The Chocolate Company Simulation Report

Strategic Management Accounting (SMA) is the accounting of information that supports long-term organisational performance and strategic decision making. Traditional Accounting is focused on measuring short term financial results. But SMA is both financial and non-financial performance measures that assist organisations to achieve an adequate sustainable competitive advantage (Bhimani et al., 2019).

The simulation from Edumundo Chocolate Company provided a realistic setting in which teams managed a virtual manufacturer competing with other teams in a simulated marketplace. Within the simulation each team was responsible for making strategic decisions (production planning, price decisions, marketing spend and inventory control). Each week, over a four-week period, teams implemented their strategic decisions through a five-round process, whereby results were reflected in financial performance and league ranking.

This report will critically evaluate how the simulation contributed to the students achieving the Strategic Management Accounting module's key learning outcomes. In particular, the report will address the following:

• Demonstrating how organisations implement non-traditional long-term improvements in performance, using techniques for manufacturing businesses.
• Demonstrating how organisations use non-financial performance measurement models for strategic management systems.
• Demonstrating how organisations process quantitative and qualitative data when making strategic decisions.

This report will draw upon simulation outcomes; financial performance measures over time; changes in league ranking; and an individual's reflections on their strategic decision-making.

Financial metrics like profit, revenue, and cost control are the main focus of traditional accounting systems. However, strategic management accounting approaches that prioritize long-term value creation, operational effectiveness, and competitive positioning are becoming more and more common in contemporary organizations (Langfield-Smith et al., 2021).

The Edumundo simulation illustrated a number of unconventional methods for enhancing performance, especially through marketing investment and strategic production planning.

2.1 Strategic Production Planning

Managing production capacity while avoiding excess inventory was one of the simulation's main challenges. The company had a lot of unsold inventory in the early stages of the simulation, which showed ineffective use of production resources. In order to match output with anticipated market demand, the group had to modify production levels in subsequent rounds.

From the standpoint of strategic management accounting, this represents the idea of capacity optimization and lean production, in which businesses aim to reduce waste while producing enough to satisfy demand (Drury, 2018). The team improved inventory turnover and decreased storage costs by modifying production levels in later rounds by analyzing demand trends and inventory data in Excel.

2.2 Pricing Strategy and Market Positioning

Pricing decisions were a major part of the strategy in the simulation. Initially, the company sold chocolate products at a high price, resulting in low product demand and unused inventory. However, in later rounds of the simulation, the group used a more competitive pricing strategy with increased marketing investment to try to boost sales.

This approach uses different pricing strategies to take into account competitors and market demand, which is known as strategic pricing (Kaplan & Atkinson, 2015). By lowering their prices and increasing their promotions, the company was able to increase its sales and be more competitive in the marketplace.

2.3 Marketing Investment and Long-Term Brand Value

Marketing investment was one of the main factors influencing product demand in the simulation. Greater marketing investment increased brand awareness and subsequently increased the amount of chocolate sold.

Strategically, marketing investment is a means of improving long-term performance because it allows customers to build loyalty to the company's brand (Kotler & Keller, 2020). Thus, the simulation showed how long-term success is the result of the strategic nature of investment decisions, rather than short-term financial performance.

Through this simulation, it became clear that manufacturing companies must find the right balance between production efficiency, pricing strategy and marketing investments before they can achieve sustainable improvement in performance.

Modern organizations increasingly use non-financial performance indicators to assess organizational success in addition to financial metrics. According to Kaplan and Norton (1996), these metrics offer information about long-term strategic performance, customer satisfaction, and operational effectiveness.

A number of non-financial performance metrics that affected strategic decision-making were included in the Edumundo simulation.

3.1 Market Share and Competitive Position

Market share, which represents the company's competitive position in relation to other teams in the simulation universe, was a significant non-financial metric.

When the business successfully attracted clients through competitive pricing and marketing investment, its market share grew. Because it represented the company's capacity to successfully compete in the market, this metric offered a more comprehensive view of performance than just financial profit.

Market share is a key performance indicator in the customer perspective, which emphasizes competitive positioning and customer satisfaction, according to the Balanced Scorecard framework (Kaplan and Norton, 1996).

3.2 Inventory Management Efficiency

Another critical non-financial performance indicator was inventory control. Having excess inventory during the initial rounds of this simulation was indicative of poor demand forecasting and inefficient planning of production. By analysing sales revenue and adjusting production levels, the group was able to improve on their inventory control efficiencies in subsequent rounds. Proper inventory control is critical to operational performance and supply chain efficiency (Heizer et al., 2020). Additionally, decreasing inventory levels also positively impacts the overall financial performance of a business by minimising storage costs and avoiding product obsolescence.

3.3 League Table Position

The league table ranking system used in the simulation allowed teams to compare their performance with those of their competing teams in the league, where their league positions would act as strategic benchmarks for guiding other teams to continue improving their performance relative to competitors. Many people in management theorise that benchmarking is one way in which businesses use strategy to identify other successful businesses and enhance their operational performance (Horngren et al., 2018); therefore, each group's league table ranking is one metric of their overall competitiveness in the simulation.

In summary, non-financial measures of performance are essential to providing a more complete assessment of organizational performance when combined with traditional business operating metrics (financially based).

4.1 Quantitative Data Analysis

The simulation relied heavily upon quantitative data to inform and support critical strategic decisions. The financial results accumulated from 2026 through to 2030 contain significant trends and implications for decision-making. Between these years, total assets rose from £3,500,775 in 2026 to £6,012,362 in 2029 due to the large investment into buildings, machinery and inventory, then fell to £5,388,267 in 2030. As such, this indicates an inefficiency in the way the assets were utilised.

Despite the growth in total assets, financial performance has decreased significantly. Equity showed a sizeable drop over the period from £1,268,145 in 2026 to £2,440,382 in 2030, indicating accumulated losses and an extreme lack of profitability. Furthermore, bank debts accrued from £0 in 2026 to £5,835,741 in 2030. This shows how dependent the company is on external financing due to the lack of cash produced.

By looking at the inventory levels, once again, there is sufficient evidence that there were poor forecasting decisions made. Finished goods were £413,071 in 2026 and in 2029 the value of finished goods was £1,931,531, creating excess finished goods in relation to demand. Although inventories reduced in 2030, they remained high, indicating a lack of efficiency still exists. The aforementioned trend analysis clearly illustrates that while there were a great deal of quantitative data available, none were utilised efficiently in order to match production, pricing and demand (Drury, 2018).

4.2 Qualitative Data and Strategic Judgement

In the decision-making process, qualitative elements were just as vital as quantitative factors. The team needed to evaluate their competitors' actions on price, how consumers responded within their competitive environment, and how the marketplace was currently operating to formulate the best strategies for price and marketing. For instance, if competitors cut prices, this would require a change in strategy; however, slow responses to this competitor action resulted in both lower sales and higher inventory than anticipated during early periods.

Additionally, the manner in which customers perceive the brand affects overall business results and also plays a part in brand positioning. While spending more on marketing creates better brand awareness for consumers, this does not guarantee sustained profitability; therefore, there is evidence to show a misalignment of tactical and strategic marketing methods. One of the major components of good decision making was being able to understand customer behaviour related to price and promotion, data that cannot be measured financially alone (Kotler & Keller, 2020).

The simulation also carried with it uncertainty, and thus, managerial judgment was needed for many of the decisions made, including total marketing expense and price adjustments; these decisions were based on interpretation of the market signals, rather than being solely based on traditional financial reports. Thus, the combination of qualitative and quantitative data is very valuable to the practice of strategic management accounting (Langfield-Smith et al., 2021).

4.3 Decision-Making in a Competitive Environment

A competitive simulation environment demands a level of continual strategic adaptability. Each firm had its performance impacted not only by its internal organisational decisions but also by the decisions of its competitors (i.e., external influences). The constant struggle to keep up with competitors is evidenced by the continued increase in liabilities and the negative equity position of the firm.

In order to make effective decisions, production, pricing, and marketing strategies need to be integrated. Misalignment among these three strategies can create inefficiencies and lead to problems such as overproduction and increasing levels of debt. For example, the company increased its production levels without having sufficient demand, resulting in excessive levels of inventory; similarly, delayed adjustments in pricing led to a market share reduction.

From a strategic perspective, companies must react quickly to changes in the market and the actions taken by their competitors. The simulation shows that firms able to adapt continuously by using both financial data and market information are the firms that will be most successful; and when firms fail to do this (cases such as this example), they will continue to face declining results and financial instability (Kaplan & Norton, 1996).

Effective teamwork and cooperation among group members were required because of the simulation. Every member contributed to assessing data, strategizing, and deciding jointly during the weekly rounds of the simulation. A key strength of the group was their efficiency in handling and splitting tasks amongst members. Some members specialised in financial analysis while others tracked their data in Microsoft® Excel, and some members assessed marketing strategies and how the competition performed. By having designated responsibilities, the group improved their ability to make timely decisions for all components of the simulation without neglecting any components.

Group discussions on the results of the previous round of the simulation allowed members appropriate time to review the effectiveness of each previous decision and identify any possible improvements for the results they would generate in the next round of the simulation. By utilising this reflective technique, the group was able to learn from failures in achieving desired outcomes in past rounds and thus improve their performance over time.

In addition to areas of strength, the group faced challenges in completing goals and objectives. One of the challenges was to schedule time to meet with other group members as a result of different academic schedules and commitments. As a result of the limited availability of group members, some decisions were made in haste with little opportunity to discuss the matter.

Another example of a challenge the group encountered was correct interpretation of simulation data. At various times of the simulation, group members miscalculated their understanding of the relationship between production and demand; as a result, in the first few weeks of the simulation, the group did produce more inventory than they could sell.

The simulation could be improved in a number of ways if the group were to repeat it. First, by clearly defining positions like financial analyst, marketing strategist, and operations planner, the team could create a more organized framework for making decisions. Second, the team could use Excel forecasting tools to perform more thorough data analysis and make more precise demand predictions.

Despite these difficulties, the simulation gave participants useful experience in strategic decision-making and cooperative problem-solving in a group setting.

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