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Disney E-Commerce Leverages Business Intelligence to improve Profitability & Carlton Farr Jonathan Shaver

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Scope conference 2010 in Florida, Bill Stankiewicz attended.www.shipperswarehouse.com

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Disney E-Commerce Leverages

Business Intelligence

to improve Profitability

&

Carlton Farr Jonathan Shaver

transportation business intelligence

Disney E-Commerce Case Study | Introduction |

• Disney E-Commerce is a division of Disney Consumer Products business segment of the Walt Disney Company.

• Provides direct to consumer services including:

– Online ordering

– Customer service

– Warehousing and order fulfillment for Disneystore.com

• Corporate offices in Glendale CA

• Fulfillment Facility in Jonesville SC

• A leading logistics and financial services company

– Serves Parcel, LTL, & TL shippers with complex data needs

– Premier provider of shipping data accuracy, visibility and velocity

– Processes 500 Million + transactions

• Headquartered in Chicago IL

• Reduce freight spend 5% - 20%

transportation business intelligence

• Limited link between transportation department and finance

– Finance conducted manual accrual

• Timeliness of data

– Delays in billing information and formatting usefulness

• Comprehensive nature of the data

– Limited detail provided

– Accuracy, including the audit, was in question

• Difficulty conducting analysis on transportation spend

– Limited tools

– Data missing key elements to perform analysis

• No continued process to convert data into useful information tools

Complete Data Capture Tools to Convert Raw Data into Intelligent Output

Disney E-Commerce Case Study | Key Business Challenges |

transportation business intelligence

• Established a singular database of transportation spend and order information relative to transportation

• Created an information link between shipping spend and accounting and finance including a deeper verification of invoice cost accuracy

• Analyzed information to identify KPI’s and opportunities to initiate cost savings

• Implemented beneficial programs for internal financials and their guests

Disney E-Commerce Case Study | Leveraging Business Intelligence |

Aggregate

Aggregates data

from manifesting;

order systems, and

carrier systems

Synchronize data

between Disney

E-Commerce

transportation; finance;

and the carriers

Integrate

transportation costs

back into Accounting

and Financials

Analyze raw data

and transform to

critical enterprise

information

Statistical output that

Enables Disney

E-Commerce

performance

improvements via KPI

Synchronize Integrate Analyze Enable

transportation business intelligence

Disney E-Commerce Case Study | Aggregate |

Aggregate

transportation business intelligence

Disney E-Commerce Case Study |

Aggregate Data from Multiple Sources |

Creates one database of all data relevant to transportation spend

DC Carrier Customer

Manifesting data from distribution systems

Order and Promotional data including units per order

Transit Data from carrier Systems

Billing data via EDI from Carrier Partners

transportation business intelligence

Disney E-Commerce Case Study | Synchronize |

Synchronize

transportation business intelligence

Disney E-Commerce Case Study | Synchronize Shipper & Carrier Data|

Verify all rates, performance, delivery of packages

• Multi-Layer Freight Coding Categories

• Inbound, Outbound, Returns, Vendor Drop Ships

•Comprehensive audit of all shipping transactions

- Non-pay credits with carriers

•Non-paid items applied back at the transaction level for accounting efficiencies

transportation business intelligence

Disney E-Commerce Case Study | Integrate |

Integrate

transportation business intelligence

Disney E-Commerce Case Study | Integrate Freight Data with Finance|

Monthly accrual report produced the 1st of each month

All transactions not billed are accrued at month end

Utilize expected costs as aggregated from the manifest system Is matched against the invoiced transactions

Update systems weekly with appropriate transportation coding

January Fiscal

Year 2008

Accrued

Freight

Billed Not

Submitted

Billed and

Submitted

January Outbound

Freight Total

Freight Dollars 87,134.62$ 285,696.84$ 928,455.03$ 1,301,286.49$

Package Count 10,309 34,490 112,074 156,873

transportation business intelligence

Disney E-Commerce Case Study | Analyze |

Analyze

transportation business intelligence

• Monthly KPI (Key Performance Indicator) Reports provide high level tracking of transportation performance

• Return on Investment tracking of key initiatives

– Address Hygiene software impact on address correction and delivery performance

– Invoice verification and settlement metrics

– Key lane analysis on cost and performance puts Disney E-commerce in an improved position to evaluate parcel alternative programs; including hub drop shipping; consolidator programs

• Expected cost of shipping vs. Actual Billed Cost at a unit number level vs. Shipping and Handling charged to Guests

– Determined were undercharging for key International lanes and therefore producing unprofitable customer orders

Disney E-Commerce Case Study | Data Visibility for Analysis |

transportation business intelligence

Disney E-Commerce Case Study | Key Performance Indicator Reports|

Key Performance Indicators make key tracking data transparent and enables them to adjust accordingly

transportation business intelligence

Disney E-Commerce Case Study | Order Cycle Time Management |

2007 2008

Carrier Name Avg Cycle Time Avg Days In Transit Avg Cycle Time Avg Days In Transit

XXX 5.68 3.66 4.69 4.05

XXX 4.36 3.21 3.80 3.34

XXX 4.81 3.08 1.50 4.50

XXX 3.57 1.94 6.11 2.56

XXX 5.01 3.54 4.99 3.90

XXX 1.71 1.04 2.67 1.14

XXX 5.78 3.06 3.31 3.03

XXX 4.93 2.52 2.79 1.85

Grand Total 5.76 3.06 3.31 3.03

69% Decrease in Cycle Time

43% Decrease in Cycle Time 26% Decrease in Transit Time

Sample Data

transportation business intelligence

Disney E-Commerce Case Study | Return on Investment |

Address Hygiene impacts delivery performance

Audit verification to payment

100% EDI billingBills September November December

Processed 202,308 218,873 490,995

EDI 202,308 218,854 490,995

Paper 0 2 0

On Hold 0 0 0

Submitted to DSI 202,308 218,873 490,995

October

0

235,412

235,412

235,412

0

Aging Invoice Tracking

Total Dollars Savings

$8,135,053.18 2,102.80$

Address Hygiene

$13,040.00 0.30% 0.34%

Address Fee Dollars

(new)

Address Fee Ratio

(new)

Address Fee Ratio

(old)

XXX Shipping Credits 143,519.57$

XXX Void Credits 1,474.51$

Total 144,994.08$

IntraVex Cost (33,545.33)$

NET SAVINGS 111,448.75$

Savings YTD

transportation business intelligence

Disney E-Commerce Case Study | Budget Tracking |

transportation business intelligence

Disney E-Commerce Case Study | Customized Data Reports |

Transportation Analysis – from high level to package detail

Packages 2,242,742

Weight 50,536,671

Gross Freight 29,008,389.47$

Discount $ (10,456,472.99)$

Discount % 36%

Net Freight 18,551,916.48$

Total Net Charge 23,982,465.82$

Year to Date Summary

Average Total Discount

Average Shipment Total Net Charge

$22.80

36.05%

Average Days In Transit2.97

$10.82

Average Weight per Package

Sam

ple

Dat

a

Sample Data

transportation business intelligence

Disney E-Commerce Case Study | Enable |

Enable

transportation business intelligence

• Key savings areas

– Advanced audit and verification findings

– Key returns for address corrections

– Analysis on USPS residential / commercial verification vs. carrier billed

– Person hours associated with accuracy of information,

accrual report preparation, and transportation analysis

• Access to key cost-drivers identifying opportunities to reduce accessorial fee and adjustments

• Cost vs. Delivery analysis to make correct decisions for Guests

• Information to modify contracts and programs for rate analysis as needed

• Information to plan, budget, and make the right transportation decisions

Disney E-Commerce Case Study | Enable Cost Savings |

transportation business intelligence

Disney E-Commerce Case Study | Non-Disney E-Commerce Analysis |

Non-Disney E-Commerce

Analysis

transportation business intelligence

Disney E-Commerce Case Study | Enabling Deeper Analysis |

Div

isio

n 1

Div

isio

n 2

Div

isio

n 3

Div

isio

n 4

Div

isio

n 5

Div

isio

n 6

Div

isio

n 8

Int.

Div

isio

n

Gra

nd Tota

l

Freight Pct of Sales 2.94% 5.06% 2.29% 1.39% 2.92% 2.33% 6.64% 1.63% 1.71%

Sales Order Amt 856,952$ 860,626$ 8,468,933$ 70,400,862$ 7,885,091$ 2,328,878$ 437,610$ 1,254,639$ 92,493,591$

Total Net Charge 25,278$ 43,577$ 194,114$ 984,663$ 230,361$ 54,378$ 29,086$ 20,566$ 1,582,023$

Shipments 2,212 2,626 28,660 115,908 33,929 5,499 3,375 1 192,210

Packages 2,953 3,961 29,628 126,229 35,656 6,678 3,996 1 209,101

Weight 25,662 80,073 339,256 1,462,514 151,220 82,651 31,854 3 2,173,232

Avg Weight 12.18 32.02 12.43 13.25 4.68 15.78 9.91 3.15 11.87188826

Freight Charge Per Pound 0.88$ 0.50$ 0.55$ 0.58$ 1.35$ 0.59$ 0.83$ 6,636.07$ 0.64$

Rebate Amt (1,707)$ (2,820)$ (18,744)$ (85,254)$ (27,361)$ (5,014)$ (3,358)$ (0)$ (144,258.50)$

Sample Data

transportation business intelligence

Disney E-Commerce Case Study | Rebate Calculations & Accrual |

• Provides information to verify rebate checks and tier calculations

• Rebate checks can be accrued monthly, but applied quarterly / annually as submitted by the carrier

January Fiscal Year 2008

Accrued

Freight

Billed Not

Submitted

Billed and

Submitted

Expected Rebate

Check Amount

January Outbound

Freight Total

Freight Dollars 87,134.62$ 285,696.84$ 928,455.03$ 118,757.52$ 1,182,528.97$

Package Count 10,309 34,490 112,074 - 156,873

Accounting Period January

Monthly Gross Revenue

Tier 2,567,283.71

Amount Used to Calculate

Incentive Check 2,375,150.41

Incentive % 5%

Incentive Check 118,757.52$

Calculate parcel carrier revenue tiers and rebate amounts

Sample Data

Sample Data

transportation business intelligence

Disney E-Commerce Case Study | Key Take Away |

Complete data capture Tools to convert raw data into intelligent output

• Link transportation and finance departments via data

• Leverage data to structure contracts and programs to mitigate cost increases

• Create a database that houses key performance data as it relates to transportation

• Understand expected vs. actual costs vs. customer shipping and handling

• Delivery performance to customers