Demand planning session

Demand Planning/Supply Chain 101

February 12, 2013

Microsoft Partner Summit, Phoenix, AZ

Agenda

• Introduction

• Definition of Demand Planning

• Why Demand Planning

• Demand Forecasting

• Inventory Planning

• Replenishment Planning

• Summary of Benefits from integrated Demand Planning

• Q & A

2 2013 JustEnough Software

Introduction


Introduction

• Jeff Livingston – Director, Partner Development 15+ years Supply Chain Planning Industry Experience Supply Chain Planning experience across SMB and Tier 1

businesses with domain expertise in Demand Planning, Inventory Optimization, Replenishment/Supply Planning and S&OP.

Experience with Logility, Oracle/Demantra, JustEnough and other applications.

B.S. Mathematics – Purdue University, MBA California Polytechnic


What is “Demand Planning”

• Demand planning is a multi-step operational supply chain planning process used to create reliable forecasts of customer demand and align inventory levels and supply plans to achieve the targeted level of customer service desired by a business.

• In Short:

“ Having the Right Product, at the Right Place, at the Right Time and at the Right Price, to satisfy customerdemand.”


6© 2013 JustEnough Software

Companies encounter continuous change and require the ability to rapidly adapt in a fast changing business environment

Realities of the New Business Environment


We Live in Turbulent Times

Things beyond your control can have a major impact on your supply chain.


Traditional Planning Systems Don’t Work Anymore

• Traditional tools (spreadsheets and disconnected, fragmented systems) can not respond quickly enough to the rapid pace of change:

Global Sourcing Longer lead-times Increased Demand Volatility Faster Product Lifecycles More choices & new competitors Fewer Resources, People, Capacity…doing more with less.

Greater Demand + Longer + More Full = Increased Variability Lead-Times Container Inventory Risk

Shipments


Traditional Approach = Disconnected

Slow Processes, limited collaboration, no consensus forecasting

Multiple,non-integrated

systems

Manual processes

Finance Budget

MarketingNew Products

InventoryPlanning

SalesForecasts/Quotas

ManufacturingCapacity/Scheduling

Typical Company

Low forecast accuracyDepartmental/Silo orientation to Supply Chain Planning

Misalignment between metrics and objectivesReactive vs. Proactive/Exception based

Multiple versions of “The Truth”

E-mail overload


A Better Approach = Integrated Sales Forecasting, Inventory Planning and Replenishment Planning

Integrated Supply Chain Planning – Driving the business via ONE PLAN:

• Statistical Forecasting

• Market Intelligence• Seasonality• Lost Sales• Supersessions• Promotion Planning

Demand Forecasting

• Strategic Inventory Management

• ABC Stratification • Scenario Analysis• Time-phased

Optimization

• Recommended PO’s, WO’s and Transfer Orders

• Constrained Orders• Alerts/Exceptions

(Potential Stock Outs, Excess, Defers, Cancels, Expedites, etc.)

• Opportunity Buying

Merchandise Financial PlanningInventory PlanningOrder Planning & Replenishment


Better Approach = Significant Benefits (Supply Chain Champs)

• Demand-Driven Supply Chain Planning Leaders Have: 15% Less Inventory 17% Better Order Performance 35% Shorter Cash-to-Cash Cycle

times

• Which Translates To: 60% Better Profit Margins 65% Better EPS 2-3 X ROA 1/10 the Stock outs of their peers Source:


Better Approach - People, Plans & Objectives Aligned


Demand Planning Core ComponentsIntegrated Forecasting, Inventory Planning and Replenishment Planning

A holistic planning system that is also linked/integrated to the ERP backbone execution system (i.e. MS Dynamics)

MS Dynamics ERP

Demand Forecasting Inventory

PlanningReplenishment

Planning

Sales HistoryOn Hand balance

Open OrdersMOQ, Multiples, etc.

Events, Promotions & Market Intelligence

Forecasts, and Statistical Standard

Deviation Time-phased Inventory Policies & Strategy, ABC

Stratification, Order Constraints, Lead times, etc.

Time-Phased Inventory Plan

Recommended Orders:

Purchase Orders, Work Orders & Transfer Orders

Exceptions: Potential Stock outs, Excess, Defers, Cancels, Expedites, etc.


Do You Have an Accurate Picture of Customer Demand?


Demand ForecastingDemand Forecasting “Best Practice” process approach

There are four generally applied and recognized forecasting methods that when combined help generate an accurate demand plan:

Total Demand Forecast

Future statistical projections/extrapolations based on historical data patterns and trends

Predict and incorporate the effect of particular events,

promotions, and other factors

Seeking extrinsic knowledge from internal or market sources and coming to a forecast consensus

Generating forecasts based on pre-defined profiles and continuously maintaining those profiles based on

performance


Demand ForecastingTime Series/Statistical Forecasting

• The Process Starts with a Statistical Forecast as a baseline forecast

Premise – Historical customer demand patterns are the best indicator of future demand patterns.

Requires import/integration of Historical Sales Demand from ERP/Transaction system as foundation data (Typically 2 to 3 years of prior monthly/weekly demand)

• Statistical Forecast Engine analyzes demand history/patterns Evaluates multiple forecast methods/algorithms to determine “best-fit” or most

statistically accurate method/model. Determines appropriate level of expected sales, projected growth/decline trends

and seasonal patterns. Statistical Mean Square Error or Standard Deviation used to select best-fit model

(Standard Deviation can be used as input to “Statistical Safety Stock” calculation in Inventory Planning)


Demand ForecastingStatistical Forecasting and selecting best statistical method

Typical Types of Statistical Methods/Models applied:

Straight/flat line

Linear or non-linear growth projection

Repetition at fixed intervals

Random pattern

Trend

Seasonal

Sporadic

Constant


Demand ForecastingStatistical Forecasting and selecting best statistical method

Typical Types of Statistical Methods/Models applied:


Demand ForecastingAdd Market Intelligence and Demand Shaping activities

• The Process Continues – Improve the forecast with market intelligence inputs & forecast overrides

• Demand Shaping for Profitability: Plan promotions, events & incentives Plan new product introductions Identify cross-selling opportunities


Demand ForecastingGroup/Hierarchical & Attribute Forecasting

• Forecasts are often required or better managed at multiple levels of detail/aggregation:

Top-Down- Forecast by Product Family/Groups

- Fair-share disaggregation to SKU

- Leverage “Law of Large Numbers”

- Strategy/Budget focused

- Greater visibility to Seasonality or Trends

Bottoms-up- Sum SKU history/forecasts to family/groups

- Operationally/customer focused

Middle –Out - Blended Method

• Demand Shaping for Profitability: Plan promotions, events & incentives Plan new product introductions Identify cross-selling opportunities

Product Family

Item

Item-Location


Demand ForecastingForecasting New Products

Need to polish-up your Crystal Ball?


Demand Forecasting New Product Forecasting

• Forecasting New Items – Approaches to forecasting items that have no prior demand history?

Manual Forecast (Judgment) Like-Item Forecasting

- Supersessions/Chaining

- Copy/Merge similar product Profile/Curve Shaping

- Life Cycle Profiling

- Attribute based Profiling

- Seasonality “Group Profiling”


Demand ForecastingMeasure/Monitor Forecast Accuracy

• Measure and monitor forecast accuracy for continuous improvement:

Typical forecast accuracy measurements include:- MAD (Mean Absolute Deviation) – Used for inventory calculations

- MAPE (Mean Absolute Percent Error) – Common Forecast Accuracy metric

- Relative Error – Relative measure of error for diagnostic purposes – exceptions

Measure Accuracy of Multiple Inputs:- Accuracy of Statistical Forecast

- Accuracy of Overrides & Market Intelligence inputs

(Did inputs help/hurt the forecast accuracy?)


Demand ForecastingCollaboration and Consensus Forecasting

Consensus forecast process results in best single number to drive downstream planning process

Statistical Basel

ine Forecast

Input from Sales, Marke

ting and

Finance

Input Events

, Promo’s and Incenti

ves

Customer & Competitor Informatio

n

New

Products

Consensus

Forecast


Demand ForecastingGain Competitive Advantage via Better Forecasting

• Improved forecast accuracy hits the bottom line:

Costs go down & earnings go up:- 17% stronger perfect order fulfillment

- 15% less inventory

- 35% shorter cash-to-cash cycle times

- 1/10 of the stock outs of their peers

5% Forecast Accuracy

Improvement

10% Perfect Order

Fulfillment

$0.50 Greater

EPS


Inventory PlanningBalancing Inventory Investment with Desired Service Level

Inventory Planning – Optimizing inventory investment.


Inventory PlanningWhy Do Businesses Carry Inventory/Safety Stock?

• Economic Reasons- Lot Sizes/Ordering Costs

- Minimum Order Quantities

• Transportation Inventory- Pipeline fill

• Special Events- Promotions/Incentives, etc.

• Fluctuation Inventory – Due to Uncertainty (Safety Stock)- Uncertainty of Demand (Forecast Error)

- Uncertainty of Supply (Supplier Delivery variability)


Inventory PlanningThe Inventory/Service Level “Exponential Relationship”

Safety Stock Inventory Increases dramatically as Service Levels approach 100%

80 85 90 95 100Service Level %

Safe

ty S

tock

Qua

ntity Safety Stock

increases dramatically as Service Level

increases

Inventory PlanningForecast Accuracy & Safety Stocks

Forecast Error has a direct relationship with Safety Stocks:

Item A

Item B

Item A

Low Standard Deviation Item requires less Safety Stock

Carrying too much Safety Stock would be costly!!!

Item B

Higher Standard Deviation item requires more safety stock

Having too little Safety Stock increases the risk of stock outs!!

Small Standard Deviation

Big Standard Deviation

2013 JustEnough Software Confidential 29


Inventory PlanningNot All Items are the Same

• Inventory Stratification – Pareto Principle – ABC Classifications ABC stratification can be used to set strategic inventory policies Focus investment attention on “A” items Apply Uniform Rules to Like Items Reduce Decision Time

200 Total SKUs

40 SKUs account for 80% of the

revenue120 SKUs

account for 15% of the

revenue


Inventory PlanningSafety Stock Policy Setting

• Common techniques/policies for setting safety stocks and inventory objectives:

Fixed Safety Stock Levels Periods of Supply ( 2 weeks of Supply) Statistical Safety Stock Policy

- Target Service Level (i.e. 98% Service Level)

- Accounts for Variability of Supply/Demand

- Accounts for Lead-time and Order Quantities

Policies can be dynamic for optimization over time/season.


Inventory PlanningTime-Phased Supply Chain Network Planning

• Modeling the Distribution Network – Nodes, Sources and Lead Times:

Manufacturing/Vendors

East Region USA DC

Customers/Consumers

West Region USA DC

Canadian DC Midwest USA DC


Inventory PlanningPlanning for the Entire Supply Chain Network

An optimal replenishment plan – demand-driven pull planning

Manufacturing/Vendors

East Region USA DC

Customers/Consumers

West Region USA DC

Canadian DC Midwest USA DC

Independent Demand

Dependent Demand

Dependent Demand

Dependent Demand

Dependent Demand

Optimal replenishment policy considers all network dependencies – dependent and independent demand


Replenishment PlanningTime-Phased Supply Chain Network Planning

Traditional Re-order Point (ROP systems) trigger orders when stock falls below a defined level

Re-Order Point Logic

Reactive process – orders are initiated based on inventory level only

Assumes inventories in supply chain network are independent

Orders are needed NOW – not forward looking based on the true need date

Static ordering settings (i.e. min & Max levels)

Promotes PUSH planning

DRP Planning Logic

A Better W

ay ?


Replenishment PlanningTime-Phased Supply Chain Network Planning

An optimal replenishment plan proactively proposes orders over a future horizon based on planned inventory projections

Re-Order Point Logic

Reactive process – orders are initiated based on inventory level only

Assumes inventories in supply chain network are independent

Orders are needed NOW – not forward looking based on the true need date

Static ordering settings (i.e. min & Max levels)

Promotes PUSH planning

DRP Planning Logic

Proactive process - orders are recommended based on projected inventory position

Orders are Time-Phased over a defined future horizon – based on future need date(s)

Dynamic Ordering Policies

Holistic plan for all supply chain network dependencies – dependent demand

Promotes PULL Planning

Replenishment PlanningHow Much to Re-Order and When?

The Saw-Tooth Diagram: Orders Recommended (at lead-time) to be received into inventory on the day that you “plan” to dip into Safety Stock.

Units

SS

OQ Rate of Inventory DepletionAs demand occurs, on-hand

decreases

Model Stock

SS + CS

Inventory Max

SS + OQ

Order Received In Potential risk for stock out

Replenishment PlanOrders suggested in lead-time advance

Lead Time

The Saw-Tooth Diagram

Cycle Stock

½ OQ

CS

Time

OQ = 100Order Date = Sept. 1

Due Date = Dec. 14


Replenishment PlanningOutput = Recommended Orders + Bonus Prize

• The Replenishment Planning “Optimal Order Generation” Engine generates a stream of Recommended Orders into the future:

Purchase Orders Manufacturing Orders Transfer Orders Re-distribution Orders

• Plus a Bonus Prize = Actionable Exception/Alert conditions: Stock Outs/Excess Inventory Potential Stock Outs/Shortfalls Surplus/Defer/Cancel Orders Expedite Orders


Replenishment Planning 101Closed-Loop Planning – Release Orders to ERP

Integration of the “Demand Planning” Recommendations with the ERP system for Execution (Closed Loop Planning)

38

MS Dynamics ERP

Demand Planning

Real/Actual PO’s, WO’s and Transfer Orders

Recommended PO’s, WO’s and Transfer Orders

© 2013 JustEnough Software


Replenishment PlanningInventory Optimization and Process Maturity

• Optimizing Inventory across the Supply Chain Network: Strategically defining where inventory should be kept in the

network Setting specific stocking/ordering policies by item, location, etc. Advanced Inventory Optimization practices

- Postponement – A strategy used to eliminate excess Finished Goods Inventory , by delaying the final activities (assembly, production, packaging, tagging, etc.) until the latest possible time.

- Risk Pooling - Risk pooling suggests that demand variability is reduced by aggregating demand across multiple locations, This reduction in variability allows a decrease in safety stock and therefore reduces average inventory.


Replenishment PlanningInventory Optimization and Process Maturity

• Optimizing Inventory across the Supply Chain Network – what companies are really doing (level of process maturity):


Demand Planning SummaryRecent Trends

• DDSN – Demand Driven Supply Networks Demand-driven supply networks are driven from the front by customer

demand vs. push planning (build it and they will come). Partners in a supply chain will work more closely to shape market

demand by sharing and collaborating information – goal is to bring the supply chain eco-system into balance.

• Demand Sensing Closer to the Point of Consumption Leverage POS Data…better picture of true market demand Technological Advances (Big Data) enabling use of retail/store data

• S&OP, Demand Shaping, and Business Intelligence/Analytics Make better and more profitable business decisions, more quickly.


Demand Planning SummaryCompetitive Advantage in a Fast Changing World

• Improve forecast accuracy

• Sense demand changes and respond more quickly

• Optimize inventory across the full supply chain

• Improve customer service while reducing costs

• Increase visibility for better/faster decision making

• Increase efficiency/productivity via exception/alert-based workflow

• Bottom-line impact/results


Demand Planning SummaryMakes running a business a little bit easier…