Working Capital Management
We are currently onto the 21st century. This century has seen rapid development in the ways of problem solving and research methods. These has also increased along with the evolution of information technology which has formed and shaped the economic environment and help them in getting positioned in the market. There are many quantitative techniques which have helped the organizations in taking better financial decision. The quantitative techniques provide better understanding about the current financial situation of the organization. The organizations often face issues as to how and where to make capital investments. Whether, it should be done in some real estate or in Research and Development or in something else (Anderson, 2015). Moreover, the companies need to find out the ways in which they should raise the capital for the total capital expansions. Whether there should be any mix between the debt and equity in the organization or not? The daily operations of the account payables, receivables, credits and debits are also required to be analyzed and the management should be given with the proper key points which will help in better financial decision making. In the following sections, we will check major financial quantitative techniques being used in the organization which help in addressing various issues of the financial management.
Every organization have three main issues to take care while taking any financial decision. These are Working Capital Management, Capital Budgeting and Capital Structure. Working Capital Management decisions are related to the short – term planning of the organization (DeFusco, 2015). The manager try to understand the current assets and liabilities of the organization so that they can plan for the better optimization of the solution. The organization also needs to finalize where to park the short term surplus cash. Capital Budgeting need to be done by the managers to prioritize the expenses which will be required for faster development of the company. The Capital Budgeting makes way for the managers to carve the capital structure of the company. The managers will get to know where to make the investment. They can decide between the equity based investment and the debt based investment.
Statistical techniques are used in the organizations to provide the management with better decision making abilities. This requires an information of various factual ideas including (yet not restricted to) calculated relapse, weights of proof, connection, measurement decrease to give some examples. A decent information of stochastic procedures would be required for working in Market hazard or for evaluating subordinates (Embrechts, 2015). Extraordinary hypothesis and request measurements assume a major part in evaluating operational hazard. Valuing and portfolio administration need a decent comprehension of the dispersion of dangers in a portfolio so that fitting moves can be made. Advertising frequently utilize factual displaying methods to distinguish prospects in deals battles or even in overseeing wearing down. Fraudulent activities make utilization of many factual models from principles based ways to deal with more refined displaying. In conclusion, with such a variety of models, administration may require an autonomous approval group to give them comfort that model have been fabricated appropriately and keep on working. In numerous locales approval of models is additionally an administrative prerequisite.
Capital Budgeting and Capital Structure
The techniques like Time Series Models used for the forecast of demand and supply and many more are used for deciding the fate of the organization. The Portfolio Theory along with various regression methods help the organization to get to know various hidden parameters which can tweaked for the success of the organization. The Capital Asset Pricing Model and models like ROI-ROE analysis, PBIT-EPS analysis, Ratio Analysis, Cash Flow Analysis, Capital Structure Planning and many more financial concepts are there which form a path towards success for the management and the organization. Long Term and Short Term needs can be better forecasted with the help of various forecasting tools provided in the statistics. Univariate and multivariate regression models also helps in better understanding the scenarios. All these are required to calculate the demand and supply of the organization at any point in time. Thus, we can see that the organization have plenty of statistical tools at their disposal to use and to manage the organization in much more effective manner.
The techniques which have been discussed till now are used by the managers to put forward different analysis in front of the top management of the company. The techniques’ output is present in the form of graphs, charts, pivot tables etc. which will make more sense to the board members and top management of the organization (Kahraman, 2015). The chart and graphs make up for the most presentations. The representation of the statistical output in charts and graphs helps in easy understanding of current financial situation of the company. Suppose a company ABC is performing well year on year and its profits as well as revenues are increasing by 10% annually. This when represented in Bar Chart will clearly show the increase in the revenue and profit in most optically suitable manner. The analysis is also easily explained with graphs and charts. During the general body meetings at the organizations, the managers need to present their analysis on the demand and supply. The regression tools and cost benefit analysis helps the managers to provide better recommendations to the business. The business then takes tough decisions which are better for the appropriate function of the organization.
The managers use the statistical tools to make decisions ranging for simple procurement of materials to making strategic decisions of performing mergers and acquisitions (McNeil, 2015). Even though the civil argument on the utilization of research results for approach basic leadership and execution procedures is not new and its components have changed after some time, the issue has increased more noteworthy noticeable quality in late decades taking after the real procedures of world change that inexorably call for solid proof to support or test the developments that are actualized in an assortment of settings, including wellbeing arrangements and frameworks (Radhakrishnan, 2014). The management of the organization take bold decisions towards the operation of the business. They try to use the results provided by the statistical tools to get to know the current financial situation of the company. This helps in making an informed choice rather than just going ahead blindly with the statistical output. The decisions like investment in any new area, increasing the investment in research and development, going forward in any merger or acquisitions etc. are some of the situations where the management used the statistical tools to perform decision making.
Statistical Techniques used in Financial Management
The statistical tools use past data to predict future proposals. The past or the historical data is analyzed based on certain parameters to provide better results. The research reports and various survey details help the management to go forward with certain strategies. These strategies ensure success for the organization (Robinson, 2016). The recommendations provided by the statistical tool just enable the management to go ahead with already decided decisions. They provide extra confirmation which adds to the stability of the decisions. The techniques like Ratio Analysis and Cash Flow Analysis tells about the current financial situation of the organization. This helps the top management to decide the budget and expenditures for the next financial year accordingly. The time series models and forecasting tools uses certain methodologies to consider the current demand in the market and project the data for the estimated demand in future based on certain parameters (Saunders, 2011). The parameters can be external or internal to the organization. The company usually gets benefitted with the decisions being provided by the statistical tools. All the mechanisms push towards the better development of the organization with the help of various fact based recommendations provided by the statistical tools.
The statistical tools discussed in the previous sections are being taken into consideration for many decades now. They are performing their job well. I would like to use the models as is with limited changes. These will be related to the way the output is being projected. Some technical involvement can be brought in to have the interface of the statistical tools provide a comprehensive views and recommendations.
Conclusion
The above sections were focused towards the various quantitative tools and techniques used the organizations to make their organization better than the competitors. The quantitative techniques provide better understanding about the current financial situation of the organization (Van, 2013). The organizations often face issues as to how and where to make capital investments. The decisions like investment in any new area, increasing the investment in research and development, going forward in any merger or acquisitions etc. are some of the situations where the management used the statistical tools to perform decision making. Thus, statistical tools have been helping the management in taking decisions in a fruitful manner.
References
Anderson, D.R., Sweeney, D.J., Williams, T.A., Camm, J.D. and Cochran, J.J., 2015. An introduction to management science: quantitative approaches to decision making. Cengage learning.
DeFusco, R.A., McLeavey, D.W., Pinto, J.E., Runkle, D.E. and Anson, M.J., 2015. Quantitative investment analysis. John Wiley & Sons.
Embrechts, P. and Hofert, M., 2014. Statistics and quantitative risk management for banking and insurance. Annual Review of Statistics and Its Application, 1, pp.493-514.
Kahraman, C., Öztaysi, B. and Onar, S.C., 2015, August. Annual cash flow analysis using hesitant fuzzy sets. In Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on (pp. 1-5). IEEE.
McNeil, A.J., Frey, R. and Embrechts, P., 2015. Quantitative risk management.
McNeil, A.J., Frey, R. and Embrechts, P., 2015. Quantitative risk management: Concepts, techniques and tools. Princeton university press.
Pettinger, R., 2013. Introduction to management.
Radhakrishnan, S. and Wu, S.L., 2014. Analysts’ cash flow forecasts and accrual mispricing. Contemporary Accounting Research, 31(4), pp.1191-1219.
Robinson, D.T. and Sensoy, B.A., 2016. Cyclicality, performance measurement, and cash flow liquidity in private equity. Journal of Financial Economics, 122(3), pp.521-543.
Saunders, A. and Cornett, M.M., 2014. Financial institutions management. McGraw-Hill Education,.
Van Deventer, D.R., Imai, K. and Mesler, M., 2013. Advanced financial risk management: tools and techniques for integrated credit risk and interest rate risk management. John Wiley & Sons.
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