SCO 3056: Midterm 1

SCPC System

The essential task is to…

• manage efficiently the flow of materials, the utilization of people and equipment, and to respond to customer requirements by utilizing the capacity of suppliers, internal facilities, and (in some cases) customers to meet customer demand

SCPC System Framework

Front end

• Strategic mission of a SCPC system

• Establishes the overall company direction for supply chain planning and control

• Serves as a long-term decision support

Engine

• Tactical mission of a SCPC system

• Encompasses the set of SCPC systems for detailed material and capacity planning

• Serves as an intermediate-term decision support

Back end

•Operational mission of a SCPC system

•Depicts SCPC execution systems

•Serves as a short-term decision support

Long term support

• Strategic direction decision

• Capacity planning decision (e.g., equipment, facility, suppliers, etc.)

• To meet future market demand

Intermediate-term support

• Matching supply-demand in terms of volume and product mix

• Provides the exact material and production capacity needs

• Providing customers/suppliers information (delivery times, quantities)

 How many?

 Which models?

 Where?

 When?

 Materials?

 Inventory?

 Workforce?

 Suppliers?

 Customers?

Short-term support

• Detailed scheduling of resources to meet production

requirements

• Planning day-to-day activities

• Tracks and reports the daily use of resources and execution

 Timing/schedules

 Materials

 People

 Equipment

 Work centers

ERP (Manager)

ERP is a comprehensive software approach to support decisions concurrent with planning and controlling the business

ERP (IT Community)

 ERP is a term describing a software system that integrates application programs in finance, manufacturing, logistics, sales and marketing, human resources, and other functions in a firm

 Accomplished through a database shared by all the functions and data-processing applications

ERP

• ERP requires consistent measuring across all applications

• There are four aspects of ERP software that determine the quality of an ERP system

 The software should be multifunctional in scope

 The software should be integrated

 The software needs to be modular in structure

 The software must facilitate basic planning and control activities

Transaction Processing

the posting and tracking of the activities that

document the business

 Efficient handling of the transactions as goods move through each step of the process

is the primary goal of an ERP system

Decision support

the system helps the user make intelligent judgments

about how to run the business

 This is a second objective of an ERP system

How ERP Connects the Functional Units

• A typical ERP system is made up of functionally oriented and tightly

integrated modules

• All the modules of the system use a common database that is updated in

real time

• ERP vendors are constantly looking for ways to improve the functionality of

their software, so new features are often added

The Scope of ERP Applications

Typical ERP Modules

• Finance

 Automatic capture of basic accounting transactions at the source

• Manufacturing and Logistics

 Largest and most complex of the module categories

 Typical components include:

Sales and operations planning

Materials management

Plant maintenance

Quality management

Production planning and control

Project management

• Sales and Marketing

 Customer and sales management, forecasting, and so on

• Human Resources

 Supports the need to manage, schedule, pay, hire, and train people

Data Integration

• ERP works from a single database

• Transactions are processed in real time

• Data entered by one functional area updates all other functional areas and

the data are processed in real time

 Eliminates reposting of data (errors)

 Ensures a common vision instantly displayed

• Data warehouse: a special program that is designed to automatically

archive and process data for uses that are outside the basic ERP system

applications

How Supply Chain Planning and Control Fits Within ERP

• ERP is concerned with all aspects of a supply chain

 managing materials

 Scheduling machines and people

 Coordinating suppliers and key customers

• The coordination required for success runs across all functional units in the

firm

 An ERP system is designed to provide the information and decision support needed to

coordinate this

Evaluating System Effectiveness

• An ERP system can provide the data needed for a comprehensive set of

performance measures

 This allows the firm to evaluate strategic alignment of the various functions with the

firm’s strategy

• Three major functional areas make up the internal supply chain of a

manufacturing enterprise

 Purchasing

 Manufacturing

 Sales and distribution

• Tight cooperation is required between these three functions for effective

manufacturing planning and control

Implications if all Three Areas are Allowed to Work Independently

• Purchasing will buy the largest quantities possible

 Result in large amounts of raw material inventory

• Manufacturing group desires to maximize production volumes

 Spread the fixed costs of production over as many units as possible

 Result in high WIP

 Time between batches increases

 Response time to unexpected demand increases

• Distribution will try to fully load every truck

 Minimize transportation cost

 Result in larges amount of inventory in distribution centers

• Sales group might sell product that cannot possibly be delivered on time

Integrated Supply Chain Metrics

• Developed by the APICS Supply Chain Council

• Designed to measure the impact of decisions on the entire supply chain

• Avoids incentives to behave independently by developing metrics that

reflect the entire supply chain

Cash-to-Cash Cycle Time

• Cash-to-cash cycle time: integrates the purchasing, manufacturing, and

sales/distribution cycles

 Calculating the measure requires the use of data related to purchasing, accounting,

manufacturing, and sales

• Is a measure of cash flow

 Where cash comes from

 Where cash is spent

 Net change in cash

• Cash-to-cash cycle time = Inventory days of supply

+ Days of sales outstanding

- Average payment period for material

Integrated ERP Data for Cash-to-Cash

Cycle Time Calculation

Sales & Operations Planning (S&OP)

• An integrated business process that links strategic goals to production in

order to balance supply and demand within a supply chain

• It aims to coordinate various business elements including sales,

marketing, finance, operations, new product development, manufacturing,

and sourcing to derive one integrated plan

• It is performed at least once a month and is reviewed by management at

an “aggregate level”

• It provides the key communication links for top management to coordinate the

various planning activities

The Role of S&OP

• The role of S&OP is to balance supply and demand at the volume (overall sales

rates, production rates, aggregate inventories, and order backlogs) level

Volume

(big picture, product family production rates, etc.)

Mix

(details, individual products)

The Monthly S&OP Process

S&OP Structural Decisions

Who are the S&OP players?

How many product families?

What’s the appropriate unit of measure for

each product family?

Who are the S&OP Players?

• Executive champion/sponsor– senior executive

• S&OP process owner– director of sales administration, demand manager,

materials manager, sales manager, production control manager

• Demand planning team– demand manager, product manager, forecast

analyst, sales manager, salesperson, customer service manager, sales

administration manager, new products coordinator, and S&OP process owner

• Supply planning team– plant manager, materials manager, purchasing

manager, master scheduler, distribution manager, production control

manager, new products coordinator, and S&OP process owner

• Pre-S&OP team– demand manager, materials manager, customer service

manager, forecast analyst, product manager, master scheduler, plant

manager, purchasing manager, controller, new product coordinator, and SIOP

process owner

• Executive S&OP team–upper management representative of each functional

area

S&OP and Communication

The plan must be expressed in

terms that are meaningful to non-

manufacturing executives

The operations portion of the plan

must be stated in terms that

manufacturing functions can use

Communicating S&OP Information–

Displays

Information can be

conveyed in several ways:

Charts (monthly forecast,

cumulative production,

alternative plans)

Tabular displays (easily

captured and

communicated using

spreadsheets)

S&OP Keys to Success

Data integrity

Widely understood and transparent process

Active participation from various parts of the organization

Great communication – especially when something changes or there’s a problem

Top management involvement is imperative in the S&OP process. The S&OP process should relate directly to the strategic plan.

Top Management Role

Commit to the S&OP process

Modify performance measures and reward structures to align with the plan

Force resolution of trade-offs between functions

Lead the cultural change

Functional Roles

What is the

primary

responsibility of

each department

given the

S&OP?

• Hit the plan

And what is the

second most

important

responsibility?

• Communicate

when something

will prevent hitting

the plan

Forecasting

he process of predicting a future event

All forecasts are wrong, but some are useful

 knowing demand enables firms to match supply

• Forecasting is crucial to business decisions

 capacity, scheduling, inventory, advertising, etc

Function of a Forecast

• Marketing: Planning of promotions and pricing

• Operations: Planning of production and procurement, selecting

suppliers, determining capacity requirements, managing inventory

• Strategy: Planning of business expansion/contraction

• Finance: Cash flow planning; coordination with investors,

budgeting

• Human Resources: Hiring/layoffs, seasonal recruiting, training

Forecast Horizon

• Strategic planning (Plan the system)

 Generally involves long-range plans related to:

Types of products and services to offer

Facility and equipment levels

Facility location

• Tactical planning (Plan the use of the system)

 Generally involves short- and medium-range plans related to:

Inventory management

Workforce levels

Purchasing

Production

Budgeting

Scheduling

Time Series

chronologically ordered data that may contain one or more components of demand

• The key idea about time series analysis is that past demand

contains substantial information about future demand

• Forecast based only on past values

 assumes that factors that influenced past will continue to influence

future

Time-Series Decomposition

Average demand: An ‘average’ around which observations

vary.

Trend: A predictable increase or decrease in the level over time.

Seasonality: A pattern of predictable and recurring shifts in the

level.

Random Noise: Unpredictable variations in the demand

pattern.

The Causes of Seasonality

• Annual Seasonality

 Insurance enrollments

 Weather effects

• Quarterly Seasonality

 Textbook purchases

• Monthly Seasonality

 End-of-the month/Payday Effects

• Weekly Seasonality

 Weekend shopping/outdoor

• Daily Seasonality

 Lunch/End-of-Workday Effects

Forecasting Notation

•At : Demand observed in period t

•Ft : Forecast of demand for period t

 i.e. forecast of next period’s demand : Ft+1

Simple Moving Average

• is a series of arithmetic means

• useful when demand is neither growing nor declining rapidly

• does not forecast trend or seasonality well

• requires much historical data

• how to select n (the period length)?

 Longer periods provide more smoothing (less responsive)

 Shorter periods react to trends more quickly (more responsive)

Weighted Moving Average

• Simple moving average formula implies equal weighting for all

periods

• Weighted moving average permits unequal weights on prior

demand

• When a detectable trend or pattern is present, weights can be

used to place more emphasis on recent values

• The assignment of weights rely on expertise/intuition

• The sum of the weights must be equal to 1

Exponential Smoothing

• A sophisticated weighted moving average forecasting

method

 weights decline exponentially

 most recent data are weighted most

• The most used of all forecasting techniques

• Well accepted for six reasons

 Exponential models are surprisingly accurate

 Formulating an exponential model is relatively easy

 The user can understand how the model works

 Little computation is required to use the model

 Computer storage requirements are small

 Tests for accuracy are easy to compute

Exponential Smoothing (Formula)

• Requires smoothing constant (𝛼)

 ranges from 0 to 1

 subjectively chosen to reflect responsiveness

Forecast Effects of Smoothing Constant

Regression Analysis

Regression identifies a relationship between two or more correlated variables by fitting a line to a set of data points

• Simple linear regression - the simplest form of regression that involves a linear relationship between two variables

Y = a + bX

• Y is value of dependent variable, a is the y-intercept of the line, b is the slope, and X is the value of the independent variable

Linear Trend

Multiple Linear Regression

Often, more than one independent variable may be a valid

predictor of future demand

•In this case, the forecast analyst may utilize multiple regression.

•Analogous to linear regression analysis, but with multiple independent

variables.

•Multiple regression supported by statistical software packages.

Dealing with Components

Option 1

• Estimate demand components separately (this is useful if

components are very stable)

1) Only Trend- Already covered in linear regression !!!

2) Only Seasonality

3) Both trend and seasonality: Compute trend on seasonalized data

4) Both trend and seasonality: Compute trend on deseasonalized data

Option 2

• Use forecasting methods that model components explicitly

(this is useful if components are not very stable)

• e.g.: Trend-adjusted exponential smoothing

Example-1: Only Seasonality

1. Calculate seasonal index

2. Forecast demand using known

methods (Moving average,

exponential smoothing, etc.)

3. Adjust forecast for seasonality

using seasonal index

• The seasonal index is the ratio of the amount sold during each season divided by the average for all seasons.

Trend-Adjusted Exponential Smoothing

• An trend in data causes the exponential forecast to always lag the actual data

• Can be corrected somewhat by adding in a trend adjustment

• To correct the trend, we need two smoothing constants

 Smoothing constant alpha ()

 Trend smoothing constant delta (δ)

Choosing Alpha and Delta

Forecast Errors

• Forecast error is the difference between the forecast value and

what actually occurred.

Forecast Errort = Demandt – Forecastt

et = At – Ft

• All forecasts contain some level of error.

• Sources of error

 Bias – when a consistent mistake is made

 Random – errors that are not explained by the model being used

Accuracy is the magnitude of difference between actual and forecast demand

Bias is a systematic pattern of over-forecasting or under-forecasting demand

Mean Absolute Error (MAE)

The MAE is sometimes also

referred to as MAD, i.e. Mean

Absolute Deviation

Easy to use; gives you a

measure of how many units you

are off, on average

Mean Squared Error

(MSE)

The square root of this gives you something similar to a standard deviation of a forecast error

Forecast Accuracy

100% - MAPE

Facilitates cross-time series comparisons due to

adjustment of scale – however, does not work for

intermittent demand, and can be very skewed for low

demand items.

Choosing a Forecasting Method

• No single technique works in every situation

You want to achieve:

• No pattern or direction in forecast error

 Error = (At - Ft) = (Actual - Forecast)

 Seen in plots of errors over time

• Smallest forecast error

 Mean square error (MSE)

 Mean absolute deviation (MAD)

 Mean absolute percentage error (MAPE)

Managing Inventory

• Inventory: the stock of any item or resource used in an organization

 Includes raw materials, finished products, component parts, supplies, and work-in-process

 A typical firm has roughly 30% of its current assets and as much as 90% of its working capital invested in inventory

• Inventory system: the set of policies and controls that monitor levels of

inventory

 Determines what levels should be maintained, when stock should be replenished, and how

large orders should be

Why Carry Inventory?

Anticipation stock …to meet anticipated demand

• Seasonal inventories …to smooth production requirements

• Safety stock …to protect against stock-outs (risk in demand)

• Pipeline inventory (WIP) …to maintain independence of operations (risk in supply)

• Cycle stock …to take advantage of order cycles, exploiting economies of scale

• Hedging inventory …to help hedge against price increases…to take advantage of quantity discounts

Why Not Carry Inventory?

• Inventory = stacks of money sitting on forklifts, on shelves, and in trucks and

planes while in transit

• For many businesses, inventory is the largest asset on the balance sheet at

any given time

• Inventory can be difficult to convert back into cash

• It is a good idea to try to get your inventory down as far as possible

 The average cost of inventory in the United States is 30 to 35 percent of its value

Objective of Inventory Control

• Inventory management has two main concerns:

 Level of customer service (Having the right goods available in the right quantity in the right

place at the right time)

 Costs of ordering and carrying inventories

Key Inventory Terms

Lead Time: time interval between ordering & receiving an order

• variability ↑  additional stock to reduce risk of shortage between deliveries

Holding (Carrying) Costs: cost to carry an item in inventory for a

length of time

• interest/taxes, insurance, depreciation, obsolescence, deterioration, spoilage,

pilferage, breakage, warehousing, opportunity cost…

 Percentage of unit price (e.g., 20% – 40%)

Example: $100 item in inventory for 1 year costs $20 – $40

 Dollar amount per item

(Fixed) ordering cost / Set up cost: → that does NOT depend on

quantity

• preparing invoices, shipping, inspecting quantity & quality, moving goods to

temporary storage / machine adjustments, changing cutting tools

Shortage/stockout costs: costs when demand exceeds supply

(difficult to measure objectively)

• Opportunity cost of not making sale, loss of customer goodwill, late charges

• Lost production or downtime

Single Period Inventory Model

GOAL: identify order quantity that

minimizes lost sales and unsold

inventory

Consider the problem of deciding how

many newspapers to put in a hotel lobby

Demand is uncertain (i.e. stochastic)

Solving Single Period Model

• Assume we want an 80 percent

chance of not running out (i.e.

service level: probability that

demand will not exceed supply)

• Assume that the probability

distribution of sales is normal with

a mean of 90 lbs and a standard

deviation of 10 lbs

• Stocking 90 lbs yields a 50

percent chance of stocking out

Economic-Order Quantity Model

AKA: Reorder point systems (ROP), Continuous review systems

Economic Order Quantity (EOQ)

• Assumptions:

 One product

 Demand is known and stable

 Lead time is known and constant

 Price per unit is constant (no quantity discount)

 All demand is satisfied (No backorder or shortage)

Trade-off between inventory carrying cost and

ordering costs is modeled

Economic Order Quantity Model (order size)

Questions

• When to order from

the supplier?

• How much to

order?

Objective

• Minimize total

annual cost

• Frequent orders

 Small size

 Incur fixed cost frequently

 Low average inventory level

• Infrequent orders

 Large size

 Incur fixed cost infrequently

 High average inventory level

Economic Order Quantity Model Total Cost

Economic Order Quantity Model When to Reorder

Stochastic Inventory Control

• Recall when demand is deterministic

 reorder point R = dL

 However, the demand is often uncertain, therefore the R needs to be re-considered

• Use safety stock (SS) to tackle uncertainty

• Safety stock: the amount of inventory carried in addition to the expected

demand

 deterministic demand requires no SS

 higher service level requires more safety stock

 desired service level helps us determine the optimal size of safety stock

Stochastic Inventory Control (models)

• Fixed Order Quantity Model

 an order of a fixed quantity Q is placed every time the inventory falls

below a reorder point R

 event-triggered

 Continuous review

• Fixed Time Period Model

 A quantity that depends on the current inventory level is ordered (order

up to a target level)

 time-triggered

 Periodic review

Fixed Order Quantity (FOQ) Model

Fixed Time Period (FTP) Model

Fixed Time Period (FTP) Model (formula)

Multi-Period Models – Comparison

ABC Classification System

• A-B-C approach

 Classifying inventory according to some measure of importance, and allocating control efforts accordingly

 A items (very important)

10 to 20 percent of the number of items in inventory and about 60 to 70 percent of the annual dollar value

 B items (moderately important)

 C items (least important)

50 to 60 percent of the number of items in inventory but only about 10 to 15 percent of the annual dollar value