The increasing sophistication and expanding role of demand forecasting present new opportunities for retailers to fully optimize everything from assortment planning to pricing, space management and replenishment in both their traditional and new digital selling channels. Retail Systems Research (RSR) presents the results of its first annual benchmark study by analysts Brian Kilcourse and Nikki Baird on the state of retail demand forecasting. This complimentary webinar answers key questions such as: What are the challenges and opportunities in demand forecasting? Has forecasting accuracy improved? In what areas? What does this mean for retailers? How can retailers integrate demand forecasting in other areas of their operations? Can retailers have (or should they have) a single demand forecast for everything? What is the potential impact of new cloud-based demand forecasting systems?

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5. FEATURED SPEAKER
SPEAKER
Brian Kilcourse Rafael Gonzalez Caloni
Managing Partner EVP Marketing
Retail Systems Research Predictix
Debbie Hauss
MODERATOR
Editor-in-Chief
Retail TouchPoints

6. Crystal Ball 2.0: The
State of Retail
Demand Forecasting
B RIAN K ILCOURSE
M ANAGING P ARTNER , RSR R ESEARCH
M AY , 2011

7. A LITTLE BIT ABOUT RSR…
Our Mission: To provide the best research in retail built on:!
 Expertise gained through real world practitioner experience"
 Objective views"
 Unique, high value products & services"
 Perspective: industry view from consumer to source"
 Focus on customer experience"
Because RSR is built entirely of retail veterans, we are the only
analyst firm that can truly provide:!
 Genuine insight into business and technology challenges facing the extended retail
industry"
 Thought leadership and advice on navigating these challenges for specific companies
and the industry at large"

8. Study Premise: “past results are
no predictor of future performance”
The statement “past results are no predictor of future performance” is almost
a cliché when it comes to both financial performance and retail trends, as proved
by the recent economic downturn. As retailers add more optimization capabilities
to everything from assortment planning to pricing to space management and
replenishment, both the sophistication and the role of demand forecasting present
new opportunities for retailers."
RSRʼs first annual benchmark study into retailersʼ demand forecasting capabilities
explored how changes in the business cycle and in channels have impacted the
discipline. We wanted to identify:"
• Whether forecasting accuracy has improved!
• Whether the output of a demand forecasting integration with various parts
of the retail organization is improving!
• Whether retailers think it is possible to have a single demand forecast for
everything and why or why not – and how close they come to their ideal.!

9. The Growing Importance of
Demand Forecasting
Demand Forecasting's Importance
Over the Last 3 Years
Unchanged
12%
Grown
less
important
3%
Two events have catapulted Demand Grown
more
Forecasting in importance:
important
85%
#1 The Recession
#2 Focus on The Customer
9

10. Business/financial 53%
43%
planning 62%
63%
Supply chain planning 60%
67%
Merchandise financial 49%
Everything
50%
planning 46%
37%
Assortment planning 37%
33%
20%
Space planning 13%
All
26%
Size planning & 16%
13%
optimization
Winners
18%
Pack planning 16%
10%
& optimization
Others
21%
Price planning 23%
20%
Demand Forecasting Touches
& optimization 23%
Where Demand Forecasting is Currently Used
32%
Markdown pricing 27%
36%
existed as isolated pockets within siloed organizations.
16%
Channel planning 13%
18%
in their demand forecasting abilities, up until now those abilities have
55%
But, while there are areas where retailers have grown fairly sophisticated
Replenishment 60%
54%
10

11. Very Different Attitudes About What
“One Version Of The Truth” Means
(But No One Attitude Prevails….)
Forecast Attitudes
Winners Others
Different uses require different forecasts that
43%
should then be reconciled across the
32%
enterprise.
A single demand forecast is critical to 17%
achieving a “single version of the truth” 38%
A single source for forecasts, or a
27%
consolidated forecast, is the best way to get
12%
to "one version of the truth"
A single demand forecast is impossible to 7%
achieve 10%
A single demand forecast isn’t as important 7%
as a single set of demand assumptions 8%
11

12. Not Surprisingly, Winners
Have Improved
Forecast Accuracy Over the Last 3 Years
Winners Others
70%
Grown more accurate
40%
17%
Stayed the same
48%
3%
Don't know
10%
10%
Grown less accurate
2%
12

13. Business Challenges

14. The Top Challenge:
Recession-Era Promotional
Activity To Trigger Demand
Top-3 Business Challenges of Demand Forecasting
All Winners Others
42%
Recent economic factors make it exceedingly
38%
difficult to forecast demand
46%
40%
Too many promotions in the marketplace make
54%
demand difficult to forecast
31%
32%
Fragmentation of demand makes it difficult to
38%
forecast an accurate aggregate picture
29%
31%
Consumer behavior has fundamentally shifted and
23%
we haven’t figured it out yet
37%
27%
Seasonal and erratic sales patterns 19%
31%
14

15. The Forecasting Challenge Closely
Reflects Another Challenge: The
After-Effects Of Aggressive Pricing
To Trigger Demand
Top Three (3) Business Challenges Driving Pricing Strategies
2011 2010
Increased price sensitivity of consumers 58%
46%
Increased pricing aggressiveness from 48%
competitors 38%
Increased price transparency - the impact of 40%
comparative price shopping 11%
Need to protect our brand's price image 38%
28%
Increased promotional intensity of competitors N/A
32%
Need to provide consistency in price across 32%
channels 6%
Need to provide more localized pricing 14%
7%
Respond to segment blurring 10%
16%
Source: Optimizing Price in a Transparent World,
Benchmark Study, RSR Research, April 2011
15

16. Aggressive Pricing + Transparency =
Increased Price Sensitivity =
Difficulty Forecasting Future Demand
Forecast Types That Present A "Major Challenge"
Winners Others
54%
Price sensitivity
39%
42%
Promotions
53%
42%
Long term forecasts
50%
38%
New product introductions
47%
33%
Assortment sensitivity
29%
16

17. Winners Are Most Keenly Aware
Of The Omni-Channel Effect
Operational Challenges ("Major Challenge")
Winners Others
Difficulty in capturing cross-channel events that 42%
affect customer behavior and channel demand 21%
Information lags or “holes” both on the supply
42%
chain side, sales side, or the marketing/
45%
promotions side
Un-integrated multiple demand signals in 38%
planning and logistics 41%
A “throw it over the wall” mentality across
31%
assortment, price, promotions, space, and
32%
replenishment planning
Poor understanding of customer behavior by 31%
channels 29%
Inconsistent or non-existent in-process forecast 31%
performance metrics 47%
17

18. Opportunities

19. The Best Near-Term Opportunity:
Getting Better
Value vs. Challenge of Forecast Accuracy by Forecast Type
Very Valuable Major Challenge
Long term forecasts 68%
46%
New product introductions 65%
44%
Promotions 60%
47%
Baseline demand (continuity goods) 59%
12%
Price sensitivity 53%
45%
Short term forecasts 46%
21%
Seasonal items 42%
28%
Assortment sensitivity 36%
30%
Markdowns 33%
25%
Short lifecycle items 26%
30%
Intermittent items 16%
21%
19

20. Directionally, Most Retailers Agree – Except
About The Omni-Channel Effect (And What That
Might Mean To The S/C Network Design)
Opportunities to Overcome Forecast Accuracy Challenges
("A Lot of Value")
Winners Others
A forecast suitable for multiple situations (new products, 81%
promotions, end of life, etc.) 52%
A single view of demand, inventory, and supply across the 81%
supply chain and all selling channels 68%
76%
An integrated forecasting infrastructure 63%
71%
Better forecast models to reduce forecast error 67%
62%
Improve execution to better respond to changes in demand 53%
Optimize inventory investment to reduce the portion of 52%
inventory that is stocked for protection against demand 55%
variability 52%
Improved cross-channel demand forecasts 13%
48%
A single demand forecast 42%
40%
Supply and distribution network redesign 16%
Inventory postponement strategies to increase flexibility 33%
(for example, “manufacture to order”) 37%
25%
Reduce or even eliminate delivery “latency” 19%

21. Organizational Inhibitors

22. Top Inhibitors…
For Winners, the top inhibitors have to do
with siloed activities that are disconnected
to the hyper-competitive realities of today’s
retail landscape;
For Others, it’s the system….

23. Top Organizational Inhibitors
Winners Others
55%
Purchase of supply is disconnected from fulfillment of demand
31%
Our current solution has difficulties with challenging forecasting
50%
problems (such as promotions, new product introductions, short
41%
lifecycle products, intermittent items)
The “80/20” rule: 20% of our forecast challenges take up 80% of our 30%
time 34%
Our processes prevent us from responding quickly to changes in 30%
demand 34%
Our systems prevent us from forecasting at a low enough level of 30%
granularity 38%
Getting consensus between departments involved in developing 25%
forecasts takes too long 21%
Time and investment required to replace our current forecasting 25%
system 34%
Organizational differences prevent us from working well together to 20%
meet demand 28%
Demand management is built around stores; doesn’t work well for 20%
other channels 14%
Restrictions in how we replenish prevent us from taking advantage of 20%
demand 17%
We cannot tell how new marketing initiatives in non-store channels 15%
such as social media is affecting demand in stores 24%

24. Top Organizational Inhibitors
Winners Others
55%
Purchase of supply is disconnected from fulfillment of demand
31%
Our current solution has difficulties with challenging forecasting
50%
problems (such as promotions, new product introductions, short
41%
lifecycle products, intermittent items)
The “80/20” rule: 20% of our forecast challenges take up 80% of our 30%
time 34%
Our processes prevent us from responding quickly to changes in 30%
demand 34%
Our systems prevent us from forecasting at a low enough level of 30%
granularity 38%
Getting consensus between departments involved in developing 25%
forecasts takes too long 21%
Time and investment required to replace our current forecasting 25%
system 34%
Organizational differences prevent us from working well together to 20%
meet demand 28%
Demand management is built around stores; doesn’t work well for 20%
other channels 14%
Restrictions in how we replenish prevent us from taking advantage of 20%
demand 17%
We cannot tell how new marketing initiatives in non-store channels 15%
such as social media is affecting demand in stores 24%

25. Top Organizational Inhibitors
Winners Others
55%
Purchase of supply is disconnected from fulfillment of demand
31%
Our current solution has difficulties with challenging forecasting
50%
problems (such as promotions, new product introductions, short
41%
lifecycle products, intermittent items)
The “80/20” rule: 20% of our forecast challenges take up 80% of our 30%
time 34%
Our processes prevent us from responding quickly to changes in 30%
demand 34%
Our systems prevent us from forecasting at a low enough level of 30%
granularity 38%
Getting consensus between departments involved in developing 25%
forecasts takes too long 21%
Time and investment required to replace our current forecasting 25%
system 34%
Organizational differences prevent us from working well together to 20%
meet demand 28%
Demand management is built around stores; doesn’t work well for 20%
other channels 14%
Restrictions in how we replenish prevent us from taking advantage of 20%
demand 17%
We cannot tell how new marketing initiatives in non-store channels 15%
such as social media is affecting demand in stores 24%

26. But, Retailers Agree: Better Tech
IS A Key To Overcoming
Inhibitors Overcoming Inhibitors ("Very Valuable")
Winners Others
Technologies that enable better monitoring of changes in 74%
demand or deviations from forecasts 64%
Technologies that produce better forecasts for challenging
74%
events (promotions, new product introductions, intermittent
59%
items, short lifecycle items)
Executive-level support of more coordinated demand 70%
management processes 69%
67%
Technologies that enable more granular demand forecasts
43%
A stronger demand management process, to sync forecasts 63%
with sales & ops plans 41%
55%
More management-by-exception analysis capabilities
41%
Technologies that facilitate forecast consensus building 50%
between departments 28%
New or improved KPIs to measure not only forecast accuracy
47%
and service levels, but also process measures like number of
34%
forecast adjustments
Cross-channel fulfillment processes to make all inventory 33%
available in every channel 14%
Process changes to allow greater flexibility in responding to 26%
demand 41%
26

27. But, Retailers Agree: Better Tech
IS A Key To Overcoming
Inhibitors
Overcoming Inhibitors ("Very Valuable")
Winners Others
Technologies that enable better monitoring of changes in demand or 74%
deviations from forecasts 64%
Technologies that produce better forecasts for challenging events
(promotions, new product introductions, intermittent items, short
74%
59%
lifecycle items)
Executive-level support of more coordinated demand management 70%
processes 69%
Technologies that enable more granular demand forecasts 67%
43%
A stronger demand management process, to sync forecasts with sales 63%
& ops plans 41%
More management-by-exception analysis capabilities 55%
41%
Technologies that facilitate forecast consensus building between 50%
departments 28%
New or improved KPIs to measure not only forecast accuracy and
47% Let’s Take
service levels, but also process measures like number of forecast A Look
34%
adjustments
Cross-channel fulfillment processes to make all inventory available in 33%
every channel 14%
Process changes to allow greater flexibility in responding to demand 26%
41%
27

28. The Use Of KPI’s Lags Their
Perceived Value – By a Long
Shot! Value vs. Use of Forecast KPI's
Very Valuable In Use Today
Improved margins per category, sub-category, item 79%
58%
Increased Turns per category, sub-category, item 76%
29%
Lower Inventory Carrying Costs 69%
38%
Forecast Accuracy 66%
38%
Lower Out of Stock rates 65%
46%
Improved sales per category, sub-category, item 65%
31%
Lower Inventory Investment 62%
10%
More efficient forecasting process (staff productivity) 60%
6%
Fewer forecast adjustments 58%
6%
Reductions in inactive stock 52%
6%
Better yielding investment in safety stock 50%
10%
Fewer forecast exceptions 48%
4%
Improved Replenishment cycle time 42%
4%
Faster Order-to-delivery cycle rates 35%
28
4%

29. Technology Enablers

30. Technology: Value vs. Implemented
Winners-Value Winners - Impl. Others - Value Others - Impl.
74%
"What-if" scenario modeling 50%
45%
35%
Integrated replenishment, purchasing and forecasting 50%
70%
72%
processes 36%
58%
Integrated optimization of space and replenishment 20%
39%
25%
55%
Predictive analytics that warn of deviations from forecast 20%
59%
22%
55%
Integrated optimization of assortment and space 20%
41%
32%
55%
Customer-based demand forecasting 50%
43%
32%
53%
Bottom-up (or “DRP”) forecasting capabilities 55%
24%
47%
50%
Continuous, time-phased demand forecasting 65%
52%
43%
Modeling process to convert insights into quantitative 50%
65%
48%
forecasts 32%
45%
Integrated optimization of size and pack 30%
45%
36%
35%
Forecasting workflows to manage the process 35%
41%
32%
Common forecast performance metrics across 32%
35%
62%
organizations 29%
In-process forecast performance measures that align 20%
30%
21%
with a multi-channel environment. 28%

31. Opportunities For Retailers

32. Tier 1 vs. Tier 2:
Different Problems To Overcome
The Top Organizational Inhibitors
T1 Mid
Our current solution has difficulties with challenging forecasting
61%
problems (such as promotions, new product introductions,
short lifecycle products, intermittent items)
30%
The “80/20” rule: 20% of our forecast challenges take up 80% 35%
of our time 40%
Our processes prevent us from responding quickly to changes 35%
in demand 40%
Time and investment required to replace our current 35%
forecasting system 30%
30%
Purchase of supply is disconnected from fulfillment of demand
40%
Organizational differences prevent us from working well 30%
together to meet demand 0%
Getting consensus between departments involved in 26%
developing forecasts takes too long 10%
Our systems prevent us from forecasting at a low enough level 22%
of granularity 70%

33. RSR recommends four steps:
• Examine Forecasting as a Stand-Alone
Process
• Every Process Requires an Owner
• Should Disconnected Forecasting
Processes Remain Disconnected?
• Don’t Rely on the Technology to Force
Process Change
33

34. What we do
We
help
Retailers
WHOLESALERS
( )
Make
be+er
Forecasting
Planning
Assortment … on the cloud
Pricing/promo
Replenishment
DECISIONS
Contents Proprietary & Confidential © 2011 Predictix LLC

35. Key challenges in forecasting
1 Difficult
forecasts
=
promo3ons,
new
products,
…
2 Omni-­‐channel
=
new
demand
signals
to
consider
3 Silos
=
inconsistent,
disconnected
forecasts
4 Heavy
investments
=
too
costly
to
replace
systems
Contents Proprietary & Confidential © 2011 Predictix LLC

36. Cracking difficult forecasts:
Design to take advantage of the cloud
The
iPad
2
is
as
fast
as
a
Cray
2
supercomputer
from
1985
–
and
would
have
s3ll
been
on
the
list
of
top
supercomputers
in
the
mid-­‐90s
May 9, 2011
Contents Proprietary & Confidential © 2011 Predictix LLC

37. Cracking difficult forecasts:
Design to take advantage of the cloud
The
iPad
2
is
as
fast
as
a
Cray
2
supercomputer
from
1985
–
and
would
have
s3ll
been
on
the
list
of
top
supercomputers
in
the
mid-­‐90s
May 9, 2011
Unlimited computing power on demand
=
More powerful science
=
30 – 50% better forecasts
Contents Proprietary & Confidential © 2011 Predictix LLC

38. Meeting the omni-channel challenge:
Be prepared to adapt to what’s next
Contents Proprietary & Confidential © 2011 Predictix LLC

39. Meeting the omni-channel challenge:
Be prepared to adapt to what’s next
Forecast engines
100% configured
fit for purpose/data
fast time to value
high performance
Contents Proprietary & Confidential © 2011 Predictix LLC

40. Breaking down silos and avoiding heavy investments:
Unified forecasting layered on existing systems
Planning Silo Pricing Silo Supply Chain Silo
Unified forecasting
" Different forecasts for different needs, and
" One version of the truth, and
" No rip and replace
Contents Proprietary & Confidential © 2011 Predictix LLC

41. Meeting the key challenges in forecasting
1 Use
the
cloud
to
drive
beNer
forecasts
2 Adapt
to
and
integrate
new
demand
signals
3 Overlay
beNer
forecasts
across
silos
4 Extend,
don’t
replace,
exis3ng
systems
Contents Proprietary & Confidential © 2011 Predictix LLC

42. Your
GoToWebinar
A/endee
Viewer
is
made
of
2
parts:
1.
Viewer
Window
2.
Control
Panel
Type
your
quesAon
here

43. FEATURED SPEAKER
SPEAKER
Brian Kilcourse Rafael Gonzalez Caloni
Managing Partner EVP Marketing
Retail Systems Research Predictix
Debbie Hauss
MODERATOR
Editor-in-Chief
Retail TouchPoints

44. For a free copy of RSR’s May
2011 Benchmark Report:
Crystal Ball 2.0: The State of
Retail Demand Forecasting
http://www.rsrresearch.com

45. You can download this presentation here:
http://rtou.ch/Crystal-Ball
Contact Info:
Brian Kilcourse
bkilcourse@rsrresearch.com
Rafael Gonzalez Caloni
rafael.gonzalez@predictix.com