MAN6927 Supply Chain Analytics Assignment 3: Personal Learning Portfolio

MAN6927 SUPPLY CHAIN ANALYTICS
ASSIGNMENT 3: PERSONAL LEARNING PORTFOLIO


Problem 1: Transportation Network Planning
Optimal shipment plan

Fig 1: Optimal shipment plan
The optimisation allocates production across five plants to minimise logistics cost while meeting demand. Each plant supplies specific regions within its capacity. Total variable transport cost is AUD 192,900, and total cost is AUD 323,900, representing the lowest feasible system cost.
WA, VIC & NSW single-plant rule
With the single-plant supply rule, WA remains supplied only at P1, VIC at P5 and NSW at P4 because this is the route that minimises the cost subject to the constraint. Limiting such markets to a single plant, however, raises the overall supply chain cost since the company is unable to distribute shipments flexibly to pursue less expensive alternatives to other markets.

Changed Tasmania & Asia demand, and one plant shutdown.

Fig 2: Changed Tasmania & Asia demand
Plant P3 is optimal to close due to lower capacity and higher transport costs; demand is redistributed, increasing total cost to AUD 310,200.
Asia is served only by P4 & P5.

Fig 3: Asia is served only by P4 & P5
As long as Asia is limited to P4 and P5, the best strategy would be to use all the 1,900 Asia units in P5 because it will incur the lowest transport cost (AUD 16). The base case is unchanged in all other market allocations. The cost of transport is marginally higher at AUD 193,200, and the overall cost to AUD 324200 (an increase of just AUD 300). The effect is not so much since P5 has been serving Asia effectively.
P1 is limited to 2500 units.

Fig 4: P1 limited to 2500 units
At the 2,500 limits of Plant P1, the leftover WAS will go to P4 and P5 and incur higher costs of transport. Total cost increases to AUD 329,800; the limited capacity hurts supply efficiency.
Feasibility: average transport cost ? 13.5

The average transport cost of AUD 13.5 per unit is unfeasible, remaining slightly above this figure for deliveries to eastern Australian markets. Given fixed plant capacities and geography, reducing costs would require additional capacity or new distribution points.

Problem 2: Demand Forecasting
Deseasonalisation

Fig 5: Deseasonalisation
Deseasonalisation removes seasonal fluctuations to reveal true construction trends. By dividing actual values by seasonal indices, results show a clear long-term decline from 20122020, followed by gradual recovery after 2021.
Holts Linear Smoothing Forecast

Fig 6: Holts Linear Smoothing Forecast
The method used by Holt models both the level and trend without the seasonal adjustment. The forecast using smoothing parameters ?=0.25 and ?=0.15 in the year 2024 is increasing steadily, with an initial value of about 8239 in Q1 to 9512 in Q4. This is an indication of the ongoing post-pandemic recovery trend and a slowly recovering construction industry.
HoltWinters Forecast (? = 0.25, ? = 0.15, ? = 0.25)

Fig 7: HoltWinters Forecast ?=0.25, ?=0.15, and ?=0.25
The Holt-Winters multiplicative model uses trend and seasonality. Using ?=0.25, ?=0.15, and ?=0.25, seasonal demand peaks and troughs are captured in the forecast. According to the analysis, the result shows a gradual increase after 2024 - the rates approach approximately 8385 in Q1 and approximately 10016 in Q4, which can be attributed to the further increase in the construction cycle because of the existence of seasonal recovery factors.

Compare models
Table 1: Evaluation metrics
Metric Value
MAD (Mean Absolute Deviation) 953.22
MSE (Mean Squared Error) 1,585,818.72
MAPE (Mean Absolute Percentage Error) 0.1425 (14.25%)

Holt-Winters is a better forecast for Western Australia since it includes both trend and seasonality. Although Holt captures the trend, it does not take into account the seasonal trends, so Holt-Winters is smoother and can be relied on in terms of planning.
Spike Scenario Explanation

Fig 8: Spike Scenario Explanation
Substituting with the original September 2017 spike inflates both the Holt and the Holt-Winters forecasts, and increases trend and 2024 estimates unnaturally. Holt-Winters demonstrates a greater seasonal uplift, which demonstrates the distortion of smoothing models and bad planning by extreme outliers.
10% stimulus adjustment

Fig 9: 10?pacity Stimulus Adjustment
A 10% rise in Holt-Winters in the predictive forecast of 2024 implies an increased level of construction work, which will reach a peak in the fourth quarter, in which additional labour, material, and equipment planning will be needed due to an increase in demand.

Problem 3: MoonChem Delivery Strategy
Current Full-Truckload Cost

Fig 10: Current Full-Truckload Cost
The current plan used by MoonChem makes one truckload delivery per customer every month as a means to replenish consignment inventory. It means that there will be 12 deliveries per customer in a year, which causes high costs of transport, except for handling, due to a lack of consolidation of trucks. The high frequency of fine, frequent shipments in the annual cost indicates greater ordering costs and a higher cycle inventory, resulting in the policy not being efficient in terms of the demand size.
Evaluation of delivery alternatives

The analysis of delivery methods demonstrates that centralising shipments and lowering the frequency of delivery will result in an impressive reduction in the overall logistics expense. Compared to the full-truck policy, shared-truck or scheduled-delivery models will lower the ordering costs and inventory turnover (Sneps-Sneppe, 2023). By optimising the truck size with the real demand, MoonChem will be able to achieve greater replenishment, less idle capacity and better cost of distribution.
Recommendation

Rather than shipping individual complete truckloads, MoonChem ought to implement a consolidated scheduled-delivery plan. Due to the tiny, consistent demand from customers, vehicles are now underutilised and prices are high. Consolidated routing reduces transportation costs, increases truck utilisation, and ensures a steady supply. This strategy promotes effective supply chain planning and service consistency while better balancing transportation and holding expenses.
Impact on consignment inventory

With consolidated deliveries, consignment inventory increases slightly because shipments are less frequent, raising average cycle stock at customer sites. However, this increase is small and offset by substantial transportation cost savings. Inventory remains adequate to prevent stockouts, and scheduled deliveries enhance predictability. Overall, the strategy reduces total logistics cost while keeping customer service and product availability high.
Problem 4: Polaris Industries
Introduction
Polaris Industries compares world manufacturing and sourcing decisions to balance the cost, quality and responsiveness of the supply chain. It also outsources most of the components, but final assembly is done in-house to safeguard quality and brand image. This case discusses location decisions, cost models, exchange-rate risks and labour trends to find out the most economically efficient and most prudent manufacturing base.
Analysis

Fig 11: Current Full-Truckload Cost
This table involves a comparison of the 5-year labour, production, transport, and tariff costs of Polaris in the U.S., Mexico, and China to calculate Net Present Value. The outcomes indicate that the U.S. has the lowest total cost (the highest NPV savings ($12.7M) and, thus, is the most economical location to be compared with Mexico and China.
1) Outsource Components, In-Source Assembly
Polaris outsources to its suppliers to lower the production cost and to utilise the expertise of the suppliers. Last manufacturing is retained in-house to control quality, secure intellectual property, and have the flexibility to manufacture products of various types and to customise to particular requirements.
2) Lowest-Cost Manufacturing Location
According to the NPV analysis, the United States offers the highest cost savings ($12.7M), compared to Mexico and China, because labour costs are stable, tariffs are lower, and logistics are efficient (Shou, 2022)
3) Exchange-Rate Sensitivity
A change of 15 per cent in the exchange rate would make a difference to Mexico and China. Nonetheless, the U.S. is most cost-efficient, such that the recommendation does not change with changes in the exchange rates.
4) Labour Increase in Mexico
Assuming that the labour in Mexico rises by 20 per cent per year, then the cost advantage of Mexico will be lost very fast, and therefore, Mexico would be less competitive. Therefore, the U.S. has stayed put since the labour escalation reinforces its stand.
5) Additional Factors
Supply-chain risk, trade policies, lead times, logistics reliability, quality control capability, workforce skills, currency stability and geopolitical factors are the trends that Polaris must take into account when making the final decision about the location of manufacturing.

Problem 5: Qantas Revenue Management
Effectiveness of Qantas Strategy (20242025)
The 2024-2025 strategy of Qantas is shown to have great financial recovery and the ability to discipline itself after the pandemic disruptions. The airline had preferred profitable route reinstatements as opposed to the speedy capacity enlargements, and this helped maintain high yields within the domestic and overseas routes. In the domestic market, Qantas leveraged two-brand positioning (Qantas + Jetstar) to retain market share on core business routes, including SydneyMelbourneBrisbane, and enhance the profit margin performance as well as secure premium demand. Long-haul reinstatement and up-gauging on the most profitable routes (Sydney-London and Melbourne-Los Angeles) were gradual internationally, to capitalise on high global travel demand and competitor capacity constraints (O'Connell, 2025).
The renewal of the fleet and the reactivation of the A380 and Boeing 787 increased seat economics, whereas Project Sunrise is an indicator of long-term competitiveness in the ultra-long-haul travel. Also, the Qantas Loyalty was one of the largest sources of earnings, and was supported by high membership development, retail relationships and growth in non-air revenues.
Nonetheless, brand trust was influenced by reputational issues and regulatory oversight. Goodwill was damaged by customer dissatisfaction, service reliability concerns, and credit handling and pricing practice investigations by ACCC (Heiets et al., 2021). Also, a challenge with the execution was the rising operational costs, supply chain delays, fuel volatility and labour market constraints. As a whole, although Qantas has made effective steps to recover its profitability and positioning, to be successful over the long run, it needs to enhance service quality, regain brand confidence and maintain a disciplined approach to cost labour and fleet management so that it can have a sustainable competitive advantage.
Recommended Revenue Management Strategies
To enhance performance in 2024-2025, Qantas would be recommended to implement data-driven revenue management approaches, which would enhance pricing accuracy, monetisation of loyalty and capacity efficiency (Wittmer & Bieger, 2021). To start, the introduction of sophisticated AI-powered dynamic pricing can be used to rationalise the fare rates based on dynamic real-time demand prediction, competitive fare scraping, seasonality, and willingness-to-pay indicator by customers. This will minimise discount leakage and maximise premium cabin yields, especially in the business routes and long-haul routes.
Second, the focus of loyalty yield optimisation needs to be changed to spend-based tier progression, specific reward availability, and the personalised offer based on behavioural data. High-value customer retention and non-ticket revenues can be boosted by improving the Qantas Frequent Flyer shopping partnerships, SME loyalty incentives and premium-tier privileges (Zhang et al., 2021).
Third, optimisation of capacity through the origin-destination modelling, aircraft up-gauging of high-demand routes, and flexibility of frequencies during off-peak time can help increase load factors and decrease the cost per seat. Supply chain and fleet risks are also reduced through wet-lease capacity buffers and strategic alliances (e.g., Emirates, Oneworld).
Fourth, enhance supplementary products, including paid seat upgrades, fast-track services, in-app convenience packages, travel packages, and carbon-offset subscriptions (Zhao & Chen, 2024). Lastly, enhancing network responsiveness, such as regular schedule reviews, tactical promotions, and moving cabins around, will make the network responsive in a competitive context. The combination of these strategies will make the company more profitable, valued by customers and more resilient in the changing aviation market.

References

Heiets, I., Oleshko, T., & Leshchinsky, O. (2021). Airline-within-Airline business model and strategy: case study of Qantas Group. Transportation Research Procedia, 56, 96-109. https://www.sciencedirect.com/science/article/pii/S2352146521006396
O'Connell, J. F. (2025). The Airline IndustryA Comprehensive Overview: Dynamic Trends and Transformations. https://books.google.com/books?hl=en&lr=&id=9HeNEQAAQBAJ&oi=fnd&pg=PT11&dq=2024-2025+strategy+of+Qantas+is+shown+to+have+great+financial+recovery+and+the+ability&ots=EtJqr54jCL&sig=7ptBTr4oX-269nfU9bBkff7FDwU
Shou, T. (2022, July). A literature review on the net present value (NPV) valuation method. In 2022 2nd International Conference on Enterprise Management and Economic Development (ICEMED 2022) (pp. 826-830). Atlantis Press. https://www.atlantis-press.com/proceedings/icemed-22/125975449
Sneps-Sneppe, M. (2023, May). Use of the criteria NPV and IRR for choosing among investment projects. In 22nd International Scientific Conference Engineering for Rural Development Proceedings (pp. 745-750). https://www.iitf.lbtu.lv/conference/proceedings2023/Papers/TF146.pdf
Wittmer, A., & Bieger, T. (2021). Airline StrategyFrom Network Management to Business Models. In Aviation Systems: Management of the Integrated Aviation Value Chain (pp. 139-184). Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007/978-3-030-79549-8_5

Zhang, G., Law, C. C., Zhang, Y., & Yang, H. (2021). Price discrimination and yield management in the airline industry. https://research.usq.edu.au/item/q6689/price-discrimination-and-yield-management-in-the-airline-industry
Zhao, J., & Chen, Y. (2024). Strengths and Weaknesses of Qantas's Flight Network. International Journal of Management Science Research, 7(1), 9-15.