Spend AnalyticsUnderstanding Your Company’s Spend

Presented by David Arleth and Thomas Housley

May 8th, 2008

Uses of Spend Analytics

• Comparison Benchmarking Compare annual expenditures Benchmark intra-company spend

• Compliance Reporting Identify rogue purchasing Aggregate spend

• Savings Analysis Prioritize sourcing events Set realistic targets

• Budget Decision-making Begin best-in-class discussion Strategize cuts in expenditure

Categorization

Categorize unknown

suppliers Gain insight into spend

3

Sample Spend Analysis / Opportunity Identification Timeline

Opportunity Identification

• Review data with Sourcing and commodity specialists

• Develop sourcing hypotheses for priority categories

• Interview key stakeholders, as appropriate

• Develop estimated savings opportunity based on market knowledge, category expertise, and database benchmarks

• Finalize commodity sourcing strategies & economic opportunities

• Present initial recommendations for sourcing plan

Savings Estimates

Data Cleaningand

Categorization

Data Validation

Finalize Spend Categorization

• Receive fiscal year A/P data

• Validate data structure and fields

• Cleanse and categorize data

• Map categories to schema (UNSPSC, etc.)

• Validate and refine the initial categorization output

• Present initial categorization and review and refine for relevancy

• Re-categorize select suppliers and commodity classifications based on modifications provided by category owners

• Develop electronic format that allows for dynamic review and manipulation of the categorization

• Present refined categorization to core team

6 - 8 week plan from time of data receipt

Actual time may vary depending on corporate spend size and complexity

Apply Savings Estimates

Svgs (%) Svgs ($)

Category Subcategory $MM Address Low High Low High

Direct MaterialsComponents 30 0% 0

0% 0% 0.0 0.0Rubber 20 0% 0

Government Taxes 30 0% 0 0% 0% 0.0 0.0

MarketingCreative Agency 20 90% 18

8% 13% 2.2 3.5Commercial Print 10 90% 9

Logistics

Truckload 10 80% 8

3% 8% 0.4 0.9Ocean 10 80% 8

Small Parcel 5 90% 5

Organizations Clubs 20 0% 0 0% 0% 0.0 0.0

IT Products / Services

Telecom 10 100% 10 8% 13% 0.7 1.2

IT Hardware 5 80% 46% 12% 0.5 1.1

Document Output 5 80% 4

MachineryDies / Cutting 7 90% 6

4% 9% 0.4 1.0Material Handling 5 90% 5

MRO

General Industrial 3 80% 2

5% 9% 0.3 0.5Electrical 2 80% 2

Safety 2 80% 2

TravelAir 3 90% 3

4% 8% 0.2 0.4Hotel 3 80% 2

Total 200 44% 87 6% 10% 5.0 9.0

Spendx Addressability

x Savings

Identified Savings

Monthly Savings

1 2 3 4 5 6 7 8 9 10 11 12

70% 80% 90% 95% 100% Compliance

0.10 0.12 0.13 0.14 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15

Monthly Savings

1 2 3 4 5 6 7 8 9 10 11 12

70% 80% 90% 95% 100% Compliance

0.10 0.12 0.13 0.14 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15

Wave 1Address: $23MMSave: $1.3 – 2.2MM

• Telecom• Truckload• General Industrial Supplies• Electrical Supplies• Safety Supplies

Wave 2Address: $38MMSave: $2.2 – 4.0MM

Month 1 6 12

Realized Savings Timing

• Creative Agency• Ocean Logistics• Document Output• Material Handling Equip• Hotels

• Commercial Print• Dies / Cutting• IT Hardware• Small Parcel• Air Travel

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Monthly Savings

1 2 3 4 5 6 7

70% 80% 90% 95% 100% Compliance

0.10 0.12 0.13 0.14 0.15 0.15 0.15

Wave 3Address: $28MMSave: $1.5 – 2.8

• Savings count 12 months after implementation

• For most categories (particularly spend at facilities), there will be a ramp-up to adoption and compliance for a newly implemented supplier

• Product substitution, testing, etc., may push implementation and adoption beyond the expected timeframe

• Identified Savings x Compliance = Realized Savings

Realized Savings

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Consistent and deliberate reporting of non-compliant spend can result in improved savings realization

Sample Office Supplies Compliance Report

Supplier SpendLost

SavingsCost Center Description

Cost Center Manager

ID TECHNOLOGY INC $12,269.67 $1,944.74 California MFG David Wehner

ID TECHNOLOGY INC $780.93 $123.78 California MFG David Wehner

OFFICE DEPOT #358 $576.78 $91.42 California MFG David Wehner

OFFICE DEPOT #662 $369.58 $58.58 California MFG Rupert Fox

ID TECHNOLOGY INC $345.96 $54.83 Denver DC John Kirk

OFFICE DEPOT #512 $156.64 $24.83 Philadelphia Sales Jennifer Sheff

ID TECHNOLOGY INC $138.61 $21.97 Philadelphia Sales Jennifer Sheff

OFFICE DEPOT #512 $68.91 $10.92 Philadelphia Sales Jennifer Sheff

OFFICE DEPOT #358 $52.58 $8.33 California MFG David Wehner

TUMBLEWEED $43.35 $6.87 IT Douglas Warren

OFFICE DEPOT $32.45 $5.14 IT Scott Ruffin

OFFICE DEPOT #406 $14.99 $2.38 IT Victor Moyer

TOTAL $15,002.99 $2,377.97    

Keys to successful compliance reporting

• Accurate categorizations to ensure rogue vendors don’t slip through the cracks

• Cost Center, end user information integrated into data cubes

• Category savings % information to calculate lost opportunity

• Identify acceptable off-contract vendors

• Senior level support and visibility to put “teeth” into reporting

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Spend analysis can enhance Category Management and Supplier Performance Management

• When used in conjunction with a comprehensive supplier performance management program, spend analysis can yield the following benefits: Provide supplier with visibility into line item data for additional continuous

improvement opportunities (ex. mfg discounts) Provide category manager and supplier with visibility into additional spend

(ex. items to target at the plant level) Depending on availability of data, reports can be generate to share KPI’s

such as lead times, order accuracy, invoice exceptions

• Reduce the number of instances of a supplier name in AP system to streamline invoicing process for suppliers and customer

• Identify areas of concerns through analysis of YOY category spending trends

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Packaging Materials

Chemicals, Gases and Fuels

MRO Supplies

Administrative Products

Information Technology Products

Marketing Services

Building and Facility Services

Industrial Services

Vehicles, Vehicle Acc. and Comp.

Industrial Machinery and Equipment

Administrative Services

Information Technology Services

Building Materials

Eng, Research & Tech Services

Financial and Insurance Services

Lower Spend/Rev Average Higher Spend/Rev

Notes• BIC = Top four ranked companies

• Spend/Revenue used as indicator of rank

• Customer is better than average for 60% of categories

• Customer is below average on mostly Corporate driven categories

• There remains opportunity in deltas from BIC

Best

Partnering with a 3rd party provider allows for insight into best in class performers otherwise unavailable through internal sources

Industry Best In Class

Customer Average

Corporate Category

Sample output of a comprehensive spend benchmark

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Spend Analysis market overview

Three primary paths exist for implementation of a Spend Analysis Solution

Solution Path Advantages Disadvantages

Software Provider: Emptoris, Ketera, Procuri, BIQ, Zycus

• BI Software enables dynamic “drill downs” and manipulate of data

• Solution can be distributed to large user base• SAAS solutions cheaper and easier to

implement• Typically self service: customer categorizes

(control)

• Lack of strong sourcing/category expertise • Hosted solutions are expensive to implement

and maintain• Typically self service: customer categorizes

(time/effort)

Procurement Service Provider: ICG Commerce, Accenture, IBM

• Strong category expertise resulting in more accurate categorizations

• Strong sourcing expertise resulting in improved savings identification and implementation

• Typically more “accepting” of customer specific schemas

• Provider will categorize data with validation from client

• More expensive, as typically part of a larger outsourcing or consulting agreement

• Typically one time events, will need to re-engage provider for refresh if you are not in long term agreement

In house solution: Customer resources

• Can be customized to meet customer’s needs (ERP integration)

• Potentially less expensive depending on IT infrastructure (ex. Oracle APEX platform)

• Very IT extensive• Lack of expertise in spend analytic design

principals (fuzzy matches, auto mapping, data cube development)