Assessing Brand Portfolio Normative Consistency and Trends with the Normative Position of Brands and Trends Package Page 47 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 ABSTRACT The Online Normative Position of Brands & Trends (NPB & Trends) Package is used in Strategic Market Planning (SMP) to assess the consistency of each strategic business unit (SBU) relative to its normative position at the end of each year of operation, and the trends in normative con- sistency over the course of competition. Based on an analy- sis of the strength and trends in their own brand portfolio and the brand portfolios of their competitors displayed on the Growth Share Matrix, participants check the position of each SBU on the Growth Gain Matrix relative to its norma- tive position. Corrective action is taken, if necessary, to improve their own trends in normative consistency over the course of competition. Insights are derived about competi- tor’s strategies by evaluating the normative consistency and trends of competitor brand portfolios. Based on their analysis of their own and competitor brand portfolios, the SMP is adjusted to optimize the performance of the overall brand portfolio while maintaining cash in balance. Based on reviewer feedback, an online survey of participants at the end of the Fall 2011 semester revealed that the NPB & Trends Package is easy to use, helpful in understanding normative consistency, and analyzing the brand portfolio. Participants indicated that the NPB & Trends Package adds substantial value to their Strategic Market Planning and Marketing Strategy learning experience. INTRODUCTION The Normative Position of Brands & Trends (NPB & Trends) Package is a decision support system that enables competing participant teams in the marketing simulation COMPETE (Faria, 2006) to assess the consistency of each SBU in their own brand portfolio and the brand portfolios of their competitors relative to its normative position. SBUs are specific product offerings in specific regions that have specific target markets with specific needs and pur- chase motivations, a specific set of strategies, facing a spe- cific set of competitors with specific competing strategies. The Excel-based NPB & Trends Package automatical- ly extracts relevant data via external links from the Excel- version of the COMPETE simulation results. The Excel- version of the simulation results are generated by the in- structor/administrator from the original dos-text based COMPETE simulation results. Later, the Excel-version of the simulation results are uploaded to the COMPETE Online Decision Entry System (CODES) repository for subsequent access by competing participant teams. Only relevant data used in the calculation of the relative market share (RMS), industry growth rate (IGR), brand growth rate (BGR), SBU Sales Revenue (SSR), Maximum Sustain- able Growth Rate (MSGR), and Weighted Average Growth Rate (WAGR) that are used to generate the Boston Con- sulting Group (BCG) Growth Share Matrix (GSM) and Growth Gain Matrix (GGM) are extracted from the simula- tion results. This decision support package saves substan- tial time needed to identify and enter the relevant data and reduces the potential for data entry error. DECISION SUPPORT SYSTEMS Several scholars have commented on the value of in- cluding decision support software/systems in computer simulations (Keys & Biggs, 1990; Teach, 1990; Gold & Pray, 1990, Wolfe & Gregg, 1989). In addition, the litera- ture is replete with references to the use and impact of deci- sion support systems with computer simulations (Affisco & Chanin, 1989, 1990; Burns & Bush, 1991; Cannon et al., 1993; Fritzsche et al., 1987; Grove et al., 1986; Halpin, 2006; Honaiser & Sauaia, 2006; Markulis & Strang, 1985; Mitri et al., 1998; Muhs & Callen, 1984; Nulsen et al., 1993, 1994; Palia, 1989, 1991; Peach, 1996; Schellen- berger, 1983; Shane & Bailes, 1986; Sherrell et al., 1986; Wingender & Wurster, 1987; Woodruff, 1992). Decision support systems (DSSs) are defined as …a collection of data, systems, tools, and techniques with supporting software and hardware by which an organi- zation gathers and interprets relevant information from business and environment and turns it into a basis for… action (Little, 1979; Burns & Bush, 1991). In addition, they are defined as computer-based information sys- tems that support the process of structuring problems, evaluating alternatives, and selecting actions for more effective management (Forgionne, 1988). Further, they are described as the hardware and software that permit decision-makers to deal with a specific set of related ASSESSING BRAND PORTFOLIO NORMATIVE CONSISTENCY & TRENDS WITH THE NORMATIVE POSITION OF BRANDS & TRENDS PACKAGE Aspy P. Palia University of Hawaii at Manoa aspy@hawaii.edu mailto:aspy@hawaii.edu Page 48 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 problems by providing tools that amplify a manager’s judgment (Sprague, 1980). DSSs used with business simulations yield several benefits. These include greater depth of understanding of simulation activity with resulting increase in plan- ning (Keys et al., 1986), in-depth understanding of quantitative techniques as students visualize the results of their applications, sensitivity to weaknesses in tech- niques used, and experience in capitalizing on their strengths (Fritzsche et al., 1987). Other benefits include minimization of paperwork and errors, error-free graphical representation of output, a competitive tool with increasing value as simulation progresses, and po- tential for participants to create their own DSSs (Burns & Bush, 1991). In addition, DSSs enhance understand- ing of complex business relationships and provide addi- tional value over time (Halpin, 2006). Further, DSSs provide realism, relevance, literacy, flexibility and op- portunity for refinement (Sherrell et al., 1986). Some authors contend that combining an active student generated database in the form of a simulation game with a DSS will result in improved decision mak- ing, lead to improved pro-active rather than re-active strategic planning, and result in improved simulation game performance and enhanced learning (Muhs & Callen, 1984). Others have reported no support for the premise that DSS usage improves small group decision making effectiveness (Affisco & Chanin, 1989), and that DSS usage to support manufacturing function decisions resulted in decreased manufacturing costs and in- creased “earnings/cost of goods sold” ratio in the second year of play (Affisco & Chanin, 1990). Given the inconsistent findings with regard to the efficacy of DSSs reported in the literature, does DSS usage increase decision effectiveness and/or enhance learning? One scholar notes that while the DSS assists the decision maker, it does not make decisions, nor can it substitute for intelligent analysis and synthesis (Schellenberger, 1983). In addition, as with other com- puter-based or experiential learning techniques, the effectiveness of DSSs or the decisions made are less im- portant than the insights they generate. The level of insight generated depends heavily on the clear explana- tion of the purpose, significance, assumptions, usage, and limitations of the DSS and underlying concepts ap- plied, by the instructor. In addition, the level of insight generated depends heavily on the debriefing process used by the instructor to crystallize student learning (Cannon et al., 1993). The primary purpose of this paper is to present this new user-centered learning tool that helps to prepare stu- dents for strategic market planning and marketing decision- making responsibilities in their future careers. The objec- tive of this decision support package is to provide partici- pant teams the opportunity to apply integrated strategic market planning. An online survey is used to evaluate the NPB & Trends Package usage experience, and the value- added to the overall learning experience. MARKETING STRATEGY Marketing managers are charged with the responsibil- ity of planning, organizing, implementing, and controlling marketing plans and programs that are designed to achieve a specific set of objectives (Bagozzi et al, 1998; Churchill & Peter, 1995; Dyer & Horman, 1991; Kotler, 2003; Ko- tler, 1988; Kotler & Keller, 2007; Lehman & Winer, 1988; Lilien, 1993; Lilien & Rangaswamy, 2003; McCarthy & Perreault, 1984; McCarthy & Perreault, 1987; Perreault & McCarthy, 1996). First, marketing managers identify opportunities and threats in the external environment. They analyze the ma- jor customer segments, strategic competitor groupings, and salient market and environmental trends. Major customer segments are identified and their needs, purchase motiva- tions, unmet needs are analyzed. Major strategic competi- tor groups are identified and their performance, image, ob- jectives, strategies and weaknesses are analyzed. The size, growth, profitability, entry barriers, cost structure, distribu- tion system, trends, and key success factors as well as emerging submarkets in the relevant product market are investigated. Relevant trends in the social-cultural, techno- logical, economic, legal, political and other non- controllable external environments are studied. This exter- nal analysis is used to identify opportunities, threats, trends and strategic uncertainties. Next, marketing managers analyze their own firm’s performance on such dimensions as profitability, sales, shareholder value analysis, customer satisfaction, product quality, brand associations, relative cost, new products, employee capability and performance. In addition, they study their own strategic problems, constraints, strengths, weaknesses and liabilities. This internal analysis is used to identify their own strengths, weaknesses, liabilities, prob- lems, constraints and uncertainties. Then, marketing managers (a) identify strategic alter- natives with regard to product market investment strategies, customer value proposition, assets, competencies, and syn- ergies, and functional strategies and programs, (b) select a strategy, (c) implement an operating plan, and (d) periodi- cally review and adapt strategies. Based on the above analysis of the opportunities and threats in the external environment and an assessment of the firm’s own strengths and weaknesses, marketing man- agers generate a vision, define a mission, establish specific goals, and formulate a strategy in order to achieve the mis- sion. Strategies used include differentiation strategy, low- cost strategy, focus strategy, preemptive move, and syner- gy. An offering can be differentiated based on perfor- mance, quality, prestige, features, service backup, reliabil- Page 49 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 ity, and/or convenience. A low-cost strategy involves the creation of a sustainable cost advantage through high mar- ket share, favorable access to raw materials, and/or state-of -the-art manufacturing equipment. A focus or niche strate- gy seeks to establish and maintain dominance in a narrow product line. It is central to the creation of a sustainable competitive advantage. The preemptive move strategy generates an asset or competency, forms the basis of a sus- tainable competitive advantage and inhibits competitors. Finally, synergy can be achieved through sharing sales force or office space, and reduces cost or investment need- ed (Aaker, 2011). In performing their responsibilities, marketing manag- ers are faced with scarce resources (discretionary marketing dollars) and unlimited wants to allocate these limited re- sources across individual SBUs in their brand portfolio in order to achieve their objectives. Consequently, they need to allocate the scarce resources at their disposal both effec- tively and efficiently. The efficient allocation of scarce marketing resources in order to optimize the overall perfor- mance of a brand portfolio is the heart of strategic market planning. STRATEGIC MARKET PLANNING Strategic market planning is a complex problem for multi-product, multimarket companies. These firms may have numerous products serving several markets with dif- fering potentials. Some products may be in a dominant position relative to competitors, while others may be in a weaker position. Each product will have its own strategy, and may face several competitive products having their own marketing strategies. Some products may be profita- ble while others may need cash to finance growth or to fight competition. Faced with this complex situation, the organization must allocate its limited resources among these products in order to optimize its overall performance (Abell & Ham- mond, 1979). In order to optimize the overall performance of its portfolio of products, the organization first monitors and analyzes the performance of each of its strategic busi- ness units (products). This analysis is conducted by the firm in order to decide which strategic business units to build, maintain, harvest, and divest. One of the best known and widely used models for this purpose is the Boston Con- sulting Group Product Portfolio Analysis model (Kotler, 1988). The product portfolio analysis model developed by the Boston Consulting Group assigns strategic roles for each product based on the product’s market growth rate and market share relative to competitors. These individual roles are then integrated into a strategy for the whole port- folio of products, taking into consideration the product portfolios of the main competitors. The objective of the firm, when using the product portfolio approach, is to opti- mize the performance of the entire portfolio of products, while maintaining cash flow in balance. Differences in growth potential, relative market share and hence cash flow potential unique to each product are identified. This analy- sis helps to determine which products represent investment opportunities, which products should supply investment funds, and which products should be candidates for elimi- nation. The growth share matrix (GSM) and the growth gain matrix (GGM) are used to display the relevant information about the firm’s portfolio of products. These displays help to reduce the inherent complexity of the problem to man- ageable proportions. The heart of product portfolio analy- sis involves the creation and interpretation of the GSM and GGM displays for the firm and its main competitors. Based upon GSM data, each firm’s strategic business units (products) are classified into four categories – “Cash Cows,” ”Dogs,” “Problem Children,” and “Stars” (Abell & Hammond, 1979; Day, 1986). The Product Portfolio Analysis package enables an organization to generate GSMs and GGMs for their own and competing firms. These matrices are used in strategic market planning. Static, comparative static and dynamic analysis of the product portfolios of the firm and its main competitors can be performed with the use of the revised package. Based on these displays, the organization can (1) check for internal balance in the brand portfolio, (2) look for trends, (3) evaluate competition, (4) consider other fac- tors not captured in the portfolio display, and (5) develop alternative “target” portfolios along with associated strate- gies for achieving them and (6) check financial balance (Palia, 1991, 1995, 1996, 2002, 2010). The SMP NPB & Trends Package enables the organi- zation to check the position of each SBU on the GGM rela- tive to its normative position. If necessary, corrective ac- tion is taken to improve trends in normative consistency over the course of competition. Insights are derived about competitor’s strategies by evaluating the normative con- sistency and trends of competitor brand portfolios. Based on their analysis of their own and competitor brand portfo- lios, the SMP can be adjusted to optimize the performance of the overall brand portfolio while maintaining cash in balance. THE MARKETING SIMULATION COMPETE COMPETE (Faria, 2006) is a marketing simulation designed to provide students with marketing strategy devel- opment and decision-making experience. Competing stu- dent teams are placed in a complex, dynamic, and uncertain environment. The participants experience the excitement and uncertainty of competitive events and are motivated to be active seekers of knowledge. They learn the need for and usefulness of mastering an underlying set of decision- Page 50 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 making principles. Competing student teams plan, implement, and control a marketing program for three high-tech products in three regions Region 1 (R1), Region 2 (R2) and Region 3 (R3) within the United States. These three products are a Total Spectrum Television (TST), a Computerized DVD/Video Editor (CVE) and a Safe Shot Laser (SSL). The features and benefits of each product and the characteristics of con- sumers in each region are described in the student manual. Based on a marketing opportunity analysis, a mission state- ment is generated, specific and measurable company goals are set, and marketing strategies are formulated to achieve these goals. Constant monitoring and analysis of their own and competitive performance helps the teams better under- stand their markets and improve their decisions. Each decision period (quarter), the competing teams make a total of 74 marketing decisions with regard to mar- keting their three brands in the three regional markets. These decisions include nine pricing decisions, nine ship- ment decisions, three sales force size decisions, nine sales force time allocation decisions, one sales force salary deci- sion, one sales force commission decision, twenty-seven advertising media decisions, nine advertising content deci- sions, three quality-improvement R&D decisions, and three cost-reduction R&D decisions. Successful planning, im- plementation, and control of their respective marketing programs require that each company constantly monitor trends in its own and competitive decision variables and resulting performance. The teams use the COMPETE Online Decision Entry System (CODES) (Palia & Mak, 2001; Palia et al., 2000) to enter their decisions and retrieve their results. These result files in Excel format are subse- quently downloaded and used to update the NPB & Trends package. NORMATIVE POSITION OF BRANDS & TRENDS PACKAGE The web-based Normative Position of Brands & Trends Package Version 2.0 is accessible online to com- peting participant teams in the marketing simulation COMPETE. The Normative Position of Brands & Trends Package Version 2.0 is a zipped folder “NPB & Trends.zip” which consists of an Excel workbook “NPB & Trends.xls” (with external links to each of x.xls COMPETE output files) and x.xls Excel version of sam- ple COMPETE output for all specified periods “x”. This NPB & Trends.xls workbook consists of five work- sheets: (a) NPB by Year, (b) NPB by SBU, (c) Coordi- nates, (d) Profitability, and (e) Ratios. First, the Ratios worksheet (see Figure 1) consists of external links to the quarterly COMPETE output files. This worksheet extracts the earnings per share (EPS) and sales volume (in $s) for each company from the quarterly results for the first twelve quarters (three years) of operation. Based on the extracted EPS and sales volume, this worksheet calculates the return on total assets (ROTA) – a measure of how well the firm is managing its assets to generate profit, net profit margin (NPM) – a measure of how profitable the sales are, and sales-to-assets turnover (SATO) – a measure of how well the firm is using its assets to generate sales, for each company during each quarterly period of opera- tion. The total assets are approximated as the common stock plus the current retained income during each quarterly period of operation, since the short-term notes payable of competitors is unknown. The approxi- mate total assets at the end of each year of operation are Original Number Retained Common of Income Stock 1 2 3 4 5 Shares 1 2 3 4 5 (in $'000s) 1 2 3 4 5 (in $'000s) 1 2 3 4 5 0.91$ 1.35$ 0.54$ 1.06$ -$ 2,000,000 1,820$ 2,700$ 1,080$ 2,120$ -$ 11,000$ 12,820$ 13,700$ 12,080$ 13,120$ 11,000$ 40,000$ 52,820$ 53,700$ 52,080$ 53,120$ 51,000$ 0.45$ 0.83$ 0.44$ 1.16$ -$ 2,000,000 900$ 1,660$ 880$ 2,320$ -$ 13,720$ 15,360$ 12,960$ 15,440$ 11,000$ 40,000$ 53,720$ 55,360$ 52,960$ 55,440$ 51,000$ 1.52$ 0.95$ 1.34$ 0.78$ -$ 2,000,000 3,040$ 1,900$ 2,680$ 1,560$ -$ 16,760$ 17,260$ 15,640$ 17,000$ 11,000$ 40,000$ 56,760$ 57,260$ 55,640$ 57,000$ 51,000$ 2.29$ 1.32$ 2.01$ 2.16$ -$ 2,000,000 4,580$ 2,640$ 4,020$ 4,320$ -$ 21,340$ 19,900$ 19,660$ 21,320$ 11,000$ 40,000$ 61,340$ 59,900$ 59,660$ 61,320$ 51,000$ 0.93$ 0.19$ 0.57$ 1.02$ -$ 2,000,000 1,860$ 380$ 1,140$ 2,040$ -$ 23,200$ 20,280$ 20,800$ 23,360$ 11,000$ 40,000$ 63,200$ 60,280$ 60,800$ 63,360$ 51,000$ 0.46$ 0.01$ 0.38$ 0.31$ -$ 2,000,000 920$ 20$ 760$ 620$ -$ 24,120$ 20,300$ 21,560$ 23,980$ 11,000$ 40,000$ 64,120$ 60,300$ 61,560$ 63,980$ 51,000$ 0.71$ 0.72$ 0.69$ 0.55$ -$ 2,000,000 1,420$ 1,440$ 1,380$ 1,100$ -$ 25,540$ 21,740$ 22,940$ 25,080$ 11,000$ 40,000$ 65,540$ 61,740$ 62,940$ 65,080$ 51,000$ 1.42$ 1.53$ 1.58$ 0.01$ -$ 2,000,000 2,840$ 3,060$ 3,160$ 20$ -$ 28,380$ 24,800$ 26,100$ 25,100$ 11,000$ 40,000$ 68,380$ 64,800$ 66,100$ 65,100$ 51,000$ 0.30$ 0.23$ 0.61$ (3.37)$ -$ 2,000,000 600$ 460$ 1,220$ (6,740)$ -$ 28,980$ 25,260$ 27,320$ 18,360$ 11,000$ 40,000$ 68,980$ 65,260$ 67,320$ 58,360$ 51,000$ (0.47)$ (0.14)$ 0.29$ (1.39)$ -$ 2,000,000 (940)$ (280)$ 580$ (2,780)$ -$ 28,040$ 24,980$ 27,900$ 15,580$ 11,000$ 40,000$ 68,040$ 64,980$ 67,900$ 55,580$ 51,000$ 0.35$ 0.38$ 0.71$ (1.23)$ -$ 2,000,000 700$ 760$ 1,420$ (2,460)$ -$ 28,740$ 25,740$ 29,320$ 13,120$ 11,000$ 40,000$ 68,740$ 65,740$ 69,320$ 53,120$ 51,000$ 1.61$ 1.00$ 1.97$ (0.32)$ -$ 2,000,000 3,220$ 2,000$ 3,940$ (640)$ -$ 31,960$ 27,740$ 33,260$ 12,480$ 11,000$ 40,000$ 71,960$ 67,740$ 73,260$ 52,480$ 51,000$ 1 2 3 4 5 Period 1 2 3 4 5 Period 1 2 3 4 5 Period 1 2 3 4 5 38,500$ 34,700$ 44,100$ 38,400$ -$ 1 4.73% 7.78% 2.45% 5.52% #DIV/0! 1 0.73 0.65 0.85 0.72 - 1 3.45% 5.03% 2.07% 3.99% 0.00% 35,600$ 30,000$ 38,600$ 33,500$ -$ 2 2.53% 5.53% 2.28% 6.93% #DIV/0! 2 0.66 0.54 0.73 0.60 - 2 1.68% 3.00% 1.66% 4.18% 0.00% 50,200$ 36,900$ 56,400$ 41,300$ -$ 3 6.06% 5.15% 4.75% 3.78% #DIV/0! 3 0.88 0.64 1.01 0.72 - 3 5.36% 3.32% 4.82% 2.74% 0.00% 60,500$ 52,200$ 81,100$ 52,100$ -$ 4 7.57% 5.06% 4.96% 8.29% #DIV/0! 4 0.99 0.87 1.36 0.85 - 4 7.47% 4.41% 6.74% 7.05% 0.00% 37,800$ 38,600$ 52,000$ 35,600$ -$ 5 4.92% 0.98% 2.19% 5.73% #DIV/0! 5 0.60 0.64 0.86 0.56 - 5 2.94% 0.63% 1.88% 3.22% 0.00% 33,800$ 40,100$ 43,500$ 29,600$ -$ 6 2.72% 0.05% 1.75% 2.09% #DIV/0! 6 0.53 0.67 0.71 0.46 - 6 1.43% 0.03% 1.23% 0.97% 0.00% 44,900$ 55,100$ 61,900$ 37,700$ -$ 7 3.16% 2.61% 2.23% 2.92% #DIV/0! 7 0.69 0.89 0.98 0.58 - 7 2.17% 2.33% 2.19% 1.69% 0.00% 59,500$ 70,700$ 85,000$ 51,200$ -$ 8 4.77% 4.33% 3.72% 0.04% #DIV/0! 8 0.87 1.09 1.29 0.79 - 8 4.15% 4.72% 4.78% 0.03% 0.00% 44,900$ 47,100$ 53,300$ 35,900$ -$ 9 1.34% 0.98% 2.29% -18.77% #DIV/0! 9 0.65 0.72 0.79 0.62 - 9 0.87% 0.70% 1.81% -11.55% 0.00% 43,200$ 42,200$ 43,400$ 32,300$ -$ 10 -2.18% -0.66% 1.34% -8.61% #DIV/0! 10 0.63 0.65 0.64 0.58 - 10 -1.38% -0.43% 0.85% -5.00% 0.00% 59,100$ 56,900$ 60,000$ 45,100$ -$ 11 1.18% 1.34% 2.37% -5.45% #DIV/0! 11 0.86 0.87 0.87 0.85 - 11 1.02% 1.16% 2.05% -4.63% 0.00% 75,300$ 74,100$ 82,000$ 56,200$ -$ 12 4.28% 2.70% 4.80% -1.14% #DIV/0! 12 1.05 1.09 1.12 1.07 - 12 4.47% 2.95% 5.38% -1.22% 0.00% Sales (In '000s) Net Profit Margin Sales to Asset Turnover (Approximate) Return on Total Assets (Approximate) Earnings per Share Earnings (Net Profit After Tax) (in $'000s) Current Retained Income (in $'000s) Total Assets (Approximate) (in $'000s) Company Company Company Company Company Company Company Company Figure 1 Ratios Worksheet Page 51 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 used by the Profitability worksheet to calculate the ap- proximate annual return on total assets (ROTA). Second, the Profitability worksheet (see Figure 2) consists of external links to the quarterly COMPETE output files. This worksheet extracts the annual earn- ings per share (EPS) and cumulative earnings per share (EPS) at the end of each year of operation (from the period 4, 8, and 12 quarterly COMPETE output files). Based on the extracted EPS, this worksheet computes the annual net profit after tax and the cumulative annu- al profit of each company. This worksheet also has in- ternal links to the Ratios worksheet. Based on the ex- tracted and computed results, the Profitability work- sheet calculates the approximate annual return on total assets (ROTA) for each company by dividing the com- puted annual net profit after tax by the approximate total assets at the end of each year of operation extract- ed from the Profitability worksheet. Third, the Coordinates worksheet consists of exter- nal links to the quarterly COMPETE output files. This worksheet extracts the quarterly sales in units (see Fig- ure 3) and price in $s (see Figure 4) for each SBU (each product in each region) during each decision period for each company from the quarterly results for the first twelve quarters (three years) of operation. Based on the extracted quarterly sales (in units), this worksheet cal- culates the brand growth rate (BGR) for each SBU for each company, the industry growth rate (IGR) for each SBU during the Year 1-2 and Year 2-3 periods, and the relative market share (RMS) of each SBU for each com- pany. The RMS indicates the degree of dominance of a specific SBU and is determined by dividing the sales (in units) of a specific SBU by the sales (in units) of the strongest competitor. The Coordinates worksheet also calculates the SBU sales revenue (SSR) for each SBU for each year for each company based on the quarterly sales (in units) and price (in $s) extracted from the COMPETE output files. In addition, this worksheet calculates the weighted av- erage growth rate (WAGR) of all nine SBUs by weighting each SBU’s BGR with its SSR. Finally, this worksheet calculates the maximum sustainable growth rate MSGR (Abell & Hammond 1979) for each compa- ny for each year of operation, based on the annual RO- TA extracted from the Profitability worksheet. Fourth, the NPB by SBU worksheet (see Figure 5) consists of internal links to the Coordinates worksheet. This worksheet extracts the RMS, IGR, BGR, and SSR for each SBU for each company for the year 1-2 and year 2-3 periods from the Coordinates worksheet. In addition, the worksheet extracts the MSGR and WAGR for each company for the year 1-2 and year 2-3 periods from the Coordinates worksheet. The data in the NPB by SBU worksheet are organized by SBU by year for each company. This facilitates analysis of trends (comparative static analysis) in the brand portolio. Total Assets (approx.) ROTA (approx.) Company Year 1 Cumulative Year 1 Year 1 Company 1 10,340,000.00$ 10,340,000.00$ 61,340,000.00$ 16.86% Company 2 8,900,000.00$ 8,900,000.00$ 59,900,000.00$ 14.86% Company 3 8,640,000.00$ 8,640,000.00$ 59,660,000.00$ 14.48% Company 4 10,320,000.00$ 10,320,000.00$ 61,320,000.00$ 16.83% Company 5 -$ -$ 51,000,000.00$ 0.00% Company Year 2 Cumulative Year 2 Year 2 Company 1 7,040,000.00$ 17,380,000.00$ 68,380,000.00$ 10.30% Company 2 4,900,000.00$ 13,780,000.00$ 64,800,000.00$ 7.56% Company 3 6,440,000.00$ 15,080,000.00$ 66,100,000.00$ 9.74% Company 4 3,760,000.00$ 14,080,000.00$ 65,100,000.00$ 5.78% Company 5 -$ -$ 51,000,000.00$ 0.00% Company Year 3 Cumulative Year 3 Year 3 Company 1 3,580,000.00$ 20,960,000.00$ 71,960,000.00$ 4.97% Company 2 2,940,000.00$ 16,720,000.00$ 67,740,000.00$ 4.34% Company 3 7,160,000.00$ 22,240,000.00$ 73,260,000.00$ 9.77% Company 4 (12,620,000.00)$ 1,460,000.00$ 52,480,000.00$ -24.05% Company 5 -$ -$ 51,000,000.00$ 0.00% Net Profit After Tax Figure 2 Profitability Worksheet Page 52 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Quarterly Sales (in Units) Company 1 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 1,456 1,400 978 7,863 8,845 6,360 73,754 79,400 64,861 Period 2 555 681 448 13,997 15,056 11,100 67,955 71,960 60,602 Period 3 1,006 1,308 788 23,627 25,219 19,634 44,153 46,214 40,742 Period 4 1,997 2,784 1,827 7,887 10,805 6,996 133,073 140,654 114,840 Period 5 1,294 1,758 1,199 5,000 6,695 4,878 81,965 88,147 70,175 Period 6 567 699 480 9,503 14,533 11,764 65,499 76,916 64,513 Period 7 959 977 773 18,395 27,352 20,036 28,917 34,226 30,614 Period 8 1,882 2,380 1,762 12,114 18,351 12,519 98,185 117,040 99,969 Period 9 1,449 1,804 1,645 8,628 11,415 6,073 83,467 110,533 93,330 Period 10 723 721 701 14,714 22,766 13,714 75,730 100,823 99,497 Period 11 1,038 1,201 982 23,495 36,376 26,220 45,856 76,272 84,780 Period 12 2,122 3,269 2,750 11,690 23,928 12,344 116,973 143,508 175,000 Company 2 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 1,190 1,131 1,049 8,552 9,101 5,609 76,156 63,885 44,316 Period 2 577 515 522 12,529 13,599 8,881 55,252 50,965 36,020 Period 3 933 854 741 14,294 16,416 12,076 48,545 45,896 43,464 Period 4 1,900 1,408 1,218 14,663 17,085 12,770 83,873 85,058 88,505 Period 5 1,281 1,335 1,121 10,304 11,965 8,483 64,454 66,836 57,235 Period 6 719 757 649 16,842 17,544 13,120 75,456 80,230 77,752 Period 7 1,208 1,433 1,139 23,207 24,846 17,763 76,554 81,838 84,920 Period 8 1,932 2,271 1,788 18,493 22,103 15,951 144,265 159,980 152,026 Period 9 1,360 1,696 1,373 11,600 15,593 9,877 80,736 101,030 92,889 Period 10 700 900 800 13,989 21,273 13,227 69,307 98,026 88,292 Period 11 1,282 1,818 1,365 17,303 29,355 18,731 71,992 87,213 79,043 Period 12 1,898 2,511 2,136 16,139 27,026 18,626 125,209 169,832 153,487 Company 3 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 1,500 1,400 1,058 10,100 13,985 8,989 104,139 115,652 79,455 Period 2 800 700 542 11,350 17,159 9,787 98,656 108,415 71,253 Period 3 1,358 1,390 1,198 20,047 26,971 17,685 90,191 96,272 61,291 Period 4 2,484 2,525 2,264 19,944 23,405 17,089 179,462 192,887 120,490 Period 5 1,630 1,707 1,437 11,646 17,258 11,700 100,435 115,182 75,213 Period 6 736 878 669 14,263 22,217 14,725 86,303 100,969 57,105 Period 7 1,359 1,674 1,319 19,317 35,446 20,533 80,678 104,761 65,593 Period 8 2,583 3,088 2,626 17,984 29,735 18,891 144,809 211,032 115,002 Period 9 1,388 1,871 1,887 10,505 20,122 10,041 91,037 111,765 74,881 Period 10 575 897 826 12,896 25,929 13,656 75,904 92,268 61,576 Period 11 1,106 1,514 1,371 18,672 39,295 20,773 61,849 83,345 55,425 Period 12 2,059 2,778 2,837 15,468 34,068 18,060 118,199 170,114 122,307 Company 4 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 1,300 1,440 1,043 8,720 7,345 6,849 86,636 82,563 71,011 Period 2 678 760 498 11,576 10,964 9,976 76,714 73,078 64,391 Period 3 1,165 1,200 795 13,683 16,461 11,369 64,933 70,922 54,109 Period 4 1,646 1,814 1,310 11,640 14,718 10,606 97,448 98,633 82,527 Period 5 1,183 1,347 944 7,094 7,131 6,862 71,851 73,249 70,812 Period 6 601 739 548 8,286 10,966 7,987 64,002 65,059 56,503 Period 7 993 1,500 946 9,768 11,674 13,028 56,630 65,558 37,586 Period 8 1,708 2,670 1,637 7,693 9,493 12,310 87,231 94,709 79,698 Period 9 1,326 2,030 538 6,000 6,498 16,907 51,929 79,128 30,220 Period 10 647 1,200 449 9,389 7,714 20,291 50,000 74,917 21,220 Period 11 1,043 2,175 1,212 13,074 10,093 23,600 46,166 77,980 17,034 Period 12 1,816 3,700 1,280 13,007 4,143 22,864 78,067 146,128 2,400 Company 5 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 0 0 0 0 0 0 0 0 0 Period 2 0 0 0 0 0 0 0 0 0 Period 3 0 0 0 0 0 0 0 0 0 Period 4 0 0 0 0 0 0 0 0 0 Period 5 0 0 0 0 0 0 0 0 0 Period 6 0 0 0 0 0 0 0 0 0 Period 7 0 0 0 0 0 0 0 0 0 Period 8 0 0 0 0 0 0 0 0 0 Period 9 0 0 0 0 0 0 0 0 0 Period 10 0 0 0 0 0 0 0 0 0 Period 11 0 0 0 0 0 0 0 0 0 Period 12 0 0 0 0 0 0 0 0 0 Figure 3 Coordinates Worksheet – Quarterly Sales (in Units) Page 53 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Price (in $s) Company 1 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 4,500.00$ 4,200.00$ 4,500.00$ 450.00$ 420.00$ 450.00$ 54.00$ 50.00$ 54.00$ Period 2 4,500.00$ 4,200.00$ 4,500.00$ 450.00$ 420.00$ 450.00$ 54.00$ 50.00$ 54.00$ Period 3 4,400.00$ 4,100.00$ 4,400.00$ 450.00$ 420.00$ 450.00$ 53.00$ 50.00$ 53.00$ Period 4 4,450.00$ 4,150.00$ 4,450.00$ 455.00$ 425.00$ 450.00$ 54.00$ 51.00$ 54.00$ Period 5 4,400.00$ 4,150.00$ 4,400.00$ 455.00$ 425.00$ 435.00$ 53.00$ 50.00$ 52.00$ Period 6 4,400.00$ 4,150.00$ 4,400.00$ 455.00$ 425.00$ 435.00$ 53.00$ 50.00$ 52.00$ Period 7 4,400.00$ 4,150.00$ 4,400.00$ 450.00$ 420.00$ 435.00$ 52.00$ 49.00$ 51.00$ Period 8 4,350.00$ 4,120.00$ 4,350.00$ 440.00$ 415.00$ 430.00$ 51.00$ 48.00$ 50.00$ Period 9 4,300.00$ 4,100.00$ 4,200.00$ 425.00$ 410.00$ 410.00$ 47.00$ 47.00$ 47.00$ Period 10 4,400.00$ 4,100.00$ 4,200.00$ 425.00$ 410.00$ 410.00$ 47.00$ 47.00$ 47.00$ Period 11 4,500.00$ 4,100.00$ 4,250.00$ 435.00$ 410.00$ 410.00$ 47.00$ 46.00$ 46.00$ Period 12 4,600.00$ 4,125.00$ 4,250.00$ 435.00$ 410.00$ 410.00$ 47.00$ 47.00$ 47.00$ Company 2 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 4,500.00$ 4,200.00$ 4,500.00$ 450.00$ 420.00$ 450.00$ 54.00$ 50.00$ 54.00$ Period 2 4,556.00$ 4,250.00$ 4,556.00$ 450.00$ 420.00$ 450.00$ 54.00$ 50.00$ 54.00$ Period 3 4,556.00$ 4,250.00$ 4,556.00$ 450.00$ 420.00$ 435.00$ 54.00$ 50.00$ 50.00$ Period 4 4,432.00$ 4,432.00$ 4,432.00$ 445.00$ 420.00$ 435.00$ 50.00$ 50.00$ 50.00$ Period 5 4,430.00$ 4,100.00$ 4,200.00$ 445.00$ 420.00$ 435.00$ 50.00$ 50.00$ 50.00$ Period 6 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 415.00$ 415.00$ 48.00$ 48.00$ 48.00$ Period 7 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 415.00$ 415.00$ 48.00$ 48.00$ 48.00$ Period 8 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 415.00$ 48.00$ 48.00$ 48.00$ Period 9 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 408.00$ 48.00$ 47.00$ 48.00$ Period 10 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 404.00$ 408.00$ 47.00$ 47.00$ 48.00$ Period 11 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 404.00$ 408.00$ 47.00$ 47.00$ 48.00$ Period 12 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 405.00$ 405.00$ 47.00$ 47.00$ 48.00$ Company 3 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 4,080.00$ 3,900.00$ 3,910.00$ 440.00$ 410.00$ 420.00$ 49.00$ 47.00$ 49.00$ Period 2 4,200.00$ 4,000.00$ 4,100.00$ 440.00$ 410.00$ 430.00$ 51.00$ 49.00$ 51.00$ Period 3 4,350.00$ 4,150.00$ 4,250.00$ 440.00$ 410.00$ 420.00$ 51.00$ 49.00$ 51.00$ Period 4 4,350.00$ 4,150.00$ 4,250.00$ 440.00$ 410.00$ 420.00$ 51.00$ 49.00$ 51.00$ Period 5 4,350.00$ 4,150.00$ 4,250.00$ 440.00$ 410.00$ 420.00$ 51.00$ 49.00$ 51.00$ Period 6 4,350.00$ 4,150.00$ 4,250.00$ 440.00$ 410.00$ 420.00$ 51.00$ 49.00$ 51.00$ Period 7 4,300.00$ 4,100.00$ 4,200.00$ 440.00$ 410.00$ 420.00$ 49.00$ 47.00$ 48.00$ Period 8 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 49.00$ 47.00$ 48.00$ Period 9 4,700.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 60.00$ 47.00$ 48.00$ Period 10 4,700.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 60.00$ 47.00$ 48.00$ Period 11 4,700.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 60.00$ 47.00$ 48.00$ Period 12 4,700.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 60.00$ 47.00$ 48.00$ Company 4 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 4,300.00$ 4,100.00$ 4,200.00$ 450.00$ 430.00$ 440.00$ 53.00$ 50.00$ 52.00$ Period 2 4,300.00$ 4,100.00$ 4,300.00$ 450.00$ 430.00$ 430.00$ 53.00$ 50.00$ 52.00$ Period 3 4,300.00$ 4,100.00$ 4,300.00$ 450.00$ 430.00$ 440.00$ 53.00$ 50.00$ 52.00$ Period 4 4,400.00$ 4,300.00$ 4,360.00$ 470.00$ 442.00$ 440.00$ 55.00$ 52.00$ 51.00$ Period 5 4,400.00$ 4,250.00$ 4,380.00$ 460.00$ 436.00$ 440.00$ 52.00$ 51.00$ 52.00$ Period 6 4,400.00$ 4,125.00$ 4,380.00$ 460.00$ 420.00$ 440.00$ 52.00$ 50.00$ 52.00$ Period 7 4,400.00$ 4,125.00$ 4,380.00$ 460.00$ 415.00$ 435.00$ 52.00$ 48.00$ 50.00$ Period 8 4,390.00$ 4,150.00$ 4,250.00$ 455.00$ 425.00$ 425.00$ 51.00$ 48.00$ 49.00$ Period 9 4,360.00$ 4,050.00$ 4,190.00$ 440.00$ 405.00$ 405.00$ 49.00$ 45.00$ 47.00$ Period 10 4,600.00$ 4,150.00$ 4,190.00$ 440.00$ 415.00$ 405.00$ 50.00$ 45.00$ 47.00$ Period 11 4,650.00$ 4,150.00$ 4,250.00$ 435.00$ 415.00$ 404.00$ 48.00$ 46.00$ 46.00$ Period 12 4,600.00$ 4,150.00$ 4,250.00$ 430.00$ 430.00$ 404.00$ 46.00$ 46.00$ 46.00$ Company 5 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 2 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 3 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 4 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 5 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 6 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 7 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 8 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 9 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 10 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 11 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 12 -$ -$ -$ -$ -$ -$ -$ -$ -$ Figure 4 Coordinates Worksheet - Price Page 54 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Fifth, the NPB by Year worksheet (see Figure 6) con- sists of internal links to the Coordinates worksheet. This worksheet extracts the RMS, IGR, BGR, and SSR for each SBU for each company for the year 1-2 and year 2-3 peri- ods from the Coordinates worksheet. In addition, the work- sheet extracts the MSGR and WAGR for each company for the year 1-2 and year 2-3 periods from the Coordinates worksheet. The data in the NPB by Year worksheet are sorted by year by SBU for each company. This facilitates analysis of the brand portfolio (static analysis) in the year 1 -2 or year 2-3 period. The relevant data are extracted from the COMPETE Results Excel workbook x.xls to the NPB & Trends work- book as indicated in the Data Extraction Tables for the Ra- tios and Profitability Worksheets (see Figure 7), and the Coordinates Worksheets (see Figures 8 and 9). In each of the Data Extraction Tables, the Excel worksheet (tab), page number in the Excel-version of the COMPETE results printout, and cell references for each account are shown in the COMPETE Results Workbook table (on the right). The corresponding cell references for each account are shown in the NPB & Trends workbook table (on the left) in the Data Extraction Tables. For instance, in the Data Extraction Table for the Rati- os and Profitability worksheets (see Figure 7), the Earnings per Share for Company 1 in Period 1 in cell B9 on the Rati- os worksheet in Figure 1 is extracted from cell E9 in the “Earnings per Share By Time Period” table on the “EPS, Mkt%, SF Activity” worksheet of the COMPETE results workbook 1.xls. Similarly, the Net Profit After Tax for Company 1 in Year 1 in cell B6 on the “Profitability” worksheet in Figure 2 is extracted from cell F9 in the “Earnings Per Share By Time Period” table on the “EPS, Mkt%, SF Activity” worksheet of the COMPETE results workbook. In addition, in the Data Extraction Table for the Coor- dinates worksheet – Sales in units (see Figure 8), the Com- pany 1 TST – Region 1 Period 1 Sales (in Units) in cell B113 on the Coordinates worksheet – Quarterly Sales (in Units) in Figure 3 is extracted from cell D10 in the “Market Share By Product By Company For Region 1” table on the “Market Share” worksheet of the COMPETE results work- book 1.xls. Similarly, the Company 2 TST – Region 1 Pe- riod 1 Sales (in Units) in cell B128 on the Coordinates worksheet – Quarterly Sales (in Units) in Figure 3 is ex- tracted from cell D11 in the “Market Share By Product By Company For Region 1” table on the “Market Share” work- sheet of the COMPETE results workbook 1.xls. Further, in the Data Extraction Table for the Coordi- nates worksheet - Price (see Figure 9), the Company 1 TST – Region 1 Period 1 Price in cell N113 on the Coordinates worksheet - Price in Figure 4 is extracted from cell D32 in the “Actual Price By Product By Region By Company” table on the “Forecast, Prices” worksheet of the COMPETE results workbook 1.xls. Similarly, the Company 2 TST – Region 1 Period 1 Price in cell N126 on the Coordinates worksheet – Price in Figure 4 is extracted from cell D33 in the “Actual Price By Product By Region By Company” table on the “Forecast, Prices” worksheet of the COMPETE results workbook 1.xls. In summary, the Ratios worksheet (see Figure 1) cal- culates the Total Assets (except for Short Term Notes Pay- able), ROTA, NPM, and SATO for each company by peri- od based on the extracted EPS and Sales data. The Profita- bility worksheet (see Figure 2) calculates the approximate ROTA for each company by year based on the extracted Net Profit After Tax and Total Assets data. The Coordi- nates worksheet – Quarterly Sales in Units (see Figures 3) calculates the RMS, IGR, and BGR for each SBU based on the extracted Sales in Units data by SBU by Company. In addition, the Coordinates worksheet calculates the SSR for each SBU based on the extracted Sales in Units (see Figure 3) and Price (see Figure 4) data by SBU by Company. Fur- ther, the Coordinates worksheet - Quarterly Sales in Units (see Figure 3) calculates the WAGR for each company by year based on the Sales in Units data by SBU by Company. Finally, the Coordinates worksheet calculates the MSGR for each company by year based on the ROTA calculated in the Profitability worksheet from the extracted Net Profit After Tax and Total Assets (approximate) calculated by the Ratios worksheet. The NPB by SBU (see Figure 5) and NPB by Year (see Figure 6) worksheets consolidate and present the RMS, IGR, BGR, MSGR, WAGR and SSR (extracted from the Coordinates, Profitability, and Ratios worksheets) for each company by SBU and by Year respectively. The use of external links ensures relevant data are extracted from relevant sources (statements) in the simulation results and precludes data entry error. Cell comments clarify variables extracted from the COMPETE results to the Coordinates worksheets (see Figures 10 and 11). NORMATIVE POSITION OF BRANDS & TRENDS PACKAGE USE The Normative Position of Brands & Trends Pack- age is used by competing participant teams in Strategic Market Planning. This package is used together with the Interactive Online Boston Consulting Group (BCG) Matrix Graphics Package (Palia et al., 2002). The BCG Matrix Graphics Package is used to gen- erate the BCG Growth Share Matrix (GSM) and Growth Gain Matrix (GGM) displays (see Figure 12) for each company (team) based on its performance. GSM and GGM displays are generated at the end of the second and third year of operations and permit the par- ticipant teams to conduct static, comparative static, and dynamic analyses of their own brand portfolio and the brand portfolios of their main competitors. By super- imposing the display at the end of the second year of operations on the display at the end of the third (current) year, the participant teams can determine the trajectories (direction and degree of movement) of each of their brands. Competitor brand trajectories can also Page 55 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 SBU Recommended GSM GGM SBU Year RMS IGR Typology Strategy Normative Actual C / NC Trend BGR MSGR WAGR Trend Trend SSR TST - 1 1-2 0.75 0.44% H? BS (O) G L NC -6.22% 10.30% -1.74% 20,594,700.00$ TST - 1 2-3 1.02 -0.50% H* HS H H C NC ==> C 13.40% 4.97% 32.91% H? ==> H* L ==> H 23,844,100.00$ TST - 2 1-2 0.79 18.32% -5.82% 24,056,700.00$ TST - 2 2-3 0.77 19.32% ==> 20.31% ==> ==> 28,761,225.00$ TST - 3 1-2 0.70 16.94% 4.28% 18,453,500.00$ TST - 3 2-3 0.88 16.36% ==> 44.23% ==> ==> 25,714,200.00$ CVE - 1 1-2 0.65 -0.27% -15.67% 20,206,775.00$ CVE - 1 2-3 0.99 3.17% ==> 30.03% ==> ==> 25,225,825.00$ CVE - 2 1-2 0.64 16.26% 11.69% 28,125,405.00$ CVE - 2 2-3 0.79 16.81% ==> 41.17% ==> ==> 38,738,850.00$ CVE - 3 1-2 0.75 19.78% 11.58% 21,338,100.00$ CVE - 3 2-3 0.70 25.86% ==> 18.61% ==> ==> 23,923,910.00$ SSL - 1 1-2 0.67 -3.89% -13.91% 14,326,711.00$ SSL - 1 2-3 0.93 -6.39% ==> 17.29% ==> ==> 15,135,222.00$ SSL - 2 1-2 0.59 7.96% -6.47% 15,548,144.00$ SSL - 2 2-3 0.94 12.19% ==> 36.29% ==> ==> 20,187,120.00$ SSL - 3 1-2 0.71 8.82% -5.61% 13,563,540.00$ SSL - 3 2-3 1.09 4.74% ==> 70.62% ==> ==> 21,187,749.00$ Legend: H* = Healthy Star BS (O) = Build Share on Offense G = Gainer C = Consistent S* = Sick Star BS (D) = Build Share on Defense L = Loser NC = Not consistent H? = Healthy Problem Child HS = Hold Share H = Holder S? = Sick Problem Child H = Harvest H$ = Healthy Cash Cow D/W = Divest / Withdraw S$ = Sick Cash Cow HX = Healthy Dog SX = Sick Dog For example: If TST-1, Year 1-2 RMS = 0.95 and IGR = 12.4%, then SBU Typology = H? and Recommended Strategy is BS (O) Based on BS (O) strategy, normative position of TST-1 on GGM should be G. However, if actual position of TST-1 on GGM is a L, then the brand TST-1 is not consistent with its normative position. SBU Recommended GSM GGM SBU Year RMS IGR Typology Strategy Normative Actual C / NC Trend BGR MSGR WAGR Trend Trend SSR TST - 1 1-2 0.81 0.44% H? BS (O) G L NC 11.74% 7.56% 40.81% 22,268,530.00$ TST - 1 2-3 0.98 -0.50% H* HS H H C NC ==> C 1.95% 4.34% 10.54% H? ==> H* L ==> H 22,532,000.00$ TST - 2 1-2 0.79 18.32% 48.31% 23,763,600.00$ TST - 2 2-3 0.76 19.32% ==> 19.48% ==> ==> 28,392,500.00$ TST - 3 1-2 0.78 16.94% 33.06% 19,727,400.00$ TST - 3 2-3 0.82 16.36% ==> 20.80% ==> ==> 23,830,800.00$ CVE - 1 1-2 1.09 -0.27% 37.59% 29,758,340.00$ CVE - 1 2-3 1.01 3.17% ==> -14.26% ==> ==> 25,383,330.00$ CVE - 2 1-2 0.73 16.26% 36.04% 31,679,380.00$ CVE - 2 2-3 0.78 16.81% ==> 21.96% ==> ==> 37,792,372.00$ CVE - 3 1-2 0.84 19.78% 40.63% 23,126,215.00$ CVE - 3 2-3 0.72 25.86% ==> 9.30% ==> ==> 24,612,210.00$ SSL - 1 1-2 0.88 -3.89% 36.73% 17,443,900.00$ SSL - 1 2-3 1.00 -6.39% ==> -3.74% ==> ==> 16,401,204.00$ SSL - 2 1-2 0.79 7.96% 58.21% 18,800,104.00$ SSL - 2 2-3 1.00 12.19% ==> 17.28% ==> ==> 21,436,747.00$ SSL - 3 1-2 1.19 8.82% 75.19% 17,967,254.00$ SSL - 3 2-3 0.91 4.74% ==> 11.23% ==> ==> 19,858,128.00$ Legend: H* = Healthy Star BS (O) = Build Share on Offense G = Gainer C = Consistent S* = Sick Star BS (D) = Build Share on Defense L = Loser NC = Not consistent H? = Healthy Problem Child HS = Hold Share H = Holder S? = Sick Problem Child H = Harvest H$ = Healthy Cash Cow D/W = Divest / Withdraw S$ = Sick Cash Cow HX = Healthy Dog SX = Sick Dog For example: If TST-1, Year 1-2 RMS = 0.95 and IGR = 12.4%, then SBU Typology = H? and Recommended Strategy is BS (O) Based on BS (O) strategy, normative position of TST-1 on GGM should be G. However, if actual position of TST-1 on GGM is a L, then the brand TST-1 is not consistent with its normative position. Normative Position of the Brands + Trends Company 1 Normative Position of the Brands + Trends Company 2 SBU Typology Recommended Strategy GSM GGM GGM Position Consistency ConsistencyPosition GSM GGM Position Consistency SBU Typology Recommended Strategy GGM Position Consistency Figure 5 NPB by SBU Worksheet (for Companies 1 & 2) Page 56 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 SBU Recommended GSM GGM SBU Year RMS IGR Typology Strategy Normative Actual C / NC Trend BGR MSGR WAGR Trend Trend SSR TST - 1 1-2 0.75 0.44% H? BS (O) G L NC -6.22% 10.30% -1.74% 20,594,700.00$ TST - 2 1-2 0.79 18.32% -5.82% 24,056,700.00$ TST - 3 1-2 0.70 16.94% 4.28% 18,453,500.00$ CVE - 1 1-2 0.65 -0.27% -15.67% 20,206,775.00$ CVE - 2 1-2 0.64 16.26% 11.69% 28,125,405.00$ CVE - 3 1-2 0.75 19.78% 11.58% 21,338,100.00$ SSL - 1 1-2 0.67 -3.89% -13.91% 14,326,711.00$ SSL - 2 1-2 0.59 7.96% -6.47% 15,548,144.00$ SSL - 3 1-2 0.71 8.82% -5.61% 13,563,540.00$ TST - 1 2-3 1.02 -0.50% H* HS H H C NC ==> C 13.40% 4.97% 32.91% H? ==> H* L ==> H 23,844,100.00$ TST - 2 2-3 0.77 19.32% ==> 20.31% ==> ==> 28,761,225.00$ TST - 3 2-3 0.88 16.36% ==> 44.23% ==> ==> 25,714,200.00$ CVE - 1 2-3 0.99 3.17% ==> 30.03% ==> ==> 25,225,825.00$ CVE - 2 2-3 0.79 16.81% ==> 41.17% ==> ==> 38,738,850.00$ CVE - 3 2-3 0.70 25.86% ==> 18.61% ==> ==> 23,923,910.00$ SSL - 1 2-3 0.93 -6.39% ==> 17.29% ==> ==> 15,135,222.00$ SSL - 2 2-3 0.94 12.19% ==> 36.29% ==> ==> 20,187,120.00$ SSL - 3 2-3 1.09 4.74% ==> 70.62% ==> ==> 21,187,749.00$ Legend: H* = Healthy Star BS (O) = Build Share on Offense G = Gainer C = Consistent S* = Sick Star BS (D) = Build Share on Defense L = Loser NC = Not consistent H? = Healthy Problem Child HS = Hold Share H = Holder S? = Sick Problem Child H = Harvest H$ = Healthy Cash Cow D/W = Divest / Withdraw S$ = Sick Cash Cow HX = Healthy Dog SX = Sick Dog For example: If TST-1, Year 1-2 RMS = 0.95 and IGR = 12.4%, then SBU Typology = H? and Recommended Strategy is BS (O) Based on BS (O) strategy, normative position of TST-1 on GGM should be G. However, if actual position of TST-1 on GGM is a L, then the brand TST-1 is not consistent with its normative position. SBU Recommended GSM GGM SBU Year RMS IGR Typology Strategy Normative Actual C / NC Trend BGR MSGR WAGR Trend Trend SSR TST - 1 1-2 0.81 0.44% H? BS (O) G L NC 11.74% 7.56% 40.81% 22,268,530.00$ TST - 2 1-2 0.79 18.32% 48.31% 23,763,600.00$ TST - 3 1-2 0.78 16.94% 33.06% 19,727,400.00$ CVE - 1 1-2 1.09 -0.27% 37.59% 29,758,340.00$ CVE - 2 1-2 0.73 16.26% 36.04% 31,679,380.00$ CVE - 3 1-2 0.84 19.78% 40.63% 23,126,215.00$ SSL - 1 1-2 0.88 -3.89% 36.73% 17,443,900.00$ SSL - 2 1-2 0.79 7.96% 58.21% 18,800,104.00$ SSL - 3 1-2 1.19 8.82% 75.19% 17,967,254.00$ TST - 1 2-3 0.98 -0.50% H* HS H H C NC ==> C 1.95% 4.34% 10.54% H? ==> H* L ==> H 22,532,000.00$ TST - 2 2-3 0.76 19.32% ==> 19.48% ==> ==> 28,392,500.00$ TST - 3 2-3 0.82 16.36% ==> 20.80% ==> ==> 23,830,800.00$ CVE - 1 2-3 1.01 3.17% ==> -14.26% ==> ==> 25,383,330.00$ CVE - 2 2-3 0.78 16.81% ==> 21.96% ==> ==> 37,792,372.00$ CVE - 3 2-3 0.72 25.86% ==> 9.30% ==> ==> 24,612,210.00$ SSL - 1 2-3 1.00 -6.39% ==> -3.74% ==> ==> 16,401,204.00$ SSL - 2 2-3 1.00 12.19% ==> 17.28% ==> ==> 21,436,747.00$ SSL - 3 2-3 0.91 4.74% ==> 11.23% ==> ==> 19,858,128.00$ Legend: H* = Healthy Star BS (O) = Build Share on Offense G = Gainer C = Consistent S* = Sick Star BS (D) = Build Share on Defense L = Loser NC = Not consistent H? = Healthy Problem Child HS = Hold Share H = Holder S? = Sick Problem Child H = Harvest H$ = Healthy Cash Cow D/W = Divest / Withdraw S$ = Sick Cash Cow HX = Healthy Dog SX = Sick Dog For example: If TST-1, Year 1-2 RMS = 0.95 and IGR = 12.4%, then SBU Typology = H? and Recommended Strategy is BS (O) Based on BS (O) strategy, normative position of TST-1 on GGM should be G. However, if actual position of TST-1 on GGM is a L, then the brand TST-1 is not consistent with its normative position. Normative Position of the Brands + Trends Company 1 Normative Position of the Brands + Trends Company 2 GSM GGM GGM Position Consistency ConsistencyPosition SBU Typology Recommended Strategy GSM GGM Position Consistency SBU Typology Recommended Strategy GGM Position Consistency Figure 6 NPB by Year Worksheet (for Companies 1 & 2) Page 57 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Account Cell Ref. Worksheet (Tab) Page # Account Cell Ref. Ratios Worksheet (Tab) Period 1 Earnings per Share Company 1 Period 1 B9 from ==> EPS, Mkt%, SF Activity 8 Company 1 EPS By Time Period E9 Earnings per Share Company 2 Period 1 C9 from ==> EPS, Mkt%, SF Activity 8 Company 2 EPS By Time Period E10 Earnings per Share Company 3 Period 1 D9 from ==> EPS, Mkt%, SF Activity 8 Company 3 EPS By Time Period E11 Earnings per Share Company 4 Period 1 E9 from ==> EPS, Mkt%, SF Activity 8 Company 4 EPS By Time Period E12 Earnings per Share Company 5 Period 1 F9 from ==> EPS, Mkt%, SF Activity 8 Company 5 EPS By Time Period E13 Sales (In '000s) Company 1 Period 1 B26 from ==> Quality, Dollar Sales 14 Company 1 Dollar Sales * 1000 G29 Sales (In '000s) Company 2 Period 1 C26 from ==> Quality, Dollar Sales 14 Company 2 Dollar Sales * 1000 G30 Sales (In '000s) Company 3 Period 1 D26 from ==> Quality, Dollar Sales 14 Company 3 Dollar Sales * 1000 G31 Sales (In '000s) Company 4 Period 1 E26 from ==> Quality, Dollar Sales 14 Company 4 Dollar Sales * 1000 G32 Sales (In '000s) Company 5 Period 1 F26 from ==> Quality, Dollar Sales 14 Company 5 Dollar Sales * 1000 G33 Profitability Worksheet (Tab) Net Profit After Tax Company 1 Year 1 B6 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 1 EPS for Year F9 Net Profit After Tax Company 2 Year 1 B7 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 2 EPS for Year F10 Net Profit After Tax Company 3 Year 1 B8 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 3 EPS for Year F11 Net Profit After Tax Company 4 Year 1 B9 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 4 EPS for Year F12 Net Profit After Tax Company 5 Year 1 B10 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 5 EPS for Year F13 Net Profit After Tax Company 1 Cumulative C6 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 1 EPS for Game G9 Net Profit After Tax Company 2 Cumulative C7 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 2 EPS for Game G10 Net Profit After Tax Company 3 Cumulative C8 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 3 EPS for Game G11 Net Profit After Tax Company 4 Cumulative C9 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 4 EPS for Game G12 Net Profit After Tax Company 5 Cumulative C10 from ==> EPS, Mkt%, SF Activity 8 Period 4 Company 5 EPS for Game G13 Net Profit After Tax Company 1 Year 2 B14 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 1 EPS for Year F9 Net Profit After Tax Company 2 Year 2 B15 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 2 EPS for Year F10 Net Profit After Tax Company 3 Year 2 B16 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 3 EPS for Year F11 Net Profit After Tax Company 4 Year 2 B17 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 4 EPS for Year F12 Net Profit After Tax Company 5 Year 2 B18 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 5 EPS for Year F13 Net Profit After Tax Company 1 Cumulative C14 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 1 EPS for Game G9 Net Profit After Tax Company 2 Cumulative C15 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 2 EPS for Game G10 Net Profit After Tax Company 3 Cumulative C16 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 3 EPS for Game G11 Net Profit After Tax Company 4 Cumulative C17 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 4 EPS for Game G12 Net Profit After Tax Company 5 Cumulative C18 from ==> EPS, Mkt%, SF Activity 8 Period 8 Company 5 EPS for Game G13 Net Profit After Tax Company 1 Year 3 B22 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 1 EPS for Year F9 Net Profit After Tax Company 2 Year 3 B23 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 2 EPS for Year F10 Net Profit After Tax Company 3 Year 3 B24 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 3 EPS for Year F11 Net Profit After Tax Company 4 Year 3 B25 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 4 EPS for Year F12 Net Profit After Tax Company 5 Year 3 B26 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 5 EPS for Year F13 Net Profit After Tax Company 1 Cumulative C22 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 1 EPS for Game G9 Net Profit After Tax Company 2 Cumulative C23 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 2 EPS for Game G10 Net Profit After Tax Company 3 Cumulative C24 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 3 EPS for Game G11 Net Profit After Tax Company 4 Cumulative C25 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 4 EPS for Game G12 Net Profit After Tax Company 5 Cumulative C26 from ==> EPS, Mkt%, SF Activity 8 Period 12 Company 5 EPS for Game G13 Data Extraction from COMPETE Results Workbook.xls To NPB & Trends Workbook COMPETE NPB & Trends Workbook COMPETE Results Workbook x.xls (x = Period Number) Ratios & Profitability Worksheets Figure 7 Data Extraction Table – Ratios & Profitability Worksheets Page 58 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Figure 8 Data Extraction Table – Coordinates Worksheet – Sales (in Units) Account Cell Ref. Worksheet (Tab) Page # Account Cell Ref. Coordinates Worksheet (Tab) Company 1 TST - Reg 1 Period 1 Sales (in Units) B113 from ==> Market Share 13 Company 1 TST - Reg 1 Market Share (in Units) D10 Company 1 TST - Reg 2 Period 1 Sales (in Units) C113 from ==> Market Share 13 Company 1 TST - Reg 2 Market Share (in Units) D20 Company 1 TST - Reg 3 Period 1 Sales (in Units) D113 from ==> Market Share 13 Company 1 TST - Reg 3 Market Share (in Units) D30 Company 1 CVE - Reg 1 Period 1 Sales (in Units) E113 from ==> Market Share 13 Company 1 CVE - Reg 1 Market Share (in Units) F10 Company 1 CVE - Reg 2 Period 1 Sales (in Units) F113 from ==> Market Share 13 Company 1 CVE - Reg 2 Market Share (in Units) F20 Company 1 CVE - Reg 3 Period 1 Sales (in Units) G113 from ==> Market Share 13 Company 1 CVE - Reg 3 Market Share (in Units) F30 Company 1 SSL - Reg 1 Period 1 Sales (in Units) H113 from ==> Market Share 13 Company 1 SSL - Reg 1 Market Share (in Units) H10 Company 1 SSL - Reg 2 Period 1 Sales (in Units) I113 from ==> Market Share 13 Company 1 SSL - Reg 2 Market Share (in Units) H20 Company 1 SSL - Reg 3 Period 1 Sales (in Units) J113 from ==> Market Share 13 Company 1 SSL - Reg 3 Market Share (in Units) H30 Company 2 TST - Reg 1 Period 1 Sales (in Units) B128 from ==> Market Share 13 Company 2 TST - Reg 1 Market Share (in Units) D11 Company 2 TST - Reg 2 Period 1 Sales (in Units) C128 from ==> Market Share 13 Company 2 TST - Reg 2 Market Share (in Units) D21 Company 2 TST - Reg 3 Period 1 Sales (in Units) D128 from ==> Market Share 13 Company 2 TST - Reg 3 Market Share (in Units) D31 Company 2 CVE - Reg 1 Period 1 Sales (in Units) E128 from ==> Market Share 13 Company 2 CVE - Reg 1 Market Share (in Units) F11 Company 2 CVE - Reg 2 Period 1 Sales (in Units) F128 from ==> Market Share 13 Company 2 CVE - Reg 2 Market Share (in Units) F21 Company 2 CVE - Reg 3 Period 1 Sales (in Units) G128 from ==> Market Share 13 Company 2 CVE - Reg 3 Market Share (in Units) F31 Company 2 SSL - Reg 1 Period 1 Sales (in Units) H128 from ==> Market Share 13 Company 2 SSL - Reg 1 Market Share (in Units) H11 Company 2 SSL - Reg 2 Period 1 Sales (in Units) I128 from ==> Market Share 13 Company 2 SSL - Reg 2 Market Share (in Units) H21 Company 2 SSL - Reg 3 Period 1 Sales (in Units) J128 from ==> Market Share 13 Company 2 SSL - Reg 3 Market Share (in Units) H31 Company 3 TST - Reg 1 Period 1 Sales (in Units) B143 from ==> Market Share 13 Company 3 TST - Reg 1 Market Share (in Units) D12 Company 3 TST - Reg 2 Period 1 Sales (in Units) C143 from ==> Market Share 13 Company 3 TST - Reg 2 Market Share (in Units) D22 Company 3 TST - Reg 3 Period 1 Sales (in Units) D143 from ==> Market Share 13 Company 3 TST - Reg 3 Market Share (in Units) D32 Company 3 CVE - Reg 1 Period 1 Sales (in Units) E143 from ==> Market Share 13 Company 3 CVE - Reg 1 Market Share (in Units) F12 Company 3 CVE - Reg 2 Period 1 Sales (in Units) F143 from ==> Market Share 13 Company 3 CVE - Reg 2 Market Share (in Units) F22 Company 3 CVE - Reg 3 Period 1 Sales (in Units) G143 from ==> Market Share 13 Company 3 CVE - Reg 3 Market Share (in Units) F32 Company 3 SSL - Reg 1 Period 1 Sales (in Units) H143 from ==> Market Share 13 Company 3 SSL - Reg 1 Market Share (in Units) H12 Company 3 SSL - Reg 2 Period 1 Sales (in Units) I143 from ==> Market Share 13 Company 3 SSL - Reg 2 Market Share (in Units) H22 Company 3 SSL - Reg 3 Period 1 Sales (in Units) J143 from ==> Market Share 13 Company 3 SSL - Reg 3 Market Share (in Units) H32 Company 4 TST - Reg 1 Period 1 Sales (in Units) B158 from ==> Market Share 13 Company 4 TST - Reg 1 Market Share (in Units) D13 Company 4 TST - Reg 2 Period 1 Sales (in Units) C158 from ==> Market Share 13 Company 4 TST - Reg 2 Market Share (in Units) D23 Company 4 TST - Reg 3 Period 1 Sales (in Units) D158 from ==> Market Share 13 Company 4 TST - Reg 3 Market Share (in Units) D33 Company 4 CVE - Reg 1 Period 1 Sales (in Units) E158 from ==> Market Share 13 Company 4 CVE - Reg 1 Market Share (in Units) F13 Company 4 CVE - Reg 2 Period 1 Sales (in Units) F158 from ==> Market Share 13 Company 4 CVE - Reg 2 Market Share (in Units) F23 Company 4 CVE - Reg 3 Period 1 Sales (in Units) G158 from ==> Market Share 13 Company 4 CVE - Reg 3 Market Share (in Units) F33 Company 4 SSL - Reg 1 Period 1 Sales (in Units) H158 from ==> Market Share 13 Company 4 SSL - Reg 1 Market Share (in Units) H13 Company 4 SSL - Reg 2 Period 1 Sales (in Units) I158 from ==> Market Share 13 Company 4 SSL - Reg 2 Market Share (in Units) H23 Company 4 SSL - Reg 3 Period 1 Sales (in Units) J158 from ==> Market Share 13 Company 4 SSL - Reg 3 Market Share (in Units) H33 Company 5 TST - Reg 1 Period 1 Sales (in Units) B173 from ==> Market Share 13 Company 5 TST - Reg 1 Market Share (in Units) D14 Company 5 TST - Reg 2 Period 1 Sales (in Units) C173 from ==> Market Share 13 Company 5 TST - Reg 2 Market Share (in Units) D24 Company 5 TST - Reg 3 Period 1 Sales (in Units) D173 from ==> Market Share 13 Company 5 TST - Reg 3 Market Share (in Units) D34 Company 5 CVE - Reg 1 Period 1 Sales (in Units) E173 from ==> Market Share 13 Company 5 CVE - Reg 1 Market Share (in Units) F14 Company 5 CVE - Reg 2 Period 1 Sales (in Units) F173 from ==> Market Share 13 Company 5 CVE - Reg 2 Market Share (in Units) F24 Company 5 CVE - Reg 3 Period 1 Sales (in Units) G173 from ==> Market Share 13 Company 5 CVE - Reg 3 Market Share (in Units) F34 Company 5 SSL - Reg 1 Period 1 Sales (in Units) H173 from ==> Market Share 13 Company 5 SSL - Reg 1 Market Share (in Units) H14 Company 5 SSL - Reg 2 Period 1 Sales (in Units) I173 from ==> Market Share 13 Company 5 SSL - Reg 2 Market Share (in Units) H24 Company 5 SSL - Reg 3 Period 1 Sales (in Units) J173 from ==> Market Share 13 Company 5 SSL - Reg 3 Market Share (in Units) H34 Data Extraction from COMPETE Results Workbook.xls To NPB & Trends Workbook COMPETE NPB & Trends Workbook COMPETE Results Workbook x.xls (x = Period Number) Coordinates Worksheet Page 59 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Figure 9 Data Extraction Table – Coordinates Worksheet – Price Account Cell Ref. Worksheet (Tab) Page # Account Cell Ref. Coordinates Worksheet (Tab) Company 1 TST - Reg 1 Period 1 Price N113 from ==> Forecast, Prices 13 Company 1 TST - Region 1 Price D32 Company 1 TST - Reg 2 Period 1 Price O113 from ==> Forecast, Prices 13 Company 1 TST - Region 2 Price G32 Company 1 TST - Reg 3 Period 1 Price P113 from ==> Forecast, Prices 13 Company 1 TST - Region 3 Price J32 Company 1 CVE - Reg 1 Period 1 Price Q113 from ==> Forecast, Prices 13 Company 1 CVE - Region 1 Price E32 Company 1 CVE - Reg 2 Period 1 Price R113 from ==> Forecast, Prices 13 Company 1 CVE - Region 2 Price H32 Company 1 CVE - Reg 3 Period 1 Price S113 from ==> Forecast, Prices 13 Company 1 CVE - Region 3 Price K32 Company 1 SSL - Reg 1 Period 1 Price T113 from ==> Forecast, Prices 13 Company 1 SSL - Region 1 Price F32 Company 1 SSL - Reg 2 Period 1 Price U113 from ==> Forecast, Prices 13 Company 1 SSL - Region 2 Price I32 Company 1 SSL - Reg 3 Period 1 Price V113 from ==> Forecast, Prices 13 Company 1 SSL - Region 3 Price L32 Company 2 TST - Reg 1 Period 1 Price N128 from ==> Forecast, Prices 13 Company 2 TST - Region 1 Price D33 Company 2 TST - Reg 2 Period 1 Price O128 from ==> Forecast, Prices 13 Company 2 TST - Region 2 Price G33 Company 2 TST - Reg 3 Period 1 Price P128 from ==> Forecast, Prices 13 Company 2 TST - Region 3 Price J33 Company 2 CVE - Reg 1 Period 1 Price Q128 from ==> Forecast, Prices 13 Company 2 CVE - Region 1 Price E33 Company 2 CVE - Reg 2 Period 1 Price R128 from ==> Forecast, Prices 13 Company 2 CVE - Region 2 Price H33 Company 2 CVE - Reg 3 Period 1 Price S128 from ==> Forecast, Prices 13 Company 2 CVE - Region 3 Price K33 Company 2 SSL - Reg 1 Period 1 Price T128 from ==> Forecast, Prices 13 Company 2 SSL - Region 1 Price F33 Company 2 SSL - Reg 2 Period 1 Price U128 from ==> Forecast, Prices 13 Company 2 SSL - Region 2 Price I33 Company 2 SSL - Reg 3 Period 1 Price V128 from ==> Forecast, Prices 13 Company 2 SSL - Region 3 Price L33 Company 3 TST - Reg 1 Period 1 Price N143 from ==> Forecast, Prices 13 Company 3 TST - Region 1 Price D34 Company 3 TST - Reg 2 Period 1 Price O143 from ==> Forecast, Prices 13 Company 3 TST - Region 2 Price G34 Company 3 TST - Reg 3 Period 1 Price P143 from ==> Forecast, Prices 13 Company 3 TST - Region 3 Price J34 Company 3 CVE - Reg 1 Period 1 Price Q143 from ==> Forecast, Prices 13 Company 3 CVE - Region 1 Price E34 Company 3 CVE - Reg 2 Period 1 Price R143 from ==> Forecast, Prices 13 Company 3 CVE - Region 2 Price H34 Company 3 CVE - Reg 3 Period 1 Price S143 from ==> Forecast, Prices 13 Company 3 CVE - Region 3 Price K34 Company 3 SSL - Reg 1 Period 1 Price T143 from ==> Forecast, Prices 13 Company 3 SSL - Region 1 Price F34 Company 3 SSL - Reg 2 Period 1 Price U143 from ==> Forecast, Prices 13 Company 3 SSL - Region 2 Price I34 Company 3 SSL - Reg 3 Period 1 Price V143 from ==> Forecast, Prices 13 Company 3 SSL - Region 3 Price L34 Company 4 TST - Reg 1 Period 1 Price N158 from ==> Forecast, Prices 13 Company 4 TST - Region 1 Price D35 Company 4 TST - Reg 2 Period 1 Price O158 from ==> Forecast, Prices 13 Company 4 TST - Region 2 Price G35 Company 4 TST - Reg 3 Period 1 Price P158 from ==> Forecast, Prices 13 Company 4 TST - Region 3 Price J35 Company 4 CVE - Reg 1 Period 1 Price Q158 from ==> Forecast, Prices 13 Company 4 CVE - Region 1 Price E35 Company 4 CVE - Reg 2 Period 1 Price R158 from ==> Forecast, Prices 13 Company 4 CVE - Region 2 Price H35 Company 4 CVE - Reg 3 Period 1 Price S158 from ==> Forecast, Prices 13 Company 4 CVE - Region 3 Price K35 Company 4 SSL - Reg 1 Period 1 Price T158 from ==> Forecast, Prices 13 Company 4 SSL - Region 1 Price F35 Company 4 SSL - Reg 2 Period 1 Price U158 from ==> Forecast, Prices 13 Company 4 SSL - Region 2 Price I35 Company 4 SSL - Reg 3 Period 1 Price V158 from ==> Forecast, Prices 13 Company 4 SSL - Region 3 Price L35 Company 5 TST - Reg 1 Period 1 Price N173 from ==> Forecast, Prices 13 Company 5 TST - Region 1 Price D36 Company 5 TST - Reg 2 Period 1 Price O173 from ==> Forecast, Prices 13 Company 5 TST - Region 2 Price G36 Company 5 TST - Reg 3 Period 1 Price P173 from ==> Forecast, Prices 13 Company 5 TST - Region 3 Price J36 Company 5 CVE - Reg 1 Period 1 Price Q173 from ==> Forecast, Prices 13 Company 5 CVE - Region 1 Price E36 Company 5 CVE - Reg 2 Period 1 Price R173 from ==> Forecast, Prices 13 Company 5 CVE - Region 2 Price H36 Company 5 CVE - Reg 3 Period 1 Price S173 from ==> Forecast, Prices 13 Company 5 CVE - Region 3 Price K36 Company 5 SSL - Reg 1 Period 1 Price T173 from ==> Forecast, Prices 13 Company 5 SSL - Region 1 Price F36 Company 5 SSL - Reg 2 Period 1 Price U173 from ==> Forecast, Prices 13 Company 5 SSL - Region 2 Price I36 Company 5 SSL - Reg 3 Period 1 Price V173 from ==> Forecast, Prices 13 Company 5 SSL - Region 3 Price L36 Data Extraction from COMPETE Results Workbook.xls To NPB & Trends Workbook COMPETE NPB & Trends Workbook COMPETE Results Workbook x.xls (x = Period Number) Coordinates Worksheet Page 60 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Figure 10 Coordinates Worksheet – Quarterly Sales With Cell Commments (in Units) Quarterly Sales (in Units) Company 1 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 1,456 1,400 978 7,863 8,845 6,360 73,754 79,400 64,861 Period 2 555 681 448 13,997 15,056 11,100 67,955 71,960 60,602 Period 3 1,006 1,308 788 23,627 25,219 19,634 44,153 46,214 40,742 Period 4 1,997 2,784 1,827 7,887 10,805 6,996 133,073 140,654 114,840 Period 5 1,294 1,758 1,199 5,000 6,695 4,878 81,965 88,147 70,175 Period 6 567 699 480 9,503 14,533 11,764 65,499 76,916 64,513 Period 7 959 977 773 18,395 27,352 20,036 28,917 34,226 30,614 Period 8 1,882 2,380 1,762 12,114 18,351 12,519 98,185 117,040 99,969 Period 9 1,449 1,804 1,645 8,628 11,415 6,073 83,467 110,533 93,330 Period 10 723 721 701 14,714 22,766 13,714 75,730 100,823 99,497 Period 11 1,038 1,201 982 23,495 36,376 26,220 45,856 76,272 84,780 Period 12 2,122 3,269 2,750 11,690 23,928 12,344 116,973 143,508 175,000 Company 2 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 1,190 1,131 1,049 8,552 9,101 5,609 76,156 63,885 44,316 Period 2 577 515 522 12,529 13,599 8,881 55,252 50,965 36,020 Period 3 933 854 741 14,294 16,416 12,076 48,545 45,896 43,464 Period 4 1,900 1,408 1,218 14,663 17,085 12,770 83,873 85,058 88,505 Period 5 1,281 1,335 1,121 10,304 11,965 8,483 64,454 66,836 57,235 Period 6 719 757 649 16,842 17,544 13,120 75,456 80,230 77,752 Period 7 1,208 1,433 1,139 23,207 24,846 17,763 76,554 81,838 84,920 Period 8 1,932 2,271 1,788 18,493 22,103 15,951 144,265 159,980 152,026 Period 9 1,360 1,696 1,373 11,600 15,593 9,877 80,736 101,030 92,889 Period 10 700 900 800 13,989 21,273 13,227 69,307 98,026 88,292 Period 11 1,282 1,818 1,365 17,303 29,355 18,731 71,992 87,213 79,043 Period 12 1,898 2,511 2,136 16,139 27,026 18,626 125,209 169,832 153,487 Company 3 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 1,500 1,400 1,058 10,100 13,985 8,989 104,139 115,652 79,455 Period 2 800 700 542 11,350 17,159 9,787 98,656 108,415 71,253 Period 3 1,358 1,390 1,198 20,047 26,971 17,685 90,191 96,272 61,291 Period 4 2,484 2,525 2,264 19,944 23,405 17,089 179,462 192,887 120,490 Period 5 1,630 1,707 1,437 11,646 17,258 11,700 100,435 115,182 75,213 Period 6 736 878 669 14,263 22,217 14,725 86,303 100,969 57,105 Period 7 1,359 1,674 1,319 19,317 35,446 20,533 80,678 104,761 65,593 Period 8 2,583 3,088 2,626 17,984 29,735 18,891 144,809 211,032 115,002 Period 9 1,388 1,871 1,887 10,505 20,122 10,041 91,037 111,765 74,881 Period 10 575 897 826 12,896 25,929 13,656 75,904 92,268 61,576 Period 11 1,106 1,514 1,371 18,672 39,295 20,773 61,849 83,345 55,425 Period 12 2,059 2,778 2,837 15,468 34,068 18,060 118,199 170,114 122,307 Company 4 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 1,300 1,440 1,043 8,720 7,345 6,849 86,636 82,563 71,011 Period 2 678 760 498 11,576 10,964 9,976 76,714 73,078 64,391 Period 3 1,165 1,200 795 13,683 16,461 11,369 64,933 70,922 54,109 Period 4 1,646 1,814 1,310 11,640 14,718 10,606 97,448 98,633 82,527 Period 5 1,183 1,347 944 7,094 7,131 6,862 71,851 73,249 70,812 Period 6 601 739 548 8,286 10,966 7,987 64,002 65,059 56,503 Period 7 993 1,500 946 9,768 11,674 13,028 56,630 65,558 37,586 Period 8 1,708 2,670 1,637 7,693 9,493 12,310 87,231 94,709 79,698 Period 9 1,326 2,030 538 6,000 6,498 16,907 51,929 79,128 30,220 Period 10 647 1,200 449 9,389 7,714 20,291 50,000 74,917 21,220 Period 11 1,043 2,175 1,212 13,074 10,093 23,600 46,166 77,980 17,034 Period 12 1,816 3,700 1,280 13,007 4,143 22,864 78,067 146,128 2,400 Company 5 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 0 0 0 0 0 0 0 0 0 Period 2 0 0 0 0 0 0 0 0 0 Period 3 0 0 0 0 0 0 0 0 0 Period 4 0 0 0 0 0 0 0 0 0 Period 5 0 0 0 0 0 0 0 0 0 Period 6 0 0 0 0 0 0 0 0 0 Period 7 0 0 0 0 0 0 0 0 0 Period 8 0 0 0 0 0 0 0 0 0 Period 9 0 0 0 0 0 0 0 0 0 Period 10 0 0 0 0 0 0 0 0 0 Period 11 0 0 0 0 0 0 0 0 0 Period 12 0 0 0 0 0 0 0 0 0 Author: TST Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 1. Author: CVE Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 5. Author: SSL Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 9. Author: TST Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 1. Author: TST Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 1. Author: TST Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 1. Author: TST Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 1. Author: CVE Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 5. Author: CVE Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 5. Author: CVE Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 5. Author: CVE Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 5. Author: SSL Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 9. Author: SSL Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 9. Author: SSL Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 9. Author: SSL Region 1 Unit Sales extracted from Unit Sales by Product by Region Table for Period 9. Page 61 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Figure 11 Coordinates Worksheet – Price With Cell Commments Price (in $s) Company 1 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 4,500.00$ 4,200.00$ 4,500.00$ 450.00$ 420.00$ 450.00$ 54.00$ 50.00$ 54.00$ Period 2 4,500.00$ 4,200.00$ 4,500.00$ 450.00$ 420.00$ 450.00$ 54.00$ 50.00$ 54.00$ Period 3 4,400.00$ 4,100.00$ 4,400.00$ 450.00$ 420.00$ 450.00$ 53.00$ 50.00$ 53.00$ Period 4 4,450.00$ 4,150.00$ 4,450.00$ 455.00$ 425.00$ 450.00$ 54.00$ 51.00$ 54.00$ Period 5 4,400.00$ 4,150.00$ 4,400.00$ 455.00$ 425.00$ 435.00$ 53.00$ 50.00$ 52.00$ Period 6 4,400.00$ 4,150.00$ 4,400.00$ 455.00$ 425.00$ 435.00$ 53.00$ 50.00$ 52.00$ Period 7 4,400.00$ 4,150.00$ 4,400.00$ 450.00$ 420.00$ 435.00$ 52.00$ 49.00$ 51.00$ Period 8 4,350.00$ 4,120.00$ 4,350.00$ 440.00$ 415.00$ 430.00$ 51.00$ 48.00$ 50.00$ Period 9 4,300.00$ 4,100.00$ 4,200.00$ 425.00$ 410.00$ 410.00$ 47.00$ 47.00$ 47.00$ Period 10 4,400.00$ 4,100.00$ 4,200.00$ 425.00$ 410.00$ 410.00$ 47.00$ 47.00$ 47.00$ Period 11 4,500.00$ 4,100.00$ 4,250.00$ 435.00$ 410.00$ 410.00$ 47.00$ 46.00$ 46.00$ Period 12 4,600.00$ 4,125.00$ 4,250.00$ 435.00$ 410.00$ 410.00$ 47.00$ 47.00$ 47.00$ Company 2 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 4,500.00$ 4,200.00$ 4,500.00$ 450.00$ 420.00$ 450.00$ 54.00$ 50.00$ 54.00$ Period 2 4,556.00$ 4,250.00$ 4,556.00$ 450.00$ 420.00$ 450.00$ 54.00$ 50.00$ 54.00$ Period 3 4,556.00$ 4,250.00$ 4,556.00$ 450.00$ 420.00$ 435.00$ 54.00$ 50.00$ 50.00$ Period 4 4,432.00$ 4,432.00$ 4,432.00$ 445.00$ 420.00$ 435.00$ 50.00$ 50.00$ 50.00$ Period 5 4,430.00$ 4,100.00$ 4,200.00$ 445.00$ 420.00$ 435.00$ 50.00$ 50.00$ 50.00$ Period 6 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 415.00$ 415.00$ 48.00$ 48.00$ 48.00$ Period 7 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 415.00$ 415.00$ 48.00$ 48.00$ 48.00$ Period 8 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 415.00$ 48.00$ 48.00$ 48.00$ Period 9 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 408.00$ 48.00$ 47.00$ 48.00$ Period 10 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 404.00$ 408.00$ 47.00$ 47.00$ 48.00$ Period 11 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 404.00$ 408.00$ 47.00$ 47.00$ 48.00$ Period 12 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 405.00$ 405.00$ 47.00$ 47.00$ 48.00$ Company 3 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 4,080.00$ 3,900.00$ 3,910.00$ 440.00$ 410.00$ 420.00$ 49.00$ 47.00$ 49.00$ Period 2 4,200.00$ 4,000.00$ 4,100.00$ 440.00$ 410.00$ 430.00$ 51.00$ 49.00$ 51.00$ Period 3 4,350.00$ 4,150.00$ 4,250.00$ 440.00$ 410.00$ 420.00$ 51.00$ 49.00$ 51.00$ Period 4 4,350.00$ 4,150.00$ 4,250.00$ 440.00$ 410.00$ 420.00$ 51.00$ 49.00$ 51.00$ Period 5 4,350.00$ 4,150.00$ 4,250.00$ 440.00$ 410.00$ 420.00$ 51.00$ 49.00$ 51.00$ Period 6 4,350.00$ 4,150.00$ 4,250.00$ 440.00$ 410.00$ 420.00$ 51.00$ 49.00$ 51.00$ Period 7 4,300.00$ 4,100.00$ 4,200.00$ 440.00$ 410.00$ 420.00$ 49.00$ 47.00$ 48.00$ Period 8 4,300.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 49.00$ 47.00$ 48.00$ Period 9 4,700.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 60.00$ 47.00$ 48.00$ Period 10 4,700.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 60.00$ 47.00$ 48.00$ Period 11 4,700.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 60.00$ 47.00$ 48.00$ Period 12 4,700.00$ 4,100.00$ 4,200.00$ 430.00$ 410.00$ 410.00$ 60.00$ 47.00$ 48.00$ Company 4 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 4,300.00$ 4,100.00$ 4,200.00$ 450.00$ 430.00$ 440.00$ 53.00$ 50.00$ 52.00$ Period 2 4,300.00$ 4,100.00$ 4,300.00$ 450.00$ 430.00$ 430.00$ 53.00$ 50.00$ 52.00$ Period 3 4,300.00$ 4,100.00$ 4,300.00$ 450.00$ 430.00$ 440.00$ 53.00$ 50.00$ 52.00$ Period 4 4,400.00$ 4,300.00$ 4,360.00$ 470.00$ 442.00$ 440.00$ 55.00$ 52.00$ 51.00$ Period 5 4,400.00$ 4,250.00$ 4,380.00$ 460.00$ 436.00$ 440.00$ 52.00$ 51.00$ 52.00$ Period 6 4,400.00$ 4,125.00$ 4,380.00$ 460.00$ 420.00$ 440.00$ 52.00$ 50.00$ 52.00$ Period 7 4,400.00$ 4,125.00$ 4,380.00$ 460.00$ 415.00$ 435.00$ 52.00$ 48.00$ 50.00$ Period 8 4,390.00$ 4,150.00$ 4,250.00$ 455.00$ 425.00$ 425.00$ 51.00$ 48.00$ 49.00$ Period 9 4,360.00$ 4,050.00$ 4,190.00$ 440.00$ 405.00$ 405.00$ 49.00$ 45.00$ 47.00$ Period 10 4,600.00$ 4,150.00$ 4,190.00$ 440.00$ 415.00$ 405.00$ 50.00$ 45.00$ 47.00$ Period 11 4,650.00$ 4,150.00$ 4,250.00$ 435.00$ 415.00$ 404.00$ 48.00$ 46.00$ 46.00$ Period 12 4,600.00$ 4,150.00$ 4,250.00$ 430.00$ 430.00$ 404.00$ 46.00$ 46.00$ 46.00$ Company 5 TST - Reg 1 TST - Reg 2 TST - Reg 3 CVE - Reg 1 CVE - Reg 2 CVE - Reg 3 SSL - Reg 1 SSL - Reg 2 SSL - Reg 3 Period 1 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 2 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 3 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 4 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 5 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 6 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 7 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 8 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 9 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 10 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 11 -$ -$ -$ -$ -$ -$ -$ -$ -$ Period 12 -$ -$ -$ -$ -$ -$ -$ -$ -$ Author: TST Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 1. Author: TST Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 1. Author: TST Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 1. Author: TST Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 1. Author: TST Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 1. Author: CVE Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 5. Author: CVE Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 5. Author: CVE Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 5. Author: CVE Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 5. Author: CVE Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 5. Author: SSL Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 9. Author: SSL Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 9. Author: SSL Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 9. Author: SSL Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 9. Author: SSL Region 1 Price extracted from Actual Price By Product By Region By Company Table for Period 9. Page 62 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 be generated and analyzed. Based on these BCG GSM and GGM displays, the competing participant teams can (1) check for internal balance in their brand portfolios, (2) look for trends, (3) evaluate competition, (4) consider factors not captured in the portfolio display, (5) develop possible "target" portfolios along with associated strategies for achieving them, and (6) check for financial balance (Palia, 2010). Checking for internal balance includes an assess- ment of the strength of their own SBU portfolio. A strong diversified portfolio consists of the majority of brands being leaders with an RMS greater than 1x, the presence of at least one large healthy cash cow, a few large healthy stars (future cash cows), and small healthy problem children and dogs. In addition, the weighted average growth rate (WAGR) of the nine SBUs, depict- ed by a diamond on the GGM, should be just less than or equal to the maximum sustainable growth rate (MSGR) depicted by a vertical line on the GGM. When the WAGR is less than or equal to the MSGR, this im- plies that the firm is not overextending its resources. Further, the actual position (Gainer / Loser) of each SBU on the GGM is checked for consistency with its normative position indicated by the recommended strategy for that SBU based on its position on the GSM. Tentative ideas for improving the internal balance should result from this analysis. Looking for trends involves superimposing the Year 1-2 GSM and GGM display on the current Year 2- 3 GSM and GGM display to reveal the direction and rate of movement of each SBU. Positive and negative trends in RMS, IGR, BGR, SSR, and WAGR relative to MSGR are assessed. In addition, the trend in consisten- cy between the actual position of each SBU on the GGM and its normative position indicated by the recom- mended strategy from Year 1-2 to Year 2-3 is assessed. Some tentative ideas for improving upon the current trends in the SBU portfolio should result from this anal- ysis. When evaluating competition, the GSM and GGM displays are generated for each of the firm’s major competitors. Even though these GSM and GGM dis- plays in the real world may not be as reliable for one’s own firm, they will display the best information availa- Figure 12 BCG Growth Share Matrix & Growth Gain Matrix Graphic Display Page 63 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 ble about competitors. Each competitors GSM and GGM displays are carefully studied to determine what each is doing. Are their strategies coherent? Which are their “cash cows,” “stars,” “problem children,” and “dogs?” How close is each competitor’s WAGR to its MSGR? Are the actual positions of their SBUs con- sistent with their normative positions on the GGM. Useful insights and potential weaknesses of each com- petitor can be revealed. Too much emphasis on one SBU may drain their resources and leave them vulnera- ble to market share-gaining strategies on other SBUs by another firm. The Normative Position of Brands & Trends packages is used in the above three steps to assess whether each SBU in a brand portfolio is consistent with its normative position on the GGM. The actual position of the SBU is determined by its performance, and indicates whether the brand is a Gainer (BGR is greater than IGR), Holder (BGR is equal to IGR), or Loser (BGR is less than IGR). The normative (ideal) position of the SBU on the GGM is determined by the recommended strategy (Build Share, Hold Share, Har- vest, or Divest/Withdraw) which in turn is based on the SBU position on the GSM (Cash Cow, Star, Problem Child, or Dog). NORMATIVE POSITION OF BRANDS & TRENDS PACKAGE PROCESS First, the participant teams download and unzip the Normative Position of Brands.zip folder. Next, they login to CODES and download, rename and save the Excel version of results for all twelve periods (quarters) “x” in the unzipped “C:\Normative Position of Brands” directory. Then, they update the NPB & Trends.xls workbook with team data. For instance, to update the NPB & Trends worksheet with team data, they first open the unzipped Normative Position of Brands.zip folder, then open the NPB & Trends.xls workbook, and finally click “Update file” in the pop-up menu that ap- pears. First, the EPS and Sales (in $’000s) for each company for each period are extracted from the ‘Earnings Per Share By Time Period’ table on the ‘EPS, Mkt%, SF Activity’ page, and from the ‘Dollar Sales By Region By Company (in Millions)’ table on the ‘Quality, Dollar Sales’ page re- spectively, of the Excel version of the COMPETE results for the first twelve periods (quarters) of operation. Next, the Unit Sales by Product by Region for each Company for each period is extracted from the ‘Market Share By Product By Company For Region 1,’ ‘Market Share By Product By Company for Region 2,’ and ‘Market Share By Product By Company For Region 3’ tables on the ‘Market Share’ page of Excel version of the COMPETE results for the twelve periods (quarters) of operation. Finally, the price for each SBU for each company for each period is extracted from the ‘Actual Price By Product By Region By Company’ table on the ‘Forecast, Prices’ page of Excel version of the COMPETE results for the twelve periods (quarters) of op- eration. The ‘NPB by SBU’ and ‘NPB by Year’ worksheets present the RMS, IGR, BGR, and SSR for each SBU for each company for each period and the MSGR and WAGR for each company for each period computed in the ‘Ratios,’ ‘Profitability,’ and ‘Coordinates’ worksheets from the ex- tracted data. The use of external links ensures relevant data are extracted from relevant sources (statements) in the sim- ulation results and precludes data entry error. Cell com- ments (see Figures 10 & 11) clarify variables, cell formulae and functions used. Color-coded cells specify where data are extracted. The NPB by SBU (see Figure 5) and NPB by Year (see Figure 6) worksheets consolidate and present the RMS, IGR, BGR, MSGR, WAGR and SSR (extracted from the Coordinates, Profitability, and Ratios worksheets) for each company by SBU and by Year respectively. Based on the RMS and IGR, the SBU typology and the recommend- ed strategy are entered for each SBU as depicted on the Growth Share Matrix (GSM). Based on the recommended strategy, the Normative Position of each SBU is entered and compared with the Actual Position of the same SBU on the Growth Gain Matrix. For instance, a brand with an RMS of 0.95 and an IGR of 15% is classified as a Healthy Problem Child (H?). The recommended strategy is to Build Share on Offense {BS(O)}. Consequently, the Nor- mative Position of this SBU is a Gainer on the Growth Gain Matrix (GGM), implying that the BGR is greater than the IGR. If the Actual Position of this SBU on the GGM is a Loser, as the BGR is less than the IGR, then this SBU is not consistent with its normative position. The normative position of each SBU is evaluated when Checking the Internal Balance of the brand portfolio, when Looking for Trends from one year to the next, and when Evaluating Competitor brand portfolios. Tentative ideas for improvement in the internal balance and trends of the brand portfolio are generated. Next, the normative position of each SBU in the brand portfolio is assessed, and the trends in normative position of the SBUs from one year to the next are evaluated. In addition, an identical procedure is used to assess the internal balance and trends in the brand portfolios of each competitor. Useful insights and potential weaknesses of competition can be revealed. STRENGTHS AND LIMITATIONS The Normative Position of Brands & Trends Package is used in Strategic Market Planning to assess the con- sistency of each SBU in a brand portfolio relative to its normative position on the GGM. This package is used to assess the normative consistency of each SBU when the user checks the internal balance of the SBU portfolio, looks Page 64 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 for trends in SBU trajectories, and/or evaluates the SBU portfolios of major competitors. Positive anecdotal student feedback was received dur- ing Spring and Fall 2011 semesters. Some undergraduate students reported that the decision support packages were very useful and helpful. They indicated that the automatic extraction feature saved a lot of time that would otherwise be necessary to identify, enter and compute the necessary figures. They hoped that it would continue to be used in the future as it definitely made a difference. Other students indicated that they did not make full use of the DSS. The analysis has some limitations. First, the total as- sets of competitors are approximated as the common stock plus the current retained income during each quarterly peri- od of operation, since the short-term notes payable of com- petitors is unknown. The approximate total assets at the end of each year of operation are used by the Profitability worksheet to calculate the approximate annual return on total assets (ROTA). Second the MSGR calculation is af- fected as there is no long-term debt or dividends in the COMPETE simulation. These shortcomings exist in the real world where accurate, timely and relevant information on competitor brand portfolios is not always available. Yet, an analysis of competitor brand performance, even though the information may be approximate, is critical to the development of a strategic market plan. Admittedly, integrated strategic market planning is a complex iterative task that requires considerable effort, judgment and experience. The user needs to (a) monitor the performance of their SBU portfolio as well as the SBU portfolios of their major competitors over several years, (b) calculate the relative market share (RMS), industry growth rates (IGR), SBU Sales Revenue (SSR), brand growth rates (BGR), weighted average growth rates (WAGR) and maxi- mum sustainable growth rate (MSGR), (c) generate the Growth Share Matrix (GSM) and Growth Gain Matrix (GGM) visual displays, (d) interpret and analyze these dis- plays on a sustained basis, (e) formulate an integrated stra- tegic market plan, and (f) accurately project performance results and expenses incurred. Despite these limitations, the Normative Position of Brands & Trends Package is a simple yet powerful web- based user-centered learning tool that extracts relevant data from the simulation results, precludes data entry error, and saves considerable time involved in identifying and enter- ing relevant data. Yet, in order to maximize learning about Strategic Market Planning, and actualize the potential of the Normative Position of Brands & Trends Package, the instructor needs to (a) explain the purpose, significance, assumptions, usage, and limitations of this DSS package, (b) require inclusion of a sample analysis in a team report and/or presentation, and (c) test students on their under- standing of the underlying concepts at the end of the se- mester. In the final analysis, use of the Normative Position of Brands & Trends Package and integrated strategic market planning can help to optimize the overall performance of the brand portfolio while maintaining cash in balance and thereby justify the considerable effort and time involved. Figure 13 Survey Responses – Package Usage Page 65 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 USER FEEDBACK An online survey was used to assess participant usage and learning experience of the Normative Position of Brands & Trends package at the end of the Fall 2012 se- mester. This online survey consisted of ten questions that assessed (a) package usage and usefulness in identifying normative consistency of brands, (b) package impact on awareness and learning about the normative consistency of brands and the strategic market planning process, (c) pack- age attributes, (d) package usage time, (e) package usage experience, and (f) value added to the course learning expe- rience by the package, simulation, decision support sys- tems, and concepts covered using five-point Likert and/or rating scales. Nine students (53%) of the 17 participants in the course completed the online survey. Seven (7) of these 9 students (77.8%) used the package four or more times. The remaining 2 students (22.2%) used the package once (see Figure 13). All 9 students agreed (3 strongly agreed and 6 agreed) that the package helped them to identify SBUs (brands) that were inconsistent with their normative posi- tion (recommended strategy) on the GGM (see Figure 14). In addition, 7 students agreed that the package prompt- ed them to understand the reasons why the SBU position on the GGM was inconsistent with its normative position (3 students strongly agreed (33.3%), 4 students agreed (44.4%), and the remaining 2 students were neutral (22.2%) (see Figure 15). Further, 8 students agreed that the package helped io identify competitor SBUS that were inconsistent with their normative position on the GGM (3 students strongly agreed, 5 students agreed, and one student skipped the question) (see Figure 16). Students rated the degree to which the NPB & Trends Package improved their awareness of (a) the normative consistency of their brand positions, (b) the underlying reasons, (c) the normative consistency of competitor brands, and (d) the strategic market planning process using a five-point rating scale from 1- Strongly Disagree to 5 - Strongly Agree. The average ratings of 8 students on im- proved awareness and learning are (a) 4.38 for SBU Nor- mative Consistency, (b) 3.50 for potential reasons for in- consistency, (c) 4.25 for Competitor SBU Normative Con- sistency, and (d) 3.88 for Strategic Market Planning Pro- cess (see Figure 17). Next, students rated various attributes of the NPB & Trends Package using a five-point rating scale from 1 – Very Poor to 5 – Very Good. The average ratings of the 8 respondents to this question on rating the attributes of the NPB & Trends Package are 4.38 on Access (Online), 4.50 on Availability (24/7), 4.25 on Flexibility (any team), 4.38 on Auto-extract feature (no data entry), 4.25 on Cell com- ments (explanatory), 4.25 on Detailed results (by SBU by period), 4.13 on Summary overview (by SBU/Year), 3.88 on Ease of use, and 4.00 on Usage time (see Figure 18). Figure 14 Survey Responses – Normative Consistency Identification Page 66 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Figure 15 Survey Responses – Normative Consistency Understanding Figure 16 Survey Responses – Normative Consistency Inferences Page 67 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 The majority of the 8 respondents reported that down- loading the package took 1 minute or less, downloading the simulation results (Excel format) took 2 to 5 minutes, up- dating the package with the simulation results took 1 mi- nute or less, and analyzing the results took 16 or more minutes (see Figure 19). Participants commented on their NPB & Trends Pack- age usage experience and suggest improvements. One stu- dent “liked the usage and the ease of the auto extracts.” Another student commented “It (the package) really helped me to understand how our brands were really positioned, and their movements from year to year.” A third student commented “very easy to use and very helpful. A more clear explanation on the cells would have been helpful.” Yet another student commented “the NPB & Trends Pack- age was incredibly useful, in interpreting the data and could serve as a great tool to not only understand consistency with the Normative Position, but also in analyzing the GGM” (see Figure 20). Then, students rated the value added to their strategic market planning learning experience by various factors such as topic coverage, in-class demo, “Hands-On” ses- sions, and Online access using a five-point rating scale from 1 – No value added to 5 – Significant value added. The average ratings of the 8 respondents on the value add- ed to their strategic market planning learning experience are 3.63 on Topic Coverage, 3.63 on In-Class demo, 3.63 on “Hands On” sessions, and 4.38 on Online access (see Figure 21). Finally, participants rated the value added to the Mar- keting Strategy learning experience by the NPB & Trends Package, the marketing simulation COMPETE, marketing DSS packages, Online PPM Graphics Package, Online PPA Graphics Package, and Online Course Handouts Repository using a five-point rating scale from 1 – No value added to 5 – Significant value added. The average ratings of the 8 respondents on the value added to their Marketing Strategy learning experience are 4.13 on NPB & Trends Package, 4.00 on the marketing simulation COMPETE, 3.13 on mar- keting DSS packages, 4.00 on Online PPM Graphics Pack- age, 4.00 on Online PPA Graphics Package, and 3.00 on Online Course Handouts Repository (see Figure 22). In summary, the participants reported a positive usage, awareness, understanding, usage time and learning experi- Figure 17 Survey Responses – Awareness & Learning Page 68 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Figure 18 Survey Responses – Normative Consistency Package Attributes Page 69 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Figure 19 Survey Responses – Normative Consistency Package Usage Time Page 70 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Figure 20 Survey Responses – Normative Consistency Package Comments Page 71 - Developments in Business Simulation and Experiential Learning, volume 39, 2012 Figure 21 Survey Responses – Strategic Market Planning Learning Experience ence with the NPB & Trends Package. They appreciated the Access, Availability, Flexibility, Auto-extract, detailed results, summary overview, ease of use and minimal usage time attributes of the package. They “liked the usage and ease of the auto extracts,” “enhanced understanding of the position of the SBUs and their movement from year to year,” and commented that the package was “very easy to use and very helpful,” and that “it is a great tool to not only understand consistency with the Normative Position, but also in analyzing the GGM.” They felt that the Topic cov- erage, In-class demo, “Hands On” sessions, and Online access features added substantial value to the strategic mar- ket planning learning experience. In addition, they report- ed that the NPB & Trends Package, the marketing simula- tion COMPETE , marketing DSS packages, and Online PPM and PPA Graphics Packages as well as the Online Course Handouts Repository added value to the Marketing Strategy learning experience. CONCLUSION The Normative Position of Brands & Trends Package is a user-centered learning tool that helps to prepare stu- dents for strategic market planning and marketing decision- making responsibilities in their future careers. The package enables users to apply strategic market planning. They use this package to assess the consistency of the actual position of each SBU in a brand portfolio on the Growth Gain Ma- trix (GGM) with its normative position. This normative position is based on the recommended strategy derived from the position of the SBU on the Growth Share Matrix (GSM). Participants use this package as they check the internal balance of their SBU portfolio, look for trends, and evaluate competitors during the strategic market planning process. Participants apply integrated strategic market plan- ning in order to optimize the performance of their brand portfolio while maintaining cash in balance. 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On the Efficacy of Manage- rial Decision Support Systems in a Business Gaming Environment, Proceedings of the International Simula- tion and Gaming Association, 102-109. Woodruff, C. K. (1992). A Graphics Application Extension For A Simulated Decision Support System Environ- ment. In J. Gosenpud & S. Gold (Eds.), Developments in Business Simulation and Experiential Exercises, Vol. 19, 5-10. Reprinted from Bernie Keys Library (9th ed.)) Table of Contents Volume 39, 2012 Designing the Training Challenge Follow The Leader: Are we Teaching our Students to be Thinkers or Followers? Two Free-Rider-Accepting Methods of Organizing Groups for a Business Game Additional Benefit Through Competency Models Assessing Brand Portfolio Normative Consistency & Trends With The Normative Position of Brands & Trends Package Modeling the Impact of Marketing Mix on the Diffusion of Innovation in the Generalized Bass Model of Firm Demand Play it Forward! The Design and Development of a Forward Contract Simulation Positioning the Company: Increasing Profits in Social Networks Merger of Companies in Business Game Exercise Towards a Knowledge-Based Approach for Autonomouse Trading Agent An Exploratory Study of the Impact of a Simulation Exercise on the Managerial and Personality Traits and the Decision Making Styles of Marketing Students Should the Concept of Potential Customers be the Foundation of Demand Theory in Business Simulations? Teaching Sustainability Experientially Drawing Upon Experience and Research to Improve Future Communications Improving Assessments of Student Learning Outcomes (SLO) Over Time The Effect of Affective Domain Characteristics on Behavioral or Psychomotor Outcomes Gossip? No, Not Me! An Experiential Exercise Student Advisement Using Gantt Charts: An Experiential Exercise in Management Theory Practicing Teachers as Digital Game Creators: A Study of the Design Considerations Designing and Solving Crossword Puzzles: Examining Efficacy in a Classroom Exercise Difficult Times Call for Innovative Measures: Microfinance as Experiential Learning in Higher Education Catalysts, Client Services, and Community Change: Interdisciplinary Collaboration in a Nascent Microfinance Initiative Build A Business . . . In An Hour or Less: Getting Closer to Reality into the Classroom Smart Goals: How the Application of SMART Goals can contribute to achievement of Student Learning Outcomes The Use of Data in "Live" Cases to Encourage Systems Thinking and Integrative Analysis: An Exercise Linking Human Resource Programs and Financial Outcomes in Real Organizations Experiential Education as a Process of Changing Mental Frames by Inducing Insight Learning Process and Content Integration in an Experiential Learning Guided Internship Program Good-bye Discussion Thread: Creating a Community of Inquiry in an Online Master's Program Fiction as a Constructivist Tool for Learning Process Consultation in an Online Environment: Shaping the Context, Introducing the Dialogue Can Simulations Provide a Better Experience? A Capstone Application Modeling a Modest Proposal for Increasing the Efficiency of Academic Reserarch Dissemination Experience GEO: A Massively Multiplayer Game SysTeamsGames Three Games for Management Simulation SimVenture - A Start-Up Business Simulation Stellarbucks Simulation Developing Games Using Strategy Maps and Balanced Scorecards Strategy Dynamics Models - Powerful But Simple In-Class Games Simulating Scenarios for Financial Statement Analysis A Valuation Model of the Simulated Firm Writing the Land: An Interdisciplinary Experiential Approach On the Estimation of the Probability of Meeting Financial Commitments: A Behavioraial Finance Perspective Using Business Simulations