Group: RA2P1. Pitinun Srirungruang2. Amonrat Zinthai3. Aditya Mahardhika Yustika Putra4. Koganti Rishi Kumar

AgendaAgenda

• Company Background• Analysis• Inventory Strategy• Service Strategy• Investment Strategy

Company BackgroundCompany Background

• MRS MAC’S is Australian Company• Product

– savory pie and pastry

• Head Quarter– In Perth and Western Australia

• Export– New Zealand, Singapore, and Hong Kong

AnalysisAnalysis

• Problem

• Poor Inventory Management• Poor service• Poor Investment Decision

AnalysisAnalysis

• Solution– Issue with Inventory

• Identified Storage and staging area• New technologies• Process

– The current Service Performance and Scope for Improvement

– Investment Approach

Inventory StrategyInventory Strategy

• Forecasting Demand of Meat Pie

• Total Annual Demand Forecast:

3,791 boxes

Period Months Demand Forecast

Each month

1 January - March 279

2 April - May 318

3 June - July 254

4 September - December 389

Inventory StrategyInventory Strategy

• Causes of Seasonal Demand

• Christmas Time• Weather• School Holiday• Same product but Different brand• Increase of Income Rate• New Flavors

Inventory StrategyInventory Strategy

Input variables  

D - Annual Demand (box) 3,791

Co - Ordering Cost 4,500

Ch - Carrying cost per unit 96

EOQ (Optimal order quantity) 596.16

Minimal Total Cost 57,231

• EOQ model for Mrs Mac’s Distributor

ComparisonComparisonEOQ and Demand ForecastEOQ and Demand Forecast

• Assumption:– Open Monday – Friday– Holiday 10 days per year– 250 days open per year

• Order cycle time:– No. day open per year/ (D/Qopt)

= 250/(3,791/596)

= 39.3 working days– Approximately 2 months

ComparisonComparisonEOQ and Demand ForecastEOQ and Demand Forecast

MonthDemand Forecast

EOQExcessive & Shotage

2 months Sum

Jan – Feb 558 596 38 38

Mar – Apr 597 596 -1 37

May – Jun 572 596 24 61

Jul – Aug 508 596 88 149

Sept – Oct 778 596 -182 -33

Nov - Dec 778 596 -182 -215

3,791 3,576

Inventory StrategyInventory Strategy

• EOQ model for Beef

Discount Category

Unit Cost

Order Quantity

(Q)

Annual Cost

Carrying Ordering Purchase Total

1 5.00 1,600 1,040 5,200 663,425 669,665

2 4.70 40,000 26,000 5,200 623,620 654,820

3 4.30 80,000 52,000 5,200 570,546 627,746

4 3.80 120,000 78,000 5,200 504,203 587,403

Inventory StrategyInventory Strategy

• EOQ model for Flour

Discount Category

Unit Cost

Order Quantity

(Q)

Annual Cost

Carrying Ordering Purchase Total

1 1.20 46,349 9,270 11,124 181,968 202,362

2 1.10 50,000 10,000 10,312 166,804 187,116

3 0.95 100,00 20,000 5,156 144,058 169,214

Inventory StrategyInventory Strategy

• EOQ model for Butter

Discount Category

Unit Cost

Order Quantity

(Q)

Annual Cost

Carrying Ordering Purchase Total

1 1.50 18,749 10,312 15,468 96,671 122,451

2 1.35 30,000 16,500 9,667 87,003 113,171

3 1.25 60,000 33,000 4,834 80,559 118,392

Service StrategyService Strategy

• Approach for Service Improvement– Current Scenario– Various alternatives available– Main focus area according to Iain– Future considerations

Comparison among different Comparison among different solution pathssolution paths

Factor Current Scenario Case 1 Case 2

Po 0.3113 0.0448 0.0157

W 0.0046 0.0333 0.0334

p 0.1620 0.5833 0.8333

Proposed Strategy

• Proposal based on the results of Queuing analysis

• Multichannel (M/M/m)

• Reasons for using this particular strategy

• Possible advantages and forecasts

Investment StrategyInvestment Strategy

Scenario:• Current capacity: 4000 boxes• Initial investment of $50,000.00 for an additional

of 2000 boxes

Question:

“Whether or not to go ahead with the investment?”

SolutionsSolutions

• Perform an investment analysis using NPV simulations approach

• Performing IRR based on NPV results

Model advantagesModel advantages

• The NPV Excel solution identifies all cash flows through the next 6 years of investment.

• The Excel solution for IRR would help the firm to decide which is the most profitable investment.

• Predict the outcome of a decision in the face of uncertainty.

• To assess the probability of a profit and the probability of a loss.

Simulation ResultSimulation Result

NPV Maximum Profit

NPV Under Random Variable

Annual unit sale price trend

10.5% 8% - 10.5%

Annual Sales demand 9.5% 7.5% -9.5%

NPV $ 15,506.81 $ 3,756.10 - $ 8,624.40

IRR 28% 22% - 25%