao performance to within two percent). "Once we felt confident that the model was able to accurately capture and represent reality, we were ready to begin asking key questions and conducting simulations to determine the answers. What we found was that the FSR levels were saturated, and more important, that other factors, particularly the availability of spare parts, were limiting overall Ao. The model helped us to identify the right mix of FSRs and subsequently to quantify the benefit gained by reinvesting operational dollars into more problematic areas," Herbert explained. Ultimately, based on the initial application of the model, PM NV/RSTA reduced FSR support by three, realizing cost savings to be applied to other, key areas impacting overall Ao. Since the initial pilot exercise, PM NV/RSTA has used the model to validate staffing levels, inform staffing decisions for future contracting needs, and develop an overall better, more specific understanding of the 'sustainment tail' for some of its major systems. For example, the PM is now in the process of applying the model to the Base Expeditionary, Targeting, and Surveillance Systems- Combined (BETSS-C) to determine optimal sustainment parameters, such as total number of FSRs and support personnel required to maintain a specific level of Ao. "The model continues to help us make better, and more informed business decisions that directly impact system sustainment and overall Ao and OR rates," Herbert concluded. Setting the Stage to Address Broader Sustainment Issues Currently, the US Army is in process of reviewing its Intelligence, Surveillance, and Reconnaissance portfolio of systems. This review will entail a closer review of sustainment parameters for existing systems, including overall cost of sustainment over a period of years. The PEO for IEW&S highlighted the importance of understanding the sustainment tail, particular from a funding perspective. "Incorporating the sustainment tail into the budget process is difficult and results in lack of forecasting for sustainment costs and demands for spare parts and maintenance support personnel many of which are contractors we call FSRs," said Cole. " Today, those costs are absorbed in Other Contingency Operation funding requests that are resourced year-to-year. As that funding declines, we will be faced with some tough decisions and potential sustainment funding shortfalls that will give us little alternative than to take systems out of the fight." PM NV/RSTA's FSR Rightsizing/Sustainment Model has the potential to play a central role in helping the US Army as it continues to examine its ISR portfolio and make decisions regarding system retention and sustainment. Since the "heavy-lifting" of the model's development has been completed, the model can now be adapted to other systems and scenarios by incorporating new process maps, assumptions, and key input and output variables. In this fashion, the model can then run various simulations to determine the most cost effective way to sustain any system. For example, if there is an understanding that sustainment funding for a particular system must be reduced by $50 million, the FSR Rightsizing/Sustainment Model can be leveraged to simulate numerous situations to determine where costs can be reduced without resulting in a negative impact on overall system Ao and OR. "The FSR Rightsizing/Sustainment Model is a great tool that inputs many factors to right-size FSR support. FSRs are costly in order to provide the level of expertise we need in a combat environment. The model gives the PM a basis for adjusting FSR support to the right levels to match numbers of FSRs to readiness levels. There is a knee in the curve due to factors such as intra-theater transportation - - in sum, more FSRs does not necessarily equal better readiness," said Cole "The model helps us find that knee in the curve so we have the right number of FSRs to provide the required level of support. The model is just that, a model and it can be applied to any system to improve overall sustainment." explained. Herbert concluded, "the model's power resides in the fact that it can be used to simulate real situations and determine the effects on desired outcomes without having to spend an inordinate amount of time or money."

Page last updated Fri July 22nd, 2011 at 12:16