Priority Information Requirements for the Brigade Combat Team

Developing and managing tactical-level information requirements is a chal lenging and dynamic process that is supported by scarce, even occasional ly conflicting, doctrine. This article will focus exclusively on the development of priority intelligence requirements (PIRs), which when aggregated with friendly-forces information requirements (FFIR), form the overarching commander’s critical information requirements.1 Although PIRs are typically managed by the brigade S-2 and tasked down to the brigade information-collection (IC) manager, they are ultimately approved and owned by the brigade command er. Therefore PIR development is a commander-driven process and occurs in perpetuity. It requires a foundation al understanding of both past and present doctrine, but, more impor tantly, it necessitates a holistic under standing of how the commander visu alizes employing his/her brigade com bat team (BCT) in a Joint contested environment. Rather than rewrite doctrine to create more requirements, such as targeting-intelligence requirements in the new Army Techniques Publication 2-01, the definition of PIR should be broadened and enhanced from its current state. After all, to find the high-payoff tar gets (HPTs) in PIR, one need not look any further than the “indicator” column of the IC matrix. PIRs are best de fined as information requirements pertaining to the enemy or operation al environment, deemed critical to ei ther 1) reaching a commander’s deci sion point (DP)2 or 2) achieving a spe cific desired effect.3 This definition ultimately provides a spectrum to frame PIR-development methodology. The first part of this definition is what intelligence professionals grapple with the most – directly tying PIR to decision points at echelon. However, the second part of the definition is often overlooked by those outside the fires and targeting com munity. This is where the command er’s operational visualization comes into play and directly influences the types of PIR he/she considers to be most effective during that specific phase. To support a dynamic commander in a complex operational environment, effective PIR will provide three symbiot ic functions: driving the commander’s DPs, supporting shaping efforts by en abling the targeting cycle and applying classical game theory. DP tactician On the far-left limit of the spectrum, you have commanders who prefer to employ their organization using DP tactics, which in football would be the equivalent of running an option play.4 The commander directs the staff to develop a single robust plan consisting of multiple branches and sequels at each identified DP of the operation. The goal is to provide the commander with the greatest amount of operational flexibility while also maximizing tempo.5 For example, a commander may direct the brigade staff to plan an offensive operation with the desired endstate of successfully enveloping the remaining two mechanized-infantry battalions (MIBN) of 111th Brigade Tactical Group (BTG). The operational environment will influence when and where these Figure 1. DP 1A. (Graphic by author) Figure 2. DP 1B. (Graphic by author) offensive operations can occur, but so will the enemy. Factors such as the enemy’s composition, capability, array and higher headquarters’ desired end state will all bear some influence on the development of the Blue Force course of action (CoA). This first DP 1 will also serve as the first branch in the operational plan, and it will ultimately provide the commander with two distinguishable op tions. Each of the two options will include three tactical tasks, each of which will be executed by one infantry battalion simultaneously. The primary distinguishing feature be tween these two branch plans will be the designated avenue of approach (AoA) to which the main effort will be committed. DP 1A includes one infantry battalion fixing the enemy on the southern AoA while simultaneously committing one infantry battalion to conduct a penetration. Another bat talion serves as the main effort to con duct an envelopment of the enemy on the northern AoA. DP 1B includes one infantry battalion fixing the enemy on the northern AoA while committing one infantry battalion to conduct a penetration, and another battalion as the main effort to conduct the envel opment on the southern AoA. While both options are feasible, only one will be optimal based on how the supporting PIR are answered at that time. Both proposed branch plans will re quire unique operational conditions, answered by PIR and FFIR, which must be met to achieve that DP. The infor mation requirements associated specifically with the enemy and terrain will ultimately become brigade PIR. Since weather and terrain are perpet ual considerations, this example will drive DP 1 with an enemy-focused PIR. To do so, we need to have an accurate understanding of the relative combat power our BCT is able to impose upon the enemy – an FFIR. Also, we must be aware of the minimum forces required to achieve each of the tactical tasks, based on the correlation of forces and means. Classical correlation-of-force theory posits that an enemy in a deliberate defense can effectively defend against up to three times its combat power.6 Based on the task-organization of a standard infantry BCT (IBCT), we are able to commit one infantry battalion to fix the enemy, one to penetrate the enemy’s defensive positions and a third to envelop the enemy in sector. After accounting for all the preceding information, we now know that the enemy is likely to mount a successful defense against the penetration and envelopment with any formation greater than two mechanized-infantry companies (MICs) supported by complex obstacle belts. One example of an effective PIR that supports this DP is: Will the remnants of 111th BTG com mit and retain less than or equal to two MICs to defend any single avenue of approach? By integrating this minimum-force re quirement into PIR development, we can more precisely define the information requirements needed to achieve that commander’s DP, which will allow for IC planning and synchronization. With each commander at echelon hav ing a shared understanding of DP 1A and 1B, the brigade commander is able to call an audible (keeping in line with the earlier football example) that his subordinate commanders are then able to execute rapidly while maintain ing a high operational tempo. This concept is best illustrated using one of the most important products generated during the military deci sion-making process: the decision-support matrix (Table 1). Conditions-setter On the other end of the spectrum are commanders who prefer a more pro active shaping effort that applies center-of-gravity analysis to systematical ly dismantle the enemy’s order of bat tle.7 They tend to prefer plans that consist of a multitude of condition-based triggers and innovative efforts intended to flatten the kill chain by ac celerating the sensor-to-shooter se quence. Rather than employing collection as sets to determine the composition and disposition of the enemy, they prefer employing them to target the enemy’s critical capabilities via its critical vul nerabilities. This effectively allows the commander to artificially achieve the minimum-force requirements through the successful reduction in the ene my’s relative combat power. In this scenario, PIR are intended to directly enable the targeting process, shape the battlespace and set conditions for maneuver elements to rapid ly seize a position of relative advantage. One such example would be tak ing the preceding plan and replacing DP 1 with a trigger to commit the main effort to the northern AoA. This con ditions-based trigger is distinguishable from DP 1 because it is a predeter mined action independent of the enemy’s array of forces. Through a deliberate-targeting pro cess, the staff identifies the specific conditions required to meet this trigger. Rather than attempt to directly re duce the enemy’s total combat power by targeting its maneuver formations, the staff recommends targeting the enemy’s counter-mobility assets (mine layers, ditch-digging assets, etc.). Table 1. Decision-support matrix for DPs 1A and 1B.

Targeting these engineer elements would reduce the enemy’s relative combat power by neutralizing assets that are deemed critical to defensive operations – the desired effects. These desired effects account for the latter half of our definition of PIR. If successful, achieving these desired ef fects would deny the enemy the ability to establish a deliberate defense supported by obstacles and force the enemy to establish a hasty defense with minimal obstacles. If all other variables remain the same, the shift from a deliberate to a hasty defense consequentially reduces the minimum-force requirement from a 3:1 to 2:1 force ratio.8 Once the need to neutralize these crit ical protection assets is identified, they will be analyzed in the target working group, added to the HPTs list and validated by the brigade com mander during the target-approval board. For a collection plan to effectively sup port the decide, detect, deliver and assess targeting cycle, HPTs (much like DPs) must be directly supported by PIR. An example of a PIR that supports these HPTs is: Where will the enemy employ the predominance of its counter-mobility assets? In this example, the term counter-mobility assets in the PIR will focus col lection efforts specifically on the enemy’s MDK-2M (ditch-digging vehicle) and GMZ-2 (minelayer). Due to the high level of specificity, the IC matrix, which refines PIR into essential ele ments of information (EEI), indicators and specific information requirements, will be far more concise.9 Game theorist The science of strategic reasoning, commonly known as classical game theory, can be traced back to the 1950s, when it was first used to study the decision-making process of ratio nal players in a zero-sum game. Since then, history has provided us with multiple military case studies in which game theory may be applied in retro spect: the Battle of Midway,10 Battle of Bismarck and Battle at Tannenberg11 between Russia and Germany in 1914, to name a few. The concept of applying game theory, in its original zero-sum form, to PIR development may seem novel, but it is far from it. Unlike current doctrine, historical doctrine incorporated this framework of strategic reasoning into PIR development.12 A review of Army Field Manual (FM) 34-2, Collection Management and Synchronization Planning, circa 1994 provides several ancillary examples of how classical game theory can be used to develop

PIR.

This framework of strategic reasoning is well represented in each example of effective PIR while remaining absent in the following examples of ineffec tive PIR, excerpted from Appendix D of FM 34-2, that demonstrate this point.13 Example of poor PIR “Will the enemy attack? If so, where, when and in what strength?”

• This PIR is obviously not a result of staff wargaming. There are several specific criticisms we can make.

• This PIR actually contains four significantly different questions. Which of these four questions is the priority? Unless given more guidance, collection assets must decide for themselves which part of the PIR to collect against.

• It assumes the intelligence staff knows absolutely nothing about the enemy situation. Actually, they probably know more about the situation than “the enemy might attack sometime, somewhere and in some strength.” Using the intelligence preparation of the battlefield process, they can provide more focused PIR than this.

• Finally, when wargaming potential friendly and enemy CoAs, the staff should find some aspects of this PIR to be irrelevant to the friendly CoA. For example, your defense may be fully capable of defeating the enemy regardless of when they actually attack. Perhaps the focus need be only where they will attack, supporting a decision on employment of the friendly reserve. Examples of good PIR Just as there are no standard situation templates or friendly CoAs that will serve in all situations, there is no stan dard set of PIRs. Good PIRs, however, have some things in common:

• They ask only one question.

• They focus on a specific fact, event or activity.

• They provide intelligence required to support a single decision. Examples: Figure 3. Relationship of specific information requirement (SIRs) to indicators to EEIs to PIR. (Adapted from Figure 4-5, FM 3-98)

“Will the enemy use chemical agents on our reserve force before it leaves AoA Jean-Marie?” “Will the enemy defend Objective Kevin using a forward-slope defense?” “Will 43rd Division send its main attack along AoA 2?” As you can see, all examples of good PIR are framed as “yes” or “no” questions, simplifying the information requirement into the positive or negative presence of an independent variable (similar to EEIs as defined in Figure 4-5 of FM 3-98). Initially, this ap proach may seem too binary for a complex operational environment, but further analysis indicates that if used correctly, it can be an effective meth odology at the tactical level. This is particularly apparent when a com mander is unable to obtain the critical information needed to reach a DP or achieve a desired effect. In our preceding scenario, this would imply that the brigade’s ability to an swer PIR in a timely manner has been compromised by either environmental constraints or resourcing limitations. In other words, Blue Force does not have the capacity to identify the ene my’s composition along both the northern and southern AoA (for DP 1) or to detect and target all remaining counter-mobility assets in the area of operations (conditions-based trigger). To apply classical game theory to this scenario, the staff must first identity the four possible outcomes of the pre ceding operation. For simplicity, let us assume there is an absolute parity (1:1) in combat power at echelon be tween these two opposing formations. In its most basic form, each command er essentially has two options. For the Blue Force commander, the first option is to commit the main effort to the northern AoA, and the second op tion is to commit the main effort to the southern AoA. For the opposing-forces (OPFOR) commander, Option 1 is to commit the defensive main effort to the northern AoA, and Option 2 is to commit the defensive main effort to the southern AoA. To calculate the probability and payoff in this zero-sum game, we must also apply a universal point system. One point will be awarded to a command er who achieves opposing minimum force with the main effort, and a sec ond point will be awarded to a com mander whose main effort is commit ted to an engagement area with advantageous terrain for that specific element. This scenario posits a Blue Force IBCT conducting offensive oper ations against two OPFOR MIBN. The severely restricted terrain in the southern AoA is ideal for the primarily dismounted Blue Force elements. Conversely, the two high-speed mobility corridors in the northern AoA are advantageous to the primarily mecha nized formation of the OPFOR. Figures 4 and 5 are graphic depictions of the four potential options, along with a payoff matrix accounting for the points earned by the commanders in each of the four outcomes. In these examples, both players have a clear dominant strategy, with an apparent Nash Equilibrium in the lower-left quadrant of the payoff matrix. The Blue Force commander’s dominant strategy is to commit the main effort to the southern AoA. Using this strategy, Blue Force will certainly have advantageous terrain for a dismounted formation and will have a modest 50-percent chance of achieving the minimum-force requirement with its main effort. The OPFOR commander’s dominant strategy is to commit the defensive main effort to the northern corridor. With this strategy, the OPFOR will have both advantageous terrain and will achieve the minimum-force re quirement with its main effort. Bearing this in mind, the staff is able to determine the most favorable op tion to each commander, as well as how Blue Force can increase the probability of achieving minimum force with its dominant strategy. Figure 4. Four game-theory CoAs.

Our final PIR will synthesize all the preceding elements (DPs, targeting and classical game theory) to support a dynamic commander’s operational visualization: Will the enemy commit two or more counter-mobility assets to the southern AoA? This PIR is ideal because, while it sup ports the BCT shaping efforts and commander’s DPs, it also provides Blue Force with the highest likelihood of achieving the minimum-force re quirement with its main effort. If able to neutralize the enemy’s counter-mobility assets in the southern AoA, the minimum-force requirement will be effectively reduced from a 3:1 to a 2:1 ratio, which will then change the score in the lower-right quadrant of Figure 5 from “1,1” to “2,0”, further improv ing the Blue Force commander’sal ready dominant strategy. Conclusion In the preceding examples, I provided both commanders and their staffs with a cognitive framework to generate tac tical-level PIR that are effective in complex operational environments. This framework is based on both past and present doctrine, as well as les sons-learned while I served as IC man ager during two combat-training-center rotations. Large-scale combat operations require commanders and staff personnel who are dynamic, fluid and integrated in their operational approach. When en acting their operational visualization, dynamic commanders are likely to use all three cognitive frameworks, each at a different phase of the operation:

• Initially, the game theorist will seek to lessen the volume of operational variables during a time when information is limited. Figure 5. Scorecard for game-theory approach.

• Next, the conditions-setter will aim to reduce the enemy’s ability to generate combat power while also preserving his/her own.

• Lastly, the DP tactician will maximize operational flexibility by planning against a degraded enemy and fewer operational variables. To support this dynamic progression, the staff must ensure that all three symbiotic functions of effective PIR are represented throughout the plan ning process. In doing so, this ap proach will produce PIRs that are ulti mately capable of mutually supporting DPs, the targeting cycle and the con ceptual application of classical game theory. CPT David Tillman, a student in the Military Intelligence Captain’s Career Course, was the brigade IC manager, 1st BCT “Bastogne,” 101st Airborne Di vision (Air Assault), Fort Campbell, KY, when he wrote this article. Previous assignments include IC platoon leader and brigade IC manager, 3rd Armored BCT (ABCT), 4th Infantry Division, Fort Carson, CO; and assistant S-2 and in telligence, surveillance, reconnaissance manager, 4th Squadron, 10th Cavalry Regiment, 3rd ABCT, 4th Infantry Di vision, Fort Carson. CPT Tillman’s mili tary schools include the Defense Intelligence Agency (DIA) Collection-Manager Basic Course; Signals Intelligence/Electronic Warfare Officer Course; DIA Primary, Alternate, Con tingency and Emergency Essentials Figure 6. DPs, targeting, game-theory nexus.

Course; DIA Joint Intermediate-Target ing Course; Intelligence, Surveillance, Reconnaissance Manager Course; and the Military Intelligence Basic Officer Leadership Course. He has a bachelor’s of arts degree in criminal justice from Southern Illinois University, and he is currently a graduate student at North eastern University College of Professional Studies for a master’s of arts de gree in strategic intelligence and anal ysis. CPT Tillman has completed one rotation at the National Training Center, one rotation at Joint Readiness Training Center and one deployment in support of Operation Spartan Shield. Notes 1 FM 3-55, Information Collection, 2013. 2 COL Thomas M. Feltey and CPT Matthew Mattingly, “Initial Commander’s Critical Information Requirements and the 5 Common Command Decisions,” AR MOR, Fall 2017 edition. 3 FM 2-0, Intelligence, 2018. 4 Eric Slater, “Decision-Point Tactics: Elevating Intelligence Preparation of the Battlefield in a Decisive-Action Training Environment,” Small Wars Journal, Sept. 30, 2015. 5 FM 3-90-1, Offense and Defense, 2013. 6 John J. Mearsheimer, “Assessing the Conventional Balance: The 3:1 Rule and Its Critics,” International Security 13, No. 4 (1989), accessed Dec. 16, 2020. 7 Dr. Joe Strange and COL Richard Iron, “Understanding Centers of Gravity and Critical Vulnerabilities,” The Forge. De fence Journal, 2004. 8 Dale Spurlin and Matthew Green, “De mystifying the Correlation of Forces Cal culator,” Infantry, January 2017. 9 FM 3-98, Reconnaissance and Security Operations, 2015. 10 Carl H. Builder, Steven C. Bankes and Richard Nordin, “Command Concepts: a Theory Derived from the Practice of Command and Control,” Santa Monica,

CA: RAND, 1999.

William P. Fox, “Applied Game Theory to Improve Strategic and Tactical Military Decisions,” Journal of Defense Management 6, No. 2 (2016). 12 FM 34-130, Intelligence Preparation of the Battlefield, 1994. 13 FM 34-2, Collection Management and Synchronization Planning, 1994. ABCT – armored brigade combat team AO – area of operations AoA – avenue of approach BCT – brigade combat team BLUFOR – Blue Forces (friendly forces) BTG – brigade tactical group CoA – course of action DIA – Defense Intelligence Agency DP – decision point EEI – essential elements of information FFIR – friendly forces information requirement FM – field manual HPT – high-payoff target IBCT – infantry brigade combat team IC – information collection MIBN – mechanized-infantry battalion MIC – mechanized-infantry company OPFOR – opposing force PIR – priority intelligence requirement SIR – specific information requirement Acronym Quick-Scan Donovan Research Library Donovan Research Library Maneuver Center of Excellence hosts Armor student papers on various subjects, https://www.benning.army.mil/Library/Virtual.html, and back issues (1988-1982) of ARMOR magazine, https://www.benning.army.mil/Library/ CavalryArmorJournal/index.html Back-issue archiving shared with eARMOR (1983 through current edition), http://www.benning.army.mil/armor/earmor/