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Demand Planning 7.0 Mark K Williams, CFPIM, CSCPFebruary 12, 2013 QAD Global Supply Chain Planning Practice QAD West Coast User Group.

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Presentation on theme: "Demand Planning 7.0 Mark K Williams, CFPIM, CSCPFebruary 12, 2013 QAD Global Supply Chain Planning Practice QAD West Coast User Group."— Presentation transcript:

1 Demand Planning 7.0 Mark K Williams, CFPIM, CSCPFebruary 12, 2013 QAD Global Supply Chain Planning Practice QAD West Coast User Group

2 2 Introduction to DynaSys Introduction to forecasting Demand Planning 7.0 attributes Easy On Boarding Agenda Introduction

3 3 Introduction to DynaSys

4 “Offer to our customers, a Comprehensive and Effective Planning Solution dedicated to Supply Chain Excellence, benefiting from our 27 years of expertise.” The Mission of DynaSys Introduction to DynaSys

5 5 A Few DynaSys Customers

6 Global Customers With Multiple Sites Introduction to DynaSys Baxter Healthcare : 25 sites Essilor : 18 sites Ipsen : 110 sites Mapa/Spontex : 27 sites Everris : 32 sites

7 DynaSys Customer Base Introduction to DynaSys 7

8 Tactical Strategic Demand Planning Distribution Planning Production Planning Procurement Planning SUPPLIERSUPPLIER CUSTOMERCUSTOMER Internet Collaboration Integration KPI’s Operational ProcurementProductionDistributionSales Supply Chain Planning Suite Introduction to DynaSys Master Planning Network & Inventory Optimisation Not Yet!

9 9 Introduction to Forecasting

10 An Industry Supply Chain Introduction Physical Supply Chain Information Supply Chain Natural Resources SuppliersProductionDistributionRetailConsumers

11 An estimate of future demand. A forecast can be constructed using quantitative methods, qualitative methods, or a combination of methods, and it can be based on extrinsic (external) or intrinsic (internal) factors. Various forecasting techniques attempt to predict one or more of the four components of demand: cyclical, random, seasonal, and trend. APICS Dictionary What is a Forecast? Introduction

12 4 Components of Demand Trend New! Cyclical Random New Product Follows Economy Seasonal Daily (fast food) Annually (snow plows) Mature Product Outlier

13 Forecasts Are More Accurate When Aggregated Introduction How Many Brown, Size 10 Shoes Will We Sell Thursday? Not Very Accurate – Just a Wild Guess How Many Shoes Will We Sell This Month? Better Chance Of Being Accurate – Can Use Data

14 Forecasts Become Less Accurate With Time Introduction

15 To Improve Forecast Accuracy, Involve Your Customers & Major Stakeholders Introduction

16 16 It All Sounds Good, But….

17 17 Sr. Managers Meet To Discuss Forecasting Introduction

18 18 “We have 42,000 SKU’s and a limited budget for personnel to do forecasting. How do we get the most bang for the buck??” “Sales, Marketing & Demand Planning all think they are better at forecasting promotions. Who is right?” “My old company kept 2 weeks of Safety Stock on hand for each item. Isn’t that enough?” “Which products are behind budget?” “The forecast is always wrong, why bother?” Senior Management Discussion Overheard… Introduction

19 19 “The Forecast Is Always Wrong, Why Bother?” Senior Management Overheard….

20 Forecasting Rule #1 Why Forecast? The Forecast Is WRONG

21 To anticipate change -Promotions -New products -Product retirements -Customer buying habits To anticipate inventory and capacity demands To procure materials in a timely manner To project costs of operations into budgeting processes & manage cash flow Why Forecast?

22 22 The Quandary Why Forecast? Overseas Supplier Supplier Lead Time Item Scanned Delivery Expected Customer Lead Time East Coast DC

23 Often have employees that work overtime for months, followed by layoffs Are poor users of manufacturing capacity Are unable to fulfill “surprise” customer orders Face huge expediting charges Have excessive inventory write-offs Have the dreaded combination of a poor customer service level and too much inventory! Disappoint customers by not responding to promotions on time Companies That Do Not Adequately Forecast: Why Forecast?

24 Out of Stock Rates Double on Promoted Items Introduction Source: Stax, Inc. Store Audits Average On-Shelf Availability Levels

25 Value Proposition and ROI Reduced costs -Inventory reductions 8-10% in 6 months, 12-70% over 2-3 yrs -Reduced obsolescence and inventory write-offs 30-50% -Total cost reductions 1-2% Improved Performance -On-time delivery to customers improvement 10-40% -Plant efficiency improved between 2 and 33% -Improvement in forecast accuracy – 5-20% -Improved profitability 1-3% Source: IIF and other industry sources 25 Why Forecast?

26 26 “We have 42,000 SKU’s and a limited budget for personnel in forecasting. How do we get the most bang for the buck??” Senior Management Overheard….

27 27 Isolating importation errors Identification of items behaving badly Identification and correction of historical anomalies Superior Forecast Engine ABC Analysis to separate the critical from the trivial Multi-level forecasting DP 7.0 Answers…. Overcoming Limited Resources

28 Statistical Forecasting Interface QAD Demand Planning 7.0 ShortcutsShortcuts Collaborative Messages Excel Like Grid Graphs ControlsControls

29 29 Isolating Importation Errors Overcoming Limited Resources

30 30 When importing data, problems can occur DP 7.0 makes it easy to identify problems that the user can fix DP 7.0 automatically highlights items with high forecast error – major time saver Importation & Correction Introduction

31 31 1.Click items without standard cost 2.Select Unit Conversion Issues 3.The list of 30 items appears Fix a problem once, & it is fixed permanently Identifying Import Problems Isolating Importation Errors 1 2 3

32 32 Identifying Import Problems Isolating Importation Errors 1 3 2

33 33 Identification Of Items Behaving Badly Overcoming Limited Resources

34 34 Last Month’s Alerts Highlight Forecast Problems Identification of Items Behaving Badly Last Month’s Forecast Was Very Wrong – User Should Review

35 35 Modifying Alert Parameters Identification of Items Behaving Badly Deviation Gap set at 10% will generate no alert Change Deviation Gap to 5% generates an alert

36 36 Identification And Correction Of Historical Anomalies Overcoming Limited Resources

37 37 Forecasts are built on pattern recognition What if your sales history included: -Extraordinary demand caused by a competitor’s stockouts? -A weather driven surge or absence of demand? -A drop in orders caused by your prolonged stockout? -Would you want the future to reflect that past? DP 7.0 provides statistical boundaries that help identify these anomalies, allowing you to accept or modify them Why Modify History? Identification & Correction of Historical Anomalies

38 38 Outliers In Sales History Identification & Correction of Historical Anomalies

39 39 Options for Outliers Identification & Correction of Historical Anomalies A. Item looks suspicious B. Modify history C. Accept history Actual History Modified History Suspicious Quantity Validation Modification

40 40 Superior Forecast Engine Overcoming Limited Resources

41 Method used to select the “best fit” time series forecasting techniques for your data Judged to be one of the most accurate in the world There are over 30 other forecasting methods available including: -Curve Fitting -Exponential Smoothing -Regression -New Product -Lifecycle One size DOES NOT fit all! Forecast Pro Superior Forecast Engine

42 42 ABC Analysis To Separate The Critical From The Trivial Overcoming Limited Resources

43 First noted by Vilfredo Pareto Items are classified as: -A items (fastest movers) 20% = 80% of sales or usage -B items (middle-range movers) 30% = 15% of sales or usage -C items (slow movers) 50% = 5% of sales Focus on fast moving items Useful in many applications -In forecasting, where we want to keep our attention ABC Inventory Management ABC Analysis To Separate The Critical From The Trivial

44 44 Tighter Alert Parameters For “A” Items ABC Analysis To Separate The Critical From The Trivial Deviation Gap set at 10% will generate no alert Change Deviation Gap to 5% generates an alert

45 ABC Classification ABC Analysis To Separate The Critical From The Trivial A=80%

46 ABC Classification ABC Analysis To Separate The Critical From The Trivial A=60%

47 47 Multi-Level Forecasting Overcoming Limited Resources

48 48 Number of SKU’s Aggregation improves accuracy Forecasting resources Collaboration Why Not Forecast At The Item Level? Multi-Level Forecasting

49 49 Bottom Up – Top-Down Forecasting Multi-Level Forecasting Product Group

50 Determine Difference Lower & Upper Forecasts Multi-Level Forecasting

51 Revised Forecast Multi-Level Forecasting

52 52 “Sales, Marketing & Demand Planning all think they are better at forecasting promotions. Who is right?” Senior Management Overheard….

53 Demand Plan Statistical Forecast Sales Input Marketing Input Customer Input New Product Development Collaboration in the Demand Planning Process Forecasting Promotions

54 54 Enable Collaboration Retain each collaborators input Measure each collaborators accuracy DP 7.0 Answers Forecasting Promotions

55 55 Original, Non-Promotional Forecast Forecasting Promotions Original Forecast 27,271

56 56 1st Collaborator – Marketing Forecasting Promotions Marketing Forecast 35,000

57 57 2nd Collaborator - Sales Forecasting Promotions Sales Forecast 60,000

58 58 3 rd Collaborator – Demand Planning Forecasting Promotions DP Forecast 45,000

59 59 Each collaborator inputs their forecast A predefined hierarchy determines which forecast has precedence in determining the final forecast All forecasts are stored in the system After the promotion the system can determine which of the forecasts was the most accurate When Forecasting Promotions Forecasting Promotions

60 60 “My Old Company Kept 2 Weeks Of Safety Stock On Hand For Each Item. Isn’t That Enough?” Senior Management Overheard….

61 How Do You Determine Safety Stock Levels? Based on producing 1 months average sales and the “2 Week Safety Stock” philosophy, is the amount of inventory appropriate? Could it be improved? 61 Calculating Safety Stock Production Qty = 1 Month Average Safety Stock = 2 Weeks

62 How Do You Determine Safety Stock Levels? Like the previous example, the forecast & actual totaled 600 for six months Based on producing 1 months average sales and the “2 Week Safety Stock” philosophy, is the amount of inventory appropriate? Could it be improved? 62 Calculating Production Qty = 1 Month Average Safety Stock = 2 Weeks

63 How Do You Determine Safety Stock Levels? The best way to calculate safety stock is based on: -Forecast accuracy -Desired service level -Lead time 63 Calculating Safety Stock

64 64 Safety Stock Screen Calculating Safety Stock

65 Impact of Desired Service Level 65 Calculating Safety Stock

66 Impact of Differing Lead Times 66 Calculating Safety Stock

67 Replace Safety Stock In EA 67 Calculating Safety Stock Current Safety Stock imported from EA EA Safety Stock compared to Calculated Safety Stock After reviewing the computed Safety Stock levels, you can have them exported back to EA, or you can ignore them Calculated Safety Stock Current Safety Stock In EA

68 68 Easy On Boarding DP 7.0

69 69 Why EOB? Easy On Boarding DP 7.0 Configurability Strength Can adapt to almost every business process Can be fine tuned to suit user requirements DP 7.0 Configurability Weakness Complex Longer setup time Higher learning curve for customer

70 70 DP 7.0 is a highly configurable tool -EOB is designed to meet 90% of customer requirements “out of the box” -Reduces implementation time -Speeds the process of the customer getting value from the software EOB is a preconfigured database that includes: -Hierarchies mapped to QAD EA -Standard import / export with QAD EA -Standardized process & parameters -Standardized screens -Standardized KPI’s What is EOB? Easy On Boarding

71 Integration 71 Easy On Boarding

72 72 Join us in San Antonio, TX May 6-9, 2013 Early Bird Ends Soon! Building the Effective Enterprise

73 Mark K. Williams, CFPIM, CSCP QAD Global Supply Chain Practice © 2013 QAD Inc Demand Planning Contact


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