TM Descriptions v35 cao 202503015 pdf 1 1.pdf

UNCLASSIFIED

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 1 of 11

Transformational Model for Decision Advantage Descriptions for the Tier-2 Decision Functions of the BattleAnalysis, BattlePlanning, BattleCommand, and BattleManagement Decision Domains

The following table provides descriptions and examples for the 52* Decision Functions (DFs) of Command and Control (C2) and Intelligence as defined in the Transformational Model (TM), a Model-Based Systems Engineering (MBSE) decomposition of warfighter decisions.

These explanations cover the Tier-2 decompositions of the BattleAnalysis, BattlePlanning, BattleCommand, and BattleManagement DFs. These explanations are not authoritative; the Systems Modeling Language (SysML) model provides the definitions of the DFs. This document is an accompaniment to those definitions. If you wish to join our effort to build and refine the TM or have questions or feedback, please contact the DAF ABMS CFT.

*There are 52 Tier-2 DFs in the Decision Domains of Intelligence and C2: 12 in BattleAnalysis, 12 in BattlePlanning, 15 in BattleCommand, and 13 in BattleManagement.

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 2 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

Combined Joint All-Domain Ops: military decision-making for the application, threat, and management of violence toward some national (or equivalent) goal

DecisionDomain: TM-BA BattleAnalysis “What is real?”

BattleAnalysis:

Turning data into information and relevant information into actionable knowledge

While the Decision Domains and Decision Functions do not respect duty titles, units, ranks, or echelons, TM-BA DFs are commonly performed by units/platforms responsible for surveillance, Electro-Magnetic Spectrum Operations, and military intelligence.

TM-BA.2.CIN

Clarify Information

Needs “what additional information do they need?”

Clarify Information Needs (CIN) anticipates and evaluates questions and knowledge gaps, whether asked directly or implied from context. CIN refines those questions and gaps with feedback and looks for patterns and gaps in aggregate Requests for Information (RFIs). CIN mediates dependencies between BattleAnalysis instances and other decision domains.

A unit requests information about a surface-to-air missile system in the southern area of operations. CIN seeks to discern does it matter whether they intend to avoid the threat or target it? Will a data dump of current knowledge suffice, or does it need to be contextualized or tailored to that unit? Is further observation for pattern-of-life or interactions with the broader defense system necessary?

TM-BA.2.ASP

Appraise Signal

Pedigree & Provenance “credibility of the source, vulnerability of the path”

Appraise Signal Pedigree & Provenance (ASP) rates the credibility of producers of observation and measurement data and assesses the impact that information transport paths may have had on data qualities including uncertainties. ASP compares confidence in data sets given sources and paths and assesses changes in pedigree and provenance over time.

Two signal reports from different sources may have the same reported uncertainty (e.g., ellipse size, frequency spread, etc.), however if one is from a source that regularly sends false positives, and the other ostensibly traversed a vulnerable network path, then the overall uncertainties for those two reports are different.

TM-BA.2.CSS

Choose Signal

Subgraph “looking with fresh eyes for new insight”

Choose Signal Subgraph (CSS) explores combinations of available observations (BattleSignals) and non-observations (EntityVoids), and discovers new patterns (i.e., patterns that are not already included in or are divergent from available library (a priori) knowledge). CSS assesses mutual-exclusion (paradoxical) indications there could be more than one origin for the signals, common (co-phenomenological) origins that could be a one-off or new pattern, e.g., a discovery of something novel about an Operational Environment, and anomalous absences of data.

A combination of radar plots and unfamiliar albedo measurements indicate either a new orbital object or new behavior of a relocated orbital object.

TM-BA.2.MSS

Match Signals and

Signatures “pattern matching with a priori knowledge”

Match Signals and Signatures (MSS) exploits usable libraries (a priori knowledge) of patterns and examples, looks for those patterns in a set of signals, observations, and non-observations, characterizes the confidence in possible signature matches, and assesses availability of matchable patterns and how that availability is changing over time for a particular data set or part of the Operational Environment. MSS is where common notions of “data fusion” occur (specifically the combination of uncertainties to reduce variance, i.e., convolving error ellipses, combining covariance matrices and higher order analogs thereof).

A collection of emissions from a single location and time includes a navigation beacon waveform, military data link communications, and early warning radar Type X. This set of BattleSignals constitute BattleSignatures for Ship Types Y1, Y2, and Z, therefore there are three possible signature matches.

TM-BA.2.UST

Update Signature

Templates “building and refining a library”

Update Signature Templates (UST) takes new patterns from CSS and pattern-match uncertainties from MSS and considers whether to establish a new pattern as a BattleSignature template (library entry). UST includes contextualization and parameters to refine, split, or archive an existing template. UST links BattleSignature templates together in knowledge graphs (e.g., for composite systems-of-systems, or a specific nation’s order of battle, etc.). UST compares the outputs of CSS, MSS, and DNA and the information content associated with known (MSS) versus novel (CSS) phenomena and characterizes the rates of change in that comparison.

We observe the launch of an orbital object, and none of the existing satellite signature templates match well or account for observed actions or characteristics, so we create a new library entry to correlate future observations of this particular object, and recognize if they launch second, third, etc. of this evidently new type of satellite.

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 3 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

TM-BA.2.DNA

Discover New Attributes “character development”

Discover New Attributes (DNA) creates and updates characteristic-types and associated value-ranges for objects in an Operational Environment. DNA considers contexts and observability associated with characteristic-types and value ranges.

We find out an adversary is applying anti-drone-swarm ablative armor to superstructures on a class of ships, but only at one of several shipyards performing refits, so we add a characteristic to differentiate hull numbers of the same class with “armored/not armored”.

TM-BA.2.SEH

Specify Entity

Hypothesis “naming possibilities to enable follow-on action”

Specify Entity Hypothesis (SEH) evaluates signature matches (from MSS) and novel patterns (from CSS) found within a set of data and chooses whether or not to promote some combination of BattleSignatures to a named EntityHypothesis. A hypothesis (or explanation) may be a general category (e.g., “Ship Type X”), particular object (“Hull # YYYY), and may include state information (e.g., anchored, under way). SEH is where the common notions of “track initiation and correlation” occur.

Based on new observations reported by a special forces team, what we thought was likely an ad hoc supply distribution point may also be a gathering place for adversary leadership, so we add that hypothesis as an explanation for that building.

TM-BA.2.FHP

Formulate Hypothesis

Probabilities “the shape of probabilities”

Formulate Hypothesis Probabilities (FHP) estimates the relative likelihood for explanations (from SEH) associated with something in an Operational Environment (e.g., a probability distribution over the plausible explanations for Object X), figures out how those likelihoods change with respect to each other and over time, and characterizes the overall confidence in a multi-hypothesis probability distribution.

Some confluence of indicators could be a commercial cargo aircraft, an enemy bomber, some other kind of airborne object, malicious code injected in a data feed, or a coincidence of stray voltages in several sensors. All those explanations may be roughly equally plausible, so our distribution would be “flat”.

Or one or two explanations may stand out from the rest.

TM-BA.2.DAD

Describe Attribute

Dependencies “if they shift this lever here, that gear might move over there”

Describe Attribute Dependencies (DAD) figures out how entity attributes relate to each other, both in general and with respect to specific things in an Operational Environment. Those relationships between attributes become chains-of-inference, where knowledge about some attribute(s) leads to knowledge, with some confidence, about other attributes that may or may not be directly observable. Those chains of dependencies may apply to characteristics of a single object or span multiple objects.

We may not have good location information on a bomber, but by developing knowledge of the connection between radar modes and aircraft behavior we can then take the detection of sporadic detections of a radar-type emission— associated with that class of bomber—in ground-mapping mode to assess the bomber may be flying low-level which may in-turn guide our search area choices.

TM-BA.2.ANI

Assess Nodal Interactions

“weaving a web-of-webs of possible states of the

Operational Environment”

Assess Nodal Interactions (ANI) builds, updates, and refines a knowledge graph with all credible combinations of explanations of objects in an Operational Environment. ANI characterizes how those explanations (EntityHypotheses from SEH+FHP) form compositions, how they provide or consume resources from each other, how they support or threaten each other, in what activities they are often found together, and how all those relationships depend on other relationships and on time and context. ANI “prunes” this knowledge graph of possible descriptions of the OE to eliminate nonsensical conclusions.

Given the possibilities that a certain group of surface contacts could be military ships of various types, civilian/commercial vessels, etc., by combining their locations and behaviors with other information in the OE, we can conclude that either of two or neither of the adversary’s advanced destroyers are among the surface contacts, but there is no supported explanation where both destroyers are among the group of contacts.

TM-BA.2.DSP

Determine Subgraph

Probabilities “asserting reality is somewhere within this bounded subspace”

Determine Subgraph Probabilities (DSP) considers webs-of-webs (i.e., versions of reality that could explain observations) produced by ANI. DSP estimates and updates probabilities between subgraphs and chooses which to assert as “first approximation” predictive mental models of the Operational Environment. DSP also conducts the interplay of the other battle analysis decisions.

Given all the possible combinations of explanations of sensed and reported data, we assess that there are two dominant meta-explanations (i.e., they are the most probable explanations and approximately equivalent in terms of their overall probability) and a “close third”. We now must choose whether to offer up just the two dominant, to include the close third or more for decision makers to base their actions on.

TM-BA.2.DIR

Discern Information

Relevance “information has different value to different users”

Discern Information Relevance (DIR) acts as a check on DSP, considers the likelihood that biases could drive choices and assertions in analysis, and assesses interactions between battle analysis and other decision-making types (e.g., planning, command, battle management, execution, etc.). DIR calibrates the trade-offs in ANI between exploitation of current knowledge, and exploration for new knowledge. DIR adjudicates seams between BattleAnalysis instances and other decision domains.

Given that forces in a particular Area of Operations are actively engaged, such that pivoting away from their current course of action would be highly costly, we need to determine if a possible emerging phenomenon is relevant to their decision to stay the course or pay the cost to pivot.

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 4 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

DecisionDomain: TM-BP BattlePlanning

“What could we do?”

BattlePlanning:

Creating recipes for success and avoiding avoidable errors

While the Decision Domains and Decision Functions do not respect duty titles, units, ranks, or echelons, TM-BP DFs are performed by nearly all units/platforms, with lower-echelon planning artifacts typically nesting under higher-echelon plans.

TM-BP.2.IGP

Interpret Intelligence, Guidance, & other Plans “where will this plan nest with others?”

Interpret Intelligence, Guidance, & other Plans (IGP) ingests Operational Environment, disposition of forces, and order of battle information, as well as orders, policies, and plans (whether on-the-shelf or in development), and extracts details that both inform and bound plan development. IGP also flags gaps and conflicts within those information sources and mediates dependencies between BattlePlanning instances and other decision domains.

A tactical unit’s review of guidance documents reveals a possible conflict between priorities from a theater-level document and a local Joint Task Force message.

TM-BP.2.PFS

Project Future States “imagining the worlds to plan for”

Project Future States (PFS) imagines and chooses attributes of future Operational Environments in various possible conditions and considers the ways those futures would likely unfold to find paths and barriers to success. PFS also conducts the interplay of the other planning decisions and determines what level of detail and fidelity is appropriate for a plan to balance specificity against applicability. PFS is where the common notion of “wargaming” occurs. In that capacity, PFS can “call” services of other decision domains to further develop plan elements, i.e., a planner can “put on their commander/analyst/battle manager/ship captain/pilot/etc. hat” and consider how those actions and decisions will unfold in the projected future state(s).

Consider a region of the world, five years from now, extrapolated from current events.

Also consider a contingency that isn’t forecast from today’s conditions but is plausible and worth being ready for.

How could a plan unfold in those two futures?

TM-BP.2.MAS

Make Assumptions

“bounding the problem space” also “the most dangerous thing a planner must do”

Make Assumptions (MAS) locks down degrees of freedom in plans to allow planning progression and completion and considers the consequences of different sets of assumptions for different plans or parts of plans. MAS looks for conflicts between assumptions and characterizes how a set of assumptions contributes to overall uncertainty in a plan.

The number (n) of aircraft carriers a nation might have in a future timeframe: we could have some idea based on production rates, etc. However, in some cases, it may be very difficult to formulate a single coherent plan that can account for both the n and the n+1 (or more) situations, due to the force projection coverage/gap-fill that next carrier provides. So, we assume for Plan A that nation X has no more than n aircraft carriers…

TM-BP.2.COC

Create Operational

Concepts “bounding the solution space”

Create Operational Concepts (COC) develops and refines operational approaches and designs that apply preferences for certain plan solutions over others, either by applying weights to planning options or excluding all but those options that fit the concept.

We may bound a plan as de-escalatory (i.e., favoring and exploiting reversible actions, etc.) in order to support other instruments of national power.

TM-BP.2.DAP

Design Architectures &

Processes “balancing flexibility with predictability”

Design Architectures & Processes (DAP) develops, evaluates, and compares structures of actors and activities (e.g., organizational constructs, system-of-systems logical integrations, authority structures, process configurations, etc.) and considers underlying rules and connections between them.

Due to a directive from non-military leadership, we need to develop and organizational construct that balances multi-national integration with national sovereignty sensitivities of certain coalition members.

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 5 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

TM-BP.2.DDP

Determine

Dependencies “rube-goldberg-ing a plan”

Determine Dependencies (DDP) both chooses and guesses at how various elements of a plan should and might interact (including causes and effects, series and parallel orderings, mutual exclusions and synergies, connections, groupings, etc.), appraises costs and risks, and how plan variations affect those appraisals, and considers plan resilience with respect to how complicated it is.

When comparing different possible versions of a plan, we determine that Version A is high risk, high cost, but high pay-off with medium probability of success, Version B is low risk, high cost, medium pay-off with high probability of success, and Versions C and D are both high risk, low cost, with medium probability of success.

TM-BP.2.NTO

Nominate

Transformation Objectives

“the mission is the ‘Why’, now we need to figure out the ‘How’”

Nominate Transformation Objectives (NTO) considers plausible changes in activities and capabilities (whether voluntary for own-side, imposed on adversaries, etc.) that would advance or achieve a command-defined mission, and deduces the likelihood those changes would bring about preferred conditions in an Operational Environment. NTO proposes arrangements and hierarchies of objectives and estimates how utilities associated with achieving an arrangement of objectives compares to the value a commander derives as a result.

One way to accomplish our mission to paralyze the adversary’s current freedom-of-maneuver in the South Area of Operations could be to reduce their ability to sense that AO, block their entry corridors, and introduce friction for the adversary units already in that AO.

TM-BP.2.DRE

Designate Resourcing

“best applications of available stuff”

Designate Resourcing (DRE) chooses resources for inclusion in a plan, considers various options for uses of those resources, evaluates the consequences of restricting usage of resource as assets for particular objectives, and establishes baselines for resource costing.

For this version of the draft plan, we will not include squadrons typically assigned to tasks in CCMD X even though those commanders may allow it (those possibilities will be included in a different version). For the squadrons we do include, we will treat them all as multi-role except for Squadrons Y and Z which will be dedicated to SOF support.

TM-BP.2.MAF

Map Asset Flow

“best applications of available stuff”

Map Asset Flow (MAF) chooses progressions of asset locations and readiness states that constitute initial conditions for pursuit of objectives within a plan, considers the pros and cons of various options, and details triggers and circumstances for selecting options.

If Branch Plan Z is activated, the following units will need to relocate as follows…, and cyber defense teams X and Y will need to go to full-crew 24-hour ops.

TM-BP.2.CPC

Construct PlanCOAs

“specifying tasks”

Construct PlanCOAs (CPC) maps specified and implied tasks to objectives, accounting for operational restraints and constraints, where tasks may have varying levels of detail and may be prescriptive, proscriptive, template-based, etc. CPC considers orders-of-operation options, their actuarial characteristics (costs, rewards, etc.) as calculated by DDP, and likelihoods of success/failure.

Template approach: if an adversary ship Type X breaks away from its group, the following kill-webs are conditionally feasible within Plan Y (except in Branches Y.3, Y.4, and Y.5) …

Prescriptive approach: take-off from Base A at ####z, proceed to location B, perform action C…

TM-BP.2.IGO

Integrate & Grade

Options “bringing it all together”

Integrate & Grade Options (IGO) compiles and connects planning elements into draft plans, determines if a draft is complete with respect to an appropriate level of detail, compares mutually exclusive options, and chooses which draft plans to present to commanders for possible activation.

Snapping the chalk line on draft options:

Plan a – Aggressive, resource intensive, non-reversible effects heavy… Plan b – De-escalatory, resource efficient, reversible and non-reversible effects…

TM-BP.2.API

Assess Plan Implications

“what are we leaving out?”

Assess Plan Implications (API) acts as a check on PFS by reflecting on the choices involved in creation of a plan, considers the “negative space”, i.e., situations not planned for, counterfactuals, and lessons learned, characterizes risks within and between plans, and adjudicates seams between instances battle planning and other Decision Domains.

Of the ## plan options we’re developing, none seem to account for the possibility of Event X… Is that important?

Overall, are we developing a set of brittle or resilient plan options?

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 6 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

DecisionDomain: TM-BC BattleCommand “What matters?”

BattleCommand:

The wisdom to recognize and seize advantageous initiatives when they avail; the courage to act when they don’t.

While the Decision Domains and Decision Functions do not respect duty titles, units, ranks, or echelons, TM-BC DFs are typically performed by individuals imbued with command authority. That could be via some legal construct or situationally dependent.

TM-BC.2.TEI

Translate External

Inputs “connecting military & non-military decision-making”

Translate External Inputs (TEI) internalizes information from, and provides feedback to, decision domains beyond Combined & Joint Military Ops (e.g., diplomatic, political, legal, economic, etc.)

and participates in strategy development. TEI informs other command decisions with goals, boundaries, heuristics, and biases.

A commander in the military of Nation X—a signatory to the Geneva Conventions—recognizes stipulations on treatment of prisoners as important information for Operational Limits (IOL), resource allocation (AAR), etc.

TM-BC.2.CCW

Cultivate Command

Wisdom “Coup d’oeil” or “Command intuition about the most important thing”

Cultivate Command Wisdom (CCW) pieces together and adapts a relationship-centric, predictive mental model of an Operational Environment and its future (for planning) or present (in the fight) evolutions. CCW looks for and discerns emerging decisive points in an unfolding battle. CCW also conducts the interplay of the other command decisions.

From a series of observations and reports, a commander realizes a discrepancy in adversary behaviors between sectors, exposing a certain brittleness related to pivoting between offensive actions and defensive reactions in a particular sector, and that brittleness could be exploited as a wedge to poison adversary momentum.

TM-BC.2.DCV

Define Command Value

“how ways and means justify desired ends”

Define Command Value (DCV) integrates a set of premises which can be applied to situations and circumstances in an Operational Environment to answer questions about what a commander values. DCV develops a rubric (either brittle or flexible/adaptable) to judge an outcome and a path (“worldline”) to that outcome against other paths and outcome options.

Done well: a commander provides a clear, flexible value function that subordinate commanders and other decision makers can apply to many situations to enhance the congruence between their own value judgements and what matters to their commander.

Done poorly: a commander provides combination of rules that lead to paradoxes and internal inconsistencies and ambiguities.

Not done (in effect) at all: a commander withholds any usable value function such that subordinates’ only option is to consult the commander about each new situation and choice.

TM-BC.2.CMP

Craft Material Gain/Loss

Profile “calculus of war for material costs”

Craft Material Gain/Loss Profile (CMP) quantifies and composes generalized formulas for actuarial trade-offs between tangible and intangible gains (capturing territory, controlling network enclaves, extending windows to act, seizing a usable airfield, etc.) and losses (expending consumables like time, munitions, fuel, energy, lives, etc.).

Eliminating Target A is worth expenditure of x# of Munition B, a loss of up to y# of lives and z# of Platform C.

TM-BC.2.FOP

Forge Opportunity Gain/Loss Profile

“if we do this, what else can or can’t we do?”

Forge Opportunity Gain/Loss Profile (FOP) quantifies and composes generalized formulas for availability trade-offs between path-of-action gains and losses that contribute to the “worldline” argument in CommandValue functions defined in DCV and factor in how those trade-off calculations change over time and with different circumstances.

Attacking Target A is mutually exclusive with attacking Targets B, C, and/or D.

A successful attack on Target D opens the possibility of attacking Target E or F.

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 7 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

TM-BC.2.SRP

Shape Upside/Downside

Risk Profile “what volume of risk would we accept given…? ”

Shape Upside/Downside Risk Profile (SRP) considers upside (positive) and downside (negative) risk. Risk is the influence of uncertainty on goals.

Due to the adversary’s organizational construct and culture in the North Area of Operations, eliminating the leadership echelon of an enemy unit is likely to lead to paralysis in lower echelons, whereas similar action in the South AO is likely to increase the uncertainty associated with the actions of the subordinate units due to their culture of independent action. Those similar actions have different risks, and therefore one may fit into a commander’s risk profile while the other does not.

TM-BC.2.DRA

Designate Roles &

Authorities “delegating or withholding agency”

Designate Roles & Authorities (DRA) maps decision-making roles to organizations, units, positions, and/or specific people, and determines if and how to delegate command authorities, including the authority to further delegate or withhold authorities, to organizations, units, positions, and/or specific people.

Unit’s X, Y, and Z are designated to perform the roles multi-domain Battle Management in their respective AO, but only Unit Z is given the authority to activate certain offensive cyber ops plans.

TM-BC.2.AAR

Apportion & Allocate

Resources “what part of the inventory is on the table”

Apportion & Allocate Resources (AAR) ascertains resource availability and determines which resources can/cannot be used for particular missions, i.e., to comprise an order-of-battle, and under what circumstances.

During planning a commander specifies several space capabilities as available for use in certain high-pay-off missions but will not release those resources for use in other missions.

During the battle, however, the commander alters the guidance to include several more missions in the list where the capabilities may be employed.

TM-BC.2.IOL

Impose Operational

Limits “restraints and constraints”

Impose Operational Limits (IOL) defines, updates, and rescinds prescriptive or proscriptive rules that bound solution options for decision-makers, e.g., rules of engagement, operating area restrictions, minimum force requirements, national caveats, etc. Operational Limits are typically categorized as restraints and constraints.

No irreversible effects on dual-use bases/ports/facilities.

All strikes must have PR assets on airborne alert to proceed.

TM-BC.2.EMP

Enumerate Mission

Priorities “describing the what without prescribing the how”

Enumerate Mission Priorities (EMP) chooses and racks-and-stacks—in terms of importance— missions (specifically CommandMissions). CommandMissions are desired interim or final “end state” conditions or outcomes in an Operational Environment.

Degrade the supported-supporting relationship between the adversary’s missile force and air force.

Alter an adversary’s relationship with its northern coastline from low-danger to critical vulnerability.

1 TM-BC.2.ABP

Activate Battle Plans

“choosing a common point of departure”

Activate Battle Plans (ABP) sets plan option activation/cancellation criteria, chooses plans, branch plans, and/or sequels for immediate or conditional activation or cancellation, and iterates with planners to adjust, adapt, and refine plan options and drafts.

Any unit, connected or not, upon realization of the following conditions (with high confidence), activate Branch Plan 7D and proceed independently or as ad hoc teams.

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 8 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

TM-BC.2.SBR

Synchronize Battle

Rhythms “avoiding tunnel vision and absenteeism”

Synchronize Battle Rhythms (SBR) chooses and adapts the rates and detail-levels at which commanders’ “sample” their Operational Environment (e.g., update briefs, battlefield circulation, etc.). SBR sets conditions for pivoting between rapid and measured battle rhythms and trigger out-of-cycle revisits, to optimize CCW and DCV outputs, and avoid overreactions to noise and delayed reactions to contingencies.

Done well: a commander sets a predictable battle rhythm that has flexible ramp-up/down and out-of-cycle options and calibrates their rhythm when they detect mismatched command attention with subordinate initiative.

Done poorly: a commander focuses continuous attention on a few areas, “overfitting” the situations and over-reacting to rapidly changing but poorly understood situations, while ignoring others, thereby “underfitting” those situations and leaving subordinate commanders without coherent guidance.

Not done (in effect) at all: a commander sets no battle rhythm, so subordinates have no way to predict or rely on engagements.

TM-BC.2.CDW

Calibrate Decision

Weights “shaping others’ decision-making”

Calibrate Decision Weights (CDW) develops and adjusts decision-making heuristics, i.e., “all-else-equal, lean toward X-type options” for decision-makers to improve decision speeds and likelihood of coherence with command intent.

Bias toward irreversible effects today to reduce adversary capacity tomorrow.

When able, use reversible effects in order to facilitate diplomatic efforts.

TM-BC.2.IBO

Impel Battle Orders “intervene to avoid hesitation”

Impel Battle Orders (IBO) assesses the decision-making environment, recognizes when a subordinate faces a consequential decision for which necessary information is unavailable (to anyone), and makes a choice to either intervene or not. IBO also directs new, unplanned specific actions.

A commander realizing that a subordinate is in a situation wherein, given the current set of guidance and available information, that subordinate commander will not be able to derive any clarity as to which actions will achieve versus detract from command value. The commander intercedes and provides specific immediate actions to take, so that the subordinate can get past the ambiguity and then continue to seize initiative.

TM-BC.2.CCQ

Contemplate

Consequences “it might be time to question my instincts and develop new ones”

Contemplate Consequences (CCQ) acts as a check on CCW, predicts when a commander’s intuition may be mismatched to certain situations, recognizes the role a commander’s upstream decision have on down-stream decision-making (e.g., in lower echelons). CCQ adjudicates seams between instances of BattleCommand and other decision domains.

A commander is considering several adjustments to current guidance, and each change is valid and reasonable, but in aggregate there are down-side consequences that could detract from the efficacy of the individual changes, so the commander calibrates and sacrifices some changes to achieve a better overall outcome.

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 9 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

DecisionDomain: TM-BM BattleManagement

“What should we do?”

BattleManagement:

Orchestrating and exploiting the chaos of combat

While the Decision Domains and Decision Functions do not respect duty titles, units, ranks, or echelons, TM-BM DFs are commonly performed by Tactical C2 units such as Control and Reporting Centers, Tactical Air Operations Centers, Carriers and Destroyers, E-2D/E-3/E-7, etc., and other units performing intelligence production, electronic warfare, and cyber ops.

TM-BM.2.PGP

Parse Guidance & Plans

“understanding commanders’ intent and the plan”

Parse Guidance & Plans (PGP) extracts, digests, and cross-references guidance, orders, and plans, from documents, messages, etc., in context, to inform other battle management decisions with heuristics, biases, constraints, restraints, and templates. PGP posits implied tasks, flags gaps and conflicts in guidance and plans, and mediates dependencies between instances of Battle Management and other decision domains.

Based on theater guidance, planning documents, and e-mails from operational units a Battle Manager realizes that a particular branch plan is no longer viable because the loadouts that certain aircraft ended up taking off with do not match the assumptions that branch plan is based on.

TM-BM.2.FCC

Facilitate Coordination &

Collaboration “fixing our mismatched perceptions”

Facilitate Coordination & Collaboration (FCC) maps out information exchange (logical) webs and evaluates communicated information in context, to assess differences between our own and others’ perceptions and perspectives. FCC crafts messages that remedy those differences and characterizes the differences and how they are changing over time.

On their tactical display, a Battle Manager sees the Precise Position Location and Identification (PPLI) of a friendly fighter aircraft turn east toward its deployed base but does not know why since this would constitute an early departure. On SATCOM, the Battle Manager hears a warning about a ballistic missile salvo that may impact that particular base. On chat, the Battle Manager sees posts between the CRC responsible for defense of that base and the associated PATRIOT unit. The Battle Manager realizes that, by the time the fighter makes radio contact with the base ATC, they may be within range of the PATRIOT. The fighter is not on SATCOM and therefore likely does not know the base may not be unsuitable for recovery and the CRC and PATRIOT may not be aware of the fighter’s approach. The Battle Manager contacts all parties to ensure they know each other and the relevant status while working alternatives for the fighter and supporting the base defense preparation.

TM-BM.2.ISU

Improve Situational

Understanding “aligning my own perceptions to reality”

Improve Situational Understanding (ISU) constructs, refines, and adapts an action-focused, predictive mental model of an Operational Environment and how it may change in the near-term, improves that view of reality as new information becomes available, and triggers focused curiosity by selecting specific things and situations for further evaluation and possible action.

ISU also conducts the interplay of the other battle management decisions.

Based on reports in various forms (chat, data links, voice comms, sensor products, other messages) a Battle Manager predicts a loss of mutual support within one of the Defensive Counter Air lanes, determines what events should appear that would either confirm or disconfirm that prediction.

TM-BM.2.PSA

Posture & Sustain

Assets “setting the chessboard for impending attacks”

Posture & Sustain Assets (PSA) chooses positions, modes of operation, and readiness states for units and weapon systems, along with resource commitments, that are optimized for impending, anticipated, and possible military actions, accounting for friendly-adversary-environment moves and counter-moves.

Based on multiple events, including an adversary's repositioning of a space-based sensor, a coalition commander's report signaling a new mission phase, and an unexpected outage in a secondary communication link, a Battle Manager considers the current posture of sensing assets under their control. The Battle Manager directs a pivot in the positioning and operation modes for some of those sensors, so they are ready for the new circumstances emerging in the Operational Environment. This involves accepting calculated risk by reducing redundancy in coverage to prioritize support for the coalition's evolving objectives, as well as a shift sensor postures designed to balance readiness for future tasks, mitigate the impact of the communication outage, and deny the adversary the opportunity to gather valuable data from their newly established field of regard.

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 10 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

TM-BM.2.SDM

Search Domains

“guessing the shape of our ignorance”

Search Domains (SDM) aggregates unknowns about the Operational Environment, estimates upside and downside risks, and expresses general curiosity by asking well-crafted questions that drive useful information gathering. SDM also characterizes the Operational Environment with respect to complexity and chaos to inform decisions about whether to stick with a plan, adapt a plan, use a plan as a point of departure, or abandon a plan.

Based on several rapidly evolving events, a Battle Manager assesses that a recently received Air Tasking Order change is no longer applicable nor executable.

TM-BM.2.DSG

Discern Significance “expectations versus observations”

Discern Significance (DSG) considers messages (all types of communicated information) in context to assess how influential and revealing various events (or non-events) are with respect to other situations in the Operational Environment. DSG also looks for possible errors in ISU’s expectations and considers the consequences of misperceptions.

A Battle Manager sees a post in a navy coord chat room regarding an immediate re-tasking for a maritime patrol aircraft and assesses the aircraft will likely require escort protection if it will be loitering in a particular location and that a ship-in-distress situation may be developing.

TM-BM.2.PAE

Perceive Actionable

Entity “writing predicate phrases:

sink ship, investigate bogey, jam radar, hack server, etc.”

Perceive Actionable Entity (PAE) determines possible, desirable, and permissible actions to take on something in the Operational Environment—whether it is a target (e.g., to investigate or prosecute) or a task objective (e.g., to rescue, refuel, resupply, etc.)—to achieve a specific effect, calculates the window of opportunity for those actions, and highlights conflicts between desired effects.

A Battle Manager notes adversary forces atypically crossing lanes between the adversary’s own areas of responsibility, assesses there may be a new supported-supporting relationship between two adversary command echelons, and considers actions to verify, characterize, and exploit this newly discovered relationship.

TM-BM.2.AOP

Apply Objective

Priorities “all else equal, use the resource for this-not-that”

Apply Objective Priorities (AOP) assesses how an action that may be taken to achieve an effect fits into commander’s intent and priorities in context, and flags ambiguities and conflicts in prioritization between commanders.

A Battle Manager recognizes an adversary server is subject to two conflicting priorities, wherein supporting one commander’s objectives would involve degrading the server, while another commander’s objectives involve monitoring the server’s behavior and mapping its connections, and initiates comms to resolve the conflict.

TM-BM.2.MEF

Match Effectors

“which tools can do the job and who’s got them in their toolkit”

Match Effectors (MEF) considers which units, agencies, formations, platforms, or weapon systems—individually or as pre-arranged force packages—potentially can & may achieve a particular effect, and rank-orders those potential matches.

When considering a BattleEffect to achieve a mission kill on an adversary surface combatant, a Battle Manager identifies two different applicable plays and associated strike assets, depending on whether the ship turns out to be an older or newer variant of the same class.

TM-BM.2.GBC

Generate BattleCOAs

“web of actions to get from now to a target and back” or “…force-packaging is just the beginning…”

Generate BattleCOAs (GBC) comes up with realm-of-the-possible dynamic mission gameplan options—webs of synchronized actions to enable and support an attack/strike/rescue/etc. force package, from current conditions to return-to-base or follow-on tasks, accounting for Operational Environment and adversary reactions—and grades the qualities of those options.

For a particular play involving joint and coalition forces in multiple domains, a Battle Manager considers several options to enable the core strike package to coalesce at their appropriate locations near or supporting the target area with the resources (information, fuel, support) necessary, including several downside risk options such as decoy and flank maneuvers.

TM for DA, DF Descriptions v35, cao 20250315, jez UNCLASSIFIED Page 11 of 11

Index.Abbreviation Title

“elevator pitch”

Transformational Model (TM) Decision Functions (DFs)

Decision Function Plain Language Explanation Examples These are questions or situations that illustrate the DF.

TM-BM.2.SBC

Sequence BattleCOAs

“quickly find as many shitty options as you can, and from the less-shitty options, pick one and go”

Sequence BattleCOAs (SBC) weaves together various combinations of deliberate and dynamic missions/tasks/force package gameplans, to determine which combinations can actually be accomplished given multiple, often conflicting objectives and limited resources, compares options with respect to command intent, and chooses one of those combinations for implementation, whether that means incorporating a new mission with minimal changes to other on-going actions, sacrificing/cannibalizing some missions to enable new ones, or wholesale shifting to a different set of missions.

With two emerging dynamic targets, and several strike package options for each target, a Battle Manager realizes they can cancel a lower-priority mission and divert some of those resources to one of the of dynamic targets and assemble one of the strike package options for the other dynamic from available on-call assets, and chooses that solution over staying the course on the lower priority target.

TM-BM.2.IBC

Implement BattleCOAs “keeping as many plates spinning as you can”

Implement BattleCOAs (IBC) formulates directions to initiate and pivot between options and adaptations for integrated missions and tasks within an on-going battle to maximize chances of success, minimize losses, exploit/manage risk, and avoid running out of options. IBC is also responsible for vetoing unimplementable choices from SBC.

Upon choosing to pivot, cancelling a lower-priority strike, cannibalizing those resources and using other on-call assets to assemble strikes for two new high-priority fleeting targets, a Battle Manager verifies all players understand the new direction, coherently acknowledge their ability to pivot and roles in the new strikes, and directs the strike leads to proceed.

TM-BM.2.EBI

Evaluate BattleCOA

Impacts “why did we choose this, and what if we had chosen that?”

Evaluate BattleCOA Impacts (EBI) acts as a check on ISU, considers the implications that there are BattleCOA options for this-but-not-that, reflects on the predictions of ISU and choices of SBC with regard to realized outcomes, and assesses interactions between battle management and other decision-making types (e.g., command, analysis, execution, etc.)

What is it about the Operational Environment that a Battle Manager doesn’t fully understand that results in lots of strike options in the North, but relatively few options in the South even though both have available resources and are about evenly contested?