nikos iosif international business development, mantis
TRANSCRIPT
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Nikos Iosif
International Business Development, MANTIS
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• British Aerospace
• Gec-Marconi aerospace
• General Motors
• Mazda Motor Parts Europe
• Messier-Bugatti Aerospace
• Messier Dowty Aerospace
• Smiths Industries
• Volkswagen Group Service
• Volvo VCE
• NATO Supply Agency
• MAN Bus & Trucks
• Porsche
• Abbey National Bank plc
• Euronet
• British Gas Transco
• British Gas Services
• Scottish Hydro Electric
• Fuji Film Sverige AB
• Pharmacia
• Esab
• MK Electric
• CPC Foods
• Lucent Technologies
• Donaldson
• Halfords
• The Wilkinson group
• Sketchley
• Superquinn
• Alcro Beckers
• Meria Nova Oy
• Carlsberg Tetley
• Get
• Technocar SEAT
• Electrolux Outdoor Products
• Electrolux Professional
• Viamar Skoda
Some Of Our Customers
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Production Planning& Scheduling
Replenishment PlanningDemand Forecasting
Executive Information
Systems
Supply Flow Management
Modelling and
Simulation
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Syncron B2B
OUR SUPPLY CHAIN VISION
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Are you operating in isolation rather than in partnership? next
Syncron - Supply Chain Management
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Do you still focus on local optimisation with limited visibility? next
Syncron - Supply Chain Management
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You can make earlier decisions in conjunction with your partners next
Syncron - Supply Chain Management
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ERP• Transactional backbone system
• System of record for all
information
• Large user base within an
organization
• Wide focus on all business
functions
– Financial, Manufacturing, etc.
SCM• Decision-support system
• Complex algorithm execution
• Rapid result generation
• Simulation modeling and what-if
analysis
• Small user base of key individuals
within an organization
• Targeted focus on key business
problems
What’s the Difference ?
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ERP• Issues purchase orders
• Reports on-hand inventory levels
• Archives actual order & shipment
history
• Issues stock replenishment orders
• Issues work orders to shop floor
SCM• Calculates optimal purchase order quantity
and timing
• Determines right product, right place, right
time, right quantity
• Uses historical and current order information
to predict customer demand
• Optimally calculates timing and quantity of
replenishments
• Creates detailed capacity, labor and material
constrained works order schedules
• Collaborative business planning
• Alerting & exception management based on
business rules
What’s the Difference ?
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Forecasting
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Purpose Of Forecast• What decisions will be made as a result of the
forecast?– Company corporate planning?– Capacity planning?– Manpower planning?– Sales targeting?– Annual budget?– Cash flow?– Production planning?– Inventory requirements?
Long-term
Short-term
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Syncron Demand Forecast Process
• Calculates future forecasts based on the demand history
and the latest demand.
• Checks for any change in the pattern of demand.
• Detects increasing or decreasing trends in demand.
• Measures and reports on the accuracy of the forecasts
including the impact of manual adjustments.
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Elements Of Syncron Forecasting
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Cyclical
variation
External factors
FORECAST COMPONENTS FORECAST COMPONENTS
Trend
Forecast Components
Base level
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Forecasting Demand
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LUMPY SLOW ERRATIC
FAST NEGATIVE TREND
NEW DYING OBSOLETE
Demand Patterns
Trend
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Forecast Error
• All forecasts are single point estimates
• Demand is usually random
• Hence, forecasts always have error
• Forecast error = actual demand - forecast
• Most important to forecast the error
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Trigg’s Tracking Signal
• Notifies the user of items where the forecast is no longer keeping track of actual demand.
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Seasonality
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• Time of year
• Public holidays
• Sales effort
• Annual price
increase
• Catalogue issue
YEARONE
YEARTWO
Causes Of Seasonality
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Volume Density
• The volume density facility allows you to define density factors on a calendar basis, and to adjust the demands, forecasts and hence recommended orders to take account of these factors.
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1997 1998 1999 2000 2001
Volume Density
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1997 1998 1999 2000 2001
Volume Density
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Volume Density
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CHANGE OF DEMAND TYPE
0102030405060708090
100
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
EastWestNorth
FAST ERRATIC LUMPY
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Exceptional Demands
0
10
20
30
40
50
60
1 3 5 7 9 11 13 15 17 19 21 23
Period
Dem
and
Flier?Flier?
If a demand is unusually high or low and unlikely to be repeated, do not use to update forecast
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STEPCHANGE
0
10
20
30
40
50
60
70
80
90
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
STEPCHANGE
AUTOMATIC RE-INITIALISATIONCONSECUTIVE FLIERS
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• User knowledge
• Statistical
monitoring
• Allocation to
similar seasonal
group
• Pre launch
• Supersession
New Products
NEW
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USERESTIMATE
NEW PRODUCTPROCESSING
CURRENT PERIODLAUNCH PERIOD
PRE-LAUNCH PRODUCTS
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USERESTIMATE
MOVINGAVERAGE
STANDARDSYNCRON
MOVING AVERAGE
NEW PRODUCT INITIALISE
NEW PRODUCTS
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REPORT DESIGN
SELECTION CRITERIA
SORTING
ARITHMETIC FUNCTIONS
GRAPHICS
DATA TRANSFERS
STORED PROCEDURES
REPORT DESIGN
SELECTION CRITERIA
SORTING
ARITHMETIC FUNCTIONS
GRAPHICS
DATA TRANSFERS
STORED PROCEDURES
USER REPORT 1
USER REPORT 1
USER REPORT 2
USER REPORT 2
USER REPORT 3
________________________________________________________________________________________________________________________________
USER REPORT 3
________________________________________________________________________________________________________________________________
SYNCRON FILES
SYNCRON FILES
REPORT GENERATOR
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Management By Exception Reports
Powerful exception reports focus management attention on items where:
– Exceptional demand last period
– Tracking signal indicates rapid change of demand level
– Strong positive trend
– Negative trend
– Demand class improved or deteriorated
– Forecasts amended by management
Essential for large inventories
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Manual Intervention
• Forecast
adjustments
• Reason codes
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Inventory Basic ConceptsReplenishment Systems
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Basic Systems In Stock Control
When to order?
How much to order?
Basic systems provide answers to the questions:
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• Fixed order quantity
• Fixed order cycle
• Min/max system
Basic Systems For Stock Control
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TIME
THE FIXED ORDER QUANTITY SYSTEM
**REORDERQUANTITY (Q)
LEAD TIME(L)
MAXIMUM RATE OF USAGEWITHOUT STOCK-OUT
Q Q
STOCK LEVEL
*REORDER LEVELPOINT (A)
EXPECTED RATEOF USAGE (R)
BUFFER STOCKLEVEL
*ROL= Forecast over lead -time + buffer stock
**ROQ can be determined by EOQ or Coverage Analysis
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THE FIXED ORDER CYCLE SYSTEM
*ORDER UP TO LEVEL
**REORDER QUANTITY
Q1
STOCK LEVEL
BUFFER STOCKLEVEL
TIME
Q2
Q2
Q3
Q3
LEAD TIME (L)
LEAD TIME (L)
REVIEW PERIOD (T)
REVIEW PERIOD (T)
Cover period
**REORDER QUANTITY
*OL=Forecast of Demand in cover period + Buffer Stock**ROQ=Order Level-Effective Stock + Back Orders
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The Inventory Process
• The Syncron inventory process recalculates the
following inventory values for each product using
the latest forecast and associated adjustments
– VAU class
– Inventory control type
– Review time
– Buffer stock
– Order level
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Turnover
Products
VALUE OF ANNUAL USAGE THE 80 - 20 RULE
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EXAMPLE VAU ANALYSIS
VAU CLASS ORDERS PERYEAR
MIN VAU MAX VAU
A1 24 99001A2 18 50001 99000A3 12 30001 50000A4 10 20001 30000B1 8 11001 20000B2 6 6001 11000B3 4 3001 6000B4 3 1501 3000C1 2 501 1500C2 1 0 500
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ABC Classification
• Basis for an ordering policy
• Guide to the relative importance of a product to the business
• Allows for effective resource management appropriate for a products importance
• Means of balancing inventory cost against risk to service
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Multi Dimensional Pareto Analysis
To separate high volume, low
valuefrom
low volume, high value
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Overview of Multi-Pareto Process
• The process works by automatically
allocating products to different
parameter sets as well as by VAU
– Volume (up to 5 different classes)
– Frequency (up to 5 different classes)
– Importance (up to 3 different classes)
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Order level for a product is an order up to level
and the value is used to determine whether an
order needs to be placed and how much to
order.
It is also used to ensure a pre-determined level
of service to the customer.
Order Level
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Customer Demand Variability
Month
Dem
an
d
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MANAGING FORECAST ERROR THE OPTIONS
MonthD
em
an
d
BUFFER STOCK
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MANAGING FORECAST ERROR THE OPTIONS
Month
Dem
an
d
BUFFER STOCK
Lead timeReview timeTarget service levelAverage demandVariability of demandBatch size
94.00 95.00 96.00 97.0012.45 13.16 13.99 15.02
223.20 186.00 148.80 111.60235.65 199.16 162.79 126.62
93 94 95 96 97 98 99 100
Target service level
Val
ue
of s
tock
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MANAGING FORECAST ERROR THE OPTIONS
Month
De
ma
nd
BUFFER STOCK EXPEDITE
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MANAGING FORECAST ERROR THE OPTIONS
Month
De
ma
nd
BUFFER STOCK EXPEDITE
Take exceptional action to meet customer demand when there is insufficient stock on hand
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MANAGING FORECAST ERROR THE OPTIONS
Month
De
ma
nd
BUFFER STOCK EXPEDITE
SPARE PRODUCTION
CAPACITY
MAKE THECUSTOMER
WAIT
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MANAGING FORECAST ERROR THE OPTIONS
Month
De
ma
nd
BUFFER STOCK EXPEDITE
SPARE PRODUCTION
CAPACITY
MAKE THECUSTOMER
WAITShort deliver?Make to order?
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• Forecast accuracy
• Target service level
• Replenishment frequency
• Lead time
• Seasonality
Buffer StockBuffer stock is the amount of safety stock that must be held in order to cover random
variations in demand or usage, based on the required service level.
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Control Of Slow Moving StockCharacteristics: -
• Many periods with zero demand
• Average demand per period is relatively small
Problems: -
• Sales or demand pattern cannot be approximated to a ‘normal distribution’ safety stock calculation cannot be based on standard deviation
• Insufficient data to forecast by exponential smoothing or moving average techniques
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Procedure For Controlling Slow-Moving Stocks
• Estimate total annual sales in appropriate units
• Estimate lead time to replace stocks
• Calculate average sales over the lead time
• Set the required service level over the lead time
• From cumulative Poisson distribution find stock level needed to meet target service level
• When an issue occurs order replacement equal to size of issue
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Order Levels Based On Poisson Distribution
Average demandduring lead time
Target service level:
90% 95% 99% 99.90%
0.50 1 2 3 40.60 2 2 3 40.70 2 2 3 40.80 2 2 3 50.90 2 3 4 51.00 2 3 4 51.20 3 3 4 61.40 3 4 5 61.60 3 4 5 71.80 4 4 6 72.00 4 5 6 8
Order levels
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The Role Of Stocks In Manufacturing
THE
CUSHION
TYPICAL SOURCES OF
SUPPLYSTOCKS THE
CUSTOMERDEMAND
Stocks decouple successive operations in the supply chain and reduces expediting
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Purchase Order Management
The Key Cost Factors
• Ordering costs
• Set-up costs
• Stock holding costs
• Stockout costs
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Economic Order QuantityECONOMIC ORDER QUANTITY
0
500
1000
1500
2000
1000 1500 2000 2500 3000
Order Quantity
Cost
Minimum cost
EOQTotal cost curve very shallow either side of EOQ - very insensitive
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Problems With EOQ Approach
Problems can be caused by:
• Difficulties in estimating ordering costs
• Difficulties in estimating true holding cost of an item at any given time
• Assumption of linear relationships between:
– Ordering costs and number of goods– Holding costs and number of units held in
stock
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Coverage Analysis
The objective of coverage analysis is to identify
the optimum ordering frequency for each
product within a group to minimise the
overall turnover stock capital investment.
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Coverage Analysis Example
COVERAGE ANALYSIS
Stock Annual No. of item Value Usage orders
£ placed annually
A 1.00 100 4 B 0.10 100000 5 C 3.00 300 5
Totals: 14
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Coverage Analysis Example
COVERAGE ANALYSIS
Stock Annual No. of item Value Usage orders
£ placed Buffer annually stock
A 1.00 100 4 10 B 0.10 100000 5 10000 C 3.00 300 5 30
Totals: 14
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Coverage Analysis Example
COVERAGE ANALYSIS
Stock Annual No. of Value item Value Usage orders of
£ placed Buffer Annual annually stock Usage
A 1.00 100 4 10 100 B 0.10 100000 5 10000 10000 C 3.00 300 5 30 900
Totals: 14 11000
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Coverage Analysis Example
COVERAGE ANALYSIS
Square Stock Annual No. of Value root of item Value Usage orders of annual
£ placed Buffer Annual usage annually stock Usage value
A 1.00 100 4 10 100 10 B 0.10 100000 5 10000 10000 100 C 3.00 300 5 30 900 30
Totals: 14 11000 140
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Coverage Analysis Example
COVERAGE ANALYSIS
Square No. of ordersStock Annual No. of Value root of pro rata toitem Value Usage orders of annual square root
£ placed Buffer Annual usage of annualannually stock Usage value usage value
A 1.00 100 4 10 100 10 1B 0.10 100000 5 10000 10000 100 10C 3.00 300 5 30 900 30 3
Totals: 14 11000 140 14
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Coverage Analysis Example
COVERAGE ANALYSIS
Stock Annual No. of item Value Usage orders Average Average Average
£ placed Buffer order stock stockannually stock quantity (units) (value)
A 1.00 100 4 10 25 22.5 22.50B 0.10 100000 5 10000 20000 20000 2000.00C 3.00 300 5 30 60 60 180.00
Totals: 14 2202.50
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Coverage Analysis Example
COVERAGE ANALYSIS
Stock Annual No. of item Value Usage orders Average Average Average
£ placed Buffer order stock stockannually stock quantity (units) (value)
A 1.00 100 1 10 100 60 60.00B 0.10 100000 10 10000 10000 15000 1500.00C 3.00 300 3 30 100 80 240.00
Totals: 14 1800.00
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Coverage Analysis
Stock Stock capital Stock capitalItem under present policy under proposed policy
£ £annually
A 22.50 60B 2000.00 1500C 180.00 240
Totals: 2205.50 1800
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Coverage Analysis
Stock Number Stock capitalitem of orders under proposed policy
£
A 2 35B 20 1250C 6 165
Totals: 28 1450
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The Coverage Curve
PRESENT POSITION
OPTIMUM CURVE
TOTAL SET-UPS PER YEAR
0 10 20 30 40
STOCKCAPITAL
**
****
** **
PRESENT NUMBEROF SET-UPS
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URGENCY FACTOR
URGENCY FACTOR
STOCK REPLENISHME
NT
STOCK REPLENISHME
NT
RECOMMENDED ORDERS
RECOMMENDED ORDERS
PURCHASE ORDER
MANAGEMENT
PURCHASE ORDER
MANAGEMENT
Stock Replenishment
FORECAST
BUFFER STOCK
ORDERING POLICY
STOCK DETAILS
CONSTRAINTS
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Stock Replenishment
• Determines whether or not an order should be
placed and recommends when and how much
stock to order for the current period.
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•Order scheduling runs the stock replenishment
process repeatedly for a given number of periods.
•Calculates a time phased schedule of future orders
according to the constraints of the business.
•Series of period end stocks is recommended.
Order Scheduling
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DEMAND FORECAST
ORDER SCHEDULE
Order Scheduling
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Model 1 – Consolidate Demand
Warehouse forecasts
and stock levels based
on total Branch demand
No forecast
adjustments are
transferred from
Branches
Branch forecasts and order
schedules based on local
demand
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Model 2 - Consolidate Actual Orders
Warehouse forecasts
and stock levels based
on actual Branch orders
Branch forecasts and order
schedules based on local
demand
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Model 3 – Consolidate Forecasts
Warehouse forecasts
and stock levels based
on summarised Branch
forecasts
Batch quantities are not
considered
Branch forecasts and order
schedules based on local
demand
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Model 4 – Consolidate Order Plans
Branch forecasts and order
schedules based on local
demand
Warehouse forecasts
and stock levels based
on summarised Branch
order schedules
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Model 5 - Supply Network
Warehouse forecasts and stock levels based
on Branch and independent data
Each Warehouse supplies to the other warehouses, for a
range of products
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Model 6 – Virtual Stock
Pro-rata global stock levels based on
local demand
Global forecasts and
global stock levels
based on total Branch
demand
Stock is assumed to
move between
locations
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• System configuration
• Retrospective
simulation
• What if analysis
Modelling To Reduce Uncertainty
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TURNOVER
PRODUCT
S
System ConfigurationValue Of Annual Usage
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A
B
CLOW SERVICE HIGH SERVICE
System ConfigurationTarget Service Level
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92% 94% 96% 98% 100%
What If Analysis
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• Appoint project manager(s)
• Agree project plan
• Build and test the interfaces
• Set system parameters
• Agree operational rollout
Implementation
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Range Of Training Courses• User training at all
levels
• Technical and author courses
• Senior management awareness programme
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• Support hotline 9 - 18:00
• High quality documentation
• 24 hour 7 day week capability
• Active user group
Support
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