The Impact of Sensitivity and Scenario Analysis on Business - Term Paper Example

The Impact of Sensitivity and Scenario Analysis on Business Name: Institution: Abstract The paper highlights the two techniques used in strategic planning by organizations. The first technique under consideration is sensitivity planning while the second is scenario planning. The paper gives a detailed definition of both and how they have been employed over the years. The paper also particular attention on the use and influence the techniques have had on marketing and production apart from giving their general application. Some of the short-comings and criticism of the two techniques are also highlighted. Focus then shifts to investment appraisal and break-even analysis. The link between the four concepts is then discussed and highlighted. Sensitivity Analysis A background into sensitivity analysis Sensitivity analysis is also referred to as stress testing (Mun, 2006, p. 227). The definition of the term changes based on the purpose or environment the technique is being applied. For instance in project management, F. L Harrison and David Lock define it as the repetition of the initial appraisal financial calculations using stepped variations in the values of one or more of the parameters (Harrison & Lock, 2004, p. 25). On the other hand, in their population viability analysis, Scott Mills and Mark Lindberg describe sensitivity analysis as a set of analytical and simulation based tools that that evaluate how changes in life history attributes of a demographic model affect population growth or rate of extinction (Beissinger & McCullough, 2002, p. 16). From the two definitions, it is possible to derive the general idea behind sensitivity analysis. In general, sensitivity analysis is described as a technique used to determine changes in independent variables affect the dependent variable. The technique is used to determine or test the relative importance of input model input factors (Tarantola, et al., 2004, p. 9). For instance, the productivity of a given set of employees is influenced by several factors such as monetary rewards / remuneration, working conditions, allowances and other nonmonetary benefits. Consequently, sensitivity analysis can be used to analyze how changes in each of these factors/ variables affect the productivity of the workforce given the other factors (variables) are held constant. In this scenario, the dependant variable is the employee output while the independent variables are the factors that affect the productivity (remuneration, allowances and non monetary benefits) General advantages and use of sensitivity analysis in business Sensitivity analysis is widely used in risk management. It is used to determine/ examine the change in the value of a given portfolio. Sensitivity analysis is used to highlight the risks associated with an investment. By rearranging/ restructuring each variable, sensitivity analysis models show the variations in the outcome and highlighting the risks and returns the business is exposed to. From this analysis, the manager can come up with the optimal variable combination that maximizes the businesses bottom line. Sensitivity analysis in marketing In marketing, sensitivity analysis can be used as a means of determining the most effective marketing strategies (Meek, et al., 2009, p. 223). For instance, price sensitivity analysis can be used to examine the impact of price changes on the sales volumes. If models show that the market is very price sensitive the best marketing and sales strategy in such a market would be price oriented (Meek, et al., 2009, p. 223). Moreover, sensitivity analysis can be used to determine the effectiveness of other marketing strategies. For instance, the effectiveness of adverts and promotional materials such as coupons can be examined through sensitivity analysis and based on the results these promotions can be revamped, discontinued or increased. Sensitivity analysis enables managers to identify the each variable that affects the costs and revenues and the impact each has on the overall bottom line (Meek, et al., 2009, p. 223). Variables such as random fluctuations, availability of substitutes, strength of brand loyalty, price variations in complementary goods and information available to consumers regarding prices all affect sales. Therefore, it is up to the marketing department to identify / estimate the impact each of these has and develop strategies to counter or exploit these variables. Mark Jeffery points out that effective marketing should be data driven. He argues that each marketing manager should be able to show the returns on marketing investments (ROMI). The metrics used to calculate ROMI include the net present value (NPV), the internal rate of return (IRR) and pay back in action (Jeffery, 2010, p. 127). The ROMI is then passed through a sensitivity analysis to determine if the campaign returns are achievable. Such measures give the marketing a more focused and result oriented approach (Jeffery, 2010, p. 130). Sensitivity analysis in production The technique is also critical in the production process. First of all, it can be used to identify the inputs that are most critical to the production process. By analysis each input or process using sensitivity analysis models, production managers can identify which inputs or processes are vital to the production process in terms of product quality and production time respectively. The same principles used in finance can be used to test the robustness of a production line and develop ways that ensure productivity is maximized. All that needs to be changed are the factor inputs/ variables. Vladimir Modrák and Pavol Seman point out that in manufacturing, noise may be a factor that has an impact on the production possibility curve (PCC) (Modrák & Seman, 2014, p. 74). Therefore, sensitivity analysis can be used to determine the correlation between the two and measures can be implemented to maximize productivity. In production, sensitivity analysis is run alongside simulation programs and linear programming to develop the most efficient production line (Gransberg, et al., 2006, p. 159). Criticism and disadvantages of sensitivity analysis. A prominent disadvantage of sensitivity analysis is that it does not give direct information on the likelihood of different outcomes (DIANE Publishing, 2004). Secondly, the technique assumes that the variables that are not being examined are held constant which is not the case in the real business environment. Changes in each independent variable are mutually exclusive. Therefore, assuming that only one would vary over a given period is misleading and unrealistic. Moreover, only a few inputs can be analyzed, and the statements about their deviations are not made (Götze, et al., 2007, p. 280). SCENARIO ANALYSIS A background into scenario analysis Scenario analysis involves analyzing an array of possible future outlooks based of an array of outcomes. In theory, scenarios are a synthesis of different paths (events and actors’ strategies) that lead to possible futures. In practice, scenarios often merely describe particular sets of events or variables (Roubelat, 2000, p. 4). In finance, it is described as the process of estimating the expected value of a portfolio after a certain period with the assumption of specific changes to the value of the securities making up the portfolio or key factors that would affect their value (Investopedia, 2014). A simple version of scenario analysis is the three case scenarios. In this analysis, the investment is evaluated under the worst case scenario, the most likely scenario and the best case scenario (Damodaran, 2008, p. 145). In investment appraisal, scenario analysis is based on four main components. The first one is the determination of the factors the scenarios will be based on (Damodaran, 2008, p. 147). For example, such factors could be the behavior of competitors to the introduction of a new product, or how changes in consumer preference could affect a particular brand. The second component is determination of the number of scenarios to examine for each factor (Damodaran, 2008, p. 147). The third component is the estimation of asset cashflows under each scenario (Damodaran, 2008, p. 147). The last component involves drawing up probabilities for each scenario. The probabilities assigned to each scenario are dependent on prevailing economic forecast’s or knowledge and experience about industry trends (Damodaran, 2008, p. 147). The concept first emerged on the aftermath of World War II as a method of military planning (Mietzner & Rege, 2005, p. 221). The American Air Force preempted scenarios of what its enemies my do and tried to preempt each one (Mietzner & Rege, 2005, p. 221). Herman Kahn, who spent time with the military, is credited for having a significant influence on the development of the technique. He developed the escalation ladder which laid out the distinct stages or variations of what may occur between a war and no war under different circumstances (Mietzner & Rege, 2005, p. 221). Pierre Wack, a planner at the London office of the Royal Dutch/ Shell’s group planning department redefined the technique in the 1970’s. Mr. Wack and his team used scenario analysis to preempt the 1973 global oil crisis. The team observed the rise of the Organization of Petroleum Exporting Countries (OPEC), the growing discontent among the Arab countries with the west over the six day Arab- Israel War and the rising crude oil demands in the United States of America and drew up to scenarios (Mietzner & Rege, 2005, p. 222). The first one was in line with the general belief within the organization that oil prices would remain relatively stable. However, this depended on the various factors. Key among them was the discovery of oil in Non-Arab countries. The second scenario painted a grimmer picture of the future. It predicted an impending oil prices sparked by OPEC (Mietzner & Rege, 2005, p. 220). The team observed that the organization was growing in power, and they predicted that they would exercise this power before 1975 (Mietzner & Rege, 2005, p. 220).The two scenarios enabled the management to draw up strategies and plans of action should things go wrong. Consequently, when oil prices shot up in October 1973 due to the Yom Kippur war in the Middle East, Shell was the only oil company prepared for the change (Mietzner & Rege, 2005, p. 220). These developments enabled the company grow from one of the smallest of the seven leading oil companies to the second largest in terms of size and the largest in terms of profitability (Mietzner & Rege, 2005, p. 222). Consequently, scenario analysis gained prominence globally as an integral part of business/ / investment analysis (Mietzner & Rege, 2005, p. 222). General advantages of scenario analysis The most important advantage of scenario analysis is that it enables managers to plan for a range of possible outcomes. Scenario analysis highlights the most likely outcome, the worst case scenario and the worst possible scenario. Consequently, it becomes very difficult for a manager be blindsided by any eventuality. Secondly, it can be used to calculate a project’s net present value and any deviations from that figure (Baker & Powell, 2009, p. 293). As a result, managers can evaluate the project’s stand alone risk and develop risk adjustments. Scenario analysis in marketing Scenario analysis reduces the risk of environmental uncertainty by providing an alternative for investing in information (West, et al., 2010, p. 77). It enables an organization to understand the external environment as it unfolds. Therefore, marketing managers can create future market context scenarios and evaluate their likelihood impact on the brand (West, et al., 2010, p. 77). The marketing department can, therefore, take measures to deal with each of these scenarios. It also enables marketing managers to develop multiple strategies to counter a rival’s sales and marketing plan. Scenario analysis in production The production capacity of a company must always be compatible with the market conditions/ demand for the product. Over production results in additional costs the organization such as storage costs opportunity costs and increased chances of damage. Criticism and weakness of scenario analysis Kent baker and Gray Powell point out several weakness/ flaws associated with this technique (Baker & Powell, 2009, p. 294). First of all they argue that scenario analysis is limited to few discrete outcomes when in reality the number of outcomes could be much more (Baker & Powell, 2009, p. 294). It would be very difficult for managers to envision all the possible outcomes of a process and militate against each one. Therefore, the leadership/ decision makers are forced to narrow or limit the possible scenarios bases on their impact on the organization. This process is highly subjective as each in individual would have his or her preferences (Baker & Powell, 2009, p. 294). Moreover, the process of drawing the scenarios is also subjective. Different managers can draw different conclusions from the same scenario (Baker & Powell, 2009, p. 294). An optimistic individual is likely to view a given scenario quite differently from a pessimistic individual. Therefore, the overall conclusion is biased as it is heavily influenced by the decision maker’s ideology/ opinion/ beliefs. Secondly managers have to assign estimates for the probability of each scenario occurring. Consequently, assigning the correct/ actual probabilities for each scenario is very difficult as the process is subjective (Baker & Powell, 2009, p. 294). Moreover, the technique does not provide a decision rule. It does not specify the parameters for accepting or rejecting project/ proposal/ undertaking. Instead, the outcome rests on the confidence of the manager and the probabilities he or she has placed on each scenario making the process highly subjective (Baker & Powell, 2009, p. 294). Lastly, scenario analysis assumes perfect correlation between the inputs (Baker & Powell, 2009, p. 294). The best case worst case variant assumes that all good outcomes occur together while all bad outcomes occur together (Damodaran, 2012, p. 150). However, this is misleading as a single project is likely to face a mixture of scenarios throughout its lifespan (Baker & Powell, 2009, p. 294). The link between investment appraisal, break Even analysis, sensitivity analysis and scenario analysis. A break-even analysis is a technique that compares the incoming value that an organization needs to serve its customers by delivering output of equal amount. In essence, it gives the amount of revenues that have to be generated to cover all the costs incurred. Given a predetermined selling price, one can calculate the units to be sold to cover all the variable costs and fixed costs (Cafferky, 2010, p. 1). This relationship can be represented mathematically as follows TR (at QBE) = TC (at QBE) Where TR = Total revenue TC = Total cost. If we break down the cost side of the equation and represent the TR as a function of price and quantity, the formula becomes P.Qx = TFC + AVC.Qx Where TFC = Total fixed cost AVC = Average variable costs The above relationship can be manipulated to make the quantity the subject as follows; Qx = TFC P - AVC The above equation can also be represented graphically as shown below (The break even analysis for the post office) source[Smi02]. On the other hand, investment appraisal is assessing different large scale capital projects to see what is both affordable and possible (Chapman, 2011). Some of the methods used investment appraisal are the payback period PBP, Net present value approach NPV, Return on capital employed (ROCE) and the internal rate of return (IRR) The payback period approach calculates the time frame the investment would take to recover the initial capital employed. For example is the initial capital outlay is $ 100,000 and the investment brings in $ 20,000 annually, then the payback period will be as follows PBP = initial outlay/ annual cash inflow = 100,000/ 20,000 = 5 years However, if the inflows change annually e.g. 30,000 in year 1, 50,000 in year, and 40,000 in year 3, then the PBP is as follows PBP = 2 years + 20,000/40,000 = 2.5 years. The net present value approach is calculated by discounting projected future cashflows to the present value then subtracting the summation from the initial capital outlay. If the difference is positive, then the investment is positive and vice versa. On the other hand, The IRR calculates the rate of return that would make the NPV of the project to be zero. From the discussion, it is clear that can break-even analysis, sensitivity analysis and scenario analysis can all be used as techniques in investment appraisal. In production, the break-even analysis evaluates the costs the investments and given the selling price, it determines the units that need to be sold for the costs to be covered. In marketing, the break-even point is that point that the returns from a marketing drive or strategy match the costs of the implementing the strategy. On the other hand, sensitivity analysis would highlight the factors that would affect the production process or marketing strategy. In most cases, the prices sensitivity analysis done by the marketing and sales department is involved in the pricing of the product (Verma, 2007, p. 164). With the price determined, it is up to the production department to produce the desired quantity to ensure that the company breaks even at the very least. Sensitivity analysis also evaluates the production process to ensure that the process is optimal. In essence, the sensitivity analysis rearranges all factors affecting the production and sale of a particular product while the break-even analysis highlights the financial implications of any changes introduced through the sensitivity analysis. Conversely, the scenario analysis highlights scenarios of possible outcomes if the business environment experiences drastic changes. Break-even analysis and sensitivity analysis focus on what should be done to optimize a given investment, production line or marketing strategy. On the Other hand, scenario analysis focuses on what could happen. Its aim is to pre-empt the future and not necessarily achieve optimality. Conclusion From the discussion, it is evident that the sensitivity and scenario are a vital part in business planning. Business processes such as production, sales and marketing are dependent on a number of factors. Each of these factors affects these processes differently. Therefore, it is vital that the impact of each variable is evaluated. Moreover, provisions must be made for any eventuality and this is where scenario planning comes in. As highlighted above, sensitivity analysis, break-even analysis and scenario analysis are very different. However, the three can be used together in investment appraisal. The scenarios analysis would provide all the possible outcomes from the investment. A sensitivity analysis can then be done to highlight how each independent variable affects the dependant variable under each scenario. Lastly, the break-even analysis would give the overall financial implication of all the scenarios. References Baker, K. H. & Powell, G., 2009. 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