Approaches in Sales Forecasting, Capacity Planning, and Physical Layout - Example

Supply Chain Student’s Name: Instructor’s Name: Subject: Date: Introduction In very new business venture, it is important first to consider its viability in order to ensure realization of profits. Generally, the initial market research is largely based on data obtained from existing competitors within the industry. Such data facilitates in making estimates of how the industry is performing as well making enabling a new entrant into the industry to make sales projections. This aids management of an organization to keep focus of the future objectively by analyzing current and past information. Precise sales forecasting enhances cash flow, facilitates having in-depth knowledge of both the products and the customers, and facilitates proper planning of the capacity and in determining the anticipated return on investment. Therefore, the main aim of this paper is to take a closer look at the factors to consider in venturing into retailing industry for instance a supermarket. Sales Forecasting In forecasting sales, it is important for the company to sufficiently organize and analyze data in a manner that would facilitate precise estimations. Besides, one of the key considerations that would facilitate proper sales forecasting is the source of information with respect to economic standards of a place as well as level of consumption (demand) across the demographic profile. In this regard, a few sources of information that would aid in sales forecasting are among others, like-businesses and/or competitors, trade supplies, associations, publications and directories. For a new business venture, sales forecasting would generally entail a few basic steps. First step would involve developing a customer profile based on economic and demographic data available. This should come in handy at determining the industrial trends. Although such data would be available from trade publications or directories, assumptions with respect to characteristics of the market have to be made. For instance, it is generally argued that 80% percent of sales results from 20% of a business’s clientele base. Being able to identify a sizeable percentage of potential customers would thus aid in developing the profile of the target market. A possible method is to categorize the potential customers in terms of their buying propensity with respect to age –this would be aided by carrying out a customer survey. This is illustrated in the table below. Figure 1: Propensity to Buy in relation to various Age Group Source: Bassin, WM 1993, ‘Using demographic data to drive business forecasts and profit plans’, The Journal of Business Forecasting Methods & Systems, vol. 12, no. 1, pp. 19-21 In this forecast, the major assumption is that demand is largely influenced by the area’s demographic profile. Besides, it is evident that selling one or more units of the company’s products is influenced by the age group. Some of the products which are influenced by demographic makeup are for instance confectionary, recreational equipment, clothes and entertainment equipment. Assuming that the demographic profile influences sales to large extent would entail preparing forecast of Population of Buyers (the number of customers in millions) ‘who buys at least one unit of the product’ per annum) (Bassin, 1993). Afterwards this would facilitate preparation of sales forecast by making use of population of buyers as well as other information. A projecting ‘equation for the Population of Buyers (POP) is’ for instance: PB = .47*POP1519 + .32* POP2034 + .18 * POP35UP Where; POP1519 is the number of individuals between ages 15 and 19 POP2034 is the number of individuals between ages 20 and 34 POP35UP is the number of individuals aged 35 years and above Subsequently, the number of units sold in a particular year would thus depend on population of buyers and the price of the products. A relationship would thus be derived in which coefficients are estimated by making use of linear, least squares regression to analyze data over some periods as illustrated by this equation; Sales = 50.0 + 2.996*PB – 0.2240*PRICE Where; SALES represent annual sales in million of units and PRICE represents the product’s price in cents per unit. In this regard, if population buyers falls or rises by one million customers, it would mean that ‘the number of units sold is estimated to’ fall or rise by 2.996 million units (Bassin, 1993). Consequently, it would be necessary to determine the estimated location and size of the targeted area and characteristics of such area would be established by making use of available statistics. How accessible is the supermarket? Besides, analyzing various households’ expenditures based on census data would come in handy in profiling potential customers. Besides, it would also be essential to identify some of the competitors in the targeted trading area. Profiling other competitors entails analyzing their location, number of customers and their rate of inflow/outflow, operation hours, seasonality of business, prices and quality of various product categories, number of product lines, and advertising/promotional techniques applied. This would give an insight aimed at instituting measures to lure customers into the new business. Such customer survey would aid to project sales in especially on the first few months of the year. The sales projections are supposed to be based on average monthly sales of identical competitors. However, adjustments with respect anticipated industrial trends should be made and it is important to reduce sales forecasts by a start-up year factor of at least 50% on each month during the first few months. Another consideration should be whether based on current data the business will introduce new competition strategies aimed at maximizing the needs of the customers. Some of the question that can be used in determining this is, if the business will be able to offer a better location, price, quality, price, service, and hors of service as compared to current competitors. Of importance is to put into consideration the area’s demography and level of economic development. Besides, the market share of each competitor should be put into consideration and this would help to determine the untapped markets across the population (Zeromillion.com 2011). Approaches in Sales Forecasting To project sales, the company can use either qualitative (judgmental) or quantitative methods although both methods can be applied simultaneously. Quantitative techniques would are based on data obtained from other competitors which would then be relied added, multiplied or correlated to predict sales in certain periods. In applying quantitative method, the management requires data on sales volume, disposable income, gross national product, and population of potential buyers within the market (Virtual Advisor Inc, 2009). Data obtained from competitors over the years can be sued to calculate sales based on monthly forecast and annual forecast and this would be as shown below. Figure 2. Monthly Sales Forecast (quantitative method) Sources: 2009, Virtual Advisor Inc It is important to note that such a forecast should be made for each category of product. Figure 3 Annual Sales Forecast (quantitative method) Sources: 2009, Virtual Advisor Inc Nevertheless, however precise sales forecasts maybe, they are not totally immune from the effects of fluctuations political and economic changes, staff turnover, mechanical and technical difficulties as well as trend shifts in the country of operation. Capacity Planning and Physical Layout Consequently, another important consideration to be given priority by the management is the cost of acquiring land, equipment, labor required and operational costs. Some of these costs will affect the profitability of the business; for instance labor and rent costs. Therefore, it is necessary to carry out a feasibility study to determine whether it would be feasible to lease some of the equipment instead of buying. At this point, it would be necessary to carry out strategic capacity planning putting into consideration amount of resources available and viability of each sub-project. In the case of present case study (a supermarket which is involved in retailing), the measures of capacity would be for instance: the area of store which is the input and sales volume which is the output. In this regard, it would be necessary to determine type and level of capacity required, when it would be needed and its correlation to productivity. On the other hand, it would be necessary to determine the capacity requirements; this would entail projecting sales in each particular product line, calculating labor (number of employees) and equipment requirements to meet the projected sales as well as forecasting labor and equipment availability over the planning horizon (n.a. 2010). An example of a capacity planning procedure is as illustrated below. Figure 4. Capacity Planning Process Source: n.a. 2010, Strategy capacity planning From the quantitative aspect, the cost of procuring equipment and other logistics involved would be considered whereas in from the qualitative aspect, it would be necessary to consider the level of expertise required in carrying out market research as well as knowledge and skills of the employees. Subsequently, it is also critical to come up with a catching layout of the supermarket which should be implemented at the shopping floor –this will ensure all products on the shelves are eye-catching, there is reduced congestion within the supermarket as well as ability to hold a sizeable number of customers (About.com 2011). In this regard, a befitting layout would be diagonal floor plan as it will offer excellent visibility for both the customers and cashiers. Besides, it attracts traffic flow and movement into the shopping floor. In this regard, the supermarket will be able to maximize sales volume per each square foot of every product’s allocated selling space. On the other hand, the exit and entry of customers is easier in a diagonal layout. An example of a diagonal layout is illustrated below. Figure 5. Diagonal Layout Source: About.com 2011 Conclusion Although sales forecast as well as other projections is relied upon while conducting the business, it is important to understand that they are not 100% accurate. Reason being venturing into a new market, most of the data relied upon is that of the competitors in particular and/or the whole industry in general. These are subject to fluctuations and besides, some of the competitors may doctors the data to mislead analysts. However, it is possible to collect proven facts and then test any key assumptions in the projections prior to conducting any forecast in order to increase the level of accuracy. On the other hand, it is necessary to have a margin of error which should be adjustable after carrying on business for a certain period. Subsequently, carrying out periodic self-assessment would facilitate in evaluating performance with respect to sales volume. References About.com 2011, viewed 14 March 2008, . Bassin, WM 1993, ‘Using demographic data to drive business forecasts and profit plans’, The Journal of Business Forecasting Methods & Systems, vol. 12, no. 1, pp. 19-21. n.a. 2010, Strategy capacity planning, viewed 14 March 2008, . Virtual Advisor Inc 2009, viewed 14 March 2008, < http://www.va-interactive.com/inbusiness/editorial/sales/ibt/sales_fo.html>. Zeromillion.com 2011, viewed 14 March 2008, . Read More