Transcript Document

Nikos Iosif
International Business Development, MANTIS
Some Of Our Customers
•
Fuji Film Sverige AB
•
Pharmacia
•
Esab
•
•
British Aerospace
•
Gec-Marconi aerospace
MK Electric
•
General Motors
•
CPC Foods
•
Mazda Motor Parts Europe
•
Lucent Technologies
•
Messier-Bugatti Aerospace
•
Donaldson
•
Halfords
•
Messier Dowty Aerospace
•
The Wilkinson group
•
Smiths Industries
•
Sketchley
•
Volkswagen Group Service
•
Superquinn
•
Volvo VCE
•
Alcro Beckers
•
NATO Supply Agency
•
Meria Nova Oy
•
Carlsberg Tetley
•
MAN Bus & Trucks
•
Get
•
Porsche
•
Technocar SEAT
•
Abbey National Bank plc
•
Electrolux Outdoor
Products
•
Euronet
•
Electrolux Professional
•
British Gas Transco
•
Viamar Skoda
•
British Gas Services
•
Scottish Hydro Electric
Supply Flow Management
Modelling and Simulation
Production Planning
& Scheduling
Executive Information Systems
Replenishment Planning
Demand Forecasting
Syncron B2B
OUR SUPPLY CHAIN VISION
Syncron - Supply Chain Management
Are you operating in isolation rather than in partnership?
next
Syncron - Supply Chain Management
Do you still focus on local optimisation with limited visibility?
next
Syncron - Supply Chain Management
You can make earlier decisions in conjunction with your partners
next
What’s the Difference ?
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 ?
ERP
• Issues purchase orders
SCM
• Calculates optimal purchase order quantity
and timing
• Reports on-hand inventory levels
• Determines right product, right place, right
time, right quantity
• Archives actual order & shipment
history
• Issues stock replenishment orders
• Uses historical and current order information
to predict customer demand
• Optimally calculates timing and quantity of
replenishments
• Issues work orders to shop floor
• Creates detailed capacity, labor and material
constrained works order schedules
• Collaborative business planning
• Alerting & exception management based on
business rules
Forecasting
Purpose Of Forecast
• What decisions will be made as a
result of the forecast?
–Company corporate planning?
Long-term
–Capacity planning?
–Manpower planning?
–Sales targeting?
–Annual budget?
–Cash flow?
–Production planning?
Short-term
–Inventory requirements?
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.
Elements Of Syncron
Forecasting
Forecast Components
Cyclical
variation
Base level
FORECAST COMPONENTS
Trend
External
factors
Forecasting Demand
Demand Patterns
LUMPY
SLOW
FAST
Trend
NEW
DYING
ERRATIC
NEGATIVE TREND
OBSOLETE
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
Trigg’s Tracking Signal
• Notifies the user of items where the
forecast is no longer keeping track of
actual demand.
Seasonality
Causes Of Seasonality
• Time of year
• Public holidays
• Sales effort
• Annual price
increase
YEAR
ONE
• Catalogue issue
YEAR
TWO
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.
Volume Density
1997
1998
1999
2000
2001
Volume Density
1997
1998
1999
2000
2001
Volume Density
CHANGE OF DEMAND TYPE
100
FAST
90
80
70
60
50
40
30
20
10
0
ERRATIC
LUMPY
East
West
North
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
Exceptional Demands
If a demand is unusually high or low and unlikely to be
repeated, do not use to update forecast
60
50
Flier?
Demand
40
30
20
10
0
1
3
5
7
9
11
13
15
Period
17
19
21
23
AUTOMATIC RE-INITIALISATION
CONSECUTIVE FLIERS
90
STEP
80
CHANGE
70
60
STEP
CHANGE
50
40
30
20
10
0
1st Qtr
2nd Qtr
3rd Qtr
4th Qtr
New Products
• User knowledge
NEW
• Statistical
monitoring
• Allocation to
similar seasonal
group
• Pre launch
• Supersession
PRE-LAUNCH PRODUCTS
NEW PRODUCT
PROCESSING
USER
ESTIMATE
LAUNCH PERIOD
CURRENT PERIOD
NEW PRODUCTS
USER
ESTIMATE
MOVING
AVERAGE
MOVING
AVERAGE
STANDARD
SYNCRON
NEW PRODUCT
INITIALISE
REPORT GENERATOR
REPORT DESIGN
SELECTION CRITERIA
SORTING
ARITHMETIC
FUNCTIONS
SYNCRON
FILES
GRAPHICS
DATA TRANSFERS
STORED PROCEDURES
USER REPORT 1
USER REPORT 2
USER REPORT 3
________________
________________
________________
________________
________________
________________
________________
________________
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
Manual Intervention
• Forecast
adjustments
• Reason codes
Inventory Basic Concepts
Replenishment Systems
Basic Systems In Stock Control
Basic systems provide answers to the questions:
When to order?
How much to order?
Basic Systems For Stock
Control
• Fixed order quantity
• Fixed order cycle
• Min/max system
THE FIXED ORDER QUANTITY SYSTEM
**REORDER
QUANTITY (Q)
STOCK
LEVEL
MAXIMUM RATE OF USAGE
WITHOUT STOCK-OUT
...
. ...
. ..
Q . ...
Q
..
.
..
.
..
.
..
.
..
..
.
.
.. .
LEAD TIME . .. .
.. .
(L)
TIME
*ROL= Forecast over lead -time + buffer stock
**ROQ can be determined by EOQ or Coverage Analysis
*REORDER LEVEL
POINT (A)
EXPECTED RATE
OF USAGE (R)
BUFFER STOCK
LEVEL
THE FIXED ORDER CYCLE SYSTEM
*ORDER UP TO LEVEL
Q3
**REORDER
QUANTITY
STOCK
LEVEL
**REORDER
QUANTITY
Q3
Q2
Q1
.
.
.
.
.
.
.
.
.
.
Q2
.
.
.
Cover period
.
.
.
.
.
. LEAD TIME (L)
LEAD TIME (L)
.
.
.
REVIEW
PERIOD (T)
TIME
REVIEW
PERIOD (T)
*OL=Forecast of Demand in cover period + Buffer Stock
**ROQ=Order Level-Effective Stock + Back Orders
BUFFER STOCK
LEVEL
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
VALUE OF ANNUAL USAGE
THE 80 - 20 RULE
Products
Turnover
EXAMPLE VAU ANALYSIS
VAU CLASS
A1
A2
A3
A4
B1
B2
B3
B4
C1
C2
ORDERS PER
YEAR
24
18
12
10
8
6
4
3
2
1
MIN VAU
MAX VAU
99001
50001
30001
20001
11001
6001
3001
1501
501
0
99000
50000
30000
20000
11000
6000
3000
1500
500
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
Multi Dimensional Pareto
Analysis
To separate
high volume, low value
from
low volume, high value
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)
Order Level
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.
Demand
Customer Demand Variability
Month
MANAGING FORECAST ERROR
THE OPTIONS
Demand
BUFFER STOCK
Month
MANAGING FORECAST ERROR
THE OPTIONS
BUFFER STOCK
Month
95. 00
13. 16
186. 00
199. 16
96.
13.
148.
162.
00
99
80
79
97. 00
15. 02
111. 60
126. 62
Value of stock
Demand
Lead time
Review time
Target service level
Average demand
Variability of demand
Batch size
94. 00
12. 45
223. 20
235. 65
93
94
95
96
97
98
99
Target service level
100
MANAGING FORECAST ERROR
THE OPTIONS
EXPEDITE
Demand
BUFFER STOCK
Month
MANAGING FORECAST ERROR
THE OPTIONS
BUFFER STOCK
Demand
EXPEDITE
Month
Take exceptional
action to meet
customer demand
when there is
insufficient
stock on hand
MANAGING FORECAST ERROR
THE OPTIONS
BUFFER STOCK
Demand
EXPEDITE
Month
SPARE
PRODUCTION
CAPACITY
MAKE THE
CUSTOMER
WAIT
MANAGING FORECAST ERROR THE
OPTIONS
BUFFER STOCK
Demand
EXPEDITE
Month
SPARE
PRODUCTION
CAPACITY
Short deliver?
Make to order?
MAKE THE
CUSTOMER
WAIT
Buffer Stock
Buffer 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.
• Forecast
accuracy
• Target service
level
• Replenishment
frequency
• Lead time
• Seasonality
Control Of Slow Moving Stock
Characteristics: • 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
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
Order Levels Based On Poisson
Distribution
Average demand
during lead time
0.50
0.60
0.70
0.80
0.90
1.00
1.20
1.40
1.60
1.80
2.00
Target service level:
90%
95%
1
2
2
2
2
2
3
3
3
4
4
2
2
2
2
3
3
3
4
4
4
5
Order levels
99%
3
3
3
3
4
4
4
5
5
6
6
99.90%
4
4
4
5
5
5
6
6
7
7
8
The Role Of Stocks In Manufacturing
TYPICAL
SOURCES OF
SUPPLY
STOCKS
THE
CUSTOMER
DEMAND
THE
CUSHION
Stocks decouple successive operations in the supply chain and reduces expediting
Purchase Order Management
The Key Cost Factors
• Ordering costs
• Set-up costs
• Stock holding costs
• Stockout costs
Economic Order Quantity
ECONOMIC ORDER QUANTITY
2000
Cost
1500
Minimum cost
1000
500
0
1000
EOQ
1500
2000
2500
Order Quantity
Total cost curve very shallow either side of EOQ
- very insensitive
3000
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
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.
Coverage Analysis Example
COVERAGE ANALYSIS
Stock
Annual
item Value Usage
£
A
B
C
No. of
orders
placed
annually
1.00
100
0.10 100000
3.00
300
4
5
5
Totals:
14
Coverage Analysis Example
COVERAGE ANALYSIS
Stock
Annual
item Value Usage
£
A
B
C
No. of
orders
placed Buffer
annually stock
1.00
100
0.10 100000
3.00
300
4
5
5
Totals:
14
10
10000
30
Coverage Analysis Example
COVERAGE ANALYSIS
Stock
Annual
item Value Usage
£
A
B
C
No. of
Value
orders
of
placed Buffer Annual
annually stock Usage
1.00
100
0.10 100000
3.00
300
4
5
5
Totals:
14
10
10000
30
100
10000
900
11000
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
B
C
1.00
100
0.10 100000
3.00
300
4
5
5
Totals:
14
10
10000
30
100
10000
900
10
100
30
11000
140
Coverage Analysis Example
COVERAGE ANALYSIS
Square No. of orders
Stock
Annual No. of
Value root of
pro rata to
item Value Usage orders
of
annual square root
£
placed Buffer Annual usage
of annual
annually stock Usage value usage value
A
B
C
1.00
100
0.10 100000
3.00
300
4
5
5
Totals:
14
10
10000
30
100
10000
900
10
100
30
1
10
3
11000
140
14
Coverage Analysis Example
COVERAGE ANALYSIS
Stock
Annual
item Value Usage
£
A
B
C
No. of
orders
Average Average
placed Buffer order
stock
annually stock quantity (units)
1.00
100
0.10 100000
3.00
300
4
5
5
Totals:
14
10
10000
30
25
20000
60
22.5
20000
60
Average
stock
(value)
22.50
2000.00
180.00
2202.50
Coverage Analysis Example
COVERAGE ANALYSIS
Stock
Annual
item Value Usage
£
A
B
C
No. of
orders
Average Average
placed Buffer order
stock
annually stock quantity (units)
1.00
100
0.10 100000
3.00
300
1
10
3
Totals:
14
10
10000
30
100
10000
100
60
15000
80
Average
stock
(value)
60.00
1500.00
240.00
1800.00
Coverage Analysis
Stock
Stock capital
Stock capital
Item under present policy under proposed policy
£
£
annually
A
B
C
22.50
2000.00
180.00
60
1500
240
Totals:
2205.50
1800
Coverage Analysis
Stock
item
Number
of orders
Stock capital
under proposed policy
£
A
B
C
2
20
6
35
1250
165
Totals:
28
1450
The Coverage Curve
PRESENT NUMBER
OF SET-UPS
STOCK
CAPITAL
*
PRESENT POSITION
*
* *
0
10
TOTAL SET-UPS PER YEAR
20
OPTIMUM CURVE
*
30
40
Stock Replenishment
FORECAST
BUFFER STOCK
ORDERING POLICY
URGENCY
FACTOR
STOCK
REPLENISHMENT
RECOMMENDED
ORDERS
STOCK DETAILS
PURCHASE
ORDER
MANAGEMENT
CONSTRAINTS
Stock Replenishment
• Determines whether or not an order should be
placed and recommends when and how much
stock to order for the current period.
Order Scheduling
•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
DEMAND FORECAST
ORDER SCHEDULE
Model 1 – Consolidate Demand
No forecast adjustments are
Warehouse forecasts and stock
levels based on total Branch
demand
Branch forecasts and order schedules
based on local demand
transferred from Branches
Model 2 - Consolidate Actual Orders
Warehouse forecasts and stock
levels based on actual Branch
orders
Branch forecasts and order schedules
based on local demand
Model 3 – Consolidate Forecasts
Batch quantities are not
Warehouse forecasts and stock
levels based on summarised
Branch forecasts
Branch forecasts and order schedules
based on local demand
considered
Model 4 – Consolidate Order Plans
Warehouse forecasts and stock
levels based on summarised
Branch order schedules
Branch forecasts and order schedules
based on local demand
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
Model 6 – Virtual Stock
Global forecasts and global
Stock is assumed to move
stock levels based on total
between locations
Branch demand
Pro-rata global stock levels based on local demand
Modelling To Reduce Uncertainty
• System
configuration
• Retrospective
simulation
• What if analysis
System Configuration
Value Of Annual Usage
PRODUCTS
TURNOVER
System Configuration
Target Service Level
A
B
C
LOW SERVICE
HIGH SERVICE
What If Analysis
92%
94%
96%
98%
100%
Implementation
• Appoint project
manager(s)
• Agree project plan
• Build and test the
interfaces
• Set system
parameters
• Agree operational
rollout
Range Of Training Courses
• User training at all
levels
• Technical and
author courses
• Senior
management
awareness
programme
Support
• Support hotline 9 -
18:00
• High quality
documentation
• 24 hour 7 day
week capability
• Active user group