pov - aligning aps functionality to plan demand and manage inventory

Aligning APS Functionality to Plan Demand & Manage Inventory

A Point of View

By Tom Tiede


A Point of View 1 By Tom Tiede

Introduction

Many large corporations are considering or have implemented Advanced Supply Chain Planning (APS)

software. In doing so, the goal is to improve cash flow and minimize inventory investment. Successfully

achieving these goals is dependent on a number of factors such as executive sponsorship, resource

commitment, data integrity, and process discipline. Another critical success factor is the alignment of

software functionality with the needs of the business and the unique characteristics of each item to be

planned and managed by the system. Aligned appropriately, an APS will aid significantly in:

• Improving demand plans;

• Driving out unnecessary and excessive inventory levels; and

• Meeting or exceeding service level agreements.

Overview of Demand Planning, Inventory Planning & Replenishment Planning

Leading APS providers offer a suite of solutions for Demand Planning, Inventory Planning, and

Replenishment Planning. Usually, these are highly integrated modules that allow for the seamless flow of

data from forecast through replenishment order for each item and inventory location.

Exhibit 1: Demand to Replenishment Planning

In summary form, the process begins by periodically creating a forecast (or demand plan) for each item.

Pre-defined inventory rules are attached to each item to determine the system calculations to be used for

Order Quantity, Reorder Point, and Safety Stock. Replenishment Planning monitors on hand and projected

inventory levels to determine when and how much inventory should be ordered for each item and location to

meet anticipated demand.

It is relatively simple and straight-forward process. The challenge is determining which parameters or rules

to use for each product in attempt to find the optimal balance between service performance and inventory

investment.

Demand Planning

As stated, the process begins by creating a demand plan. A demand plan is the organization’s best view of

unconstrained future demand. It is derived by creating a statistical forecast from historical data then

factoring this with forward looking information from sales, marketing, and finance to create a consensus

demand plan. This plan, in turn, is fed as key input into the Sales and Operations Planning (S&OP) process

which results in a constrained operations plan.

Historical

Demand &

Current Orders

Inventory Rules

• Service Levels

• Order Quantity

• Reorder Points

• Safety Stock

• On Hand Inventory

• Planned Receipts

• Planned Orders

DemandPlanning

InventoryPlanning

ReplenishmentPlanning

Forecasts

By Item

& Location

Inventory Plan

By Item

& Location

Recommended PO

By Item

& Location

Historical

Demand &

Current Orders

Inventory Rules

• Service Levels

• Order Quantity

• Reorder Points

• Safety Stock

• On Hand Inventory

• Planned Receipts

• Planned Orders

DemandPlanning

InventoryPlanning

ReplenishmentPlanning

Forecasts

By Item

& Location

Inventory Plan

By Item

& Location

Recommended PO

By Item

& Location



Exhibit 2: Demand Planning Process

Demand Planning serves several purposes and therefore often requires a different level of detail and time

horizon for each step in the process.

Exhibit 3: Demand Planning Time Horizons (Illustrative)

Time horizon terms to consider in the Demand Planning process include:

• Historical Horizon: defines the time period for which the historical data will be used and displayed for

forecast modeling. This is often comprised of demand history at the item-location level.

• Forecast Planning Horizon: defines the time period over which statistical forecasts are created and

adjustments may be made.

• Frozen Forecast Horizon: defines the time period for which demand planning processes will not

update/change the statistical forecast or adjusted demand plans.

• Telescopic Planning: defines the level of detail managed and communicated per time period. Near term

time periods will be managed at a more granular level of detail.

Historical data is stored in its most granular detail. In the statistical forecasting process, this data is rolled up

in a hierarchal structure so that forecasts can be created at multiple levels. Lower level forecasts (e.g. by

item and location) are used for near term inventory management and replenishment planning. Adjustments

can be applied at any level or horizon of the forecast. Creating consensus in the demand plan may require

alignment with Sales, Marketing, Finance, or other stakeholder groups. Each group may require a different

view and time horizon of an aggregated plan. Sales and Operation Planning (S&OP) generally uses a

monthly or quarterly view of anticipated demand summarized for purposes of planning long term operational

and resource requirements.

At the core of the Demand Planning process is the generation of a statistical forecast. Most Demand

Planning modules allow users to consider base (or average) demand, trend, seasonality, cycles, and

randomness in developing a forecast. Typically, a number forecast models will be available to use within the

application. The following are a few examples from a leading APS provider along with general guidelines on

how they are used.

• Derived: use when past demand data is non-existent or unreliable

• Inhibited: use to create a zero forecast

• Life Cycle Planning: use for new or end of life items

• Moving Average: use for items with very random demand histories or items with relatively flat demand

(i.e. no trend or seasonality)

S&OP

Plan(Constrained)

Consensus

Plan(Aligned)

Adjusted

Forecast(Unconstrained)

Statistical

Base LineForecast

Demand & Causal

Factor

Intelligence

Core Product Management

New Product

Introduction

Scope of “Leading Practice” Demand Planning Process

S&OP

Plan(Constrained)

Consensus

Plan(Aligned)

Adjusted

Forecast(Unconstrained)

Statistical

Base LineForecast

Demand & Causal

Factor

Intelligence

Core Product Management

New Product

Introduction

Scope of “Leading Practice” Demand Planning ProcessScope of “Leading Practice” Demand Planning Process

Frozen Period

(1 – 2 weeks)

Telescopic Granularity – Daily, Weekly, Monthly, Quarterly

Historical Horizon(12 - 36 months)

Forecast Planning Horizon

(12 – 36 months)

Frozen Period

(1 – 2 weeks)

Telescopic Granularity – Daily, Weekly, Monthly, Quarterly

Historical Horizon(12 - 36 months)

Forecast Planning Horizon

(12 – 36 months)



• Non-seasonal: use this model when demand is trending but does not vary seasonally

• Irregular: use these models for items which are seldom used or if there are zero demand months

• Seasonal: use this model when demand is often higher or lower during particular times of the year

In addition, smoothing factors can be applied to the base, trend, and seasonal components of a forecast.

Smoothing factors allow each of these components and/or more recent data history to be weighed more or

less heavily in the creation of the forecast. Products in volatile markets, for example, may need to weigh

recent demand history more heavily than products with similar year over year trends.

Another important feature to consider is the demand planning hierarchy and the application of factoring

logic. As an example, leading forecasting systems will plan and forecast at multiple, user-defined levels

within a hierarchal pyramid structure.

Each level is independently forecasted within

the hierarchy, and the initial totals across levels

are usually unequal. Since each level must

eventually equal, top-down factoring logic is

then applied. Generally, forecasts are more

accurate when performed at a higher level of

detail. Forecasting demand for an entire product

group is usually more accurate than the sum of

the forecasts for each individual item within that

product group. The same is generally true when

forecasting across multiple inventory locations

for the same item. Therefore, factoring the

lower level detail by the higher level totals is

considered as a leading business practice which

ultimately results in higher overall forecast

accuracy and service level performance.

Inventory Planning

Inventory Planning is the link between Demand Planning and Replenishment Planning. It dynamically

computes time-phased inventory levels by item and location based on anticipated demand, replenishment

lead times, and required service levels. Inventory Planning is where the business rules and parameters are

established for:

• Reorder Point = Expected demand during replenishment lead time plus safety stock

• Safety Stock = Quantity held in stock to accommodate variability in customer demand and supplier

reliability (where the service level target establishes the amount of variability to cover)

• Order Quantity = Quantity ordered from supply point when reorder point is hit (may be a fixed or

variable quantity)

Key inputs include:

• Demand forecast by item and location: as the forecast changes so does the reorder point (if so

configured)

• Replenishment lead time (and lead time variation): used in determining the reorder point

• Forecast error: used as input to safety stock calculation

• Service level target: also used as input to the safety stock calculation

Exhibit 4: Demand Planning Hierarchy

(Illustrative)

Super

Group

Product Group

Item

Item & Location

Item, Location & Other Attributes

5

4

3

2

1

Super

Group

Product Group

Item

Item & Location

Item, Location & Other Attributes

5

4

3

2

1



Exhibit 5: Inventory Reorder Point Logic (Illustrative)

The primary output is a time-phased inventory plan used as input to Replenishment Planning.

Safety stock is required to meet service levels when variability exists for demand and supply. The higher the

variability (or forecast error) and the higher the service target, the higher the safety stock needed to meet

demand. This is illustrated by the following normal distribution chart.

Exhibit 6: Normal Distribution Chart (Illustrative)

As demand becomes more variable, the curve widens and more safety stock is needed to meet an

established service level target. Slower moving items tend to have more variable demand, resulting in more

safety stock required on a relative basis.

Reorder Point

Safety Stock

Order

Qty.Order

Qty.

Order

Qty.

LeadTime

LeadTime

LeadTime

Inventory

Time

Reorder Point

Safety Stock

Order

Qty.Order

Qty.

Order

Qty.

LeadTime

LeadTime

LeadTime

Inventory

Time

K=2

Safety Stock = function(K*σF,S,LT)

Service Level = 97.7%

Shortages

Mean

All Demand Satisfied

Lead Time Demand =LT*DK=2

Safety Stock = function(K*σF,S,LT)

Service Level = 97.7%

Shortages

Mean

All Demand Satisfied

Lead Time Demand =LT*D



Organizations must also consider the diminishing rate of return on investment in safety stock, as depicted in

the following illustrative chart of the service vs. inventory trade-off curve.

High service level targets require substantially

more inventory. That is why a leading

business practice is to segment service level

targets by inventory class. For example, 98%

service level target for “A” items, 95% for “B”

items, and 90% for “C” items. This

concentrates inventory investment in those

products with the most importance to the

organization.

Most leading Inventory Planning solutions

offer several methods for calculating safety

stock, including the use of a defined service

level target for each item. Here are a few

examples and a perspective on their

recommended application.

• Fixed Quantity

— Use this method to limit investment in high cost items, new items, items with highly variable supply,

or items where forecast error exceeds the standard deviation of demand

— May also be used to maintain an agreed minimal balance for a customer

• Lead Time (sum of forecast during replenishment lead time): use for dependent demand transfer items

(e.g. from RDC to service center) to cover replenishment lead time from WH to WH

• Periods of Supply (# of days of forecast to cover)

— Use for items with less predictable demand (high error rate but less than std. deviation in demand),

less predictable service level performance (due to erratic demand or supply reliability), but desired

minimal balances

— Potentially good method for slowest moving items

— May also best used for internal transfer of dependent demand items where forecast days equal

replenishment days

• Service Level (the expected unit demand fill rate)

— Use to provide a consistent service level (e.g. 95%) for items with predictable demand patterns (i.e.

forecast error < std. deviation of demand)

— For many organizations, this will be the most prevalently used safety stock method

• Minimize Backorders (the expected order demand fill rate): use if order fill rate is deemed more

important than unit fill rate and demand is relatively predictable

A reorder point is the point at which a new order is triggered. Generally, it is derived based on expected

demand during a specified time period plus safety stock. Five common methods for deriving reorder points

and perspective on their recommend application are as follows.

• Fixed quantity

— Use for items with unpredictable demand (forecast error > std. dev. of demand), low service

requirements, and no minimal balances (or embed safety stock by increasing the fixed quantity)

— May also be used when tied to a storage unit of measure such as pallet (e.g. reorder when only one

pallet is on hand in the warehouse)

• Fixed quantity + safety stock

— Use for items with unpredictable demand but required minimal balances (e.g. new items)

Exhibit 7: Service vs. Inventory Tradeoff Curve

(Illustrative)

100

90

80

70

60

50

40

30

20

10

0S

erv

ice

Level %

Inventory Investment

90%95% 98%

100

90

80

70

60

50

40

30

20

10

0S

erv

ice

Level %

Inventory Investment

90%95% 98%



— Similar to above method but allows safety stock to be calculated using a different method

• Forecast for X periods (Periods of Supply)

— Use for items with predictable demand, ordered on a periodic basis, but with low service

requirements, and no minimal balances (or embed safety stock by increasing the number of periods

of supply)

• Forecast for X periods (Period of Supply) + safety stock

— Use for items with predictable demand and high service levels but ordered on a predetermined,

periodic basis (e.g. weekly orders for high volume items when more than one order may be

generated during the replenishment lead time)

— Allows safety stock to be calculated using a different method

• Forecast during lead time + safety stock

— Use for items with predictable demand, high service level requirements, an orders generated on non-

periodic basis

— For many organizations, this will be the most prevalently used reorder point method.

Inventory Planning logic assumes an order will be generated when inventory hits a reorder point. It does not

create the supply order, but it does assume an order quantity method will be used when creating an

inventory plan. There are several methods for determining an order quantity. Here are a few of the more

common methods and perspective on their recommended application.

• Fixed Quantity: use when the same size order is required every time (e.g. agreed allocations from

suppliers); or when demand is highly stable (minimal trending, seasonality or randomness)

• Fixed Minimal Quantity: use to take advantage of a known price break (however the minimum will be

fixed regardless of actual need, so the use of this method may be limited)

• Economic Order Quantity (EOQ)

— A fixed quantity determined by [(2*annual forecast*order cost)/(inventory carrying cost per

unit)}^0.5

— Not recommended unless these costs are known, fixed quantities are desired, and demand is stable

• Periods of Supply (# of days of forecast to cover)

— Use when ordering for a period of time rather than a fixed quantity (e.g. weekly or monthly order

quantities rather than a fixed quantity), or use when EOQ is not known with confidence

— For many organizations, this will be the most prevalently used order quantity method.



The following exhibit summarizes the recommended application of inventory planning parameters. Since

every organization’s requirements and product characteristics are unique, it should be viewed simply as

general guideline.

Exhibit 8: Recommended Application of Inventory Planning Parameters

(Illustrative)

Replenishment Planning

Replenishment Planning links planning and purchase order execution by creating recommend order

quantities based on forecasted demand, future inventory positions, and replenishment lead times.

Replenishment planning is also often referred to as Distribution Requirements Planning (DRP). Basic features

offered within the DRP modules:

• Automatically reconciles forecasts and customer orders

• Calculates a time phased (day-by-day) planned inventory (by adding in expected receipts and subtracting

the net requirements)

• Projects when inventory will drop into the safety stock

• Determines when an order must be released to prevent using safety stock

• Creates a recommended purchase quantity for authorization.

• Identifies exception situations where supply and demand are out of balance and expedited orders are

needed

Exhibit 9: DRP Example and Graphical Depiction (Illustrative)

Type of Product Order Pattern Restriction Demand Behavior Service Level

Inventory Parameters High Cost New End of Life

Dependent

Demand Item

Periodic Order

Frequency

Non-Periodic

Frequency

Handling,

Storage,

Purchasing

Restriction

Stable

Demand

Limited Trend

or Seasonality

Predictable by

Variable

Demand

σerror < σdemand

Erratic

Demand but

σerror < σdemand

Highly

Variable

σerror > σdemand

High Service

Level

Minimal

Balance

Requirements

Order Quantity

EOQ Use if lieu of fixed quantity when the order cost and carrying costs are known

Fixed Quantity Yes Yes Yes Yes Yes Yes Yes Yes Yes

Minimum Use if lieu of fixed quantity when the minimim quantity is always purchased Yes

Periods of Supply (Variable Quantity) Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes

Reorder Point

Fixed Quantity Yes Yes Yes Yes Yes Yes

Fixed + Safety Stock Yes Yes Yes Yes Yes Yes Yes

Periods of Supply + Safety Stock Yes Yes Yes Yes Yes Yes Yes Yes

Periods of Supply Yes Yes Yes Yes Yes Yes

Forecast over Lead Time + Safety Stock Yes Yes Yes Yes Yes Yes Yes

Safety Stock

Fixed safety stock quantity Yes Yes Yes Yes Yes Yes Yes

Sum of forecast over lead time Yes Yes Yes Yes

Periods of Supply Yes Yes Yes Yes Yes Yes Yes

Service level Yes Yes Yes Yes Yes Yes Yes Yes

Minimize backorders Use in lieu of service level if order fill rate is preferred metric to unit fill rate

Periods 0 1 2 3 4 5 6 7 8 9 10

Beginning Inventory 180 280 180 100 210 100 160 270 190 280

Projected Demand 100 100 80 90 110 140 90 80 110 100

Inventory (if no receipt) 80 180 100 10 100 -40 70 190 80 180

Planned Order 0 0 200 0 200 200 0 200 0 200 0

Planned Order Receipt 200 0 0 200 0 200 200 0 200 0

New Ending Inventory 280 180 100 210 100 160 270 190 280 180

Standard Order Quantity 200

Safety Stock 80

Lead Time Periods 2

Average Demand per Period 100

Periods 0 1 2 3 4 5 6 7 8 9 10

Beginning Inventory 180 280 180 100 210 100 160 270 190 280

Projected Demand 100 100 80 90 110 140 90 80 110 100

Inventory (if no receipt) 80 180 100 10 100 -40 70 190 80 180

Planned Order 0 0 200 0 200 200 0 200 0 200 0

Planned Order Receipt 200 0 0 200 0 200 200 0 200 0

New Ending Inventory 280 180 100 210 100 160 270 190 280 180

Standard Order Quantity 200

Safety Stock 80

Lead Time Periods 2

Average Demand per Period 100

-100

-50

0

50

100

150

200

250

300

1 2 3 4 5 6 7 8 9 10

Receipts

Demand

Inventory on Hand

Inventory (if no receipt)

Safety Stock



This capability is often referred to as time-phased planning. Essentially, it takes a proactive approach to

planning orders based on projected future inventory levels. Much like a material requirements planning

(MRP) system, it also allows users to define dependent demand relationships, such as in a hub and spoke

distribution network. In doing so, it lowers the overall investment in inventory.

Summary

APS capabilities in Demand Planning, Inventory Planning, and Replenishment Planning enable organizations

to reduce inventories and lower operating costs while also raising service level performance. To maximize

benefit, it requires careful thought on how best to apply the capabilities of the software to business needs

and the unique characteristics of each planned item. Whether selecting a package, implementing the

software, or tuning-up the process, organizations must recognize both the importance and challenge in

determining which planning models and parameters to use. Several methods are usually available within any

leading APS package. This overview has covered many of the more common methods and a perspective on

how they may be applied. Appropriate application, in concert with other critical success factors, will aid

greatly in helping organizations achieve and sustain desired benefits from their APS investment.

pov - aligning aps functionality to plan demand and manage inventory

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