Demand Planning in a Period of Economic...

JPK

Gro

upBusiness Forecasting and Analytics Forum

March 1-2 • San Francisco, CA

Demand Planning in a Periodof Economic UncertaintyIncorporating macroeconomic forecasts

into demand planning processes

March 1, 1:00pm

View presentation online at:

https://jpkgroupsummits.com/attendee1

Andy Fisher – End-to-End AnalyticsAndy Fisher is an experienced analytical consultant, having spent almost fifteen years

designing, developing, and implementing analytical systems in the high-tech manufacturing,consumer product, and financial service industries. His work has focused on applying

quantitative approaches to demand forecasting, financial modeling, and risk management.Prior to joining End-to-End Analytics, Andy worked at Cisco Systems in San Jose,developing and implementing statistical demand forecasting, new product demand

forecasting, and Sales and Operations Planning (S&OP) solutions. Andy holds a Ph.D. inEconomics with a focus in time series econometrics and financial economics.

Demand Planning in a

Period of Economic

Uncertainty

Andy Fisher

[email protected]

March 1, 2016

Demand planning processes usually rely on time series-

based models…

By Class, SKU, etc.

By location

By time period

Demand historyTime series models

Final demand planAutomatically select best:

• Moving average

• Exponential smoothing (ES)

• ES with trend / seasonality

• Croston’s (sporadic demand)

Consensus process

Judgmental inputs

Finalize forecast

…but there are known problems with time series

forecasting techniques

Time series techniques and simple statistical

models underperform when:

Future different from the past

Noise leads to model overffiting

Lack of history

Data contains outliers

Step changes

Insufficient variation of causal drivers

etc.

In an uncertain economy, the future is likely to look different from the past

Women’s apparel store sales through 2014 – upward

trend in 2015?

2/28/20164© End-to-End Analytics, LLC

-12%

-8%

-4%

0%

4%

8%

12%

16%

I II III IV I II III IV I II III IV I II III IV

2011 2012 2013 2014

Yo

Y G

row

th

Sales peaked in late 2014 – time series techniques

would have led to positive forecast bias – what to do?

-12%

-8%

-4%

0%

4%

8%

12%

16%

I II III IV I II III IV I II III IV I II III IV I

2011 2012 2013 2014 2015

Yo

Y G

row

th

How do economists predict the economic future?

Economic forecasting can be defined as a set of hypothetical

statements about future aggregate developments

Two focus areas in macroeconomic forecasting:

1. Business cycle analysis or nowcasting

2. Longer-term economic projections

Economists use regression models to nowcast from

more frequent economic data and “bridge” to GDP…

∆ 𝑙𝑜𝑔𝑌𝑡 =

𝑖≥1

𝑎𝑖𝑋𝑡+1−𝑖 + 𝑏𝑖∆𝑙𝑜𝑔𝑌𝑡−𝑖

Y = GDP X = frequently updated exogenous variables

Bridge model equation

…the Atlanta Fed has a freely available business

cycle model


www.frbatlanta.org

Economists use structural econometric models to

create longer-term macroeconomic forecasts…

Econometric models are based on past

relationships between variables such as

consumer spending, business investment,

etc.

These models are built using systems of

equations based on economic theory

Economists use these models to forecast how

changes in some variables will affect the

future values of others


𝐶𝑡 = 𝑎1 + 𝑎2𝑌𝑡−1𝐼𝑡 = 𝑏1 + 𝑏2(𝑌𝑡−1 − 𝑌𝑡−2)𝑌𝑡 = 𝐶𝑡 + 𝐼𝑡 + 𝐺𝑡

C = consumptionI = investmentY = GDPG = government spending

Simple Keynesian Model

…the Philadelphia Fed prepares a quarterly summary

of business economists’ economic forecasts


www.philadelphiafed.org

If you can estimate the relationship between sales

and relevant macroeconomic series…

-15%

-10%

-5%

0%

5%

10%

15%

04 05 06 07 08 09 10 11 12 13 14 15

Womens Apparel Sales

Nondurable Consumption

Yo

Y G

row

th

…then you can create sales forecast based on

expected macroeconomic conditions

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

October

Novem

ber

Decem

ber

January

February

March

April

May

June

JulyAugust

Septem

ber

October

14 15

Forecast Made in April

Forecast Made in March

Forecast Made in May

Womens Apparel Sales

Yo

Y G

row

th

𝑆𝑡 = 𝑎1𝑁𝐷𝐶𝑡 + 𝑎2𝑆𝑡−1 + 𝑆𝑡−2

S = sales YoY growthNDC= non-durable consumption YoY growth

In an uncertain economy, adding econometric models to

your process may improve demand planning outcomes

By SKU

By location

By time period

Demand historyTime series models

Moving average

Exponential smoothing (ES)

ES with trend / seasonality

Croston’s (sporadic demand)

ARIMA (statistical models)

Regression models

Macro-economic data

Business cycle models

Final demand plan

Consensus process

Judgmental inputs

Finalize forecast

Economic

adjustments

Econometric models

Economic forecasting

Economic forecasting can be defined as a set of hypothetical

statements about future aggregate developments

It involves: A view of the economic future, reflected in quantitative estimates

An underlying analytical story

A discussion of possible courses of action and their likely consequences

Economic forecasting is basically a structured way of peering into

the future using all available information

Two aspects to macroeconomic forecasting

1. Business cycle analysis or nowcasting

2. Longer-term economic projections

Source: Carnot, Koen, and Tissot (2011), Economic Forecasting and Policy

Bridge models – simple technique for using short-

term indicators to understand the business cycle

Bridge models use regression framework to “bridge”

explanatory variables to the variable to be forecast

16

∆log𝑌𝑡 =

𝑖≥1

𝑎𝑖𝑋𝑡+1−𝑖 + 𝑏𝑖∆𝑙𝑜𝑔𝑌𝑡−𝑖

Where X is the qualitative exogenous variable, Y is the quantitative endogenous variable, ∆log𝑌𝑡is the growth rate of Y

Frequently updated set of Xs to help us determine where we are in the

cycle

A subset of U.S. Economic data released each month


Date Indicator Period Source1/4/2016 ISM Manufacturing PMI December Institute for Supply Management1/4/2016 Construction Spending November Census Bureau

1/6/2016 International Trade Balance NovemberU.S. Census Bureau,U.S. Bureau of Economic Analysis

1/6/2016 ISM Non-manufacturing PMI December Institute for Supply Management1/8/2016 Total Nonfarm Payrolls December Bureau of Labor Statistics1/8/2016 Unemployment Rate December Bureau of Labor Statistics

1/15/2016 Retail Sales December U.S. Census Bureau1/15/2016 Industrial Production December Federal Reserve Board of Gov1/21/2016 Consumer Confidence January University of Michigan1/28/2016 Durable Goods December U.S. Census Bureau2/1/2016 Personal Income December U.S. Bureau of Economic Analysis

St. Louis Fed FRED and US Financial Data


Use performance statistics to validate forecast

improvements

Pag

e 19© End-to-End Analytics 2014

Forecast Accuracy metric

measures forecast error

Forecast Value Add measures

forecast performance over a

naïve model

Macroeconomics: The circular flow of income and

expenditures

Simple model: households (individuals)

and business

In a 2 sector model, income =

expenditures

5 sector model: Add financial sector,

government sector, rest of world

(overseas) sector

Additional sectors bring in leakages and

injections

Measuring the U.S. economy

3 Data sources explain the U.S. economy: Real Economy

National Income and Product Accounts (Bureau of Economic Analysis BEA)

Financial Sector Flow of Funds Accounts (Federal Reserve Fed)

International Sector Balance of Payments (BEA)

Focus is on the real economy – NIPAs Financial and International sectors relevant for impact on real

economy

GDP = C + I + G + NX Consumption, Investment, Gov’t Spending, Net Exports

National Income and Product Accounts (NIPAs)

From the circular flow model, GDP can

be measured 2 ways – the income

approach and expenditures approach

Demand Planning in a Period of Economic...

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