copyright © 2013 by the mcgraw-hill companies, inc. all rights reserved. mcgraw-hill/irwin chapter...

Copyright © 2013 by The McGraw-Hill Companies, Inc. All rights reserved.

McGraw-Hill/Irwin

CHAPTER 6: Integrated Operations Planning

McGraw-Hill/Irwin


McGraw-Hill/Irwin

• Supply chain planning• Supply chain planning

applications• Sales and operations

planning• APS system overview• Collaborative planning,

forecasting and replenishment

• Forecasting

Overview of integrated operations planning


McGraw-Hill/Irwin

• Demand planning responsiveness

• Customer relationship collaboration

• Order fulfillment/service delivery• Manufacturing customization• Supplier relationship

collaboration• Life-cycle support• Reverse logistics

Supply chain planning requires coordination of key processes


McGraw-Hill/Irwin

• Supply chain visibility is the ability to track inventory and resources– Information about available

resources is effectively evaluated and managed

– Requires exception management of potential problems as they are identified

Factors that drive effective planning


McGraw-Hill/Irwin

• Simultaneous resource consideration is the ability to include demand, capacity, material requirements, and constraints in defining alternatives– Enables identification of

trade-offs that can increase functional costs, but lower total system costs



McGraw-Hill/Irwin

• Resource utilization is a coordinated approach to making functional resource trade-offs– Considers service

requirements while minimizing combined supply chain resources

– Critical capability when firms emphasize overall asset utilization



McGraw-Hill/Irwin

• Common software applications for most planning environments include– Demand planning– Production planning– Logistics planning

• These applications can be sourced from the following options– Custom developed for the organization – Packaged solutions contained in a larger supply chain

management system– Modules within an ERP system

Supply chain planning applications overview


McGraw-Hill/Irwin

• Demand management system is the information technology component of the sales and operations planning (S&OP) process

• Demand management develops the forecasts used by other supply chain processes to anticipate sales levels

– Demand management processes must integrate • Historical forecasts• Promotional plans• Pricing changes• New product introductions

• Forecasts are then used to determine production and inventory requirements

• Must maintain forecast data consistency across multiple products and warehouse facilities

Demand planning


McGraw-Hill/Irwin

• Production planning uses requirements from demand management to develop a realistic manufacturing plan– Must integrate with manufacturing resources and constraints

• Requirements plan defines what items are needed and when

• Production planning systems match the requirements plan with the production constraints– Limitations include facility, equipment and labor availability

• Effective planning creates a time-sequenced plan to manufacture the correct items in a timely manner while operating within constraints

Production planning


McGraw-Hill/Irwin

• Logistics planning integrates overall movement demand, vehicle availability, and relevant movement cost into a decision support system that seeks to minimize overall freight expense– Analysis suggests ways freight can be shifted among carriers or

consolidated to lower expenses• Overcomes these problems resulting from individual

perspectives– Limited economies of scale– Limited information sharing– Excessive transportation expense

Logistics planning


McGraw-Hill/Irwin

+ Forecasts (sales, marketing input, histories, accounts)+ Customer orders (current orders, future committed orders, contracts)+ Promotions (promotion, advertising plans)= Period demand- Inventory-on-hand- Planned receipts= Period logistics requirements

Figure 6.1Logistics requirements


McGraw-Hill/Irwin

• Sales & operations planning is an integrated combination of – Information systems (financial, marketing and supply chain planning)– Organizational processes– Personal responsibility and accountability

Sales & operations planning (S&OP)

• Using this S&OP combination, the operations and sales groups must overcome conflicts to develop consensus and then execute their collaborative plans


McGraw-Hill/Irwin

Traditional conflicts between sales and operations groups must be resolved to reach consensus

Figure 6.2 Planning Process Conflicts


McGraw-Hill/Irwin

An overview of the S&OP process illustrating 5 major plans to be integrated

Figure 6.2 S&OP Process

11

22

33 44

55


McGraw-Hill/Irwin

• Functional leadership from all key operating areas must be committed to the S&OP process and be responsible for achieving success– Tie manager’s compensation to successful S&OP

performance– Include regular involvement and accountability at the

general management level

Making S&OP work in an organization requires senior leadership involvement


McGraw-Hill/Irwin

• Executing the process every month• Process ownership and clarity of roles and responsibilities• Organizational commitment to achieving high forecast

accuracy• Focus should be on the next 3 to 12 months• One integrated plan that integrates the actions of the entire

organization• Senior management decision making• Measuring end-to-end supply chain performance• S&OP forecast versus operating plan or budget

8 keys to successful S&OP implementation from Table 6.1


McGraw-Hill/Irwin

Figure 6.4APS framework

Period 1 Period 2 Period 3


McGraw-Hill/Irwin

Table 6.2Sample APS planning situation

Time Period 1 2 3 4 5

Requirement 200 200 200 600 200

Production Capacity 300 300 300 300 300

Alternative 1 (overtime): Production Inventory Carryover

200

-

200

-

200

-

600*

-

200

-

Alternative 2 (build ahead): Production Inventory Carryover

300 100

300 200

300 300

300

-

200

-


McGraw-Hill/Irwin

Figures 6.5APS system components

Requirements Optimization

Demand Management

ERP/Legacy System

Resource Allocation

Resource Management


McGraw-Hill/Irwin

• Facilitates more effective planning with shorter cycle times.

• Offer capability to consider the extended supply chain and make appropriate trade-offs to achieve optimal performance.

• More effective and responsive planning allows a more level assignment of resources for existing sourcing, production, storage, and transportation capacity.

Supply chain planning benefits


McGraw-Hill/Irwin

• Greater integration with enterprise financial plans.• Increased inclusion of strategic initiatives and

activities.• Improved simulation and modeling of alternatives.• Easier translation between aggregate and detailed

planning levels.

Benefits of integrated business planning


McGraw-Hill/Irwin

• CPFR coordinates the requirements planning process between supply chain partners for demand creation and demand fulfillment activities– Process initiated by the consumer products industry

• Developed to reduce unplanned and uncoordinated events that distort the smooth flow of product throughout the supply chain

Collaborative planning, forecasting and replenishment (CPFR)


McGraw-Hill/Irwin

• Develop a joint business plan• Create a joint calendar to determine product flow• Create a common sales forecast based on shared

knowledge of each trading partner’s plan– Share common forecast between retailer and suppliers– Use an iterative process to share the forecast and requirements

plan• Use the common sales forecast to develop

– Production plan– Replenishment plan– Shipment plan

CPFR process steps


McGraw-Hill/Irwin

Basic relationships for CPFR illustrated in a retail situation

Figure 6.6 CPFR in the Retail Information Technology Environment


McGraw-Hill/Irwin

• Forecast is the specific definition of what is projected to be sold, when and where

• Forecasting is a critical capability– Many logistics and supply chain

activities must be completed in anticipation of a sale

• Forecasting approaches to achieve enhanced service or reduced inventory– Improve forecast accuracy– Forecast at a higher level of

aggregation

Forecasting


McGraw-Hill/Irwin

Forecasting is influenced by replenishment time and economies of scale

Table 6.3 How Product Characteristics Influence The Need To Forecast


McGraw-Hill/Irwin

• Forecasts match the product requirements of customers with capacity of the enterprise and supply chain

• Forecasts must be more timely and accurate to align– Customer demands for higher service levels and more

product variations with– A management focus to reduce supply chain assets

Forecasting requirements


McGraw-Hill/Irwin

• Support collaborative planning– Collaborative forecasts help avoid inventory excesses and out-of-stock

situations– Common goals are needed to develop effective operating plans

• Drive requirements planning to determine– Inventory projections– Replenishment requirements– Production requirements

• Improve resource management through cost trade-offs of strategies such as– Extra production capacity– Extra storage capacity– Speculative production or product movement– Outsourcing

Logistics forecasts are necessary to


McGraw-Hill/Irwin

Forecasting model components for time period t

CyclicTrendSeasonal

Forecast

Base demand Promotion Irregular× × ×× +

=

Ft

Bt T Ct Pt IBt St


McGraw-Hill/Irwin

Description of model components

• Base demand is long-term average demand after other components are removed

• Seasonal component is annual recurring upward or downward movement in demand– E.g. Toy demand before

Christmas• Trend component is long-range

shift in periodic sales– Positive, negative or neutral

• Cyclic component is periodic shifts in demand lasting more than a year– E.g. Housing demand follows

business economic cycle• Promotional component is

demand swings initiated by a firm’s marketing activities– Advertising, deals, or promotions

• Irregular component includes random or unpredictable quantities that do not fit other components


McGraw-Hill/Irwin

Components of an effective forecast management process

Figure 6.7 Forecast Management Process


McGraw-Hill/Irwin

• Forecast database must include timely historical and planning information– Must facilitate data manipulation, summarization, analysis and reporting– E.g., Open orders, demand history, marketing tactics, economy, competitor

actions • Technique is the computational method used to combine model

components into a forecast quantity– E.g., time-series or correlation modeling

• Support system must facilitate the maintenance, updating and manipulation of the database and the forecast

• Administration includes organizational, procedural, motivational, cross-functional and personnel aspects of forecasting

Description of forecast management process components


McGraw-Hill/Irwin

• Faulty communications are costly for supply chains– Seek to reduce forecast inconsistency across multiple members

of the supply chain• Efforts to perfect a single component do not overcome

need for other components• Process design should consider strengths and weaknesses

of each individual component– Design for optimal performance of integrated system

Meaningful forecast process requires integrated and consistent combination of components


McGraw-Hill/Irwin

Bullwhip effect showing requirements error amplification between supply chain partners

Figure 6.8 Response of a Simulated Production / Distribution System to a Sudden 10 Percent Increase in Sales at the Retail Level


McGraw-Hill/Irwin

• Evaluate technique both quantitatively and qualitatively for – Accuracy– Forecast time horizon– Value of forecasting to business strategy– Data availability– Type of data pattern– Experience of the forecaster

Criteria for evaluating applicability of forecasting techniques


McGraw-Hill/Irwin

• Qualitative relies on expert opinion and special information– Costly and time-consuming– Ideal for situations with little historical data or when much managerial judgment

are required– Developed using surveys, panels and consensus meetings

• Time series focuses entirely on historical patterns and pattern changes to generate forecasts– “The past is a good predictor of the future”– E.g., moving averages, exponential smoothing, extended smoothing, and

adaptive smoothing• Causal uses specific information to develop relationships between

lead events and forecasted activity– E.g., simple or multiple regression

Categories of forecast techniques


McGraw-Hill/Irwin

Forecast techniques from Table 6.4

Moving average

Exponential smoothing

Time series

Regression

Multivariate

An unweighted average of the previous periods of sales

An exponentially weighted moving average using smoothing constants to place greater weights on more recent demands

Uses time period as the independent variable to predict future demand patterns

Uses other independent variables, such as price, promotion plans, or related product volumes, to predict sales

Uses more complex statistical techniques to identify more complex demand history relationships; techniques include spectral analysis, Fourier analysis, transfer functions, and neural networks


McGraw-Hill/Irwin

• Improving accuracy of forecasts requires error measurement followed by analysis

• Choice of method for error measurement– Simple average error can hide problems as

positive errors are offset by negative ones– Mean absolute deviation (MAD)

evaluates absolute error by ignoring the sign of the error

– Mean absolute percentage error (MAPE) is mean MAD divided by mean demand

Forecasting accuracy refers to the difference between forecasts and actual sales


McGraw-Hill/Irwin

Illustration of alternative measures of forecast error

Table 6.5 Monthly Personal Computer Demand and Forecast


McGraw-Hill/Irwin

Illustration of how relative forecast error will vary based on the level of measurement

Figure 6.9 Comparative Forecast Errors

copyright © 2013 by the mcgraw-hill companies, inc. all rights reserved. mcgraw-hill/irwin chapter...

Documents

effective planning slide

planning environments

mcgrawhill companies

production planning

mcgrawhillirwin chapter

supply chain processes

forecasts sales

inventory requirements