Essay

Running head: EFFECTS OF OPERATIONAL VARIABLES ON STRATEGIC ESTIMATES 1

EFFECTS OF OPERATIONAL VARIABLES ON STRATEGIC ESTIMATES 3

Army strategists and planners examines an operational environment (OE) in terms of the eight interlinked operational variables. This journal seeks to explain how operational variables affects strategic estimates over time and why it's important for a future sergeant major (SGM) or command sergeant major (CSM) to understand the operational variables. These variables are well defined by army doctrine reference publication (ADRP) 3.0 and abbreviated as PMESII. They include political, military, economic, social, infrastructure, information, physical terrain, and time (Shortland, Alison, & Barrett-Pink, 2018)

Political variable looks at the roles and seniority power at all ranks of leadership inclusive of formally constituted authorities and informal political powers. It affects strategic estimates by defining the effectiveness and legality of the leadership or governance in place, the available political parties, prevailing domestic political issues, and the attitude of the population to political and military leaders. Military variables deal with military and paramilitary capabilities factors in OE. This affects strategic estimates by being regulated by the composition of the military force in operation, threat actors in OE, and how they manipulate the population, what military capability does the threat actors pose and their limitations (Shortland et al., 2018).

Economic variable is all about individual and collective behaviors in regards to production, distribution, and consumption of resources across an OE. It affects strategic estimate by controls on illegal economic activities, the basis of economy like agricultural, manufacturing, and technology sector. Social variables comprise cultural, religious and ethnic composition with belief, values, customs, and behavior of population. It affects strategic estimate through constraining on cultural architecture, population distribution, religious and ethnic diversity, and number of internally displaced persons or refugees in OE (Samaras, Nuttall, & Bazilian, 2019).

Information variable shows the design, extent, and effects of citizens, organizations, and measures that collect, process, and consume information. It affects strategic estimate through restriction on types of public communication media, state of control of information environment, and threat information warfare capabilities in an OE. Infrastructure variable concerns the basic facilities, services, and installations required for proper working of a community. It affects strategic estimates by addressing the issues of common construction patterns, available and operational utilities, and existing transport network in OE (Henke, 2017).

Physical environment variable majors on geography and artificial structures plus necessary considerations like weather and climate. This affects strategic estimates by stipulation of types of terrain available, weather conditions likely to occur within mission context in OE. Time variable encompasses the timing and duration of activities, events and conditions. It affects strategic estimates by determining the key dates, time period events of mission and the cultural perception of time in that OE. So it's very important for a future SGM or CSM to understand the operational variables as it helps to plan the strategy towards the achievement of desired outcome by choosing the correct operational art.

References

Henke, M. E. (2017). The politics of diplomacy: How the United States builds multilateral military coalitions. International Studies Quarterly, 61(2): 410-424.

Samaras, C., Nuttall, W. J., & Bazilian, M. (2019). Energy and the military: Convergence of security, economic, and environmental decision-making. Energy Strategy Reviews, 26, 100409.

Shortland, N., Alison, L., & Barrett-Pink, C. (2018). Military (in) decision-making process: a psychological framework to examine decision inertia in military operations. Theoretical Issues in Ergonomics Science, 19(6): 752-772.