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Spend DataClassification
-- A Pre-requisite to Spend Analysis for Strategic Sourcing
By: Babhui Lee3rd Nov 2007
2
CONTENT
Introduction – The Need for Spend Data Classification
The Hurdles of Spend Data Classification
Alternative Solutions of Spend Data Classification
Standardization of Spend Data Classification
Implementation of Spend Data Classification
Conclusions & Recommendations
Question & Answer
3
Executive Summary
• Spend data classification results in better spend management, and is a pre-requisite for supply management and business success.
• Sufficient, accurate, and timely insight into corporate spending information is vital to the success in cost reduction.
• Leading spend data management initiatives rely on access to all spend data sources; a common classification schema; category expertise; efficient and repeatable data cleansing and classification capabilities; advanced reporting and decision support tools; and sufficient resources and executive support.
Key Takeaways
The Need For
Spend Data
Classification
5
• How much do we spend?
Can You Answer These Questions?
…inadequate spending analysis capabilities arecosting businesses $260 billion in missedsavings opportunities annually.
Aberdeen Group, “The Spending Analysis Benchmark Report: Dissecting a Corporate Epidemic”,January 2003
• On which products?• From which suppliers?
6
Create governance framework
Align with mission and objectives
Assess risk
Support customer needs
Leverage opportunities
Identify metrics
Determine quality of competition
Implement process, policy & cultural transformation
Develop communication plan & training requirements
Measure & report performance
Leverage supplier relationships
Refine demand planning
Communicate results
Adjust & Re-initiate
Capture, validate corporate-wide spend & suppliers
Segment data
Understand data (who, what, when, where, how, why)
Analyze market
Identify opportunities
Spend Analysis is the first Step to Successful Strategic Sourcing
Spend Analysis & Strategic Sourcing
7
Spend Analysis – 10 Best Practices
Classify spending at a detailed levelClassify spending at a detailed level
Enhance core spend data with vital business
intelligence
Enhance core spend data with vital business
intelligence
Increase frequency and coverage of spending
analysis
Increase frequency and coverage of spending
analysis
Utilize advanced reporting and decision support toolsUtilize advanced reporting and decision support tools
Continuously expand uses and scope of a spend data
management program
Continuously expand uses and scope of a spend data
management program
Access all spend data sources from within and without the
enterprise
Access all spend data sources from within and without the
enterprise
Adopt a common classification schema enterprise-wide
Adopt a common classification schema enterprise-wide
Establish efficient and repeatable data cleansing and
classification capabilities through the use of software or
services
Establish efficient and repeatable data cleansing and
classification capabilities through the use of software or
services
Audit existing spend capabilitiesAudit existing spend capabilities
Augment category expertise to ensure data and classification
accuracy and validation
Augment category expertise to ensure data and classification
accuracy and validation
Best Practices in Spend Analysis, Aberdeen Group, Sep 2004
8
Impacts of Inaccurate Spend Data Classification
Inaccurate Spend Data
Classification
Poor Spend
Management
Sourcing and Supplier
Management
• Lost Leverage on volume buy
• Missed savings from fragmented buy strategy
• Supplier Proliferation
Compliance
• Reduced use of preferred suppliers with contractual terms
• Difficult to enforce supplier compliance to pricing, rebates and volume discount
• Reduced accuracy of financial reporting
Inventory Management
• Excess stock • Redundant Orders • Inventory Depreciation • Increased interest payment• Reduced Cash Flow
Product Management
• Part Proliferation • Limited Part Re-use • Design, Sourcing and
Manufacturing disconnected
91 Average incremental gains achieved by 750+ survey respondents
22%43 days55 daysSourcing cycle time
33%59%44%Contract compliance rates
75%11.7%6.7%Ave. Savings from strategic sourcing
34%62%42%Spend under management
IncrementalGain1
AfterBeforePerformance Area
Source: Aberdeen Group, Aug 2007
Benefits of Better Spend Management
The Hurdles Of
Spend Data
Classification
11
Restricted ROI from Spend Management initiatives
IMPL
ICA
TIO
NS
Implement Category Management
Increase compliance
Enterprise spend visibility and control
Increase eProcurementadoption
Manage Change
Set up best practices
CPO CIOPurchasing IT
Deliver ROI from existing systems
Improve Master/Spend Data quality across Multiple systems
Ensure adoption and user satisfactionBU
SIN
ESS
MA
ND
ATE
SH
URD
LES
Spend Data Quality
Corporate Spend Data Management Initiatives
12
Framework for Spend Data Management
DataWarehouse
PLM
ERP
We are facing big hurdles in these areas
Additional Manpower is needed to Validate and Cleanse. Whose Responsibility?
13
Why Poor Quality Data?
Disparate Data sources
ManualClassification
processes
Limited Data enrichment
capabilities
•Data quality varies within each system
•Data in multiple languages
•Manual code assignment in the source systems lead to inconsistencies and inaccuracies
• Faulty mapping processes
• Reliance on supplier data enrichment
Restricted spend visibility due to inaccurate, inconsistent and non-granular classification
14
COMMON ROW LCD DRIVER, PQFP80.Display, LCD26000
DOT MATRIX LCD CONTROLLER/DRIVDisplay, LCD26000
LCD CONTROLLER/DRIVER, BGA225.Display, LCD26000
LCD PANEL 31.5,AU SKD, V2,VV3ADisplay, LCD26000
LCD PANEL 31.5,AU SKD,VV3ADisplay, LCD26000
Item DescriptionCommodity Code DescriptionCommodity Code
“million $$$ IC Driver spend classified under LCD Display”
Inaccurate Classification: Business Implications
Erroneous view of SpendReduces the negotiable spend with IC Suppliers
15
Spend Visibility - Where Are We Now?
We Are Here…
Alternative Solutions
For Spend Data
Classification
17
Better Data: Different Approaches
Spend DataClassification
Consulting Services
HostedSolutions
In-house Semi Manual
SoftwareTool
SupplierContentServices
18
How Automation Is the Best Choice?
LOW HIGH
HIGH
Leveraging existing Infrastructure
On-DemandVisibility
Consulting Services
HostedSolutions
In-house Semi Manual
SoftwareTool
SupplierContentServices
19LOW HIGH
HIGH
Repeatability
DetailedVisibility
ConsultingServicesHosted
Solutions
In-houseSemi Manual
SoftwareTool
SupplierContentServices
How Automation Is the Best Choice?
20LOW HIGH
HIGH
Time to Value
TotalCost Of
Ownership(TCO)
ConsultingServices
HostedSolutions
In-houseSemi Manual
SoftwareTool
SupplierContentServices
How Automation Is the Best Choice?
21
Automated Spend Data Classification
ScalableTaxonomy independentLanguage & Domain independentIndependent of description quality
Seamless integration capabilities
Powerful scheduler featuresExposed Java API’sIntegrates with eProcurementtools and DW
User friendlyRapid implementationEase of use“Self Learning” mechanism keeps operational costs very low
Automated ClassificationAccelerated bulk Classification rate150-300k/hrReal Time classification<2 secondsRepeatable & on-demand classification
22
Spend Analysis Automation Advantage
46%63%69%Contract compliance rates
10%12%13%Ave. Savings from strategic sourcing
51%66%78%Spend under management
ManualPartial Automation
Full Automation
Performance Area
Source: Aberdeen Group, Aug 2007
23
Automated Classification Is Inevitable
For accurate and detailed visibility over a period of time.
For “On-Demand” Spend Analysis leveraging existing IT infrastructure.
For faster time-to-value
For implementation of Supply Management best practices.
Standardization of
Spend Data
Classification
25
• United Nations Standard Products and Services Code”
• An open standard
• A taxonomy of products and services
• A practical business tool
What is UNSPSC?
26
UNSPSC StructureEach Level contains a 2-character numerical value and a textual description as follows:
SegmentThe logical aggregation of families for analytical purpose
FamilyA commonly recognized group of inter-related commodity categories
ClassA group of commodities having a common group of function
CommodityA group of substitutable products and services
27
Data Synchronizationacross company divisions,
suppliers, & global locations
Process FlowIntegration
from RFXs, to ordering,to accounts payable,
to general ledger
Part DataSynchronization
from design to manufactureto procurement& other systems
Benefits of UNSPSC
StandardCoding System
for Products& Services
28
• Automate the gathering and analyzing of spend data• Provide a uniform, enterprise-wide view of spend• “Roll up” analysis identifies contractible groups, opportunities
for strategic vendor relationships• Centralize procurement function, leverage volume for better pricing
• Collaborate with Customers or Suppliers through use of a common classification system
• Control maverick spend: reduce off-contract spend at higherprices
• Reduce inventory through product standardization
Values For Enterprise
29
• Facilitate sales function, particularly through Internetexchanges
• Qualify as preferred supplier to customers with e-procurement initiatives
• Speed up new product introductions using Web services,XML, etc.
• Facilitate globalization of your business• Collect consistent sales data across channels, regions• Collaborate with customers to improve contractcompliance, increasing the supplier’s market share – awin-win situation
Values For Suppliers
Implementation of
Spend Data
Classification
31
7-Step Spend Analysis Implementation Methodology
1. Identify Your Business Needs
2. Determine the Corresponding Visibility Needs
3. Determine the Appropriate Solution Elements
4. Determine the Appropriate Delivery Method
5. Gain Internal Support (ROI Case)
6. Evaluate Alternative Solutions
7. Select and Implement a Solution
32
Step 1 – Identify Business Needs
• Show accurate spend by supplier across different naming conventions (Supplier Rationalization)
• Roll up spend by ultimate supplier parent
• Tracking of procurement process bottlenecks
• Provide consolidated view of new company (M&A) spend by supplier and commodity
• Quantifying of savings potential • Identification and eradication of
Maverick spend• Financial Reporting – Accurately
shows where funds are going and for what
• Identification of sources of potential savings
• Reduction of supply base • Enforcement of supplier compliance
to pricing, rebates and volume discount
• Reduction of Excess and Obsolete Inventory
• Promote part re-use instead of creating new part
Future Business NeedsImmediate Business Needs
33
Step 2 – Determine Corresponding Visibility Needs
1. Supplier Master Cleansing • Normalization of Supplier
Name2. Enriched Supplier Visibility
• Financial Information, Credit Ratings
1. Item Data Validation • Completeness and accurate data
2. Item Data Cleansing • Eliminate errors and discrepancies
3. Item Classification• Auto and Manual methodology
Future Spend Management Needs Immediate Spend Management Needs
34
ETL stands for extract, transform, and load. ETL is a software that enables businesses to consolidate their disparate data while moving it from place to place, and it doesn't really matter that that data is in different forms or formats. The data can come from any source. ETL is powerful enough to handle such data disparities.
Garbage In• Inconsistent• Inaccurate• Non-granular
dataERP
PLM ETL
Analytics
DWHistoric
Spend Data
ACTUAL SCENARIO
Garbage out• Faulty Reports• Low reliability• Lower ROI
Spend Reports
DW = Data Warehouse
The true picture: Data is the culprit
Step 2 – Determine Corresponding Visibility Needs
35
ETL
Analytics
DWHistoric
Spend Data
IMPLEMENTING BEST PRACTICES
Quality In•Consistent•Accurate•Granular
data
Quality Out•Accurate Reports•Increased
reliability•Higher ROI
Garbage In•Inconsistent•Inaccurate•Non-granular
dataSPEND
REPORTSPLM
ERP
• Normalization• Classification • Supplier Enrichment
Complete Solution Architecture
Step 3 – Determine Appropriate Solution Elements
36
• Close IT-Procurement relationship
• Want to “own” data• Want to customize solution to
existing process
• Slowest approach • Requires significant up-front
organizational commitment • Requires permanently
dedicated resources
• Max insight into own spending • Min reliance on 3rd party • Data security • Max ability to customize• Max integration with other spend
management application
Self -Service
• Poor IT-Procurement collaboration
• Desire to focus on core competency
• Want to implement an effective process, not customized to fit existing process
• Continual subscription fee• Limited customization • Limited integration with
other applications• Data security issue
• Quick ROI• Minimal Internal Resources
needed • Minimal Internal commitment• Best practice imbedded in vendor
process
Managed Service
• Limited spend to be analyzed• Restricted budget • Short-term outlook
• Inconsistent Classification• Limited Enrichment• Not repeatable• Does not scale
• Lower initial cost • Limited Budget Approval
Manual
Company Characteristics Appropriate for
DisadvantagesAdvantagesApproach
Our Approach: We would like to take the hybrid approach. First, manual approach with self-service approach phasing in at the later stage.
Reason: Need Quick Result, Plan in integrating with future application (SAP), want to “own” data with minimal disclosure to external parties especially our supply base.
Concern: This approach requires permanently dedicated resources though resource could be reduced with self-service phasing in.
Step 4 – Determine Appropriate Solution Delivery Method
37
Step 5 – Gain Internal Support (ROI - Cost)
Total
Total Cost of Ownership (USD, K)
Consultation Fee Hardware Investment Additional Hires
Data Enrichment Services
Software TrainingSoftware Integration
Software Implementation
Software LicensesYr 4 +Yr 3Yr 2Yr 1
Cost Element
38
0.5%
1%
1%
1%
3%
Percent Savings
Improved Parts de-duplication & Inventory Level
Improved Supplier Consolidation and Performance
Improved Purchase Efficiency
Improve Contract Compliance
Increased Sourcing Savings thru’ effective negotiation
Benefit TypeSavings (USD, K)
602602512482Total
4242363460%
112112959080%
12612610710090%
112112969080%
210210178.516850%
Yr 4+Yr 3Yr 2Yr 1Affected Spend
100%85%80%% of Company Adopting Solution
Year 3+ Year 2Year 1
Basis of Calculation : Company Yearly Spend = $14 Billion
Sample Calculation: Savings = Company Spend x Percent Savings x Affected Spend x Adoption rate
Step 5 – Gain Internal Support (ROI - Benefits)
Benefit/Cost Ratio = (Total Benefits)/ (Total Cost of Ownership)N/B: Since benefits increase over time while cost decreases, the returns are greater in future years
39
Step 6 – Evaluate Alternative Solutions
Short-list Vendors for Spend Data Management Software Evaluation
WIPSubmitted for Evaluation
Scheduled in Nov
WIPDONE 10. ZycusWIPWIPWIPWIPWIP9. Analytics WIPWIPWIPWIPWIP8. D & B
WIPSubmitted for Evaluation
WIPWIPDONE7. Austin TetraWIPWIPWIPWIPWIP6. Vertical Net WIPWIPWIPWIPWIP5. Ketera
WIPSubmitted for Evaluation
WIPWIP DONE4. i2WIPWIPWIPWIPWIP3. Frictionless
WIPSubmitted for Evaluation
WIPWIPDONE2. EmptorisWIPWIPWIPWIPDONE 1. Ariba
Request for Quotation
Request for sample Evaluation
Request for Demo
Request for Survey
Request for Information
Vendor
40
Survey Questions Development
Data Enrichment - Service Levels (Only applicable if service delivery)
a) Service Level Terms (Only apply for service delivery):1. What % of spend do you guarantee classified?2. What % accuracy is associated with the above term?3. Do you guarantee a minimum % of spend classified per source system?
If so, what %?4. Are errors identified corrected retroactively or only to future data?5. Please describe any other service level terms you offer.
b) Briefly describe your data enrichment service process, including all phases.
c) Describe the integration of all elements in your data enrichment service process.
d) Provide a project timeline, indicating all key milestones and dependencies (both external and internal). What risk factors may affect scope?
e) Describe the process for error-correction (e.g. correcting classifications).
Step 6 – Evaluate Alternative Solutions
41
Data Enrichment - Data Normalization / Classification
a) Does your solution offer automated data classification?
b) Which of the following types of data does your automated solution consider for classification purposes?
1. Supplier Information:2. Customer-specific codes (i.e. General Ledger, Material Codes, etc.):3. Item Descriptions:4. Other (Please Specify):
c) If your solution uses multiple types of data in making classifications, are the different types of data used in parallel (all available information considered before providing a final classification) or in series (classifications based on one type of data with other types only considered when no match found)?
d) What commodity taxonomies can your solution map data to? Can custom customer structures be used?
Step 6 – Evaluate Alternative SolutionsSurvey Questions Development
42
Data Enrichment - Data Normalization / Classification (Continued)
e) How does your solution ensure consistency of classification of similar items acrossdata systems and over time?
f) Can you effectively classify direct materials spend? If so, how?
g) Do you utilize a supplier database for classification purposes? If so:1) How many unique suppliers are in it?2) What is the geographic distribution of suppliers?3) Is the database integrated into your product?4) If a customer's supplier is not in your database, is it researched and added for
future classification use?
h) How are item descriptions used in classification?
i) Describe the feedback process for customer-requested changes to classifications.
j) Describe how quality assurance (QA) testing on classifications is conducted with your solution.
Step 6 – Evaluate Alternative SolutionsSurvey Questions Development
43
Data Enrichment - Supplier Enrichment
a) Does your solution offer supplier enrichment capabilities?
b) How many suppliers do you maintain in your database?
c) What is the geographic distribution of the suppliers in your database?
d) What sources feed your supplier database?
e) Indicate if the following types of enrichment are provided for suppliers:1. Parent / Child relationships:2. Credit ratings:3. Revenues:4. Other types of enrichment (Please list):
Step 6 – Evaluate Alternative SolutionsSurvey Questions Development
44
PreKick-off
Requirement Scooping
User Acceptance Test
KickOff
• Hardware Sizing
• Estimate no. of Users
• Hardware Budget
• Application Environment: DEV, TEST, PROD
• Level of integration
• Project Goal • Implementation
Plan • Roles and
Responsibilities
• Data to be collected
• Data customization
• Application configuration
• User reporting requirement
Software Roll out
• Training • Test taking
by power users and core team members
• Desktop Application Installation
• Users roles and permission
• Go Live!!!!
Step 7 – Select & Implement Solution
Action Plan
Conclusion &
Recommendations
46
Conclusions
Spend data classification is key to successful spend management to realize cost reductions.
Spend data quality or integrity is a key challenge in most enterprises. Data validation & cleansing can be time-consuming.
Effective & efficient data classification (through automated artificial intelligence) can result in detailed and repeated enterprise spend visibility.
Standardization of spend data classification such as UNSPSC can reap significant benefits to enterprise.
Data enrichment capability is a critical criterion in evaluating any spend analysis solution
47
Recommendations
Standardize and automate processes by adopting a standard classification schema & auto-classification.
Gain executive support and build the business case.
Use spend analysis to improve contract compliance.
Leverage spend analysis & improved visibility to develop strategic sourcing plan.
Enhance category and sourcing expertise to take action on the spend data.