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Take-aways from 5 years of events at Stanford:
2008 Focus: 2013 Focus:
Enterprise software
Enterprise data
Org. units & people
Enterprise software
Enterprise & big data
Org. units & people
Data management
& analytics
Cross-functional data-intensive
operational activities
Data tsunami impacting all
functions and all industries
Creating business value with enterprise analytics
Business analytics
1. Enable direct business user access to enterprise data
2. Central analytics team for critical mass + members in
each business function
3. Blur boundary between business and IT
Enterprise & Big data
Org. units & people
Enterprise
software
Creating business value with enterprise analytics
2013 best practice: Focus on data
Three critical enablers:
What’s missing?
- Data-centric: Data access is foundational, but not a solution in itself
- Still need to enable collaboration, business processes & integration with enterprise software
 Evolve paradigm to encompass all three solution elements
Expensive, inflexible functionality and data access
Standardized – not a source of competitive differentiation
Enabling analytic “apps” at the organization
and enterprise software layers
Current status and challenges:
Enabler #1: Connect Excel and enterprise software “data islands”
 Steelwedge “Enterprise Excel” interface
Enterprise software
Enterprise data
Org. units & people
EXCEL! Valuable, but “non-enterprise” data and analytics
- Pros: Familiar, flexible, customizable
- Cons: Non-scalable, non-integrated, non-collaborative
Enabler #2: Open enterprise software data and “process enablement” to analytics
 Steelwedge “Open Apps” architecture
“Enterprise Excel” interface
“Open Apps” architecture
Mobile phone analogy
Carrier software
Texts
Enterprise software
Excel
Apple iOS
Apps explosion
Role and value of
phone transformed
Open Apps
S&OP transformed?
Will other enterprise software
providers follow suit?
“Enterprise Excel” interface
- Shortages
- Inventory and liability
- Poorly utilized capacity
- Expediting and overtime
Profits
Revenues
Costs
Material cost
Write-downs
/ write-offs
Inventory
holding costs
Income statement
Profits
Revenues
Costs
Material cost
Write-downs
/ write-offs
Inventory
holding costs
Income statement
Assets
Inventory
Balance sheet
Liabilities
Material liabilities
Capacity
Assets
Inventory
Balance sheet
Liabilities
Material liabilities
Capacity
Too muchCost
Too little
- Ours
- Customers
- Suppliers
- Commitments
- Coordination
Plan Reality
Operating
performance
- Re-planning
- Re-coordinating
- Constraints
- Fire-fighting
- Cost and conflict
- Damaged relationships - Income statement and
balance sheet impact
- Lack of control
- Lack of accountability
It’s an Uncertain World
Financial performance
Plans and performance management based on “best guess” forecasts
create risk and lost opportunity
AZTRAL
Range Forecasts and Planning:
What is the right type and amount of flexibility?
“Bucket” at end of
“supply chain pipe”
Inventory
“Supply chain pipe”
Capacity
Materials
Production
Finished
goods
Forecast accuracy lower further in future
Planning flexibility should be sized to match forecast uncertainty
- Unless forecast accuracy = 100%, flexibility is required to match supply and demand
90th
75th
25th
10th
Forecast error
percentile
Benefits of proactively planning for forecast uncertainty:
AZTRAL
- Ability to capture opportunity
- Reduced risk and liability
Range Forecasts and Performance Management
1. Create “menu” of performance alternatives for key stakeholders
2. Agree on best choice and establish alignment and accountability
Demand Demand
Vs.
“Risk aware” S&OP process:
“Range” performance management
Plan
Demand
Today: Flying blind
Service level 98%
Inventory $2M
Cost $11M
Gross margin $3M
Liability $1.2M
Low Plan High
?
?
?
?
?
?
Service level 98%
Inventory $2M
Cost $11M
Gross margin $3M
Liability $1.2M
Low Plan High
?
?
?
?
?
?
Service level 100% 99% 97%
Inventory $2.2M $1.8M $0.3M
Cost $8.3M $11.3M $13.7M
Gross margin $2.5M $2.9M $4.1M
Liability $2.1M $0.8M $0.3M
Low Base High
Service level 100% 99% 97%
Inventory $2.2M $1.8M $0.3M
Cost $8.3M $11.3M $13.7M
Gross margin $2.5M $2.9M $4.1M
Liability $2.1M $0.8M $0.3M
Low Base High
Service level 100% 99% 95%
Inventory $3.1M $2.0M $0.1M
Cost $8.0M $11.0M $13.4M
Gross margin $2.6M $3.0M $3.8M
Liability $2.5M $0.8M $0.3M
Low Base High
Service level 100% 99% 95%
Inventory $3.1M $2.0M $0.1M
Cost $8.0M $11.0M $13.4M
Gross margin $2.6M $3.0M $3.8M
Liability $2.5M $0.8M $0.3M
Low Base High
Benefits of including forecast uncertainty in performance management:
- Quantify and manage performance risks and trade-offs
- Ensure “no surprises, no excuses” alignment and accountability
AZTRAL

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Got a Unique Sales and Operations Planning (S&OP) Process? There's an App For That [Part 1]

  • 1. Take-aways from 5 years of events at Stanford: 2008 Focus: 2013 Focus: Enterprise software Enterprise data Org. units & people Enterprise software Enterprise & big data Org. units & people Data management & analytics Cross-functional data-intensive operational activities Data tsunami impacting all functions and all industries Creating business value with enterprise analytics Business analytics
  • 2. 1. Enable direct business user access to enterprise data 2. Central analytics team for critical mass + members in each business function 3. Blur boundary between business and IT Enterprise & Big data Org. units & people Enterprise software Creating business value with enterprise analytics 2013 best practice: Focus on data Three critical enablers: What’s missing? - Data-centric: Data access is foundational, but not a solution in itself - Still need to enable collaboration, business processes & integration with enterprise software  Evolve paradigm to encompass all three solution elements
  • 3. Expensive, inflexible functionality and data access Standardized – not a source of competitive differentiation Enabling analytic “apps” at the organization and enterprise software layers Current status and challenges: Enabler #1: Connect Excel and enterprise software “data islands”  Steelwedge “Enterprise Excel” interface Enterprise software Enterprise data Org. units & people EXCEL! Valuable, but “non-enterprise” data and analytics - Pros: Familiar, flexible, customizable - Cons: Non-scalable, non-integrated, non-collaborative Enabler #2: Open enterprise software data and “process enablement” to analytics  Steelwedge “Open Apps” architecture “Enterprise Excel” interface “Open Apps” architecture
  • 4. Mobile phone analogy Carrier software Texts Enterprise software Excel Apple iOS Apps explosion Role and value of phone transformed Open Apps S&OP transformed? Will other enterprise software providers follow suit? “Enterprise Excel” interface
  • 5. - Shortages - Inventory and liability - Poorly utilized capacity - Expediting and overtime Profits Revenues Costs Material cost Write-downs / write-offs Inventory holding costs Income statement Profits Revenues Costs Material cost Write-downs / write-offs Inventory holding costs Income statement Assets Inventory Balance sheet Liabilities Material liabilities Capacity Assets Inventory Balance sheet Liabilities Material liabilities Capacity Too muchCost Too little - Ours - Customers - Suppliers - Commitments - Coordination Plan Reality Operating performance - Re-planning - Re-coordinating - Constraints - Fire-fighting - Cost and conflict - Damaged relationships - Income statement and balance sheet impact - Lack of control - Lack of accountability It’s an Uncertain World Financial performance Plans and performance management based on “best guess” forecasts create risk and lost opportunity AZTRAL
  • 6. Range Forecasts and Planning: What is the right type and amount of flexibility? “Bucket” at end of “supply chain pipe” Inventory “Supply chain pipe” Capacity Materials Production Finished goods Forecast accuracy lower further in future Planning flexibility should be sized to match forecast uncertainty - Unless forecast accuracy = 100%, flexibility is required to match supply and demand 90th 75th 25th 10th Forecast error percentile Benefits of proactively planning for forecast uncertainty: AZTRAL - Ability to capture opportunity - Reduced risk and liability
  • 7. Range Forecasts and Performance Management 1. Create “menu” of performance alternatives for key stakeholders 2. Agree on best choice and establish alignment and accountability Demand Demand Vs. “Risk aware” S&OP process: “Range” performance management Plan Demand Today: Flying blind Service level 98% Inventory $2M Cost $11M Gross margin $3M Liability $1.2M Low Plan High ? ? ? ? ? ? Service level 98% Inventory $2M Cost $11M Gross margin $3M Liability $1.2M Low Plan High ? ? ? ? ? ? Service level 100% 99% 97% Inventory $2.2M $1.8M $0.3M Cost $8.3M $11.3M $13.7M Gross margin $2.5M $2.9M $4.1M Liability $2.1M $0.8M $0.3M Low Base High Service level 100% 99% 97% Inventory $2.2M $1.8M $0.3M Cost $8.3M $11.3M $13.7M Gross margin $2.5M $2.9M $4.1M Liability $2.1M $0.8M $0.3M Low Base High Service level 100% 99% 95% Inventory $3.1M $2.0M $0.1M Cost $8.0M $11.0M $13.4M Gross margin $2.6M $3.0M $3.8M Liability $2.5M $0.8M $0.3M Low Base High Service level 100% 99% 95% Inventory $3.1M $2.0M $0.1M Cost $8.0M $11.0M $13.4M Gross margin $2.6M $3.0M $3.8M Liability $2.5M $0.8M $0.3M Low Base High Benefits of including forecast uncertainty in performance management: - Quantify and manage performance risks and trade-offs - Ensure “no surprises, no excuses” alignment and accountability AZTRAL