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Next Generation Business Analytics Technology Trends

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Learning Objectives:* Understand limitations of current Business Intelligence tools* Discover how next generation tools for business and retail analytics can supplement and enhance current BI environments* Identify vendors and characteristics of next generation Business Analytics tools* Learn how companies are using next generation BA tools

Text of Next Generation Business Analytics Technology Trends

NEXT GENERATION BUSINESS ANALYTICS TECHNOLOGY TRENDSTECHNOLOGIES AND TECHNIQUES

FORBUSINESS INTELLIGENCE & PERFORMANCE MANAGEMENT

This work is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/.

PresentersMichael Beller 10 years of executive management experience leading major growth and change initiatives as COO CIO EVP of Strategy Management 15 years of management consulting experience helping clients with operations and IT strategy, planning, and execution Alan Barnett 25 years of retail management experience with Steve and Barrys, Levitz Furniture, Loehmanns, Victorias Secret Stores, and Barneys New York Merchandising Planning Information Technology Frequent speaker industry events on systems and operational planning2

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Learning Objectives

Understand limitations of current Business Intelligence tools Discover how next generation tools for Business Analytics can supplement and enhance current BI environments

Identify vendors and characteristics of next generation Business Analytics tools

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Agenda

Business analytics vs. business intelligenceWhat is Business Analytics?

Challenges for current BA environmentsIT Limitations Data and Tools!Business Impact

Next generation BA vendors and toolsBusiness trendsTechnology trends

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BUSINESS ANALYTICS VS. BUSINESS INTELLIGENCE

Business analytics is more than just traditional business intelligence and reportingBusiness Intelligence Oriented to standard and consistent metrics and analysis Focused on dashboards and predefined reports Business Analytics Oriented towards ad-hoc analysis of past performance Focused on interactive and investigative analysis by end users

Primarily answers predefined questions Provides end users indirect raw data access through cubes, reports, and summarized data Exception based reporting

Used to derive new insights and understanding Explore the unknown and discover new patterns Relies on low-level data to provide visibility to unexpected activity

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BUSINESS ANALYTICS VS. BUSINESS INTELLIGENCE Part of routine daily, monthly, and quarterly processes not a sporadic or exception based exercise

Peel the onion answers to some questions generate more questions dive deeper and deeper into the data Explore the unknown, search for new patterns and new findings and new metrics Investigate exceptions and anomalies, research hypotheses

Gain broader and deeper insight and understanding into past performanceStay focused on goal to improve business planning and overall business performance

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BUSINESS ANALYTICS VS. BUSINESS INTELLIGENCE

Business Analytics provides end users tools and data to explore and develop broader and deeper business insight What is business analytics?Continuous iterative exploration and investigation of past business performance to gain insight and drive business planningthere are $8B (yes, billion) of internally developed analytic applications with Excel as their front end. The BI players treat the output to Excel as a feature [3]

What impacts and drives business analytics?The quantity and detail of critical business transaction and related data combined with powerful and flexible data analysis tools

How do you improve business analytics?Use next generation technologies to lower data warehousing and IT infrastructure costs, Store larger amounts of historical data at granular levels of detail, and Provide ad-hoc analysis and data mining without IT development efforts. 2009 LIGHTSHIP PARTNERS LLC

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CHALLENGES FOR CURRENT BA ENVIRONMENTS

Organizations struggle to aggregate sufficient breadth and depth of data for thorough Business Analytics Level of granularityTransaction data is summarized and aggregated for analysis

Historical contextTechnical constraints often lead to less than optimal data retention

Consolidated viewData warehouses often focus on closely related systems, not enterprise views Multiple disparate data silosWebsites and ecommerce Supply chain Enterprise resource planning (ERP) CRM Financial Other, e.g., weather, competitor, etc.

80% of companies use three or more business intelligence (BI) products [1]

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CHALLENGES FOR CURRENT BA ENVIRONMENTS

Traditional data analysis and reporting tools are oriented to IT developers and difficult to modify at the speed of business Complex tier of toolsETL and EAI platforms Data warehouses Dashboards and reports Ad-hoc analysis

CostlyCapital Effort DurationComplexity leads to fragile systems and long lead times for changes

Oriented to ITCumbersome for end users Puts IT in the middle

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CHALLENGES FOR CURRENT BA ENVIRONMENTS

Current BI environments pose numerous challenges for Business Analytics and impact quality of business planning

Understanding of past performance leads to quality of future planning End users often develop cursory and summary level insight into business performance which leads to sub optimal plans BI tools have multiple versions of the truthUncertainty Wasted effort

the only way to make a difference with analytics is to take a cross-functional, cross-product, crosscustomer approach [5]

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NEXT GENERATION BA VENDORS AND TOOLS

The BA market is dynamic, rapidly expanding and poised for high growth and adoption beyond early adoptersBusiness trends Companies look to leverage investments in ERP and legacy systems Economic environment driving low risk projects with quick payback Existing data warehouse and reporting systems have limitations Cost Flexibility Data Quantity and Granularity Technology trends Massively scalable data and processing clouds for data aggregation, storage, and analysis SaaS and managed service offerings for low cost quick payback projects Minimal, if any, capital Fast implementation

Next generation tools, portals, and visualization for data analysis and presentation

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NEXT GENERATION BA VENDORS AND TOOLS

Next generation BA vendors and tools address current limitations and complement existing environments Data granularity, history, and consolidationColumnar, in-memory, and other database technologies require minimal data modeling and can load diverse and complex data

Technology cost, complexity, and end user accessSaaS and managed service require minimal initial cost

Cloud storage and processing enable massive scalability at reasonable costSAP, Oracle, and IBM purchased three major BI vendors (Business Objects, Hyperion, and Cognos) within months of one another a clear sign of the importance of both BI and BA 2009 LIGHTSHIP PARTNERS LLC

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NEXT GENERATION BA VENDORS AND TOOLS

Why are companies adopting new SaaS BI solutions?

Source: BeyeNetwork Research Report May 2009

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NEXT GENERATION BA VENDORS AND TOOLS

By one expert estimate, there are 2 new players entering the BI and BA market every week

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QUESTIONS?

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MIKE BELLER ALAN BARNETT

[email protected] [email protected]

WWW.LIGHTSHIPPARTNERS.COM

THANK YOU!This work is licensed under the Creative Commons Attribution-Share Alike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/3.0/. Lightship Partners LLC, Lightship Partners LLC (stylized), Lightship Partners LLC Compass Rose are trademarks or service marks of Lightship Partners LLC in the U.S. and other countries. Any other unmarked trademarks contained herein are the property of their respective owners. All rights reserved.

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End Notes and References1. 2. 3. Kelly, Jeff. Key considerations for business intelligence platform consolidation. searchdatamanagement.techtarget.com, February 17, 2009. http://tinyurl.com/lr4usk . Kirk, Jeremy. 'Analytics' buzzword needs careful definition. InfoWorld.com, February 7, 2006. http://www.infoworld.com/t/data-management/analytics-buzzword-needs-careful-definition-567 . Gnatovich, Rock. Business Intelligence Versus Business Analytics--What's the Difference? CIO.com, February 27, 2006. http://www.cio.com/article/18095/Business_Intelligence_Versus_Business_Analytics_What_s_the_Differenc e_?page=1 . Hagerty, John. AMR Research Outlook: The New BI Landscape. AMRresearch.com, December 19, 2008. http://www.amrresearch.com/Content/View.aspx?compURI=tcm%3a739121&title=AMR+Research+Outlook%3a+The+New+BI+Landscape. Thomas H. Davenport. Realizing the Potential of Retail Analytics. Babson Working Knowledge Research Center, June 2009. van Donselaar, K.H.; Gaur, V.; van Woensel, T.; Broekmeulen, R. A. C. M.; Fransoo, J. C.; Ordering Behavior in Retail Stores and Implications for Automated Replenishment Revised working paper dated May 12, 2009; first version: January 31, 2006. http://papers.ssrn.com/abstract=1410095

4.

5. 6.

7.

Imhoff, Claudio, and Colin White. Pay as You Go: SaaS Business Intelligence and Data Management, May 20, 2009. http://www.b-eye-research.com/

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