Fundamentals of Operations Management BUS 3 – 140 Mr. Jess Marino Spring, 2013

1. Fundamentals ofOperations ManagementBUS 3 – 140Mr. Jess MarinoSpring, 2013

2. Agenda • Introduction • Green Sheet review and other administrative items • Additional comments on the course

3. Green Sheet Review

4. Course Overview and Objectives • Understanding how an organization uses its resources, processes, data, and technologies to create goods and provide services to customers • Understanding how operational effectiveness can be a critical success factor in determining an organization’s Revenue, Profitability, and Shareholder return • Major decisions on Investments, Hiring, Cash Flow • Understanding how the Operations function interrelates with other functional organizations in a business • Understanding the managerial responsibility for Operations, even when production is outsourced, or done in regions far from corporate headquarters

5. “The Goal”

6. Course Introduction

7. Operations is a Key Element of a Supply Chain Revenue Utilization of Assets (People, Plant, Equip) Cash Inventory BALANCING keeping Customers completely satisfied and Resources optimally utilized ……. against spending the least amount of Cash and carrying the least amount of Inventory

8. Highest Level Operations Management Process Process (Transformation/ Conversion) Inputs Outputs Feedback Feedback Feedback Control There is a CONVERSION that takes Information, Intelligence, Resources, and Activities and turns them into something VALUABLE to Customers and / or Society * From Stevenson, Operations Management, Ninth Edition, McGraw Hill Irwin

9. Matching Demand and Supply follows a similar path Supply (Transformation/ Conversion) Profitable Revenue Demand Feedback Feedback Feedback Control There is a RESPONSE to a DEMAND for something valuable to Customers (Internal & External) and / or Society

10. Leverage in Effectively Managing Operations • EFFICIENCY and ELIMINATING WASTE • People • Cash • Time • Equipment • Inventory • Space • Making BETTER TRADEOFF DECISIONS • Revenue • Profit • Inventory • BREAKTHROUGH Improvements • Beyond tradeoffs

11. How Operations Interacts with Other Organizations

12. Majors Represented in BUS 140 -04, -10

13. Key intersections with Sales & Marketing and with Finance FINANCE & ACCOUNTING • Budgeting • Authorizing Capital spending • Authorizing major inventory buys • Cost accounting • Make vs. Buy decisions • Location planning • Managing international trade • Analyzing trade-off decisions

14. Key intersections with Sales & Marketing and with Finance SALES & MARKETING • Forecasting Demand • Influencing demand • Committing supply • Allocating constrained supply • Negotiating schedules with customers • Providing competitive information • Requesting new products and services • Opening new markets Being “Sold Out” is not always a good thing Demand and Supply as Constraints

15. Interaction with other Functional Organizations

16. Forecasting & Managing Uncertainty

17. Forecasting • A statement about the future value of a variable of interest • Future Sales • Weather • Stock Prices • Other Short term and Long term estimates • Several Methods • Quantitative • History and Patterns • Leading Indicators / Associations (Housing Starts & Furniture) • Qualitative • Judgment • Consensus Used for making informed Decisions and taking Actions based on those decisions

18. Forecasting • The quality of the Demand Forecast makes a MAJOR IMPACT (Positive or Negative) on: • Revenue • Market Share • Capital Investment • Hiring • Inventory • Cost • Profit Cisco wrote down $2.5B in inventory in 2001

19. Forecast can be constructed along many dimensions • Product Complexity / Granularity • Product Line • Family • Model • SKU • Time Horizon • Daily • Weekly • Monthly • Annual • Multi-year • Hourly • Unit Of Measure • Dollars • Units

20. A Demand Forecast serves many Purposes WHAT is done and WHY? Region Product Line Channel Features Product Customer Revenue Planning Revenue Scenarios Allocation Criteria Commissions & Quotas Scheduling Factory Volumes Materials Planning Balancing Factory Capacity Assessing Direct Cost @ Mixes Analyzing Absorption implications Estimating TAM and Share Pricing Targets Programs & Promotions Margins @ Mixes Message to Analysts Business Need / Benefit

21. How different Functions use Forecast information

22. Constructing a Forecast

23. Features Common to all Forecasts • Generally assumes that what drove past performance and behavior will drive future performance and behavior • Credit Rating • Insurance Rates • Other • More accurate for groups vs. individuals • Accuracy decreases as time horizon increases Forecasts WILL be wrong – the goal is to predict as closely as possible

24. Start with what you KNOW • How many people will attend the next Giants game? • Tickets already sold • Patterns of walk up sales • Visiting team • Weather • School day • Other • How many Sewing Machines will Singer sell this week? • Orders in Backlog • Inventory in Stores • Production capacity • Household Budget • Rent • Car Payment • Bills • Rest of money

25. Selecting the most useful Forecasting technique(s) • No single technique works in every situation • Two most important factors • Cost • Accuracy • Other factors include the availability of: • Historical data • Computers • Time needed to gather and analyze the data • Forecast horizon

26. Time Series Forecasts (and Behaviors) Trend - long-term movement in data Seasonality - short-term regular variations in data Cycle – wavelike variations of more than one year’s duration Irregular variations- caused by unusual circumstances Random variations- caused by chance

27. Graphs help interpret Time Series data (Figure 3.1) Irregularvariation Trend Cycles 90 89 88 Seasonal variations * From Stevenson, Operations Management, Ninth Edition, McGraw Hill Irwin

28. Managing the Forecastwith Actual Results

29. Tracking Forecast Accuracy • Level of Aggregation • Item (Mix of individual SKU’s) • Family • Product Line • Channel • Customers • Quantity • Time Buckets • Final consumer sales Absolute values and square roots eliminate the possibility of positive and negative variances canceling each other out – key for Mix tracking; less critical for Revenue tracking Regular tracking and monitoring with enable Demand SENSING, as well as contribute to increased accuracy of future forecasts

30. “Consuming” a Forecast • Was it what I expected? • Extra? • Less? • Early? • Late? • Impact on Planning and the Business

31. Causal Factors • External • Market conditions (e.g. paintings when the Painter passes away, Michael Jackson) • New competition • Competitors cannot supply • Internal • Pricing • Promotions • Incentives

32. Relevance of SUPPLY on Forecasts • Historical Sales does not always equal historical Demand • Stockouts • Substitutions • Causal Factors may distort the analysis (pricing, promotions, competitor performance) • Scarcity Behavior • Allocation • Advance buying • Hedging • Hording

33. The Relevance of Time on Forecasts

34. Forecast accuracy varies over time Over Expected SKU Errors 0 +1 +2 +3 +4 ………………………………………… +n Time in Future (Weeks) Under The further into the future, the harder to predict details with accuracy

35. Detailed Product Forecast Accuracy will vary by Time Horizon Current Week should approach 100% Current Month should be greater than 80% Quarter should be at least 70%

36. Inventory Levels in Pipeline Risk of Excess Cost to Manage Need to Forecast Higher Long Lead Time Higher High High Short Lead Time Lower Lower Low Low Relationship of Lead Time, Forecast, Inventory, and Cost

37. Hammer 3/2 timeline Generate forecast of demand and submit an order to TEC Spring selling season Nov Dec Jan Feb Mar Apr May Jun Jul Aug Receive order Leftover from TEC at the units are end of the discounted month

38. Additional Points

39. A forecast can be very complicated (or somewhat simplified)

40. Key Points from Newsvendor Case • Cost of Underforecasting (“Underage” cost) • Cost of Overforecasting (“Overage” cost) • Using Truly Variable Cost when making decisions on incremental volumes • The role of Per Cent Probability in decision making • A/F Ratio (Actual Demand / Forecast) • Bias • “Point Forecast” vs. “Range Forecast” • Managerial Lessons: • Understand VARIABILITY of the Demand • Track ACTUAL Demand • Track PREVIOUS FORECAST accuracy to future actuals

41. For any order quantity we would like to evaluate the following performance measures: In-stock probability Probability all demand is satisfied Stockout probability Probability some demand is lost Expected lost sales The expected number of units by which demand will exceed the order quantity Expected sales The expected number of units sold. Expected left over inventory The expected number of units left over after demand (but before salvaging) Expected profit Newsvendor model performance measures

42. Other Points to consider • Do not “second guess” the forecast • Significant judgment and even debate contribute to the final forecast. But once the forecast is finalized it then becomes the Demand Plan of Record for the enterprise • …… and do not say, “If only we got a better forecast” …… • The forecast should be generated as a team and managed as a team • Do not use the forecast to position or influence Supply • The forecast is an UNCONSTRAINED, honest estimate of future demand. The forecast becomes one of several INPUTS for an integrated Supply Pla • Consider Contribution Margin when considering capacity tradeoffs • Highest margin can justify bias toward overbuilding • Lowest margin can justify underbuilding • Product Transitions are very difficult to forecast, but require special attention and monitoring • New Product Introduction • End Of Life Peter Drucker: “The best way to predict the future is to CONTROL it”