Statistics for Business Decision Making - Term Paper Example

Statistics for Business Decision Making And Competitive Advantage April Table of Contents Table of Contents ii Executive Summary Introduction 2 Statistics for Decision Making and Competitive Advantage 3 Conclusion 7 Personal Opinion 8 References 9 Executive Summary Decision making must be based on some information and not mere opinions and beliefs. Decisions based on statistical data have a sound and are reliable, valid and can be generalized is sampling ethics were properly followed during data collection, collation, analysis and presentation. Models and forecast based on statistical data form a probabilistic proposition which is tangible and which spells out the chance of the organization/business performing better than it currently does. It is easier to apply statistics and make decisions that are satisfying and which fit different scenarios and situations. Further, statistical analysis provides trends which form the backbone in planning purposes. In addition, advertising/marketing bodies use statistics to understand different markets and customer behaviour in order to formulate advertising/marketing campaigns. In general, market specialists use statistically analyzed data to identify reliable opportunities to develop and expand businesses. Introduction Human beings make tangible decisions which dwarf all sources of competition if more and better information from statistical analysis is available. With statistical knowledge, many researchers have found that, it is easier to apply them and make decisions that are satisfying and which fit different scenarios and situations (Winthrop, A. 2009 p.1). According to Winthrop, statistics are used as a standard unit which uses historical performance to come up with future targets which drives businesses (p.1). To him further, statistical analyses provide deep understanding into how different business departments (sales, human resources, stocks, marketing etc) are performing in relation to the overall goals and objectives of the business. Also, statistical analysis provides trends which form the backbone in planning purposes (p.1). Statistics are also employed in policy formulation by Governments which carry out studies from time to time to have a sound foundation of the policies and decisions made. Further, businesses use statistical data to evaluate the performance of current strategies and to come up with reliable information onto which strategies are working and which just wastes of resources. Again, new business initiatives are evaluated and changed in order to improve business performance backed by survey/feedback data from statistical marketing surveys. In addition, advertising/marketing bodies use statistics to understand different markets and customer behaviour in order to formulate advertising/marketing campaigns. In general, market specialists use statistically analyzed data to identify reliable opportunities to develop and expand businesses. This paper, therefore, will highlight the importance of statistics in decision making and marketing. Also important statistics tools required by managers will be highlighted. Statistics for Decision Making and Competitive Advantage Modern day managers which are highly rated have the knowhow that they propel their businesses to a competitive advantage once they base their decisions on performance putting into considerations different situations for different scenarios (Fraser, C. 2007 p.23). To make tangible decisions, statistics are essential and the resultant information gained using past data/information should be put through using business terms and graphics/tables which are easy to comprehend even by non-statisticians in order to aid in decision making. According to Fraser, the business world has become increasingly competitive for doing business and only a few businesses (manned by the modern day managers) differentiate themselves through the use of enhanced decisions which often have foundations backed by statistics since they are useful and employ the use past and present business data/information to come up with forecasts, descriptive statistics and other statistical summaries which when combined produce a fine future business position which is reliable and valid (p.23). To ensure success in the use of statistics in decision making, statistical software have become available to model data for fast processing and consumption and hence faster decisions (p.23). To Fraser, very few businesses have capacities to understand the use of statistics to create an edge in the global arena which is full of competition (p.23). Further to her, very few businesses can come up with reliable and valid data models which can be ably used as tools to identify performance predictors as well as to compare decisions for different situations in addition to coming up with future forecasted performance values which can drive the business a notch higher (p.23). To Singh, K. (2007 p.45), a manager is better placed to make a good decision after seeing analyzed and presented data since it has detailed information and offers him/her different dimensions from which to face a certain situation. Its comprehension is far well beyond mere numbers presented in tables since no inferences can be drawn from them. Further to Singh, to better understand market trends or population traits (buyer preferences, behaviours, why, when and what they purchase as well as who they are), one needs to be well equipped with statistical data so as to identify dispersions and variations which drive competition and how to overcome it and cut a market niche (p.45). To perform in any market, one has to have the knowledge of how a change in one variable changes the others. In this regard, linear regression basics are important in driving a business competitive edge. Equation of the form, Sales = Bo+B1+B2+…+Bn apply where sales is the dependent variable while B’s are the independent variables. Variables which explain the dependent variable (see example in figure 1 below). The equation is; SALES = 252.4 + 1.43OSP (where OSP = Opening Selling Price). An increase in OSP by 1 unit increases the sales volumes by 1.43 units. The coefficient for Opening Selling Price is 1.43 and lie between 1.42 and 1.45 (t (60) = 191.13, p = 0.000, p< 0.05). The correlation coefficient between the two variables is 0.9992. This means that 99.9% of the total variation in sales can be explained by the Opening Selling Price. The way the results are presented is another important aspect in marketing, advertising and awareness creation. For effective results presentation as Freed, M. et al. (1991 p.42) puts it, graphics/tables are essential as reliable and valid memos and PowerPoint slides help in the faster understanding and digestion of the results by various audiences such that the results become part of them and remembering results is faster. According to Singh, for one to be competitive, he/she must have the knowledge to come up with a model which can be used to forecast (p.45). To Singh, a mind that is inclined towards model building and which is focused on future performance explanatory variables and which has an understanding that performance is driven by important variables which form part of the decision making, has a business competitive advantage (p.45). Summing up his assertions, Singh argues that when a manager or any one in charge understands how important decision variables predict different performance rates under different scenarios, then he/she can make binding decisions which can enhance future performance (p.45). According to Winthrop, A. (2010 p.1), statistics are also employed in the computer industry to study emerging trends as well as in the development of new products to meet consumer requirements, expectations and preferences. To Winthrop, statistics data support new product development in a better manner without which businesses/organizations will have no other better way to determine the ever increasing and changing consumer preferences (p.1). Further due to competition and demand for resources, businesses rely on statistical data to come up the best practices on how to use the existing meager resources at the same time planning for future requirements and use. In summary as Winthrop puts it, managers make use of regular (monthly/quarterly) statistical data to change business variables according to different conditions for improved overall performance (p.1). Fraser emphasizes on the use of surveys statistical data by businesses in order to come closer to the targeted market (p.23). According to Fraser, survey data is normally collated, analyzed and presented using reports in order to determine potential and existing consumer preferences and to assess their buying habits in addition to analyzing how they can be motivated to buy certain products (p.23). Normally, businesses rely heavily on such information to have a better criterion for creating a unique marketing and advertising phenomena. Fraser warns that organizations/businesses operating without such kind of data are operating in a vacuum and may be faced by difficult situations which may hinder their capabilities to provide goods and services hence solving consumer and managerial problems (p.23). Conclusion Business managers should strive to have some statistical knowledge with them as they execute their day-to-day duties since; With statistical knowledge it is easier to apply them and make decisions that are satisfying and which fit different scenarios and situations; Statistical analysis provide deep understanding into how different business departments (sales, human resources, stocks, marketing etc) are performing in relation to the overall goals and objectives of the business; Statistical analysis provides trends which form the backbone in planning purposes. Statistical data is used to evaluate the performance of current strategies and to come up with reliable information onto which strategies are working and which just wastes of resources. Further, new business initiatives are evaluated and changed in order to improve business performance backed by survey/feedback data from statistical marketing surveys; Statistics is important in understanding different markets and customer behaviour in order to formulate advertising/marketing campaigns. In general, market specialists use statistically analyzed data to identify reliable opportunities to develop and expand businesses. Personal Opinion According to me, the following statistical skills are essential to all managers since without them, decisions made will always be lopsided, un-reliable and not valid as they will have no backings; More research needs to be done on forecasting skills which will enable them take advantage of the past data to plan for the future. It is important in this case to have knowledge of statistical packages for faster analysis and report production to enable faster decisions; There if need for more skills on how to carry out linear regression is important as such data answer the question, “How much?” Explanatory variables shows the amount with which the dependent variable will change if they change by a certain amount; The use of exploratory data analysis is another important statistical tool for business managers should have as it will enable them to explore the data so as to identify; Outliers; Understand the essential variables; and To determine the presence of autocorrelations, serial correlations and multi-collinearity in the business data for corrections. These should be further researched. References Fraser, C. (2007). Business Statistics for Competitive Advantage with Excel 2007: Basics, Model Building, and Cases Virginia. Springer: New York, p. 23 Freed, M. et al. (1991). Handbook of Statistical Procedures and Their Computer Applications to Education and the Behavioural Sciences. NY: American Council on Education, Macmillan Publishing Company, p. 42 Singh, K. (2007). Quantitative Social Research Methods. Sage Publications: Los Angeles, p.45 Winthrop, A. (2010). Using Statistics to Improve and Measure Business Performance. Using Statistics to Improve and Measure Business Performance. [Online] Available from: Retrieved on 12 Apr. 2010. P.1 Read More