You have been employed to investigate ways of tracking energy consumption of the firm’s petrol and diesel cars

Assignment Brief

Part of your investigation could be in the form of forecasting the increase in demand for electric cars over the next 10 years by looking at trends in the UK and overseas. You have been employed to investigate ways of tracking energy consumption of the firm’s petrol and diesel cars

Word count: 1500 Max

1. Title and contents page
2. You have been employed to investigate ways of tracking energy consumption of the firm’s petrol and diesel cars
3. Introduce your area of research and show your methodology
4. Forecast the impact on energy consumption of switching to producing electric cars
5. How statistical analysis might be used to assist the company’s decision making and how statistical data might benefit the organisation
6. Outline the two analytical techniques you will use and why they are best for your report ( time series analysis, index numbers)
7. Provide good graphs of your analysis, and a summary of the calculations and formulae utilised
8. Provide excel worksheets (good presentation in terms of formatting and annotation will be rewarded), that you have developed, which should contain the raw data that you used in your calculations, the graphs and formulae.
9. Explanations of your calculations
10. Provide appropriate evidence of your sources, cited and referenced in Harvard format
11. Have suitable conclusions

Sample Answer

Investigating Energy Consumption and Forecasting the Impact of Electric Vehicle Transition

Contents Page

1. Introduction

2. Research Methodology

3. Forecasting the Impact of Switching to Electric Cars

4. Use of Statistical Analysis in Decision-Making

5. Analytical Techniques Used

6. Summary of Formulae and Calculations

7. Conclusion

8. References

1. Introduction

The transportation industry is under increasing pressure to reduce carbon emissions and shift towards more sustainable energy sources. Petrol and diesel vehicles contribute significantly to global CO₂ emissions. As electric vehicle (EV) technology matures, many car manufacturers are transitioning towards cleaner alternatives. This report investigates the current energy consumption of a firm’s petrol and diesel fleet and forecasts the energy impact of moving to EV production over the next ten years.

2. Research Methodology

The research used a combination of secondary data from government reports, industry publications, and manufacturer specifications to understand fuel consumption trends and predict future demand. The investigation also included statistical forecasting methods—specifically time series analysis and index numbers, to track energy consumption patterns and future shifts due to electrification. Data on fuel economy, mileage, EV growth projections, and energy conversion were compiled into Microsoft Excel for analysis and graphical presentation.

3. Forecasting the Impact of Switching to Electric Cars

By switching to electric vehicles, the firm can expect a major change in how energy is consumed. While petrol and diesel cars consume fossil fuels and emit carbon, EVs use electricity, ideally from renewable sources. Based on recent UK trends, EV registrations are growing rapidly, with over 50% of new car sales expected to be electric by 2035 (SMMT, 2024).

By applying average mileage (e.g., 12,000 miles per vehicle annually) and converting fuel usage (litres/year) to energy units (kWh/year), we estimate that total energy usage will decline significantly due to the higher efficiency of EVs, roughly 3 miles per kWh compared to 0.35 kWh/mile for petrol vehicles. The forecast suggests a 30–40% decrease in total energy consumption over the next 10 years if the fleet transitions to electric vehicles.

4. Use of Statistical Analysis in Decision-Making

Statistical analysis helps firms make data-driven decisions, reduce uncertainty, and allocate resources more efficiently. In this case, forecasting demand and tracking consumption helps the company:

• Understand future infrastructure needs (charging stations, grid upgrades)

• Monitor energy savings and emissions reductions

• Justify investment decisions and attract sustainability-focused investors

Data analytics also allow companies to simulate scenarios, compare options, and test policy outcomes before making large-scale changes.

Continued...