Course of Action (COA) In incident-level decision making, a Course of Action (COA) is an overall plan that describes the selected strategies and management actions intended to achieve Incident Objectives, comply with Incident Requirements, and are based on current and expected conditions. Ask, “How are we going to do this?”
What is step 5 of the MDMP. Step 5 -COA Comparison. ___________ is an objective process to evaluate COAs independently and against set evaluation criteria developed during mission analysis and refined during COA development. COA comparison. To identify the strengths and weaknesses of COAs, enable selecting a COA with the highest probability of ...
course-of-action development steps: analyze relative combat power ; array initial forces ; develop the scheme of maneuver ; determine c2 means and maneuver control measures
* Staff: Develop courses of action together to integrate all battlefield operating systems. * Staff: Ensure the course of action is complete, consistent with doctrine, complies with the commander's guidance, feasible, and unique. * Staff: Develop courses of action that identify what, when, where, how, and why the unit will execute.
Remember, the vision is what you want to accomplish. Mission is a general statement of how you will achieve your vision. Strategies are a series of ways of using the mission to achieve the vision. Goals are statements of what needs to be accomplished to implement the strategy.
Mission (the what and why) Developing mission statements are the next step in the action planning process. An organization's mission statement describes what the group is going to do, and why it's going to do that.
Determining resources needed to implement those tasks. Creating a timeline. Determining tracking and assessment method. Finalising the plan. Distributing the plan to everyone involved in the process of planning.
Strategy Formulation- Strategy formulation is the process of deciding best course of action for accomplishing organizational objectives and hence achieving organizational purpose.
Create an action plan to help you achieve your goal by following these five steps: Set SMART goals. Create a list of actions. Set a timeline....Monitor the progress.Set SMART goals. Image description. ... Create a list of actions. ... Set a timeline. ... Designate resources. ... Monitor the progress.Nov 30, 2021
10 Steps to Accomplishing Your VisionGo boldly after your biggest goals. ... Be your own No. ... Don't underprice yourself. ... Make sure you stand out. ... Network with big players. ... Break the checkmark addiction. ... Set aside sacred momentum time. ... Have confidence in your abilities.More items...•Jul 1, 2013
Planning is the determination of a future course of action to achieve any desired result. It is the process of thinking before doing.
Ans. Selecting an alternative means the best plan has to be adopted and implemented.Dec 8, 2019
Decision making is the process of making choices by identifying a decision, gathering information, and assessing alternative resolutions....Step 1: Identify the decision. ... Step 2: Gather relevant information. ... Step 3: Identify the alternatives. ... Step 4: Weigh the evidence. ... Step 5: Choose among alternatives.More items...•Oct 5, 2021
Planning is a management process concerned with defining goals for a company's future direction and determining the resources required to achieve those goals.
Decision making is a managerial process of selecting the best course of action out of several alternative courses for the purpose of accomplishment of the organizational goals.
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The scheme of maneuver is a narrative description of how the forces arrayed will accomplish the commander's intent. Ensure the scheme of maneuver addresses the elements of the battlefield framework (deep operations, covering force/security force, close operations, rear operations, and reserve).
DISCUSSION: Wargaming is the most valuable step within the course-of-action analysis. Observations from the CTCs indicate that few staffs understand how to war-game effectively, and that many staff officers are not involved in the procedure. By wargaming , the staff takes a course of action and begins to develop a detailed plan. Additionally, it can better synchronize the course of action when the entire staff is involved in wargaming . Information recorded during the warga me provides the information for the development of paragraph three (execution) of the operations order, the execution or synchronization matrices, and the decision support template. Because of the importance of its results, and the time it requires, more time is allocated than for any other step. Wargaming results in the identification of tasks, combat power requirements, critical events and priority efforts, task organization and command and support relationships, decision points and possible fratricide locations.
THE DECISION MATRIX WILL HELP THE STAFF RECOMMEND .
Mathematically, a Bayesian network (BN) is a probabilistic graphical model representing a set of variables with a joint probability distribution and defined dependence relations. In graphical terms, a BN is defined as a directed acyclic graph. Directed cycles are forbidden and nodes may represent any type of variable. Joint probability distributions are ones where the probability of one variable can directly affect the probability of another. A dependency relationship between the variables exists when this occurs. BN make use of conditional probability, where the probability of one event is conditional on the probability of a previous event or set of events. However, this is both a benefit and a limitation because all prior knowledge used must be applicable and trustworthy, or the “reasoning” results may be incorrect.
The impacts of implementing effects-based operations (EBO) on course of action (COA) development and evaluation will be significant. Because EBO focuses on producing effects from military activities, as opposed to the direct result of attacking targets, there is an opportunity to develop a significantly higher number of COAs that achieve the desired effects. Consequently, EBO planning will significantly increase the number of evaluated COAs and the depth of evaluation. In order to evaluate these numerous COAs, which may achieve the same desired effects by substantially different methods, metrics must be found to adequately quantify their relative merits. Desired effects may be achieved though disparate COAs, such as propaganda campaigns versus major interdictions. The Course of Action Simulation Analysis (CASA) task was created to research metrics identification, data representation and scoring approaches. This paper introduces concepts behind CASA, chronicles task results to date, and finishes with a discussion of the scoring methodologies and capabilities developed during the CASA prototyping effort. Specific areas discussed include: mission-level simulations usage to examine multiple-hypothesis solutions; ontologies and extensible mark-up language (XML) metadata representations; COA metrics identification; development of tools for data reduction, comparison and visualization; and scoring approaches. Finally, lessons learned to date are discussed.
Attrition-based scoring represents one approach to answering the need to identify a common set of scoring metrics that allow disparate COAs to be directly compared. The attrition-based scoring approach attempts to consider the kinetic effects of missions, both positive and negative. In researching this approach, several templates were constructed to account for how the results of kinetic actions affected numerous facets of the battle space, including but not limited to, adversary forces; civilian populations; economics; and political, religious, and cultural infrastructures. What quickly became obvious was that each examined application of kinetic force had numerous exceptions. When the templates were combined and revised to attempt to account for all variations, they became very large and were generally sparsely populated and unwieldy. Their sparse nature forced abstraction to allow for direct comparison, with each abstraction specific to the COAs under examination. Additionally, attempting to allow for EBO considerations expanded both template size and complexity. Following numerous failed attempts to find a means to use this scoring approach, a more fundamentally abstract approach was researched.
The military planning process depends upon analysis to anticipate and respond in real-time to a dynamically changing battlespace with counteractions. Complex technical challenges exist in automating these processes to derive hypotheses about future alternatives for mission scenarios. The military conducts combat operations in the presence of uncertainty and the alternatives that might emerge. It is virtually impossible to identify or predict the specific details of what might transpire. Current generation wargaming technologies typically execute a prescripted sequence of events for an adversary, independent of the opposing force actions. A significant research challenge for wargaming is predicting and assessing how friendly actions result in adversary behavioral outcomes, and how those behavioral outcomes impact the adversary commander’s decisions and future actions. The focus of this research was to develop technologies to assist decision makers in assessing friendly COAs against an operational-level adversarial environment. Utilizing high-performance computing (HPC) technology, it is possible to dynamically execute multiple simulations concurrently to evaluate COAs for critical elements related to execution and timing as well as overall effectiveness against a range of adversarial or enemy COAs (eCOA) [1].
The main emphasis in the task and effect-based scoring model is to account for the relative importance of the individual tasks on achieving the overall desired effects. The viewpoint here is that although a given COA may inflict dramatically more casualties than are sustained, it could still prove to be a poor COA. For example, suppose the purpose of a COA is to destroy the enemy’s ability to utilize weapons of mass destruction (WMD). It achieves 25% success on all missions without losing a single asset, but the COA would not be considered a success. The enemy will still be able to utilize WMD even though they sustained more damage than they inflicted.
Influences are a separate scoring mechanism from the metrics used to capture score-on concepts and EBO effects that may not map directly to data from the simulation. They are used to bias the score either positively or negatively based on whether a set of conditions is met.
In an effort to represent data beyond two dimensions, ontologies were evaluated. An ontology is a relational model of data. Instances are created and grouped into classes based on their attributes. Inheritance-based specification of these classes ensure uniformity and data independence in the constructs. These logical groupings of data into higher-level concepts provide a clear correlation of data into information.