• Class 5: (Feb 7): Chap 11 (Inventory Management , Forecasting, Chapter 10 – Just in Time/Lean/TOC)

• Class 6: (Feb 14): Research for Presentations• February 21 No Class• Class 7: (Feb 28) Supplemental Readings

(Reverse Logistics – need “The Forklifts Have Nothing To Do!” Available in the Lewis and Clark Bookstore); Supply Chain Security, Take home final exam

• Class 8: (Mar 7) Group presentations; Final Due

New Syllabus

ForecastinForecastingg

How far into the future do you typically project when trying to forecast the health of your industry? ]less than 4 months 3%]4-6 months 12%

]7-12 months 28% ]> 12 months 57%

Forecasting Survey

Fortune Council survey, Nov 2005

Consumer price index 51%Consumer Confidence index 44%Durable goods orders 20%Gross Domestic Product 35%Manufacturing and trade inventories and

sales 27%Price of oil/barrel 34%Strength of US $ 46%Unemployment rate 53%Interest rates/fed funds 59%

Indices to forecast health of industry

Fortune Council survey, Nov 2005

Improving customer demand forecasting and sharing the information downstream will allow more efficient scheduling and inventory management

Boeing, 1987: $2.6 billion write down due to “raw material shortages, internal and supplier parts shortages” Wall Street Journal, Oct 23, 1987

Forecasting Importance

“Second Quarter sales at US Surgical Corporation decline 25%, resulting in a $22 mil loss…attributed to larger than anticipated inventories on shelves of hospitals.” US Surgical Quarterly, Jul 1993

“IBM sells out new Aetna PC; shortage may cost millions in potential revenue.” Wall Street Journal, Oct 7, 1994

Forecasting Importance

Forecasts are usually wrong every forecast should include an

estimate of error Forecasts are more accurate for

families or groups Forecasts are more accurate for nearer

periods.

Principles of Forecasting

• Record Data in the same terms as needed in the forecast – production data for production forecasts; time periods

• Record circumstances related to the data• Record the demand separately for different

customer groups

Important Factors to Improve Forecasting

• Extrinsic Techniques – projections based on indicators that relate to products – examples

• Intrinsic – historical data used to forecast (most common)

Forecast Techniques

Forecasting errors can increase the total cost of ownership for a product - inventory carrying costs

- obsolete inventory- lack of sufficient inventory- quality of products due to

accepting marginal products to prevent stockout

Forecasting

• Essential for smooth operations of business organizations

• Estimates of the occurrence, timing, or magnitude of uncertain future events

• Costs of forecasting: excess labor; excess materials; expediting costs; lost revenues

Forecasting

Forecasting• Predicting future events• Usually demand behavior

over a time frame• Qualitative methods

• Based on subjective methods

• Quantitative methods• Based on mathematical formulas

Time Frame• Short-range to medium-range

• Daily, weekly monthly forecasts of sales data

• Up to 2 years into the future

• Long-range• Strategic planning of goals,

products, markets• Planning beyond 2 years into

the future

Demand Behavior• Trend

• gradual, long-term up or down movement

• Cycle• up & down movement repeating over

long time frame• Seasonal pattern

• periodic oscillation in demand which repeats

• Random movements follow no pattern

Forms of Forecast Movement

TimeTime(a) Trend(a) Trend

TimeTime(d) Trend with seasonal pattern(d) Trend with seasonal pattern

TimeTime(c) Seasonal pattern(c) Seasonal pattern

TimeTime(b) Cycle(b) Cycle

Dem

and

Dem

and

Dem

and

Dem

and

Dem

and

Dem

and

Dem

and

Dem

and

Random Random movementmovement

Forecasting Methods

• Time series• Regression or causal modeling

• Qualitative methods• Management judgment, expertise,

opinion• Use management, marketing,

purchasing, engineering• Delphi method

• Solicit forecasts from experts

Time Series Methods• Statistical methods using historical data

• Moving average• Exponential smoothing• Linear trend line

• Assume patterns will repeat• Naive forecasts

• Forecast = data from last period

Moving Average

Average several periods of data

Dampen, smooth out changes

Use when demand is stable with no trend or seasonal pattern

Sum of Demand In n Periods

n

Simple Moving Average

JanJan 120120FebFeb 9090MarMar 100100AprApr 7575MayMay 110110JuneJune 5050JulyJuly 7575AugAug 130130SeptSept 110110OctOct 9090

ORDERSORDERSMONTHMONTH PER MONTHPER MONTH

JanJan 120120FebFeb 9090MarMar 100100AprApr 7575MayMay 110110JuneJune 5050JulyJuly 7575AugAug 130130SeptSept 110110OctOct 9090

ORDERSORDERSMONTHMONTH PER MONTHPER MONTH

MAMAnovnov = = 33

==90 + 110 + 13090 + 110 + 130

33

= 110 orders for Nov

Simple Moving Average

Daug+Dsep+Doct

JanJan 120120 ––FebFeb 9090 – –MarMar 100100 – –AprApr 7575 103.3103.3MayMay 110110 88.388.3JuneJune 5050 95.095.0JulyJuly 7575 78.378.3AugAug 130130 78.378.3SeptSept 110110 85.085.0OctOct 9090 105.0105.0NovNov – – 110.0110.0

ORDERSORDERS THREE-MONTHTHREE-MONTHMONTHMONTH PER MONTHPER MONTH MOVING AVERAGEMOVING AVERAGE

Simple Moving Average

JanJan 120120 ––FebFeb 9090 – –MarMar 100100 – –AprApr 7575 103.3103.3MayMay 110110 88.388.3JuneJune 5050 95.095.0JulyJuly 7575 78.378.3AugAug 130130 78.378.3SeptSept 110110 85.085.0OctOct 9090 105.0105.0NovNov – – 110.0110.0

ORDERSORDERS THREE-MONTHTHREE-MONTHMONTHMONTH PER MONTHPER MONTH MOVING AVERAGEMOVING AVERAGE

==90 + 110 + 130 + 75 + 5090 + 110 + 130 + 75 + 5055

= 91 orders for Nov

Simple Moving Average

Simple Moving Average

JanJan 120120 –– – –FebFeb 9090 – – – –MarMar 100100 – – – –AprApr 7575 103.3103.3 – –MayMay 110110 88.388.3 – –JuneJune 5050 95.095.0 99.099.0JulyJuly 7575 78.378.3 85.085.0AugAug 130130 78.378.3 82.082.0SeptSept 110110 85.085.0 88.088.0OctOct 9090 105.0105.0 95.095.0NovNov – – 110.0110.0 91.091.0

ORDERSORDERS THREE-MONTHTHREE-MONTH FIVE-MONTHFIVE-MONTHMONTHMONTH PER MONTHPER MONTH MOVING AVERAGEMOVING AVERAGE MOVING AVERAGEMOVING AVERAGE

Weighted Moving Average

Adjusts moving average method to more closely reflect data fluctuations

Weighted Moving Average

WMAn = i = 1 Wi Di

where

Wi = the weight for period i, between 0

and 100 percent

Wi = 1.00

Adjusts moving average method to more closely reflect data fluctuations

Weighted Moving Average Example

MONTH WEIGHT DATA

August 17% 130September 33% 110October 50% 90

Weighted Moving Average Example

MONTH WEIGHT DATA

August 17% 130September 33% 110October 50% 90

November forecast

WMA3 = 3

i = 1Wi Di

= (0.50)(90) + (0.33)(110) + (0.17)(130)

= 103.4 orders

3 Month = 110 5 month = 91

• Averaging method • Weights most recent data

more strongly• Reacts more to recent

changes• Widely used, accurate

method

Exponential Smoothing

Ft +1 = Dt + (1 - )Ft

where

Ft +1 =forecast for next period

Dt =actual demand for present period

Ft =previously determined forecast for present period

= weighting factor, smoothing constant

Averaging method

Weights most recent data more strongly

Reacts more to recent changes

Widely used, accurate method

Exponential Smoothing

Forecast = (weighting factor)x(actual demand for period)+(1-weighting factor)x(previously determined forecast for present period)

Forecast for Next Period

0 > <= 1Lesserreactionto recent demand

Greaterreactionto recent demand

Forecast Accuracy

• Find a method which minimizes error

• Error = Actual - Forecast

Forecast Control

Reasons for out-of-control forecasts• Change in trend• Appearance of cycle• Weather changes• Promotions• Competition• Politics

Just-In-Time and and Lean ProductionLean Production

JIT In Services

Competition on speed & qualityCompetition on speed & qualityMultifunctional department store Multifunctional department store

workersworkersWork cells at fast-food restaurantsWork cells at fast-food restaurantsJust-in-time publishing for Just-in-time publishing for

textbooks - on demand publishing textbooks - on demand publishing a growing industrya growing industry

Construction firms receiving Construction firms receiving material just as neededmaterial just as needed

Producing only what is needed, Producing only what is needed, when it is neededwhen it is needed

A philosophy A philosophy An integrated management systemAn integrated management systemJIT’s mandate: JIT’s mandate:

Eliminate all wasteEliminate all waste

What is JIT ?

....

TPS is a production management system that aims for the “ideal” through continuous improvement

Includes, but goes way beyond JIT. Pillars: Synchronization

Reduce transfer batch sizes Level load production Pull production control systems (vs. push): Kanban Quality at source Layout: Cellular operations

Continuous Improvement (Kaizen): through visibility & empowerment

Lean Operations:Best Implementation is Toyota Production System

1. Overproduction

2. Waiting

3. Inessential handling

4. Non-value adding processing

5. Inventory in excess of immediate needs

6. Inessential motion

7. Correction necessitated by defects

Toyota’s waste elimination in Operations

Waste in Operations

Waste in Operations

Waste in Operations

Flexible Resources

Multifunctional workersMultifunctional workersGeneral purpose machinesGeneral purpose machinesStudy operators & improve Study operators & improve

operationsoperations

Pre-planned issues of supplies/merchandise regardless of customer demand criteria

Creates excess and shortages not efficient over the long run

The Push System

The Pull System

Material is pulled through the system when needed

Reversal of traditional push system where material is pushed according to a schedule

Forces cooperationPrevent over and

underproduction

Kanban Production Control System

Kanban card indicates standard quantity of production

Derived from two-bin inventory system

Kanban maintains discipline of pull production

Production kanban authorizes production

Withdrawal kanban authorizes movement of goods

A Sample Kanban

Types of Kanbans Bin Kanban - when bin is empty

replenish Kanban Square

Marked area designed to hold items Signal Kanban

Triangular kanban used to signal production at the previous workstation

Material KanbanUsed to order material in advance of

a process Supplier Kanbans

Rotate between the factory and suppliers

Components of Lead Time

Processing time Reduce number of items or

improve efficiencyMove time

Reduce distances, simplify movements, standardize routings

Waiting time Better scheduling, sufficient

capacitySetup time

Generally the biggest bottleneck

Preset Buttons/settings Quick fasteners Reduce tool requirements Locator pins Guides to prevent misalignment Standardization Easier movement

Common Techniques for Reducing Setup Time

Uniform Production

Results from smoothing production Results from smoothing production requirementsrequirements

Kanban systems can handle +/- 10% Kanban systems can handle +/- 10% demand changesdemand changes

Smooths demand across planning Smooths demand across planning horizonhorizon

Mixed-model assembly steadies Mixed-model assembly steadies component productioncomponent production

Quality at the Source

Jidoka is authority to stop production Jidoka is authority to stop production lineline

Andon lights signal quality problemsAndon lights signal quality problemsUndercapacity scheduling allows for Undercapacity scheduling allows for

planning, problem solving & planning, problem solving & maintenancemaintenance

Visual control makes problems visibleVisual control makes problems visiblePoka-yoke prevents defects (mistake Poka-yoke prevents defects (mistake

proof the system)proof the system)

Kaizen

Continuous improvementContinuous improvementRequires total employment Requires total employment

involvementinvolvementEssence of JIT is willingness of Essence of JIT is willingness of

workers toworkers toSpot quality problemsSpot quality problemsHalt production when necessaryHalt production when necessaryGenerate ideas for improvementGenerate ideas for improvementAnalyze problemsAnalyze problemsPerform different functionsPerform different functions

Goals of JIT

1. Reduced inventory - where?

2. Improved quality3. Lower costs4. Reduced space

requirements5. Shorter lead

time6. Increased

productivity7. Greater

flexibility

8. Better relations with suppliers

9. Simplified scheduling and control activities

10.Increased capacity11.Better use of

human resources12.More product

variety13.Continuous

Process Improvement

Use JIT to finely tune an operating system

Somewhat different in USA than Japan

JIT is still evolving JIT as an inventory reduction

program isn’t for everyone - JIT as a CPI program is!

Some systems need Just-in-Case inventory

JIT Implementation

Chapter 12

Inventory Inventory ManagemenManagementt

The average manufacturing organization spends 53.2% of every sales dollar on raw materials, components, and maintenance repair parts

Inventory Control – how many parts, pieces, components, raw materials and finished goods

Why is Inventory Important to Operations Management?

Accounting – zero inventory Production – surplus inventory or “just in

case” safety stocks Marketing – full warehouses of finished

product Purchasing – caught in the middle trying to

please 3 masters

Inventory Conflict

InventoryStock of items held to meet

future demand Insurance against stock outCoverage for inefficiencies in

systems Inventory management answers

two questions How much to order When to order

Types of Inventory

Raw materials Purchased parts and supplies In-process (partially completed) products Component parts Working capital Tools, machinery, and equipment Safety stock Just-in-case

Transportation Problems

Poor Quality

InventoryAccuracy

Policies

Training

Inventory Hides Inventory Hides ProblemsProblems

1. How much do we have now?2. How much do we want?3. What will be the output?4. What input must we get?

Correctly answering the question about when to order is far more important than determining how much to order.

Aggregate Inventory Management

Inventory Costs

Carrying Cost Cost of holding an item in inventory As high as 25-35% of value Insurance, maintenance, physical inventory, pilferage,

obsolete, damaged, lost Ordering Cost

Cost of replenishing inventory Shortage Cost

Temporary or permanent loss of sales when demand cannot be met

ABC Classification System

Demand volume and value of items vary Classify inventory into 3 categories,

typically on the basis of the dollar value to the firm

PERCENTAGEPERCENTAGE PERCENTAGEPERCENTAGECLASSCLASS OF UNITSOF UNITS OF DOLLARSOF DOLLARS

AA 5 - 155 - 15 70 - 8070 - 80BB 3030 1515CC 50 - 6050 - 60 5 - 105 - 10

Inventory controls Security controls Monetary constraints Storage locations

Why ABC?

Economic OrderQuantity

Assumptions of Basic EOQ Model

Demand is known with certainty and is constant over time

No shortages are allowedLead time for the receipt of orders

is constantThe order quantity is received all

at once

Customer specifies quantity Production run is not limited by equipment

constraints Product shelf life is short Tool/die life limits production runs Raw material batches limit order quantity

No reason to use EOQ if:

EOQ Formula

EOQEOQ = =22CCooDD

CCcc

Co = Ordering costs

D= Annual Demand

Cc = Carrying Costs

Cost per order can increase if size of orders decreases

Most companies have no ideaof actual carrying costs

When to Order

Reorder Point is the level of inventory Reorder Point is the level of inventory at which a new order is placed at which a new order is placed

RR = = dLdL

wherewhere

dd = demand rate per period = demand rate per periodLL = lead time = lead time

Fixed Variable Two Bin Card Judgmental Projected shortfall

Forms of Reorder Points

Accurate Demand Forecast Length of Lead Time Size of order quantities Service level

Why Safety Stock

Cyclic Inventory Annual Inventory Periodic Inventory Sensitive Item Inventory

Inventory Control

Vendor-Managed Inventory

Not a new concept – same process used by bread deliveries to stores for decades

Reduces need for warehousing Increased speed, reduced errors, and improved

service Onus is on the supplier to keep the shelves full or

assembly lines running variation of JIT Proctor&Gamble - Wal-Mart DLA – moving from a manager of supplies to a

manager of suppliers Direct Vendor Deliveries – loss of visibility

Defining stock-keeping units (SKUs) Increase in number of SKUs – 15% over past 3

years Dead inventory Deals Substitute items Complementary items Informal arrangements outside the distribution

channel Repair/replacement parts Reverse logistics

Inventory Management: Special Concerns

No class until 28 Feb Group presentations 7 Mar Final Exam due 8 Mar

What’s Next