• Like
RSR's Brian Kilcourse Presents The State of Retail Demand Forecasting 2011
Upcoming SlideShare
Loading in...5
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

RSR's Brian Kilcourse Presents The State of Retail Demand Forecasting 2011

  • 1,064 views
Published

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 …

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?

Published in Business , Economy & Finance
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Be the first to comment
    Be the first to like this
No Downloads

Views

Total Views
1,064
On SlideShare
0
From Embeds
0
Number of Embeds
1

Actions

Shares
Downloads
56
Comments
0
Likes
0

Embeds 0

No embeds

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
    No notes for slide

Transcript

  • 1. Your  GoToWebinar  A/endee  Viewer  is  made  of  2  parts:   1.  Viewer  Window   2.  Control  Panel   Type  your  quesAon  here  
  • 2. #LiveWebinar hashtag.
  • 3.   Launched in 2007  Over 20,000 subscribers  To provide executives with relevant, insightful content across a variety of digital mediumFree subscription to our weekly newsletter:www.retailtouchpoints.com/signup
  • 4. FEATURED SPEAKER SPEAKERBrian Kilcourse Rafael Gonzalez CaloniManaging Partner EVP MarketingRetail Systems Research Predictix Debbie Hauss MODERATOR Editor-in-Chief Retail TouchPoints
  • 5. Crystal Ball 2.0: TheState of RetailDemand Forecasting B RIAN K ILCOURSE M ANAGING P ARTNER , RSR R ESEARCH M AY , 2011
  • 6. 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"
  • 7. Study Premise: “past results areno predictor of future performance”The statement “past results are no predictor of future performance” is almosta cliché when it comes to both financial performance and retail trends, as provedby the recent economic downturn. As retailers add more optimization capabilitiesto everything from assortment planning to pricing to space management andreplenishment, both the sophistication and the role of demand forecasting presentnew opportunities for retailers."RSRʼs first annual benchmark study into retailersʼ demand forecasting capabilitiesexplored how changes in the business cycle and in channels have impacted thediscipline. We wanted to identify:"• Whether forecasting accuracy has improved!• Whether the output of a demand forecasting integration with various partsof the retail organization is improving!•  Whether retailers think it is possible to have a single demand forecast foreverything and why or why not – and how close they come to their ideal.!
  • 8. The Growing Importance of Demand Forecasting Demand Forecastings 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
  • 9. 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
  • 10. 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
  • 11. Not Surprisingly, WinnersHave Improved Forecast Accuracy Over the Last 3 Years Winners Others 70% Grown more accurate 40% 17% Stayed the same 48% 3% Dont know 10% 10% Grown less accurate 2% 12
  • 12. Business Challenges
  • 13. 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
  • 14. The Forecasting Challenge CloselyReflects Another Challenge: TheAfter-Effects Of Aggressive PricingTo 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 brands 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
  • 15. 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
  • 16. Winners Are Most Keenly AwareOf 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
  • 17. Opportunities
  • 18. 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
  • 19. 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%
  • 20. Organizational Inhibitors
  • 21. Top Inhibitors…For Winners, the top inhibitors have to dowith siloed activities that are disconnectedto the hyper-competitive realities of today’sretail landscape;For Others, it’s the system….
  • 22. 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%
  • 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. But, Retailers Agree: Better TechIS A Key To OvercomingInhibitors 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
  • 26. But, Retailers Agree: Better TechIS A Key To OvercomingInhibitors 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
  • 27. The Use Of KPI’s Lags Their Perceived Value – By a Long Shot! Value vs. Use of Forecast KPIs 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%
  • 28. Technology Enablers
  • 29. 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%
  • 30. Opportunities For Retailers
  • 31. Tier 1 vs. Tier 2:Different Problems To Overcome The Top Organizational Inhibitors T1 MidOur 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%
  • 32. RSR recommends four steps:• Examine Forecasting as a Stand-AloneProcess• Every Process Requires an Owner• Should Disconnected ForecastingProcesses Remain Disconnected?• Don’t Rely on the Technology to ForceProcess Change 33
  • 33. What we do We  help   Retailers WHOLESALERS ( ) Make  be+er   Forecasting Planning Assortment … on the cloud Pricing/promo Replenishment DECISIONSContents Proprietary & Confidential © 2011 Predictix LLC
  • 34. 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
  • 35. 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, 2011Contents 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 Unlimited computing power on demand = More powerful science = 30 – 50% better forecastsContents Proprietary & Confidential © 2011 Predictix LLC
  • 37. Meeting the omni-channel challenge: Be prepared to adapt to what’s nextContents Proprietary & Confidential © 2011 Predictix LLC
  • 38. 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 performanceContents Proprietary & Confidential © 2011 Predictix LLC
  • 39. 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 replaceContents Proprietary & Confidential © 2011 Predictix LLC
  • 40. 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
  • 41. Your  GoToWebinar  A/endee  Viewer  is  made  of  2  parts:   1.  Viewer  Window   2.  Control  Panel   Type  your  quesAon  here  
  • 42. FEATURED SPEAKER SPEAKERBrian Kilcourse Rafael Gonzalez CaloniManaging Partner EVP MarketingRetail Systems Research Predictix Debbie Hauss MODERATOR Editor-in-Chief Retail TouchPoints
  • 43. For a free copy of RSR’s May2011 Benchmark Report:Crystal Ball 2.0: The State ofRetail Demand Forecastinghttp://www.rsrresearch.com
  • 44. 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