Role of Quantitative Techniques in Decision Making

Introduction
In the current world, successful businesses must use quantitative methods that help in basic
leadership irrespective of whether the business was private or public organization. The technique
incorporates quantitative skills used by managers to make informed decisions which leads to
achievement of better results in the future Govindan, K., Rajendran, S., Sarkis, J., & Murugesan,
P. (2015). Private and public organizations and administration offices rely on quantitative
systems for them to improve their efficiency at work. People in different departments such as
bookkeepers, supervisors and financial experts also require the quantitative techniques to
effectively carryout their duties. It is therefore obvious that the chief managers need to learn
strategic procedures which will enable them to investigate and assess collected data. Logical
decision making often depends on quantitative techniques.
Roles of quantitative techniques for estimating meaningful measures using variables
Data is made up of variables which are always used in any kind of analysis when assessing and
evaluating collected data. In that regard, analysis that involves decision making will do so
through thorough evaluation and exploitation of variables in a particular dataset Mehmood, T.,
Liland, K. H., Snipen, L., & Sæbø, S. (2012).
Simulation technique is a quantitative technique that involves modelling of various situations
using variables to predict the end results considered in decision making by the mangers in
organizations Bulgakova et al, (2014). Additionally, linear programming model, inter
programming, sensitivity analysis, goal programming, dynamic programming, non-linear
programming, queuing theory, inventory management techniques, network analysis

(PERT/CPM), decision theory, games theory, transportation and assignment model are also some
of the quantitative techniques used.
Inputting data in a model
First identify the correct data which covers all useful information needed to solve defined
problems. Errors at this step will lead to incorrect final results in the model. Secondly, the
managers are required to understand the model where the schematics or plans and various
situations are checked and analyzed to minimize chances of any possible cause of error. In the
process, arising problems are solved through experiments to ensure better outcomes Kuik et al,
(2016).
Model is approved based on experimental results. Positive experimental results leads to approval
otherwise, problems found are corrected before the final approval which is done by the
authorities. Finally, the results are taken through actualization process. The process involves
company’s model preparation, modification and execution.
Role of quantitative techniques for estimating meaningful measures using available data
and information
Managers in different organizations use data and information in quantitative techniques based on
statistical figures such as mean and standard deviation to examine project and to make good
decisions.

Mean is the division of the total scores by the number of scores in a sample Yentes et al, (2013).
It is used to find the focal point of the scores. On the other hand, standard deviation is a measure
of dispersion that is used to measure how far the score vary from the mean Mertler, C. A., &
Reinhart, R. V. (2016).
Importance of quantitative methods to managers in decision making
Every manager in any organization needs to poses decision making skills due to their usefulness
because lack of these skills may lead to serious losses in the organizations. Other managers use
data analysis and information obtained in this process to make sound and informed decisions.