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Sales and Operations Planning Las Vegas 2011
Citation preview
Confidential
Enablers for Maturing Your S&OP Processes
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Demand(customer)
Transportation Distribution &Inventory
Supply & Manufacturing
How much demand will we
generate? At what service level
can we profitably
satisfy demand?
At what point in my supply chain
should I decouple push vs. pull?
What is the best flow path?
How should we transport
product through the supply
chain?
What activities should we outsource?
How much and where should inventory be
positioned in the supply chain?
When should we buy or make
product to make best use of capacity?
What infrastructure is
required for manufacturing &
distribution?
2
We Support Value-Driven Supply Chain Decisions
Click to edit Master title styleSome of Our Consulting Clients
3
FOOD AND BEVERAGE
RETAIL
HOME/OFFICE DURABLES
HEALTHCARE
HOME/OFFICE NON DURABLES
OTHER INDUSTRIES
SERVED
• 62 of the Fortune 500• 9 of the Top 15 US Retailers
• 13 of AMR’s Top 25 Supply Chains• 5 of the Top 20 Global Forest and Paper Companies
• 8 of the World’s 25 Largest Food & Beverage Mfgs• 9 of the Top 10 Consumer Goods Supply Chains., SC Digest
Packaging
LSPChemical/ProcessAuto/IndustrialUtilities/
Telecomm/Media
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4
Selected S&OP Objectives
Increase Profits
Free Up Capacity
Focus Resources
Increase Flexibility
Improve Forecast
Manage Complexity
Business Strategy
• Competitive Differentiation
• Geo Strategy• Financial Targets
Financial Planning
• Revenue Forecast• Budgeting• Capital Plans• Cost Control
Market Planning
• Prod Forecast• Promo Plans• Brand/Channel Strategy & Pricing
R & DCategory Mgmt
• New Prod Into• Prod Lifecycle Plan• Prod Mix/ Pricing / Placement
Sales Planning
• Sales Forecasts• Customer Business Policies/Plans
Demand Planning
• Historical Demand• Stat Forecasts
SUPPLY
DEMAND
CORPORATE
Supply Planning
• Prod Forecast• Promo Plans• Brand/Channel Strategy & Pricing
Demand Management
• Product Allocation
Operations Planning
• Sales Forecasts• Customer Business Plans
• Product Allocation
Logistics Planning
• Historical Demand• Stat Forecasts
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5
Selected S&OP ObjectivesAnalytical Enablers
Increase Profits
Free Up Capacity
Focus Resources
Increase Flexibility
Improve Forecast
Manage Complexity
Cost-To-Serve Models
Product & Customer Portfolio Management
Segmentation/ Tailored SC Networks
Network Design and Analysis
Inventory Deployment and Policy Optimization
Click to edit Master title styleReasons Companies Initiate Network StudiesCost Reduction Clear Leader and Growing
Source: 184 Chainalytics’ employee project experiences
1995-1999 2000-2004 2005-2009
Never Done Thought It Was Time 11% 2% 0%
Develop Internal Compentancy 4% 4% 8%
New Markets 9% 9% 2%
New Management 0% 6% 11%
Excess/Insufficient Capacity 20% 9% 8%
Merger/Acquisition/Divestiture 9% 15% 12%
Cost Reduction 35% 38% 46%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Cost Reduction41%
Merger, Acquisition, Divestiture
12%
Excess/Insufficient Capacity
11%
New Management6%
New Markets6%
Develop Internal Compentancy
6%
Never Done Thought It Was Time
3%
Process Re-engineering3%
Annual Planning Process3%
Politcal/Regulatory2%
New Product Introductions2% Sourcing
Change2%
Assess 3PL Outsourcing2%
Increase Service1%
Trend Last 10 Years
Trend Last 5 Years
6
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Customer/Channel Segmentation Flow Path Service Level Strategy Service Territory Alignment Inventory Deployment Mode Usage Supply Chain Risk Assessment Master/Tactical Planning Social Responsibility
Recent Focus Areas in Supply Chain Network DesignBest Use of Current Networks
Network Optimization Inventory Optimization Simulation Transportation Modeling Total Cost to Serve Portfolio Management
Types of Analysis Modeling Technologies
7
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8
Periodic versus Continuous Analysis ApproachKeeps Network In Tune, Ability to React
EF
FO
RT
NE
TW
OR
K C
OS
TS
LostOpportunityActual
$
Optimal $
Typically 24+ Months
TIME
• Require months of concentrated, cross-functional effort•Do not support answering tactical or ad-hoc questions with holistic, fact-based analysis in the interval between major studies
•Require resources to “re-learn” the model (and perhaps the business)•Lose potential opportunities by allowing the network to atrophy during the typical 12-24 month gap between major studies
Periodic
EF
FO
RT
NE
TW
OR
K C
OS
TS
TIME
Initial Study
Actual $
Optimal $
•Does not completely eliminate spikes in effort, but reduces their effort & duration
•Supports ad-hoc questions with holistic, fact-based analysis• Changing costs, demand, customers & requirements, and product mix
•Potential M&A activity•Support freight, labor, and procurement negotiations•Ensures the network remains optimal:• Plant-DC-Customer assignments, Manufacturing line configuration•Allows resources to remain constant ,maintain expertise in model & business
Continuous
Click to edit Master title styleDesign Projects Supported by Analytics and Optimization Results Typically Contrary to Conventional Wisdom
81.8%
73.2%
83.6% 83.4% 83.6%
95%
100% 100% 100% 100%
85%
62.1%
55.0%
61.4% 61.4% 61.4%
50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
100%
BASELINE 1 Best Use ofExisting
2 OptimalMachine
Deployment
3a CloseGarland
3b Close St Joe
% M
ak
e
Company planned to outsource these products. Using Activity Based Costing in the study showed they should
maintain or increase amount made in plants.
$0
$10
$20
$30
$40
$50
$60
$70
$80
Millions
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Company had always built a significant amount of inventory in non-peak season (Sep-Nov). Studied
demonstrated ability to not build during this timeframe.
9
138.3
129.7129.2
127.2
124.8124.1
121.2120.6
116.6
135.2
127.0
122.2
117.9
124.3
126.7
130.7
Achievable St Joe Total Costs In Play Targeted St Joe Total Costs In Play
Company planned to invest significantly in existing Plant 1. Greatest savings came from closing down Plant 1.
Click to edit Master title styleDesign Projects Supported by Analytics and Optimization Results Typically Contrary to Conventional Wisdom
% o
f SKU
s
Base 0% 0% 1% 18% 80%
2% Strategy 20% 6% 9% 9% 57%
12% Strategy 58% 8% 6% 9% 20%
18% Strategy 69% 7% 5% 4% 14%
1 2 3 4 5
Company believed that vast majority of their SKU’s (80%) should be stocked at ALL locations. Optimal deployment
strategy indicated 70% of SKU’s should only be stocked at ONE location.
$-
$10
$20
$30
$40
$50
$60
$70
$80
$90
Network Devices Displays Printers & OfficeEquipment
Supplies & Media Security Devices
Millions
Inventory Value Inventory Value - SMO
17%
8%
17%11%
10%
Company believed that all SKU’s within a Group needed to have the same service level. By optimizing the service level
of each sku to maximize profit, while retaining the overall service level for the Group, inventory was reduced by 14%
10
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11
Simple Strategies and Policies Typically Do Not Provide Best ResultsBlackjack Strategies
Betting:Hit/Stick:Split/Double:House Advantage:
Typical Player
Same Base Unit/RandomHit only if cant bust
Split Pairs/Double on 10/111.5 to 5%
8 decks, H17, DAS, No Surrender, Peek
Estimated casino edge for these rules: 0.69 %
Dealer Upcard Your
Hand
2 3 4 5 6 7 8 9 10 A
5 H H H H H H H H H H6 H H H H H H H H H H7 H H H H H H H H H H8 H H H H H H H H H H9 H D D D D H H H H H10 D D D D D D D D H H11 D D D D D D D D D D12 H H S S S H H H H H13 S S S S S H H H H H14 S S S S S H H H H H15 S S S S S H H H H H16 S S S S S H H H H H17 S S S S S S S S S S
A,2 H H H D D H H H H HA,3 H H H D D H H H H HA,4 H H D D D H H H H HA,5 H H D D D H H H H HA,6 H D D D D H H H H HA,7 DS DS DS DS DS S S H H HA,8 S S S S DS S S S S SA,9 S S S S S S S S S S2,2 P P P P P P H H H H3,3 P P P P P P H H H H4,4 H H H P P H H H H H5,5 D D D D D D D D H H6,6 P P P P P H H H H H7,7 P P P P P P H H H H8,8 P P P P P P P P P P9,9 P P P P P S P P S ST,T S S S S S S S S S SA,A P P P P P P P P P PDlr 2 3 4 5 6 7 8 9 10 A
Key:
H = Hit S = Stand P = Split
D = Double (Hit if not allowed)
DS = Double (Stand if not allowed)
Basic Strategy
Same Base Unit/StructuredPlayer/Dealer CardsPlayer/Dealer Cards
0.5%
Card Counter
Base Unit Multiplier via Remaining Card Favorability (Running Count)
Basic altered by FavorabilityBasic altered by Favorability
-2% (Hit and run ~ -4%)
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12
Designing Tailored Supply Chain NetworksDemand Characteristics Drive Inventory Deployment
Item-Locations 194 1%COGS $250,900,000 34%
Item-Locations 3,395 20%COGS $428,000,000 59%
Item-Locations 13,791 79%COGS $51,100,000 7%
Item-Locations 11,283 65% Item-Locations 4,001 23% Item-Locations 2,096 12%COGS 41% COGS 23% COGS 35%
Fast: >1,000/Week
Demand Variability
Dem
and
Velo
city
High: >1.5
$302,900,000
Medium: 0.6 - 1.5
$170,200,000
Low: < 0.6
$256,900,000
Slow: < 25 Units/Week
Medium: > 25 Units and <1,000/Week
COV (Std Dev Demand / Mean Demand)
0
10
20
30
40
50
60
70
80
BEAUTY HOME CARE NUTRITION PERSONAL CARE
Item-Locs(H's): 100.29, 57.7% COGS: $(M's) 22.9, 3.1%
0
10
20
30
40
50
60
70
80
BEAUTY HOME CARE NUTRITION PERSONAL CARE
Item-Locs(H's): 11.63, 6.7% COGS: $(M's) 159.9, 21.9%
0
10
20
30
40
50
60
70
80
BEAUTY HOME CARE NUTRITION PERSONAL CARE
Item-Locs(H's): 0.91, 0.5% COGS: $(M's) 120.1, 16.5%
0
10
20
30
40
50
60
70
80
BEAUTY HOME CARE NUTRITION PERSONAL CARE
Item-Locs(H's): 30.5, 17.5% COGS: $(M's) 18.9, 2.6%
0
10
20
30
40
50
60
70
80
BEAUTY HOME CARE NUTRITION PERSONAL CARE
Item-Locs(H's): 9.22, 5.3% COGS: $(M's) 120.1, 16.5%
0
10
20
30
40
50
60
70
80
BEAUTY HOME CARE NUTRITION PERSONAL CARE
Item-Locs(H's): 0.29, 0.2% COGS: $(M's) 31.2, 4.3%
0
10
20
30
40
50
60
70
80
BEAUTY HOME CARE NUTRITION PERSONAL CARE
Item-Locs(H's): 7.12, 4.1% COGS: $(M's) 9.3, 1.3%
0
10
20
30
40
50
60
70
80
BEAUTY HOME CARE NUTRITION PERSONAL CARE
Item-Locs(H's): 13.1, 7.5% COGS: $(M's) 148, 20.3%
0
10
20
30
40
50
60
70
80
BEAUTY HOME CARE NUTRITION PERSONAL CARE
Item-Locs(H's): 0.74, 0.4% COGS: $(M's) 99.6, 13.6%
Candidates for Centralization
Candidates for Full Stocking or
Direct Ship
Click to edit Master title styleReducing Stocking Locations Increases Product Velocity and Reduces Demand Variability
0%
200%
400%
600%
800%
1000%
1200%
1400%
1600%
1800%
0.0 50.0 100.0 150.0 200.0 250.0
Mean Days Between Ships
CO
V D
aily
Dem
and
0%
200%
400%
600%
800%
1000%
1200%
1400%
1600%
1800%
0.0 50.0 100.0 150.0 200.0 250.0
Mean Days Between Ships
CO
V D
aily
Dem
and
Product Stocked at All Locations
Product Stocked at Single Location
0
1
2
3
4
5
6
7
8
1 2 3 4 5
Stocking Locations
Day
s
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Dem
and
Var
iab
ilit
y
Avg Mean Days Between Shipments Avg Demand Variability
13
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14
Key Attributes
Determine Bulk & Direct to Store Articles
Determine Stored vs. Not Stored
Determine Cross Dock vs. Flow Through
59,619 total Items
56,199 Items through the future DCs
44,687 Items either Flow Through or Cross
Determine Flow Through Manual & Automation
16,770 Items Flow Through
• 994 Bulk Items
• 2,426 Direct to Store Items
• 11,512 total Items Stored
• 8,114 Items Seasonally stored
• 27,917 Items Cross Docked
• 14,112 Items Flow Through Automation
• 2,658 Items Flow Through Manual
The process that mapped Items to Flow Channels is outlined
here.
Key Items attributes and costs drivers were
considered in assigning Articles to
Flow Channels.
Designing Tailored Supply Chain NetworksProduct Characteristics Drive Flow Paths
Attributes
Live Goods
Hazmat
Remote Vendor/Store
Imported
Seasonal
High Demand Variability
Long Lead Time
Short Lead Time
High Product Value
Small Cube/Carton Sizes
Low Pick Density
Conveyable
Long Lead Time
Low Product Value
Not Small Cube/Carton Sizes
High Pick Density
Conveyable=Automation
NonConveyable=Manual
Dire
ct to
Sto
reSt
orag
eCr
oss
Doc
kFl
ow T
hrou
gh
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15
Customer & Product Portfolio ManagementWho and What is Driving our Profitability
Number of Products
• A products (22%) account for 80% of revenue and 81% of contribution margin, and 10% of the space
• While C products (46%) account for 5% of revenue and 4% of margin contribution, and 60% of storage space
There may be opportunities to reduce complexity by addressing the portfolio size and business practices associated with the large tail of low
revenue-generating PRODUCTS22%
24%46%
8%
80%
15%
5%0%
81%
15%
4%0%10%
18%
60%
12%
ABCD
ItemsRevenue
Margin
Storage Space
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6%8%
85%
1%
80%
15%
5%0%
71%
14%
15%0%
5%8%
80%
7%
ABCD
16
Number of Customers
There may be opportunities to reduce complexity by addressing the portfolio size and business
practices associated with the very large tail of low revenue-generating CUSTOMERS
Customer & Product Portfolio ManagementWho and What is Driving our Profitability
Customers
Revenue
Margin
Storage Space
• A customers (6%) account for 80% of revenue and 71% of contribution margin, and 5% of the space
• While C Customers (85%) account for 5% of revenue and 15% of margin contribution, and 80% of storage space
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StageI
Reacting
IIAnticipating
IIICollaborating
IVOrchestrating
Balance:
S&OP
Goal Development of an
operational plan
Demand and supply
matching
Profitability Demand sensing, and
conscious tradeoffs for
demand shaping to drive an
optimized demand- response
Ownership S = Sales
OP = Factory
capabilities
S = Sales and Marketing
Plans
OP = Planning and factory
capabilities
S = Go to Market Plans
OP = Design of demand
driven plan, make & deliver
processes
S = Go to Market Strategies and
Solutions
OP = Translation of demand into
plan, make, deliver, source and
service strategies, with connection
to execution
Metrics Order fill rate, asset
utilization, inventory
levels
Order fill rate, forecast
error, inventory turns,
functional costs
Demand error, customer
service, working capital,
total costs
Demand risk, customer service,
cash flow, market share and profit
Techniques/
Technology
Excel spread sheets,
ERP Supply chain
capabilities
Excel, demand forecasting,
inventory management,
general supply chain
planning tools, inventory
optimization
what if analysis for
demand shaping, what if
analysis for reconciliation
with financial plans, cost
to serve,
Analytics to find risk- value trade
offs, risk management techniques,
price optimization, complex
simulation
17
Four Stages of S&OP Maturity Companies Stuck in Early Stages
Source : AMR Research/ 2009 S&OP Study of 182 Companies
S
OP
S
OP
SOP S OP
20%
47%
19% 14%
20%
47%
19% 14%
20%
47%
19% 14%
20%
47%
19% 14%
SherTrackDemand-Driven Predictive Manufacturing