1. Forecasting

2. Forecasting and Operations Sales Production Inventory Facilities Raw Materials People Profits Products

3. Forecasting Importance Boeing, 1997: $2.6 billion write down due to “raw material shortages, internal and supplier parts shortages” Wall Street Journal, Oct 23, 1997 “IBM sells out new Aetna PC; shortage may cost millions in potential revenue.” Wall Street Journal, Oct 7, 1994 2008 Daytona 500 – new sponsor – out of stock Empty shelves

4. Principles of Forecasting

5. Impacts of Forecasting 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 - expediting costs

6. 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 Cabela’s – fishing rods

7. 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

8. 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

9. 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

10. 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

11. Simple Moving Average Jan120 Feb90 Mar100 Apr75 May110 June50 July75 Aug130 Sept110 Oct90 ORDERS MONTHPER MONTH

12. Jan120 Feb90 Mar100 Apr75 May110 June50 July75 Aug130 Sept110 Oct90 ORDERS MONTHPER MONTH MA nov = 3 = 90 + 110 + 130 3 = 110 orders for Nov Simple Moving Average D aug +D sep +D oct

13. Jan120– Feb90 – Mar100 – Apr75103.3 May11088.3 June5095.0 July7578.3 Aug13078.3 Sept11085.0 Oct90105.0 Nov –110.0 ORDERSTHREE-MONTH MONTHPER MONTHMOVING AVERAGE Simple Moving Average

14. Jan120– – Feb90 – – Mar100 – – Apr75103.3 – May11088.3 – June5095.099.0 July7578.385.0 Aug13078.382.0 Sept11085.088.0 Oct90105.095.0 Nov –110.091.0 ORDERSTHREE-MONTHFIVE-MONTH MONTHPER MONTHMOVING AVERAGEMOVING AVERAGE

15. Weighted Moving Average Adjusts moving average method to more closely reflect data fluctuations

16. Weighted Moving Average Example MONTH WEIGHT DATA August 17%130 September 33%110 October 50%90 Where do the weights come from?

17. Weighted Moving Average Example MONTH WEIGHT DATA August 17%130 September 33%110 October 50%90 November forecast WMA 3 = 3 i = 1  Wi DiWi DiWi DiWi Di = (0.50)(90) + (0.33)(110) + (0.17)(130) = 103.4 orders 3 Month = 110 5 month = 91

18. F t +1 =  D t + (1 -  )F t where F t +1 =forecast for next period D t =actual demand for present period F t =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

19. Forecast for Next Period Forecast = (weighting factor)x(actual demand for period)+(1-weighting factor)x(previously determined forecast for present period) 0 >  <= 1 Lesser reaction to recent demand Greater reaction to recent demand

20. PERIODMONTHDEMAND 1Jan37 2Feb40 3Mar41 4Apr37 5May 45 6Jun50 7Jul 43 8Aug 47 9Sep 56 10Oct52 11Nov55 12Dec 54 Exponential Smoothing

21. Exponential Smoothing Made Simple – 4 steps © Step 1: First Period Forecasted = Naïve Forecast Step 2: Remaining Periods Forecasted: (Smoothing Factor (ά) x Previous Actual Demand) Step 3: Remaining Periods Forecasted: (1- Smoothing Factor(ά) x Previous Forecast) Step 4: Remaining Periods Forecasted: Add Steps 2 and 3 © Joe Walden, 2011

22. Forecast Accuracy Find a method which minimizes error Error = Actual - Forecast Mean Absolute Deviation (MAD)

23. Forecast Control Why is my forecast out of tolerance? Reasons for out-of-control forecasts Change in trend Appearance of cycle Weather changes Promotions Competition Politics

24. Inventory Management

25. What to order When to order How much to order

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

27. Inventory Management What is Inventory? satisfy normal demand patterns Inventory management –Decisions drive other logistics activities –Different functional areas have different inventory objectives –Inventory costs are important to consider Inventory turnover Inventory carrying costs

28. Purposes of Inventory Enables the firm to achieve economies of scale Balances supply and demand Enables specialization in manufacturing Provides protection from uncertainties in demand and order cycle Acts as a buffer between critical interfaces within the supply chain Cover up inefficiencies in operations Smooth variances in customer demand An Addiction

29. Pull Push Just-in-time Inventory Management Philosophies

30. Inventory-Related Costs Inventory carrying (holding) costs –Obsolescence –Inventory shrinkage –Storage costs –Handling costs –Insurance costs –Taxes –Interest charges –Opportunity cost Stockouts

31. Costs Relevant to Inventory Management Carrying costs - Cost for holding the inventory over time - The primary cost is the cost of money tied up in inventory, but also includes obsolescence, insurance, personal property taxes, and storage costs - Typically, costs range from the cost of short term capital to about 40%/year. The average is about 25%/year of the item value in inventory.

32. Goals of inventory management

33. When to Order Reorder point (ROP) ROP = DD x RC under certainty ROP = (DD x RC) + SS under uncertainty Where DD = daily demand RC = length of replenishment cycle SS = safety stock

34. Forms of Reorder Points Fixed Variable Two Bin Card Judgmental Projected shortfall Min-Max

35. Inventory Management Questions: 3 questions: EOQ developed by Fred Harris - 1913; made popular by R.H. Wilson

36. How Much to Reorder Economic order quantity (EOQ) in dollars EOQ = √2AB/C Where EOQ = the most economic order size, in dollars A = annual usage, in dollars B = administrative costs per order of placing the order C = carrying costs of the inventory (%)

37. Basic EOQ Model Assumptions 1. Constant known demand rate 2. Cost per unit not depend on order quantity (no quantity discounts) 3. Entire order delivered at one time 4. Ordering and carrying cost known and independent 5. No stock-out because of certain demand So What?

38. EOQ Example Annual Usage = 45,000 units Ordering costs = $30 per order Carrying costs = 20% # ORDERS/YEAR = A/Q = 45,000/3674 = 12.25

39. Inventory Flows Safety stock can prevent against problem areas When fixed order quantity system is used, time between orders may vary When reorder point is reached, fixed order quantity is ordered

40. Inventory Turns What is it? How is it calculated? Why is it important?

41. Aggregate Performance Measure Average Inventory Investment: It is the dollar value of a company’s average level of inventory. Disadvantage: It makes comparisons of companies difficult. Inventory Turn Over Ratio: It is a measure that allows for better comparison among companies. Inventory Turnover = Annual cost of good sold Average Inventory Investment Disadvantage: Figures among industry may not be comparable.

42. ABC Analysis Pareto’s Law – meaningful few and trivial many 80/20 – based on Pareto’s analysis 80 percent of the wealth was in 20 percent of the people’s hands – in inventory management usually 20 percent of your items account for 80 percent of your inventory dollars

43. ABC Analysis Volume Dollar value Annual Dollar Value Customers