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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
2
• Introduction to DynaSys
• Introduction to forecasting
• Demand Planning 7.0 attributes
• Easy On Boarding
Agenda
Introduction
3
Introduction to DynaSys
“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 DynaSysIntroduction to DynaSys
Durability Expertise Partnership Loyalty
5
A Few DynaSys Customers
Global Customers With Multiple Sites
Introduction to DynaSys
Baxter Healthcare : 25 sites
Essilor : 18 sitesIpsen : 110 sites
Mapa/Spontex : 27 sites
Everris : 32 sites
DynaSys Customer Base
Introduction to DynaSys
7
Food & Beverage
39%
Pharma14%
Retail19%
Industry14%
Luxury14%
Tacti
cal
Str
ate
gic
Demand Planning
DistributionPlanning
ProductionPlanning
ProcurementPlanning
SUPPLIER
CUSTOMER
InternetCollaboration
Integration KPI’s
Op
era
tion
al
Procurement Production Distribution Sales
Supply Chain Planning Suite
Introduction to DynaSys
Master PlanningNetwork & Inventory Optimisation
Not Yet!
9
Introduction to Forecasting
Detailed monthly forecasting process
Importations Corrections Life cycle
Calculation collaboration
Metrics & validation
history Forecasts
0
10
20
30
40
50
60
70
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
Upper Limit
Forecast
Lower Limit
An Industry Supply Chain
Introduction
Physical Supply Chain
Information Supply Chain
NaturalResources Suppliers Production Distribution Retail Consumers
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
4 Components of Demand
TrendTrend
New!
CyclicalCyclicalRandomRandom
New Product
Follows Economy
SeasonalSeasonal Daily (fast food)Annually (snow plows)
Mature Product
Outlier
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
0
10
20
30
40
50
60
70
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
Upper Limit
Forecast
Lower Limit
Forecasts Become Less Accurate With Time
Introduction
To Improve Forecast Accuracy, Involve Your Customers & Major Stakeholders
Introduction
16
It All Sounds Good, But….
17
Sr. Managers Meet To Discuss Forecasting
Introduction
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
“The Forecast Is Always Wrong, Why Bother?”
Senior Management Overheard….
Forecasting Rule #1
Why Forecast?
The Forecast Is WRONG
• 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?
Why Forecast?
22
The Quandary
Why Forecast?
Overseas
Supplier
Supplier Lead Time
ItemScanne
d
Delivery Expected
Customer Lead Time
East Coast DC
• 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?
Total
Milk
Beer
Cookies & Crackers
Salty Snacks
Soft Drinks
Frozen Pizza
70% 75% 80% 85% 90% 95% 100%
92.7%
96.8%
95.0%
94.0%
94.0%
93.9%
90.1%
85.1%
88.7%
79.4%
85.8%
86.1%
89.5%
75.3%
Promoted Items All Items
Out of Stock Rates Double on Promoted Items
Introduction
Source: Stax, Inc. Store Audits
Average On-Shelf Availability Levels
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
“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
• 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
Statistical Forecasting Interface
QAD Demand Planning 7.0
Shortcuts
CollaborativeMessages
Excel
LikeGrid
Graphs
Controls
29
Isolating Importation Errors
Overcoming Limited Resources
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
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
Identifying Import Problems
Isolating Importation Errors
1
32
33
Identification Of Items Behaving Badly
Overcoming Limited Resources
34
Last Month’s Alerts Highlight Forecast Problems
Identification of Items Behaving Badly
Last Month’s Forecast Was Very Wrong – User Should
Review
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
Identification And Correction Of Historical Anomalies
Overcoming Limited Resources
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
Outliers In Sales History
Identification & Correction of Historical Anomalies
39
Options for Outliers
Identification & Correction of Historical Anomalies
A. Item looks
suspicious
B. Modify history
C. Accept history
Actual History
Modified HistorySuspicious
Quantity
Validation
Modification
40
Superior Forecast Engine
Overcoming Limited Resources
• 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
ABC Analysis To Separate The Critical From The Trivial
Overcoming Limited Resources
• 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
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
ABC Classification
ABC Analysis To Separate The Critical From The Trivial
A=80%
9Items
ABC Classification
ABC Analysis To Separate The Critical From The Trivial
6Items
A=60%
47
Multi-Level Forecasting
Overcoming Limited Resources
48
• Number of SKU’s• Aggregation improves accuracy• Forecasting resources• Collaboration
Why Not Forecast At The Item Level?
Multi-Level Forecasting
49
Bottom Up – Top-Down Forecasting
Multi-Level Forecasting
Product Group
ItemForecast(Units) Cost
DollarForecast
XR-24 2,876 2.98$ 8,570.48$ XR-34 4,578 4.98$ 22,798.44$ ::::::Total XR PG 91,684 1,127,715.66$ Total BH PG 276,908 3,465,098.00$ Total TW PG 39,489 1,975,843.00$
Total Business Unit 1 6,568,657$
Total Business Unit 2 3,972,805$ Total Company 10,541,462$
Corporate Sales Forecast 12,000,000$ Percent Difference 13.84%
Determine Difference Lower & Upper Forecasts
Multi-Level Forecasting
ItemForecast(Units)
OriginalForecast
Revised Forecast
XR-24 2,876 8,570.48$ 9,756.31$ XR-34 4,578 22,798.44$ 25,952.88$
::::::
Total XR PG 91,684 1,127,716$ 1,283,749$ Total BH PG 276,908 3,465,098$ 3,944,536$ Total TW PG 39,489 1,975,843$ 2,249,225$
Total Business Unit 1 6,568,657$ 7,477,510$
Total Business Unit 2 3,972,805$ 4,522,490$ Total Company 10,541,462$ 12,000,000$
Revised Forecast
Multi-Level Forecasting
52
“Sales, Marketing & Demand Planning all think they are better at forecasting promotions. Who is right?”
Senior Management Overheard….
Demand Plan
Statistical Forecast
Sales Input
Marketing Input
Customer Input
New Product
Development
Collaboration in the Demand Planning Process
Forecasting Promotions
54
• Enable Collaboration• Retain each collaborators input• Measure each collaborators accuracy
DP 7.0 Answers
Forecasting Promotions
55
Original, Non-Promotional Forecast
Forecasting Promotions
Original Forecast27,271
56
1st Collaborator – Marketing
Forecasting Promotions
Marketing Forecast
35,000
57
2nd Collaborator - Sales
Forecasting Promotions
Sales Forecast60,000
58
3rd Collaborator – Demand Planning
Forecasting Promotions
DP Forecast45,000
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
“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?
Part No. Jan Feb Mar Apr May Jun Total AverageForecast 98 96 103 99 105 99 600 100Actual 98 96 103 99 105 99 600 100
• Based on producing 1 months average sales and the “2 Week Safety Stock” philosophy, is the amount of inventory appropriate? Could it be improved?
Calculating Safety Stock
Production Qty = 1 Month AverageSafety Stock = 2 Weeks
62
How Do You Determine Safety Stock Levels?
Part No. Jan Feb Mar Apr May Jun Total AverageForecast 98 96 103 99 105 99 600 100Actual 285 40 220 30 10 15 600 100
• 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?
Calculating
Production Qty = 1 Month AverageSafety Stock = 2 Weeks
63
How Do You Determine Safety Stock Levels?
Part No. Jan Feb Mar Apr May Jun Total AverageForecast 98 96 103 99 105 99 600 100Actual 98 96 103 99 105 99 600 100
• The best way to calculate safety stock is based on:
- Forecast accuracy
- Desired service level
- Lead time
Calculating Safety Stock
Part No. Jan Feb Mar Apr May Jun Total AverageForecast 98 96 103 99 105 99 600 100Actual 285 40 220 30 10 15 600 100
64
Safety Stock Screen
Calculating Safety Stock
65
Impact of Desired Service Level
Calculating Safety Stock
66
Impact of Differing Lead Times
Calculating Safety Stock
67
Replace Safety Stock In EA
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
CalculatedSafety Stock
CurrentSafety Stock
In EA
68
Easy On Boarding
DP 7.0
Detailed monthly forecasting process
Importations Corrections Life cycle
Calculation collaboration
Metrics & validation
history Forecasts
0
10
20
30
40
50
60
70
1st Qtr 2nd Qtr 3rd Qtr 4th Qtr
Upper Limit
Forecast
Lower Limit
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
• 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
QAD Enterprise QADDP DataHub
QAD DP 7.0 database
SSIS PackageQAD DP-EA
DP
7.0
Impo
rt T
ask
dmtrfcst.csv
Direct ODBC connection
DP 7.0 Export Task
36.5
.9.2
Dem
and
Plan
ning
Impo
rt
Sambashared folder
orFTP transfer
Easy On Boarding
72
Join us in San Antonio, TXMay 6-9, 2013Early Bird Ends Soon!
Building theEffective Enterprise
73
Mark K. Williams, CFPIM, CSCP [email protected]
QAD Global Supply Chain Practice
www.qad.com© 2013 QAD Inc
Demand Planning 7.0
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