Army Logistics Embraces Predictive Analytics


Pat Sullivan – VP Army Programs

“The purpose of predictive analysis is to determine the impact of resourcing decisions, alternatives, changes to strategy, and demand for forces, on Army readiness.  Impacts must be assessed over the near and mid-term … Unforeseen changes in funding, demand for forces, or other factors have varying degrees of impact on current projections.” – Army Regulation 525-30. Unfortunately, the complex mathematics and stringent analysis that are necessary for predictive analytics have been performed typically by folks from the Center for Army Analysis or by cells of operational research specialists spread across the force.  The challenge for all analysts, from an operational perspective, has been in compiling the data and creating a picture that is worthy of command-level decision making.

The Army Materiel Command (AMC) has pressed forward in applying predictive analytics to create greater efficiency in supporting the Army through the Logistics Readiness Centers (LRCs).  As part of the AMC mission to provide logistical services, the command assumed responsibility for 73 LRCs worldwide.  The purpose of a LRC is to provide installation support with a broad range of essential services that include maintenance, food service, ammunition, general supply, and laundry.  Since assuming this mission, AMC has been squarely focused on enhancing customer satisfaction and readiness while efficiently managing a dwindling budget—not an easy task.

In July 2014, ProModel initiated a proof of concept (POC) project in support of AMC for a decision-making capability that will accommodate both the overall enterprise level and the tactical, local level of the LRCs.  The project required ProModel to learn LRC processes and to evaluate and analyze existing LRC maintenance records in order to identify areas for potential improvement.  For the purposes of the POC project, AMC decided to focus the efforts on one LRC, therefore the process-education and data-collection efforts required for the creation, extraction, and compilation of data were focused on the Ft. Hood LRC.  During the POC effort, ProModel pinpointed the data necessary for analysis and identified several functional needs at the LRC level.  For example, Ft. Hood LRC management expressed a need for a labor-optimization software tool that can take into account labor requirements and overtime planning on a local, LRC-based level.

The software model of processes developed for Ft. Hood was proven to work, so a scaled enterprise solution is currently in development.  The model provided sufficient evidence that the trial scenarios created during the project can be expanded to a larger scale and adapted to incorporate additional requirements.  ProModel is now tasked with delivering a labor optimization capability and a workload-management software module to support the operations of the Army Field Support Brigades (AFSBs) that manage a number of LRCs.  This new capability will enable business-case analysis of the movement of future workloads from one location to another, and it will facilitate the consolidation of resources in order to support a requirement at a particular location.

The POC effort demonstrated that, by incorporating predictive analytic methods into a custom software application, the AMC, the U.S. Army Sustainment Command, the AFSBs, and the individual LRCs will have decision-support capabilities to accommodate trial “what-if” scenarios and experimental process simulations at both the enterprise and local levels.  AMC is proceeding to the next level of development of a software tool with enterprise-wide applicability.  Soon, AMC will experience a substantial positive effect on the command’s process efficiency and on the resulting cost-management controls.  ProModel is confident that this development will provide to the AMC and to the Army a great, leading-edge, predictive-analytic tool that will change the culture of Army logistics management.

Contact VP of Army Programs – Pat Sullivan  for more information. Or, visit our web site to learn more.






Changing the Vision of Naval Aviation

Rob Wedertz – Director, Navy Programs

Rob Wedertz – Director, Navy Programs

In the very early days of learning to fly the FA-18 as a student in VFA-106 I was scheduled, along with the other students in my class, to attend a NVG (Night Vision Goggle) lab at the simulator facility.  I remember being excited about the prospect of being exposed to a technological “tool” that would remain the backdrop of my tactical flying for the next several years.  As it turned out, the lion’s share of the discussion in the lab that day did NOT focus on the supreme advantages that NVGs would provide on the battlefield, but instead the many limitations of the goggles, that if not considered carefully would place even the most proficient aviator in peril.  The most significant of these limitations was the restricted field of view (FOV).  The NVGs I would fly with over the next few years were early generation technology and design capabilities at the time limited that FOV to only 40 degrees.  To overcome this limitation, pilots had to develop a technique of continually rotating their heads from left to right in order to accurately assess the environment, both on the ground and in the air.  Without doing so was akin to flying with blinders on – not a problem if you’re a racehorse sprinting to the finish line, extremely dangerous if you’re flying a jet in congested airspace at night and at high speeds.  As luck would have it, I did learn to train my body to change the way I viewed the environment and became proficient at not only assessing what was right in front of me (within 40 degrees) but also those things that lay on the periphery.

I use the NVG discussion above often as a metaphor to promote the advantages of changing the way we view our surroundings (i.e. training our bodies to act differently) in order to assess challenges in a more holistic and comprehensive fashion.  From a business perspective, this translates to the premise of assuming a more “enterprise” perspective of challenges and opportunities in order to achieve measurable successes.  To be clear, there are often times when a laser-like focus on what is right in front of you is appropriate.  But doing so for too long is much like staring at the sun.

ProModel’s Naval Synchronization Toolset (NST) is a software-enabled decision support platform that was developed for Naval Air Systems Command to facilitate the pro-active management of the FA-18 inventory.  Much like the first generation NVGs I described above, it provides a high fidelity (limited FOV) perspective of the FA-18 inventory in order to efficiently and effectively extend the lives of FA-18 aircraft to bridge the gap to the introduction of the F-35C.  And while it has provided significant benefit to the FA-18 program office, in its present state it does not include other Navy and Marine Corps assets (i.e. E-2/C-2, MH-60, etc.)  This is potentially about to change…

As outlined in Naval Aviation Vision…

“In today’s environment of constrained resources and geopolitical challenges, the demand for Naval Aviation forces is growing, and the need has never been greater for an enterprise approach to generating readiness. Affordability is approaching the same level of importance as performance. A decade after its formation, Naval Aviation leadership maintains the enterprise approach to generating readiness pioneered by the Naval Aviation Enterprise (NAE). It remains a strong partnership among leaders and stakeholders who ensure Naval Aviation will remain a whole and ready force by creating a cost-wise and collaborative culture of continuous improvement that addresses both current and future readiness requirements.”

Naval Aviation Vision 2014-2025

ProModel has recently been invited by Commander Naval Air Forces to discuss the necessary steps to transition NST from an FA-18-centric platform to one that captures the “enterprise”.  In doing so, the Naval Aviation Enterprise (NAE) would implement a capability that embodies Naval Aviation Vision.  The benefits of doing so are outlined below:

  • As NAVAIR and the NAE face the challenge of providing ready basic aircraft to the fleet and meet readiness requirements, this approach would provide a common methodology and platform to assess all T/M/S. It would provide an “electronic” record of the decisions that were made, the COAs used to reach those decisions and the resulting quantifiable metrics supporting those decisions. The solution is a living representation of the enterprise enabling true decision support.
  • By proactively managing the NAE inventory and making decisions in a low risk environment, cost avoidance associated with non-optimal decisions will be significant. The solution enables stakeholders to see secondary and tertiary impacts of decisions immediately without waiting to collect “real time” metrics.
  • The solution supports both tactical operational and strategic analyses. The ability for key stakeholders to visualize the Health of Naval Aviation predicated on operational schedules, against the backdrop of programmed budgets, and with a constant eye on capabilities and readiness across the enterprise cannot be overstated.
  • A common operating picture of the NAE will provide stakeholders with qualitative and quantitative metrics to influence decisions that should be made today to influence tomorrow.

ProModel is supremely positioned to facilitate the rapid transition of NST from a single platform decision support tool to one that supports the Naval Aviation Enterprise.  As the NAE implements its enterprise perspective initiatives, we will “train our bodies” to assess the landscape in lockstep with them in order to achieve the same successes with the “Enterprise” version of NST.

Incidentally, NVG technology has evolved over the years (wider FOV, less scintillation, etc.)  Ironically, when using the newer technology, it was difficult to adapt muscle movements accordingly.   Fortunately that well-honed muscle memory embedded a more robust scan pattern, and in the end optimized the use of the newer technologies.  The same can be said about the NAE’s initiative to develop a more holistic view of providing aviation assets to the units tasked with carrying out our national security strategy.  That muscle memory will ensure that the NAE is consistently attentive to the needs of the enterprise as it competes for resources, manages limited budgets, and ultimately achieves success sustaining a fighting force that is centered upon warfighting wholeness.

Lead Materiel Integrator – Decision Support Tool: Provides Total Asset Visibility and Planning Capability Not Previously Available


Tim Shelton Sr. ProModel Program Manager for Army Programs

With over 6,000 current users, the Lead Materiel Integrator (LMI) Decision Support Tool (DST), developed by ProModel Corporation, is the Army’s sole equipment distribution and redistribution tool.  From sourcing equipment and improving readiness at the tactical level, to cost-based decision making at the strategic level, DST provides the total asset visibility and planning capability that was previously absent to Army staff and materiel managers.

“If you are a Logistician in today’s Army and not talking PSDs [Proposed Sourcing Decisions] you are irrelevant.”  – MG Hurley FORSCOM G4

DST not only consumes and displays authoritative data from multiple systems of record (e.g., LMP, GCSS-A, PBUSE, JMAR, DPAS, AE2S), but it also displays the “due-in” and “due-out” transactions.  This comprehensive picture is needed to provide the complete asset visibility and transactional tracking that enables Army planners and materiel managers to make timely, cost-effective distribution and redistribution decisions.

As the Army has continued to restructure, the predictive analytic capability of the tool has become the backbone of Army planning for equipment redistribution.  DST’s blue sky planning capability allows Army planners to match scheduled force structures with contoured authorizations.  Once that process is completed, the tool runs course-of-action (COA) excursions (i.e., simulations) to identify the best solution for achieving key performance metrics for redistribution of materiel.  Users can define strategies and adjust a multitude of variables to determine the optimal solution.  A few of these variables may include: second-destination transportation cost, modernization of equipment, and pure fleeting of equipment.

The impact of the Army restructuring effort is measured in the redistribution of hundreds of thousands of pieces of equipment. Using ProModel’s application framework, DST allows Army planners to run multiple, future COA excursions.  With the tool’s auto-optimization feature, these excursions optimize misaligned equipment across every major command within the Army.  Then, the blue sky planning feature sources from inactive units, and from pure excesses, to fill any confirmed shortages across the Army.  The flexibility of the tool allows newly activated or converting units to be sourced as priority fills.  This type of in-depth analysis, which previously would have taken months to accomplish, can now be accomplished in hours.  The LMI DST is facilitating the change in an ever-changing Army.

Simulating The Impact Of New Laws On Probation Systems

JCowden Profile Pic

Jennifer Cowden – Sr. Consultant

It was recently announced that the U.S. Justice Department is planning to release 6000 inmates near the end of the month due to new sentencing policies for non-violent drug-offenders.  Most of the prisoners will be placed in half-way houses and drug rehab centers as part of the “largest one-time release of federal prisoners” in U. S History, which begs the question: are these rehabilitation centers going to be ready for this sudden influx?

One state has had a similar law change recently and is rightly concerned about the impact that the new sentencing structure will have on the probation system and ancillary support services.  ProModel consultants have been working with this state’s Administrative Office of Probation to build a series of models around different aspects of the probation system.  The previous phase model studied the movement of youths through the juvenile probation system, while the model discussed in the video below addresses the adult probationer population.

In addition to gaining insight into bottlenecks in the process, the Probation Office was interested in using Predictive Analytics to assess the impact that the new law will have on the probation office workload and the local county jail occupancy rate.  As part of the law change, convicts who are guilty of certain felonies will spend part of their sentence in probation instead of spending all of it in prison.  These felons are at a higher risk level than the current average probationer,  and will likely cause a disproportionate workload increase on the probation officers as well as take up county jail space should custodial sanctions need to be implemented.  The model will be used to help quantify the increased demand so that the appropriate adjustments can be made ahead of time.

The next steps for this model is to combine it with the juvenile model in order to predict more accurately the demand on shared services and resources.

Demystifying Big Data

Rob Wedertz – Director, Navy Programs

Rob Wedertz – Director, Navy Programs

We live in a data-rich world.  It’s been that way for a while now.  “Big Data” is now the moniker that permeates every industry.  For the sake of eliciting a point from the ensuing paragraphs, consider the following:

FA-18 / Extension / Expenditure / Life / Depot / Operations / Hours / Fatigue

Taken independently, the words above mean very little.  However, if placed in context, and with the proper connections applied, we can adequately frame one of the most significant challenges confronting Naval Aviation:

A higher than anticipated demand for flight operations of the FA-18 aircraft has resulted in an increased number of flight hours being flown per aircraft.  This has necessitated additional depot maintenance events to remedy fatigue life expenditure issues in order to achieve an extension of life cycles for legacy FA-18 aircraft.

120613-N-VO377-095  ARABIAN GULF (June 13, 2012) An F/A-18C Hornet assigned to the Blue Blasters of Strike Fighter Squadron (VFA) 34 launches from the flight deck of the Nimitz-class aircraft carrier USS Abraham Lincoln (CVN 72). Lincoln is deployed to the U.S. 5th Fleet area of responsibility conducting maritime security operations, theater security cooperation efforts and combat flight operations in support of Operation Enduring Freedom. (U.S. Navy photo by Mass Communication Specialist 2nd Class Jonathan P. Idle/Released)

(U.S. Navy photo by Mass Communication Specialist 2nd Class Jonathan P. Idle/Released)

The point here is that it is simply not enough to aggregate data for the sake of aggregation.  The true value in harnessing data is knowing which data are important, which are not, and how to tie the data together.  Often times subscribing to the “big data” school of thought has the potential of distraction and misdirection.  I would argue that any exercise in “data” must first begin with a methodical approach to answering the following questions:

“What challenge are we trying to overcome?”

“What are the top 3 causes of the challenge?”

“Which factors are in my control and which ones are not?”

“Do I have access to the data that affect the questions above?”

“How can I use the data to address the challenge?”

weeds sept 2015 blog graphic

While simply a starting point, the above questions will typically allow us to frame the issue, understand the causal effects of the issue, and most importantly facilitate the process of honing in on the data that are important and systematically ignore the data that are not.

To apply a real-world example of the methodology outlined above, consider the software application ProModel has provided to the U.S. Navy – the Naval Synchronization Toolset (NST).

“What challenge are we trying to overcome?”

Since 2001, the U.S. Navy has participated in overseas contingency operations (Operation Enduring Freedom and Operation Iraqi Freedom) and the legacy FA-18 aircraft (A-D) has consumed more its life expectancy at a higher rate.  Coupled with the delay in Initial Operating Capability (IOC) of the F-35C aircraft, the U.S. Navy has been required to develop and sustain a Service Life Extension Program (SLEP) to extend the life of legacy FA-18 aircraft well beyond their six thousand hour life expectancy and schedule and perform high flight hour inspections and major airframe rework maintenance events.  The challenge is: “how does the Navy effectively manage the strike fighter inventory (FA-18) via planned and unplanned maintenance, to ensure strike fighter squadrons are adequately sourced with the right number of FA-18s at the right time?”

“What are the top 3 causes of the challenge?”

  • Delay in IOC of the F-35C
  • Higher flight hour (utilization) and fatigue life expenditure
  • Fixed number of legacy FA-18 in the inventory

“Which factors are in my control and which ones are not?”


  • High flight hour inspection maintenance events
  • Airframe rework (depot events)


  • Delay in IOC of the F-35C
  • Fixed number of legacy FA-18 in the inventory

“Do I have access to the data that affect the questions above?”

Yes.  The planned IOC of the F-35C, flight hour utilization of FA-18 aircraft, and projected depot capacity and requirements are all data that is available and injected into the NST application.

“How can I use the data to address the challenge?”

Using the forecasted operational schedules of units users can proactively source FA-18 aircraft to the right squadron at the right time; balanced against maintenance events, depot rework requirements, and overall service life of each aircraft.

Now that the challenge has been framed, the constraints have been identified, and the data identified, the real work can begin.  This is not to say that there is one answer to a tough question or even that there is a big red “Easy” button available.  Moreover, it has allowed us to ensure that we do not fall victim to fretting over an issue that is beyond our control or spend countless hours wading through data that may not be germane.

NST was designed and developed with the points made above in mind.  The FA-18 is a data-rich aircraft.  However, for the sake of the users, NST was architecturally designed to be mindful of only the key fatigue life expenditure issues that ultimately affect whether the aircraft continues its service life or becomes a museum piece.  In the end, NST’s users are charged with providing strike fighter aircraft to units charged with carrying out our national security strategy.  By leveraging the right data, applying rigor to the identification of issues in and out of their control, and harnessing the technology of computational engines, they do precisely that.

ProModel at the 2015 AUSA Global Force Symposium

Pat Sullivan - VP Army Programs

Pat Sullivan – VP Army Programs

The 2015 AUSA Global Force Symposium in Huntsville AL proved once again to be an incredible opportunity for ProModel to learn and share.  With over 5,500 people from around the world, including key leaders from the Army, DoD and Congress, ProModel conducted office calls and provided demonstrations for senior executives from Fortune 500 companies and senior General Officer’s and Senior Executive Service members from the Department of the Army, Assistant Secretary of the Army for Acquisition, Logistics and Technology, Army Materiel Command, and Training and Doctrine Command.

The theme primary for the symposium was “Win in a Complex World.”  ProModel was on point for sharing how our tools and capabilities can assist the Army with the ominous task.  The complexity of achieving defined and desired levels of readiness at the best value served as ProModel’s mantle for discussions.

With the proven success of the Lead Materiel Integrator Decision Support Tool, that supports the BCT reorganization, the European Equipment Set establishment, and the dynamic equipping requirements in the Pacific theater; the ARFORGEN Synchronization Tool (AST) that is preparing to transition to support a new readiness model; and the Naval Synchronization Tool that assists the Navy with generating and sustaining F/A-18 readiness, ProModel already has a stronghold in the market of defense complexity.

The addition of the Logistics Readiness Center maintenance optimization capability, leaps the concept of cost wise readiness to new levels.  Attendees had an opportunity to understand how ProModel solutions can uniquely assist in solving challenges related to producing the maximum readiness at the best value.  The LRC Proof of Concept demonstrates how AMC at the enterprise levels and LRCs at the tactical level can best plan and manage capabilities, optimize resources, and maximize efficiencies within and among LRCs.

Another highlight was the demonstration of, and interest in, our COTS products like Process Simulator and Enterprise Portfolio Simulator (EPS). DOD organizations and industry are seeking ways to gain greater efficiency and to stretch their limited resources. While force structure is being reduced, missions and the need for continual modernization are not. The expectation of those funding DOD is that the military will be increasingly efficient in the execution of prescribed tasks. Therefore, an understanding of how to generate efficiency through Lean practices and events, and of how to predict equipment life-cycle costs in a very complex environment, is paramount. Additionally, leaders in DOD expressed how they must apply Lean principles to their processes, identify trade-offs, and understand the downstream impacts of change.

Process and portfolio management are significant across the government sector, and they will become even more necessary during this time of decreasing budgets. EPS and Process Simulator, coupled with ProModel’s customized solutions (AST, LMI DST, and NST), provide the foundation for rapid process improvement, budget estimation, and program management. Thanks to the exceptional hospitality of the Tennessee Valley and the great response by our AUSA hosts, ProModel continues to find new and exciting ways to assist the Army in meeting it’s motto of The Strength of the Nation.

Teaching Simulation to Graduate Students Using ProModel Products and Real-World Problems

ProModel Guest Blogger:  Larry Fulton, Ph.D. & MSStat – Assistant Professor of Health Organization Management at Texas Tech University Rawls College of Business.  After serving 25 years in military medicine, Dr. Fulton began a second career in teaching and research.

Larry Fulton, Ph.D. & MSStat

Larry Fulton, Ph.D. & MSStat

Teaching introductory Monte Carlo, Discrete Event, and Continuous simulation to business graduate students requires at least two components beyond a good set of reference materials:   realistic or real-world problems and an excellent modeling platform allowing for relatively rapid development.  In the case discussed here, the real-world scenarios derived from interests and background of the professor and students (portfolio analysis, sustainability, and military medicine), while ProModel products addressed the platform requirements. Each of the case study  scenarios served to underscore various simulation building elements, while ProModel supported rapid  product development for a 14-week, lab-intensive course that included some  reviews of probability, statistics, queuing, and                                                    stochastic processes.

Scenario 1:  Monte Carlo Simulation (Portfolio Analysis)

Business students generally have an affinity for portfolio analysis, and I do as well. Using ProModel  features, one of the earliest student projects involves fitting univariate distributions to return rates to several funds and simulating results of investment decisions of various time horizons.  Students discuss methods that might account for covariance as well as autoregressive components in these simulations.  While developing the simulations, students also determine sample size requirements to bracket mean return on investment within a specified margin of error and confidence interval and use random numbers seeds.

Scenario 2:  Continuous Simulation using Rainwater Harvesting

Students in this course are generally from a semi-arid region (Central Texas), which has significant water shortages (so much so that desalinization is being considered.)  I rely 100% on rainwater harvesting for my home water supply, so extending this to each student’s particular home location is trivial. The “Tank Submodule” provides an easy mechanism for developing the simulations.  Students develop conceptual models of rainwater mechanism as well as flowcharts.  They gather rainfall data from the National Oceanic and Atmospheric Administration regarding rainfall and evaluate various roof sizes (capture space), demand figures based on occupants, and tank sizes. They also learn about the importance of order statistics (the distribution of the minimum in the tank) versus measures of central tendency that often dominate discussions of simulation. Finally, they incorporate tools and techniques to improve and assess V&V.

­­­Scenario 3:  Discrete Event Simulation using Military Scenarios

While serving as the Chief of Operations Research Branch for the Center for Army Medical Department Strategic Studies, I encouraged the use of MedModel for multiple DES projects.  The team built strategic models (resource constrained and unconstrained) for analyzing medical requirements for strategic operations. These same models serve as a basis for a team-based MedModel student capstone project.  The primary entity for these models was the patient with attributes of severity, injury type, and evacuation type.  The primary processes involved collection, treatment and evacuation. Resources included ground ambulances, air ambulances, medics, intensive care units, and operating rooms.   Locations were geographic locations throughout the entire of Afghanistan.  Evacuation paths were built, and treatment logic (triage, ground evacuation, air evacuation, etc.) provided the flow.

Bottom Line:  The ProModel products are outstanding for use in both teaching and industry.

 Larry Fulton Bio: