Next Generation Business Analytics Technology Trends

NEXT GENERATION BUSINESS ANALYTICS TECHNOLOGY TRENDS TECHNOLOGIES AND TECHNIQUES

FOR BUSINESS INTELLIGENCE & PERFORMANCE MANAGEMENT

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Presenters Michael Beller

Alan Barnett

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

25 years of retail management experience with Steve and Barry’s, Levitz Furniture, Loehmann’s, Victoria’s Secret Stores, and Barney’s New York Merchandising Planning Information Technology Frequent speaker industry events on systems and operational planning

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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 intelligence What is Business Analytics?

• Challenges for current BA environments IT Limitations – Data and Tools! Business Impact

• Next generation BA vendors and tools Business trends Technology trends

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BUSINESS ANALYTICS VS. BUSINESS INTELLIGENCE

Business analytics is more than just traditional business intelligence and reporting Business Intelligence

Business Analytics

• Oriented to standard and consistent metrics and analysis

• Oriented towards ad-hoc analysis of past performance

• Focused on dashboards and predefined reports

• Focused on interactive and investigative analysis by end users

• Primarily answers predefined questions

• Used to derive new insights and understanding

• Provides end users indirect raw data access through cubes, reports, and summarized data

• Explore the unknown and discover new patterns

• Exception based reporting

• 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 performance Stay 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 planning

“there 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 granularity Transaction data is summarized and aggregated for analysis

• Historical context Technical constraints often lead to less than optimal data retention

• Consolidated view Data warehouses often focus on closely related systems, not enterprise views Multiple disparate data silos

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

Websites and ecommerce Supply chain Enterprise resource planning (ERP) CRM Financial Other, e.g., weather, competitor, etc.

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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 tools ETL and EAI platforms Data warehouses Dashboards and reports Ad-hoc analysis

• Costly Capital Effort Duration

• Oriented to IT

Complexity leads to fragile systems and long lead times for changes

Cumbersome 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 truth

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

Uncertainty Wasted effort

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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 adopters Business trends

Technology trends

• Companies look to leverage investments in ERP and legacy systems

• Massively scalable data and processing clouds for data aggregation, storage, and analysis

• Economic environment driving low risk projects with quick payback

• SaaS and managed service offerings for low cost quick payback projects

• Existing data warehouse and reporting systems have limitations Cost Flexibility Data Quantity and Granularity

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 consolidation Columnar, in-memory, and other database technologies require minimal data modeling and can load diverse and complex data

• Technology cost, complexity, and end user access SaaS and managed service require minimal initial cost

Cloud storage and processing enable massive scalability at reasonable cost SAP, 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 References 1.

Kelly, Jeff. “Key considerations for business intelligence platform consolidation.” searchdatamanagement.techtarget.com, February 17, 2009. http://tinyurl.com/lr4usk .

2.

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 .

3.

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 .

4.

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.

5.

Thomas H. Davenport. “Realizing the Potential of Retail Analytics.” Babson Working Knowledge Research Center, June 2009.

6.

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

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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