Thoughts on a New Model for Training Investment Decisions


When I was on the inside of the Navy acquisition system, I incorrectly thought that  the strategies and procedures we used in making acquisition decisions were fairly transparent and well known to industry. After discovering that this was not the case, I found myself thinking about the topic of strategy in general, and decision making strategy in particular. It is apparent to me now that a well-understood and transparent model for making our decisions about training acquisitions could help to bring clarity and understanding to both industry and government.

I recently came across a generic model structure that I believe could illustrate how the government makes training decisions and also allow industry to anticipate those decisions and apply their efforts appropriately. Accordingly, I offer a simplified model of how the government makes strategic choices about the purchase of its training products. Hopefully, this model will provide some insight and inspiration towards increased transparency in acquisition decision making.


I propose this generic “model of theory ingredients” as a framework to help explain how the government makes strategic buying decisions in the training domain. In laying out a model, you must start by defining the initial “What?” parameter on the left side of the model. In this case, it is “What type of training medium should be used to train service personnel given the current state of training technology?” It is necessary to define the “What” because recent advances in modeling, simulation and gaming have opened up a new line of training products, including game-based immersive virtual environments, intelligent tutoring and others that were previously unavailable. In the past, training was essentially limited to text-based course materials, a simulator that closely approximated the article to be trained on and/or on-the-job training with the actual device in question. The services have been forced to explore new technologies in order to maintain proficiency and to cope with the proliferation of the number of products on which personnel need training, all while they manage declining overall defense budgets.

The next question is “Who?” In the case of the government, the “Who?” is the “requiring entity,” which is the warfare community that has decided that a new system is required and is then responsible for resourcing the acquisition of that system. Resourcing a system is a full lifecycle responsibility that includes logistical considerations, such as training that will ensure service personnel can effectively, efficiently and safely use the system in the execution of their duties. Requiring entities are often directly linked to the financial sponsors and must acquire this training in a cost-effective manner, while ensuring the system can be effectively employed. Therefore, they must strategically balance these two concerns.

The next question is “How?” The answer must be bounded by available technology within the time horizon required to enable the system to be operated prior to its introduction for use. The answer also is bounded by appropriate training mediums that align with the training requirements for the system. Given the current state of technology, there are three primary “How” media for training: courseware, tactical training equipment (form/fit/function replication) or the actual system and simulated immersive virtual environments. Each of these has been shown to be acceptable to the various requiring entities for training tactical systems. They must choose the combination of these media that will produce the most effective and efficient training solution for the end user.

The next question in the model is “When?” The requirement to have training in place prior to its introduction drives a timeline for the development of training products back through the acquisition cycle, as there are training requirements for the initial testing, the operational testing and ultimately, operational deployment. Each of these training periods generates unique sets of requirements as the users being trained are different. A developmental tester is likely to have a greater depth of experience than an operational user, and a great deal of time with the actual system since they are responsible for testing its capabilities against the system’s requirements. However, as the system moves closer to introduction, a comprehensive training solution that is appropriate for operational users is required. Given that these users will have less experience with the system — and less experience in general than a developmental tester — both the training requirement and the training solution must necessarily be different. The question becomes: What is the most effective and efficient way of meeting this fleet training requirement using the available training mediums?

To answer this question, we arrive at the end “What?” In this particular case, the “What?” is a combination of courseware/tactical training equipment simulators/system, or courseware/immersive virtual environment simulators/system. The decision between these two solution sets falls back on the pillars of effectiveness and efficiency that were previously discussed. While the constraint of cost could favor one solution set over another, a balancing of cost and trainer effectiveness in conveying the appropriate knowledge, skills and abilities is the appropriate measure for evaluating the correct training solution. How one works through these considerations in this model is what must be explored to determine how strategic decisions regarding training acquisition should be made in the defense sector in the future.

To fully evaluate how best to make these buying decisions, it is necessary to study the actual process that underlies the model. This could be accomplished by developing and executing case studies on training systems that have already been acquired by the services. In studying the process, improvements or alterations to the basic model could be made to provide a more realistic model that would better replicate the actual decision-making process. By examining how previous purchasing decisions were made through a qualitative case study methodology, for example, a better model for future decision-making that would benefit both government and industry could emerge.

Combining quantitative methods with the qualitative case study would help provide more rigor to the model. As the services are concerned with both training effectiveness and efficiency when making a buying decision, a comparative measurement of training that was previously acquired would also inform the model. Specifically, a quantitative model that explored variance between training outcomes and training acquisition cost would provide meaningful metrics for evaluating buying decisions. The most important aspects of training outcomes would include training effectiveness, training periodicity and measurements of the amount of time required to achieve a specific training objective. By measuring the variance in these factors between the courseware/simulator and the courseware/virtual environment training systems, we could develop a relative measure of training effectiveness that would provide one important data point for making an acquisition buying decision.

The other data point that should be developed through measuring variance is the overall cost of training systems. A quantitative comparison of what the total acquisition cost of the courseware/simulator combination versus the courseware/virtual environment trainer could yield another primary decision-making factor. The data in this case must move beyond just the basic number that is related to cost, but also show what that cost advantage brings to the requiring entity. Does a lower cost for a virtual environment trainer allow the requiring entity to purchase multiple training devices? Does the ability to purchase more training devices allow for greater student throughput or greater student engagement with the training device? Does greater engagement with the training device change the length of the training course and thus alter the cost equation of executing a training regime? A cost variance study could effectively answer all of these questions.

Basing future research on this model would be exceptionally helpful in offering better insight into the purchase decisions that the services are making about training acquisitions. The use of quantitative and qualitative studies that explore both the process of the decision-making and the variance in training outcomes could produce a foundation for the services to make better buying decisions and would also help industry propose better solutions in terms of price and capability to inform those decisions. In a time of increasing requirements and decreasing budgets, a decision making model of this type would be invaluable to the services, industry and the taxpayer.