Network Modelling & Inventory Optimisation

Transcription

1 Network Modelling & Inventory Optimisation 1

2 Presentation Outline Background About Hastings Deering and our consulting partner CHAINalytics Context The burning platform Scope What was open for consideration Process Optimisation Modelling Outcomes Key findings and future direction Conclusions and questions 2

3 Who is Hastings Deering? Caterpillar dealership for NT, QLD, PNG, Solomon Islands and New Caledonia Established 1932 Wholly owned subsidiary of Sime Darby Berhad - purchased in 1992 Top 5 Caterpillar dealers worldwide Traditional bricks and mortar 3000 employees 23 business service centres across our territories Sell, rent and service caterpillar machines. Parts distribution service for customers across mining, general construction, civil transport and commercial construction, power systems, government, primary industries and marine 3

4 WHO IS CHAINALYTICS? 18 of Gartner s TOP 25 supply chains 49 of TOP 10 TOP 10 TOP 10 the GLOBAL 500 FOOD & BEVERAGE RETAIL HIGH-TECH AMSTERDAM ATLANTA BANGALORE DENVER MILAN MINNEAPOLIS HELSINKI SINGAPORE SYDNEY 9 GLOBAL offices $ 27 BILLION FREIGHT SPEND CAPTURED IN FMIC 66 % WORLD POPULATION REPRESENTED BY SPOKEN LANGUAGES average 17 SUPPLY CHAIN YEARS EXPERIENCE 11 YEARS GREAT SUPPLY CHAIN PARTNER SupplyChainBrain 13 PROS TO KNOW Supply & Demand Chain Executive 2013 Gartner COOLVENDOR in supply chain services 4 Confidential 2015 Chainalytics LLC

5 Current Network Locations Top 6 locations account for 80% of sales revenue QDC 5

6 The Burning Platform $380 COKING COAL (price per tonne*) THERMAL COAL (price per tonne*) $320 $150 $115 $80 $50 $160? $80? 6

7 Working Capital in Play Turns 2.8x with PEX and 4.4x without PEX $93.6M $37.4M $306.9M Average inventory values of parts shipped in last 12 months $213.3M $56.2M $160.8M Average inventory values of parts which were NOT shipped in last 12 months $52.5M *PEX = Parts Exchange Parts (Non-PEX) *PEX Total Average Inventory in Play 7

8 In-scope Operating Cost in Play Logistics cost equating to 8.8% of total parts sales revenue Transport $23.7 M 31% Total Parts Sales Total Logistics Cost Transportation $864.9 M $75.7 M $23.7 M Warehouse Variable, $44.9 M 59% Warehouse Fixed $7.2 M 10% Warehousing Fixed $7.2 M Warehousing Variable $44.9 M Logistics Cost % 8.8% 8

9 Benchmarking To Comparable Supply Chains BEST IN CLASS AVERAGE HD PARTS (CURRENT) Warehouse Costs [1] < 2 % 2-3 % 5.5% Transport Costs [1] < 2 % % 3.5% Inventory Holding Costs [1] < 3% 4-5% 3.6% 1 Inventory Quantity Accuracy in Store > 98% 94-96% 96.5% WACC [1] < 3% 4-5% 3.0% 1 Finished Goods Stock Turns > Supplier In Full [2] > 95% 91-95% 91% 2 Supplier on Time [2] > 95% 91-95% Not Measured Supplier OTIF [2] > 90 % % Not Measured Delivery In Full [3] > 97 % 90-95% 82.1% Delivery On time Percentage [3] > 95 % 90-93% Not Measured DIFOT [3] > 94 % 85-90% Not Measured Notes [1] % of Sales Revenue [2] % By Line [3] % By Line on customers first request [4] Excludes PEX and Reman [A] 12.8% WACC [B] based on customer first request [C] Excludes HD & Reman [D] Cat stock orders Comparison dataset includes 40 supply chains in spare parts and service enterprises 9

10 Study Scope or Charter GOALS AND OBJECTIVES Y1: Develop a lean supply chain model to achieve at least 95% OTIF at the lowest operating cost to Hastings Deering. Y2: Reduce parts inventory holding by $100m Y3: Increase parts sales ~ 5% CONSIDERATION FACTORS AND DRIVERS X1: Order criticality (customer requirements) X2: Machine Type X3: Supply sources (Cat, HD, PEX, Reman, Other) X4: Inventory Turns X5: Warehousing needs X6: Logistics and Transportation costs X7: Product mix X8: Product support and contractual requirements X9: Marketing strategy GEOGRAPHY Australia: Queensland, NT Papua New Guinea Solomon Islands New Caledonia INTERDEPENDENCIES All HDAL facilities All HDAL customers All PNG sites All PNG customers FACILITIES Manhattan scale project HD/Cat Supply Network Review Field Technology & Services work streams PROCESS AND FLOWS Entire HDAL supply chain from QDC / MDC to HDAL customer sites All processes from forecasting to delivery of part(s) to customer NPI process 10

11 Current Material Flows Customer Delivery Material Flows Internal Transfer Material Flows 11

12 Demand and Order Fulfilment Profile Fulfilment Mode Revenue By Order Type 38% 30% 32% Customer Pickup Service Pickup Delivered 12

13 Item Segmentation Pareto behavior is often used to classify items into an ABC designation based on volume. An enhanced approach was used to create the ABC- XYZ matrix adding in a measure of volatility Low frequency, low volume, high variability. Hard to forecast. Neither stock nor forecast Covariance CZ CY BZ BY AZ AY Frequency of use is indicated by the size of the bubble. Med usage, med volume, med variability: collaborative forecasting, potential for differentiated fill rates High frequency, high volume, low variability: expect high forecast accuracy and consistently high fill rates. CX BX AX B items -> A items -> Quantity 13

14 Overall Approach DATA COLLECTION AND VALIDATION 1 + Collection of 12 months data, cleaning, and validating + Operational understanding, and stakeholder interviews 2 BASELINE DEVELOPMENT AND SCENARIOS + Baseline costing (transport, warehousing, inventory) + Develop scenarios to be tested 3 NETWORK OPTIMSATION + Model full list of scenarios, validate, and compare + Shortlist 3 scenarios (1, 2, and 3 hub) for further assessment 4 INVENTORY OPTIMISATION + Multi echelon SKU location level inventory modelling for target fill rates across shortlisted scenarios scenarios 5 IMPLEMENTATION PLAN AND BENEFIT CALCULATION + Developed a four-phase implementation plan + Cross functional team vetted benefit realisation calculation 14

15 Inventory Model Input and Output NETWORK SCENARIO RESULTS Forecast Demand at line level Material Flow Requirement What and Where of Inventory Inventory Optimiser OUTPUT: Average Target Stock by SKU INVENTORY CONTROL PARAMETERS Target Fill Rates by Commodity Group Lot Size and Replenishment Frequency To decide How much Lead Time and Average Delay Item Segmentation 15

16 Scenario Evaluation Rationale Scenarios were scored using three criteria: Logistics Costs, Inventory and Distance to Customer. Higher Score Better alignment with assessment criteria 3.4 Logistics Cost Score 3.2 Work. Capital Score 3.0 Dist. to Cust. Score Current State Optimise Current One-Hub (QDC) Two-Hubs Three-Hubs 16

17 Findings Future State 3 Hubs & Shopfronts 17

18 Benchmarking To Comparable Supply Chains BEST IN CLASS AVERAGE HD PARTS (CURRENT) HD PARTS (POTENTIAL) Warehouse Costs [1] < 2 % 2-3 % 5.5% 4.1% Transport Costs [1] < 2 % % 3.5% 2.6% Inventory Holding Costs [1] < 3% 4-5% 3.6% 1 <3% Inventory Quantity Accuracy in Store > 98% 94-96% 96.5% >98% WACC [1] < 3% 4-5% 3.0% 1 1.2% Finished Goods Stock Turns > Supplier In Full [2] > 95% 91-95% 91% 2 > 95% Supplier on Time [2] > 95% 91-95% Not Measured To Be Measured, >95% Supplier OTIF [2] > 90 % % Not Measured To Be Measured, >90% Delivery In Full [3] > 97 % 90-95% 82.1% Expected >=95% Delivery On time Percentage [3] > 95 % 90-93% Not Measured To Be Measured, >95% DIFOT [3] > 94 % 85-90% Not Measured To Be Measured, >90% Notes [1] % of Sales Revenue [2] % By Line [3] % By Line on customers first request [4] Excludes PEX and Reman [A] 12.8% WACC [B] based on customer first request [C] Excludes HD & Reman [D] Cat stock orders Comparison dataset includes 40 supply chains in spare parts and service enterprises 18

19 Proposed Implementation Timeline PHASE 1 REALIGN INVENTORY IN EXISTING NETWORK, ELIMINATE SLOW MOVING INVENTORY, DEFINE ORDERING POLICY, TRANSPORT RATIONALISATION Mar 17 Jun mths Sep 17 Dec 17 Mar 18 Jun 18 Sep 18 Dec 18 Mar 19 Jun 19 PHASE 2 PHASE 2A SEQ SHOPFRONT CONVERSION PHASE 2B QDC HUB TRANSITION 8-9 mths 8-12 mths PHASE 3 PHASE 3A CQ / NQ SHOPFRONT CONVERSION PHASE 3B MACKAY HUB TRANSITION mths 9-12 mths PHASE 4 PHASE 4A NT SHOPFRONT CONVERSION PHASE 4B DARWIN HUB CONVERSION 6-9 mths 4-6 mths E-COMMERCE INTEGRATED E-COMMERCE / CUSTOMER PORTAL SOLUTION mths 19

20 Conclusion and Summary Establish a clear 'project charter' supported by dedicated resources Be prepared to challenge the 'status quo' with ambitious targets Use of an independent advisor to kept focus on achieving a paradigm shift Integrated review of both supply chain network and inventory Be willing to include third party providers as part of review process Quality data mining and modelling key to identifying investment grade options 20