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Oracle Retail Demand Forecasting Cloud Service In today’s omnichannel environment, customers demand unique and tailored experiences, engage with multiple channels, and expect more convenience than ever before. Omnichannel introduces complexity as retailers balance channel-specific strategies, cross-channel customer journeys and omnichannel fulfilment. The journey towards omnichannel proficiency continues and smart retailers are capitalizing on this complexity by asking new questions. What assortment decisions drive brand loyalty? How do traditional and digital promotional vehicles contribute to my sales objectives? What, when, and where is purchase and fulfilment demand? Predictive analytics answers these questions and accuracy is your competitive differentiator. Oracle Retail Demand Forecasting Cloud Service Oracle Retail Demand Forecasting Cloud Service (RDF CS) empowers retailers to centralize demand forecasts for their omnichannel enterprise — from operations and vendor collaboration to planning and optimization to marketing and insights — accurately and efficiently. The results achieved include increased and profitability revenue through higher in-stock rates and significant reductions in inventory. For example: Within days of implementing Oracle Retail Demand Forecasting, a Russian retailer was able to reduce DC inventory levels from 4 months to 3-4 weeks, improve forecasting accuracy 90-95% for non-promotional items and 75% for promotional items, reduce of out-of-stocks by 18%, increase order-taking speed 3x and decrease store inventory 13-16% A UK grocer reported a 50% increase in overall forecast accuracy A large national electronics chain has improved in-stock rates by 2%-4% Maximize Forecast Accuracy. With RDF CS, Oracle Retail distilled 15+ years of forecasting experience across 160+ retailers worldwide into an offering that combines best-fit science and exceptive-driven processes with the agility of an extensible cloud platform. RETAIL DATASHEET KEY BENEFITS Increase revenue and expand a loyal customer base with higher in-stock rates Increase profitability and assortment flexibility with decreased inventory levels Shift focus to strategy planning & collaboration and drive operations with sophisticated and highly automated forecasts Join an active community of 160+ retailers worldwide using our industry-leading forecasting capabilities Reduce TCO by 20-40% with SaaS delivery model Increase speed-to-value by 50% with partner implementation offerings of 8-12 weeks Shift from CapEx to OpEx with Subscription-based Pricing Model

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Page 1: Oracle Retail Demand Forecasting Cloud Service - Data ... · PDF fileOracle Retail Demand Forecasting Cloud Service In today’s omnichannel environment, customers demand unique and

Oracle Retail Demand Forecasting Cloud Service In today’s omnichannel environment, customers demand unique and tailored experiences, engage with multiple channels, and expect more convenience than ever before. Omnichannel introduces complexity as retailers balance channel-specific strategies, cross-channel customer journeys and omnichannel fulfilment. The journey towards omnichannel proficiency continues and smart retailers are capitalizing on this complexity by asking new questions. What assortment decisions drive brand loyalty? How do traditional and digital promotional vehicles contribute to my sales objectives? What, when, and where is purchase and fulfilment demand? Predictive analytics answers these questions and accuracy is your competitive differentiator.

Oracle Retail Demand Forecasting Cloud Service

Oracle Retail Demand Forecasting Cloud Service (RDF CS) empowers retailers to centralize demand forecasts for their omnichannel enterprise — from operations and vendor collaboration to planning and optimization to marketing and insights — accurately and efficiently. The results achieved include increased and profitability revenue through higher in-stock rates and significant reductions in inventory. For example:

• Within days of implementing Oracle Retail Demand Forecasting, a Russian retailer was able to reduce DC inventory levels from 4 months to 3-4 weeks, improve forecasting accuracy 90-95% for non-promotional items and 75% for promotional items, reduce of out-of-stocks by 18%, increase order-taking speed 3x and decrease store inventory 13-16%

• A UK grocer reported a 50% increase in overall forecast accuracy

• A large national electronics chain has improved in-stock rates by 2%-4%

Maximize Forecast Accuracy. With RDF CS, Oracle Retail distilled 15+ years of forecasting experience across 160+ retailers worldwide into an offering that combines best-fit science and exceptive-driven processes with the agility of an extensible cloud platform.

RETAIL

CIO of the Year

[Executive Name, Title][Company Name]

2011

R E TA I L E X C E L L E N C E AWA R D S

RETAIL

RETAIL

CIO of the Year

[Executive Name, Title][Company Name]

RETAIL

R E T A I L E X C E L L E N C E A W A R D S 2 0 1 1

Retail Excellence Awards

CIO of the Year

[Executive Name, Title][Company Name]

2011

D A TA S H E E T

KEY BENEFITS

• Increase revenue and expand a loyal customer base with higher in-stock rates

• Increase profitability and assortment flexibility with decreased inventory levels

• Shift focus to strategy planning & collaboration and drive operations with sophisticated and highly automated forecasts

• Join an active community of 160+ retailers worldwide using our industry-leading forecasting capabilities

• Reduce TCO by 20-40% with SaaS delivery model

• Increase speed-to-value by 50% with partner implementation offerings of 8-12 weeks

• Shift from CapEx to OpEx with Subscription-based Pricing Model

Page 2: Oracle Retail Demand Forecasting Cloud Service - Data ... · PDF fileOracle Retail Demand Forecasting Cloud Service In today’s omnichannel environment, customers demand unique and

• Get the most from your data with best-fit science. Oracle Retail forecasting science pulls from statistics, optimization, and machine learning disciplines as each job requires, from statistical regression for modeling causalities to goodness-of-fit optimization for forecast model selection to unsupervised machine learning to pool similar performing item-locations for robust parameter estimation.

• Focus users where it counts with exception-driven processes that guide them to action, from reviewing attribute-based recommendations for new items, to approving significant forecast changes from evolving promotional strategies. The exception-driven processes get the most from your team.

• Gain the stability of traditional SaaS along with the agility to tailor core services, from defining fundamental forecasting model decisions to exception-driven processes and integrations. Oracle Retail’s extensible SaaS paradigm gets the most for your business.

Future Proof Investment. Experience high speed to value with accelerated SaaS delivery offerings, stay on the cutting edge of forecasting science, and get the most for your team.

• With partner implementation offerings starting from 8-12 weeks, high speed to value can be the cornerstone of your business case.

• Maximize your forecast accuracy today and stay on the cutting edge of forecasting science with continuous improvements to your cloud service.

• Equip your team with Oracle Retail’s comprehensive Retail Learning Subscription and Documentation Library.

For more information about Oracle Retail Demand Forecasting Cloud Service, please visit oracle.com/retail or email [email protected] to speak with an Oracle representative.

Copyright © 2017, Oracle and/or its affiliates. All rights reserved. We specifically disclaim any liability with respect to this document, and no contractual obligations are formed either directly or indirectly by this document. Oracle is a registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. 0917

CONNECT WITH US

• Centralize demand forecasts

for the enterprise

• Reflect the unique demand drivers of the retailer, such as pricing and promotions

• Adapt to recent trends, seasonality, out-of-stocks, and promotions

• Maximize accuracy through large scale statistical, optimization, and machine learning retail science methods

• Simplify forecast management through high-automation and exception-driven processes

• Provide extensibility around core analytical processes, allowing retailer-specific tailored processes to evolve with the core product

KEY FEATURES