Spending Anlaysis

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  • 1.  
  • 2. Session # 2006 Brian Corry, Senior Managing Consultant, IBM Saul Goldberg, Managing Consultant, IBM April 15, 2008 3:20 p.m. – 4:20 pm. Building a Spend Analysis Program
  • 3. Session Agenda
    • Defining the Program
    • Building the Spend Analysis Program
    • Lessons Learned Building a Spend Analysis Program
    • Spend Analysis as a Procurement Transformation Platform
  • 4. Building a Spend Analysis Program
    • Defining the Program
  • 5. What is Spend Analysis?
    • Spend analysis is an in-depth review of an organization’s expenditures focusing primarily on detailed expenditures by:
      • Individual items
      • Vendors
      • Contracting methods employed
    • These three focal points are further detailed based on unique operational characteristics and needs of the organization.
      • When additional data sets are offered for review, the opportunity for focused stratifications is increased.
    • Spend analysis results are used to enable strategic decision making at all organizational levels.
    • Automated tools are often employed to enable spend analysis efforts, but they are not required.
  • 6. Why Perform Spend Analysis? Required Due Diligence for Improvement Initiatives
    • Most Supply Chain improvement initiatives require spend analysis at some level to define the scope of the opportunity as well as baseline the current state.
      • Defines and baselines past expenditures – price, spend, TCO, frequency of procurements/contracting activity, supplier base
      • Baselines operational performance metrics
      • Uncovers workload and workforce management issues
      • Identifies gaps in reaching socio-economic goals
      • Reveals stakeholder collaboration opportunities
      • Justifies resource devotion to supply chain improvement initiatives
    Spend Analyses Facilitate The Accomplishment of Supply Chain Initiatives Strategic Sourcing Commodity Councils Inventory Management CRM Initiatives Make-vs-Buy Decisions Prime Vendor Initiatives PBL Initiatives SRM Initiatives
  • 7. Key Activities & Tasks Collect Data Normalize Data Validate with BU Analyze Data Define Data Elements Identify Opportunities
    • Collect data from systems
    • Collect hardcopy data (e.g., invoices, orders)
    • Talk to stakeholders
    • Talk to suppliers
    • Compile data into database tool
    • Cleanse data
    • Categorize purchased items
    • Identify gaps & inconsistencies
    • Produce high level spend baseline and priority listing
    • Check results with relevant stakeholders
    • Adjust data if necessary
    • Fill in gaps
    • Agree on priorities for further investigation
    • Analyze data across each dimension (e.g., product, supplier, location, negotiable vs. non-negotiable, etc.)
    • Based on spend analysis, validate findings against initial hypotheses
    • Refine opportunity assessment
    • Focus on specific opportunities and drill down
    • Determine what data needs to be collected
    • Identify data sources
  • 8. Typical Findings Revealed by the Initial Spend Analysis Strategic decision making is currently flawed, possibly fatal Opportunity loss is high
    • Structured approaches to services and material classification and categorization are rarely employed
    • Multiple specifications exist for the commodities with the same functions
    • Prices vary among the same items
    • Forecasts and budgets can be improved through utilization of spend analyses
    • Organizations have little understanding of what is being bought across the entire enterprise
    • Buying power is not fully exploited
    • A small proportion of negotiable spend is covered by long-term agreements
    • Spend data is not readily available and/or accurate to support supplier management
  • 9. Long Term Spend Analysis Benefits
    • Identify key cost drivers and breakdowns of acquired items and services and key suppliers to achieve lower cost/prices
      • Incremental value achieved is real and substantial, ranging from 3.6% to over 20% of spend.
    • Achieve a better understanding of what is being bought across the entire enterprise
      • Improved purchasing efficiency
      • Consolidate buying power and fully leverage it
      • Negotiate more advantageous prices and terms
      • Bundle high demand spend with low demand items under long-term agreements
      • Reduce maverick spending
    • Supplier rationalization
    • Identify data collection methods and improve upon the process (e.g., consolidate internal purchasing processes)
    • Develop standard internal taxonomies for categorizing commodities and services and improve enterprise reporting
    • Improve forecasts, budgets, delivery schedules, and inventory management
    • Customizable executive dashboards
    Improved strategic decision making Identify competitive opportunity improvements
  • 10. Spend Analysis Program
    • The combination of people, managerial directives, tools, and organizational will to enable repeatable efforts to identify opportunities to improve the competitive position and enable better decision making.
  • 11. Building a Spend Analysis Program
    • Building the Program
  • 12. Gaining Buy-In
      • CEO / Director / Secretary
      • CFO
      • CPO
      • CIO
      • LOB/Program Office
      • Procurement professionals
      • Suppliers
      • Clients
      • General awareness
      • Targeted calls
      • Stakeholder interviews
      • Validation and verification requests
      • Savings opportunities in cost, sourcing pipeline, maverick spend reduction, and demand management opportunities
      • Profit improvements, higher EPS, and extended budgets
      • Procurement visibility leads to better negotiation positions and compliance
      • Executive visibility
      • Integrated procurement approach with business operations leads to improved SCM (e.g., supplier performance, reduced inventory)
      • Improved customer relationships
      • Consolidation of spend data into a single interface
      • Reporting and analytics
    Identify Stakeholders Perform Outreach Articulate Value Propositions
  • 13. Overcoming Objectives
    • Spend analysis has no ROI
    • We have reporting tools
    • Our policies already require competitive sourcing
    • We did it once before, with little return
    • Our data is too dirty
    Source: Majority provided by Emptoris
  • 14. A Framework for Moving Forward
    • 4 Expand the Program
      • Build on quick wins and proof of concept results
      • Phase in operating units
      • Expand use of the data and analyses
      • Couple analysis results with other market driving information
    • 3 Establish Repeatable Processes
      • Establish benchmarks and continuously reassess progress
      • Keep the data current
      • Increase the frequency
      • Enhance spend data with business intelligence – factor in qualitative data
    • 2 Plot the Course
      • Identify required capabilities
      • Map the process and potential areas of value
      • Bridge the capability gaps
      • Adopt common taxonomies
      • Train personnel and/or acquire spend analysis software/partner
      • Identify quick win opportunities
    • 1 Assess Existing Capabilities
      • Define the spend analysis program
      • Data sources, completeness, schemata
      • Spend analytic tools and processes
      • Staff resources / spend analysts
      • Understanding of industry and market dynamics
  • 15. Desired Capabilities for a Spend Analysis Solution
    • Experience and expertise in analyzing spend in your industry
    • Ability to cleanse, normalize, and categorize spend data from a variety of sources
    • Efficiency of the analysis engine and its ability to handle the amount of data while quickly generating accurate results
    • Structure of analysis engine:
      • Rules-based engines work best on direct and indirect materials
      • Neural network engines are best for services
      • Manual: High level of expertise in spend analytics and commodities
    • In-house solution or outsourced service
      • Adequate security if the data is exported into a hosted solution
    • Integration with sourcing tools
    • Portfolio of analytical reports and data views
    • Language and currency support for multi-national entities
    Source: Majority provided by Forrester Research
  • 16. Technology Approaches
    • Performed internally or by external consultants
    • Labor-heavy utilizing generic software such as basic spreadsheet applications to classify and analyze spend
    • Generally used as a proof of concept or due to lack of budget
    Manual
    • Outsource the bulk of the effort
    • Software is not licensed or installed
    • Analytical technology usually hosted and accessed through the web browser
    • Lower total cost
    Managed Service
    • Organizations run their own program with the use of licensed specialized software tools to automate the process
    • Installed behind-the-firewall
    • Highest total cost
    Software
    • Simultaneous use of a combination of the other three approaches
    • Additional resources needed to combine/coordinate data and resources
    Phased
    • Low cost
    • Inconsistent results
    • Limited enrichment
    • Lack of scale – not easy to repeat
    • Use of transactional system data
    • Performed by experts, best practices applied – quicker ROI, faster results
    • Minimum resources needed, allows org. to focus on core procurement
    • Least flexible to customize, and incorporate into SCM toolkit
    • Security issues exporting data
    • Complete in-house control
    • Most able to incorporate into SCM toolkit; customization possible
    • Significant recurring resources
    • Longest time to results
    • Combination of advantages and disadvantages of other approaches
    • Quick ROI
    • Costs may shift as the approach shifts
    Source: Majority provided by Forrester Research
  • 17. Spend Analysts Bring Specialized Skills Separate From the Buying Function
    • “ The line between data analysis skills and advanced knowledge of technology to help analyze data has blurred.”
    • “ Buyers need to learn how to manipulate data out of large databases because most canned reports do not give you the information that is needed in the daily purchasing, or planning activities. The data is in the systems but you need to be able to access the data and use commonplace tools to get what you need out of the data.”
    • “ Buyers must be able to select the important data from the large amount we are exposed to daily, rather than expect someone to hand us a list of numbers to stick into a spreadsheet.”
    • “ And once the data analysis is complete, we must understand what the output means and how to employ it in a real world application. Thinking is still the most critical skill we bring to the party."
    Source: Majority provided by Purchasing.com
  • 18. Spend Analyst Job Profile
    • Data collection
      • Lead the spend data collection and analysis process; work to refine and verify spend categorization results; develop and implement categorization rules
      • Set-up, manage, and document sourcing databases
      • Cleanse, validate, and analyze sourcing, spend, forecast, performance metrics and other varied supply chain data
    • Analyses
      • Conduct recurring and ad-hoc market analysis, benchmark analysis and spend analysis for select categories of spend
      • Analyze spending patterns and other associated costs relative to the total cost of ownership related to the goods and services
      • Analyze current spend and vendors used through source systems
      • Understand and develop volume and growth patterns and assumptions necessary for sourcing any individual category
      • Identify opportunities for improvements
    • Sourcing
      • Assist Commodity Manager to develop sourcing strategies, spend reduction recommendations, and targets for associated savings
  • 19. Spend Analyst Skill Requirements
    • Professional
      • Analysis experience in business environment and exposure to procurement strategies
      • Experience in conducting complex financial, spend, and market analysis
      • Knowledge of strategic sourcing methodologies
      • Supply chain management orientation
      • Business transformation focus
    • Technical
      • Deep expertise in data management and warehousing (MS Access/Excel, COTS Reports)
      • Talent for building cross-functional relationships & developing cross-functional understanding
      • Strong analytical, business process analysis and problem solving capabilities
      • Experience in multiple business sectors/spend categories
      • Strong project management and quantitative skills
      • Business process analysis and design
    • Behavioral
      • Exhibits high energy and the enthusiasm to establish a new approach to sourcing
      • Ability to work independently and in a matrixed environment – able to “juggle” priorities
      • Effective time management and organizational skills
      • Effective oral and written communication skills
      • Customer service ethic and orientation and ability to interact with others
  • 20. Spend Analysis Program Maturity Connect spend analysis with business processes Source: Majority provided by Aberdeen Group
    • Executive level sponsorship
    • Full stakeholder involvement
    • Commitment present with some support
    • Initial interest but lacks commitment
    Buy In
    • Strive for more detailed visibility into spend, with end-to-end spend intelligence software
    • Strive for full automation, especially auto-classification of data
    • Ensure that data is correct and up to date in the master data system
    • Increase automation of spend intelligence gathering and processes
    • Further consolidation
    • Standardize SA processes
    • Establish SA routines
    • Strive for greater program buy-in
      • Demonstrate results using rudimentary approaches to justify further investments
    • Increase automation and data centralization
    Next Steps
    • Integrated procurement knowledge bases based on robust databases
    • Consolidated sourcing and procurement data across business units
    • Excel, Access or other local database store data with manual and automated populations which are transmitted and centrally consolidated
    • Databases standardized within org.
    • No centralized data storage
    • Data stored on individual machines
    • Fragmented procurement databases
    Data
    • Fully automated
    • Repeatable and continuous at a micro level
    • Continuously improved
    • Partially or fully automated
    • Infrequent (e.g., annually) but repeatable
    • High level
    • Ad-hoc / sporadic or non-existent
    • Not easily repeatable
    SA Processes
    • Integrated sourcing and procurement tools with spend analysis
    • Robust capabilities to provide information
    • Centralized procurement and spend analysis tools
    • No standard procurement tool
    • Locally maintained by buyers
    Procurement Tools
    • Analysis performed using data warehousing solutions
    • Standard analysis and reporting tools to support executive decisions
    Best in Class
    • Analysis performed on centrally stored information
    • Tools are local and non-standardized (e.g. Excel, Access)
    Industry Average
    • No standardized analysis tools
    • Analysis performed on ad-hoc basis
    • Manual data collection
    Laggards Analysis Tools Measures
  • 21. Spend Data Classification Maturity Continuous drive towards deeper detailed data visibility Source: Majority provided by Aberdeen Group
    • Consolidated view of spend
    • Data classified at the item level
    • Deep visibility into purchases
    • Actionable analyses
    • Supplier-based spend categorization
    • Focus on top-leverage commodity categories
    • Annual aggregation of high value commodities and/or top suppliers
    • Supplier-based classification
    • High-level assessment
    Traits
    • Requires access to 100% of spending data.
    • Requires deep expertise of commodities and suppliers
    • Requires sophisticated analytical tool support
    • Overlooks diversity of spend with a supplier
    • Can give inaccurate view of spending position with a supplier
    • Too high a level (commodity families) to develop and execute real strategies
    • Fails to examine complete spending position
    • Provides only high-level summary data
    • Relies more on instinct and experience of purchasing team than real data
    Challenges
    • Detailed view of spending by company, division, site, and buyer, item, vendor, and contracting method
    • Enables optimal sourcing strategies based on timely and accurate intelligence
    Best in Class
    • Deeper view of spending within high-level categories
    • Used to drive commodity strategies
    Industry Average
    • Identifies most obvious opportunities for aggregation
    Laggards Benefits Measures
  • 22. Building a Spend Analysis Program
    • Challenges to Building the Spend Analysis Program
  • 23. Organizational Barriers
    • Organizational culture and people
    • Technological investments
    • Competing priorities
  • 24. Data Issues
    • Experienced spend analysts
    Identifying the real issues and opportunities - Sometimes identifying opportunities is beyond the data
    • Adopt electronic procurement records using standard solutions
    • On-line capture of pertinent spend data
    Reluctance to share information
    • Realign staff
    • Acquire assistance
    Resource constraints
    • Improve data entry
    • Automated classifications
    Cleaning the data – intense efforts due to inconsistent coding
    • Adopt electronic procurement records using standardized solutions
    • On-line capture of pertinent spend data
    Data format - hardcopy data is more difficult to analyze!
    • Standardized taxonomies
    • Automated ETL
    • Data warehouse
    • Poor data
    • Decentralized locations
    • Not geared towards spend analysis (financial data)
    • Data normalization during and after input
    • Automated classifications
    • Continuous improvement in classification and normalization
    • Data is not meaningful
    • Little classification of all sources
    • Inconsistent formats, quality, and consistency (e.g., vendor name spelling, free form text)
    • Incomplete data
    Solutions Challenge
  • 25. Developing Repeatable Processes
    • Frequency
    • Automation
    • Feeding the beast
  • 26. Spend Analysis Considerations in the Public Sector
    • Socio-economic business goals
    • Transactional, not holistic, approach to savings is the priority
    • Procurement operations are not spending their own money
    • Past performance input
    • Security concerns
  • 27. Building a Spend Analysis Program
    • Lessons Learned Implementing a Spend Analysis Program
  • 28. Lessons Learned Implementing a Spend Analysis Program
    • Secure executive sponsorship
      • Find champions to support the program
    • Properly plan the program
      • Allow sufficient time and resources
      • If you can’t start big, start small
    • Build a cross-functional team
      • Involve internal customers, buyers, A/P professionals and, if needed, suppliers
    • Demonstrate usefulness of the spend analysis
      • Achieve early wins
      • Apply 80/20 rule - focus on the high spend and strategic items first
      • Provide continuous value to stakeholders by looking for opportunities and new value propositions to support stakeholder goals
    • Working with the data
      • Validate the data by involving the customers and gaining their buy-in
      • Continuously expand data capture and accuracy and increase frequency of analysis
      • Match the tools to the data compilation and management effort
      • Employ standard service and material classification and categorization schemas where possible
  • 29. Building a Spend Analysis Program
    • Spend Analysis as a Transformation Platform
  • 30. Spend Analysis as a Transformation Platform Spend Analysis Educational Opportunities Continuous Procurement Improvement Address Data & Technology Gaps Strategic Sourcing Initiatives Business Organization Realignment SCM Improvements
  • 31. Wrap Up
    • Questions
    • Share your stories