Nikos Iosif International Business Development, MANTIS

Nikos Iosif

International Business Development, MANTIS

• 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

Production Planning& Scheduling

Replenishment PlanningDemand Forecasting

Executive Information

Systems

Supply Flow Management

Modelling and

Simulation

Syncron B2B

OUR SUPPLY CHAIN VISION

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


You can make earlier decisions in conjunction with your partners next


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

• 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 ?

Forecasting

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

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

Cyclical

variation

External factors

FORECAST COMPONENTS FORECAST COMPONENTS

Trend

Forecast Components

Base level

Forecasting Demand

LUMPY SLOW ERRATIC

FAST NEGATIVE TREND

NEW DYING OBSOLETE

Demand Patterns

Trend

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

• Time of year

• Public holidays

• Sales effort

• Annual price

increase

• Catalogue issue

YEARONE

YEARTWO

Causes Of Seasonality

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.

1997 1998 1999 2000 2001

Volume Density

1997 1998 1999 2000 2001

Volume Density

Volume Density

CHANGE OF DEMAND TYPE

0102030405060708090

100

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

EastWestNorth

FAST ERRATIC LUMPY

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

STEPCHANGE

0

10

20

30

40

50

60

70

80

90

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

STEPCHANGE

AUTOMATIC RE-INITIALISATIONCONSECUTIVE FLIERS

• User knowledge

• Statistical

monitoring

• Allocation to

similar seasonal

group

• Pre launch

• Supersession

New Products

NEW

USERESTIMATE

NEW PRODUCTPROCESSING

CURRENT PERIODLAUNCH PERIOD

PRE-LAUNCH PRODUCTS

USERESTIMATE

MOVINGAVERAGE

STANDARDSYNCRON

MOVING AVERAGE

NEW PRODUCT INITIALISE

NEW PRODUCTS

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

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 ConceptsReplenishment Systems

Basic Systems In Stock Control

When to order?

How much to order?

Basic systems provide answers to the questions:

• Fixed order quantity

• Fixed order cycle

• Min/max system

Basic Systems For Stock Control

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

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

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

Turnover

Products

VALUE OF ANNUAL USAGE THE 80 - 20 RULE

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

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

valuefrom

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 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

Customer Demand Variability

Month

Dem

an

d

MANAGING FORECAST ERROR THE OPTIONS

MonthD

em

an

d

BUFFER STOCK


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


Month

De

ma

nd

BUFFER STOCK EXPEDITE


Month

De

ma

nd


Take exceptional action to meet customer demand when there is insufficient stock on hand


Month

De

ma

nd


SPARE PRODUCTION

CAPACITY

MAKE THECUSTOMER

WAIT


Month

De

ma

nd


SPARE PRODUCTION

CAPACITY

MAKE THECUSTOMER

WAITShort deliver?Make to order?

• 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.

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

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 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

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

Purchase Order Management

The Key Cost Factors

• Ordering costs

• Set-up costs

• Stock holding costs

• Stockout costs

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

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 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


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


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


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


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


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


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

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

Coverage Analysis

Stock Number Stock capitalitem of orders under proposed policy

£

A 2 35B 20 1250C 6 165

Totals: 28 1450

The Coverage Curve

PRESENT POSITION

OPTIMUM CURVE

TOTAL SET-UPS PER YEAR

0 10 20 30 40

STOCKCAPITAL

**

****

** **

PRESENT NUMBEROF SET-UPS

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

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 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

Order Scheduling

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

Model 2 - Consolidate Actual Orders

Warehouse forecasts


on actual Branch orders



demand

Model 3 – Consolidate Forecasts

Warehouse forecasts


on summarised Branch

forecasts

Batch quantities are not

considered



demand

Model 4 – Consolidate Order Plans



demand

Warehouse forecasts


on summarised Branch

order schedules

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

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

• System configuration

• Retrospective

simulation

• What if analysis

Modelling To Reduce Uncertainty

TURNOVER

PRODUCT

S

System ConfigurationValue Of Annual Usage

A

B

CLOW SERVICE HIGH SERVICE

System ConfigurationTarget Service Level

92% 94% 96% 98% 100%

What If Analysis

• Appoint project manager(s)

• Agree project plan

• Build and test the interfaces

• Set system parameters

• Agree operational rollout

Implementation

Range Of Training Courses• User training at all

levels

• Technical and author courses

• Senior management awareness programme

• Support hotline 9 - 18:00

• High quality documentation

• 24 hour 7 day week capability

• Active user group

Support

Documents

Nikos Iosif International Business Development, MANTIS