Five Key Building Blocks for a Successful Analytics Program

971 views

Published on

Using the International Institute of Analytics innovative DELTA powered Analytics Assessment as model framework, Faculty Member Sarah Gates focuses on how successful executives develop and create significant business value from analytics, especially with predictive modeling and prescriptive capabilities that are essential for organizations to compete in the 21st Century.

For more information on how your company can be helped using analytics, follow this link to the DELTA-Powered Analytics Assessment TM.

http://info.iianalytics.com/healthcarebenchmarking

To listen to this webinar, follow this link to register: http://marketing.nwasoft.com/acton/form/1578/004c:d-0002/0/index.htm

Published in: Technology, Business
0 Comments
3 Likes
Statistics
Notes
  • Be the first to comment

No Downloads
Views
Total views
971
On SlideShare
0
From Embeds
0
Number of Embeds
2
Actions
Shares
0
Downloads
0
Comments
0
Likes
3
Embeds 0
No embeds

No notes for slide
  • At the theoretical level they are the same – providing insights about what is going on in an area of the business, in real time, alerting you to activities that need to occur,. Potentially telling you what to do and whenIf you are talking about the systems – a classic BI system will tend to be implemented on ‘business’ data rather than integrating manufacturing data – and have different refresh times, reporting etc.
  • Five Key Building Blocks for a Successful Analytics Program

    1. 1. FIVE KEY BUILDING BLOCKS FOR A SUCCESSFUL ANALYTICS PROGRAM Sarah Gates Vice President, Research
    2. 2. Copyright © 2013 IIA All Rights Reserved IIA is an independent research firm that guides organizations to better leverage the power of analytics. Working across a breadth of industries, IIA uncovers actionable insights, learned directly from our network of analytics practitioners, industry experts and faculty. We deliver critical information that helps your business run smarter. IIA co-founder and Research Director, Thomas H. Davenport
    3. 3. BUSINESS INTELLIGENCE VS. MANUFACTURING INTELLIGENCE Copyright © 2013 IIA All Rights Reserved Manufacturing Intelligence • Real-time connectivity • Manufacturing analytics • Data-source independent • Manufacturing operations • Manufacturing processes • Plant floor level integration • Data source integration Business Intelligence • Static connections • Business analytics • Proprietary • Business Operations • Business Processes • ERP/Data warehouses • Constrained integration
    4. 4. Copyright © 2013 IIA All Rights Reserved Adapted from Competing on Analytics, Davenport and Harris, 2007
    5. 5. Copyright © 2013 IIA All Rights Reserved Adapted from Competing on Analytics, Davenport and Harris, 2007
    6. 6. Copyright © 2013 IIA All Rights Reserved Adapted from Competing on Analytics, Davenport and Harris, 2007
    7. 7. Copyright © 2013 IIA All Rights Reserved • Conceptually they are the same – insights into the operation to make better decisions. • At the system level – a traditional BI system may be different from a MI system • As with other industries, manufacturers are having to become more predictive and prescriptive in order to drive better performance HOW DOES BI/ANALYTICS RELATE TO MANUFACTURING INTELLIGENCE?
    8. 8. Copyright © 2013 IIA All Rights Reserved MATURING YOUR USE OF ANALYTICS It is not just having the data or the talent…..
    9. 9. Copyright © 2013 IIA All Rights Reserved Adapted from Competing on Analytics, Davenport, and Harris, 2007
    10. 10. LEVELS OF ANALYTICAL MATURITY Copyright © 2013 IIA All Rights Reserved Adapted from Analytics at Work, Davenport, Harris and Morison, 2010
    11. 11. Copyright © 2013 IIA All Rights Reserved LEVELS OF ANALYTICAL MATURITY 5. Analytical Competitors. “Analytical nirvana.” Use analytics across the enterprise as a competitive differentiator and in strategy. 4. Analytical Companies. “Good at analytics.” Highly data oriented, have analytical tools, and make wide use of analytics. Lack commitment to fully compete or use strategically. 3. Analytical Aspirations. “See the value of analytics.” Struggle mobilizing the organization and becoming more analytical. 2. Localized Analytics. “Use reporting.” And analytics or reporting is in silos. 1. Analytically Impaired. “Not data-driven.” Rely on gut feel and plan to keep doing so. They aren’t asking analytics questions and/or lacks the data to answer them.
    12. 12. BIG IDEAS • You need to think about each of the DELTA model competencies when evaluating analytics maturity • Measure your progress and set goals that will push you to continue to improve • Analytics for offense and defense are critical • Learn from other firms and industries • Take advantage of the power of predictive and prescriptive analytics. Copyright© 2013 IIA All Rights Reserved
    13. 13. Copyright © 2013 IIA All Rights Reserved In the new data economy, only those who compete on analytics win Contact us to accelerate your progress info@iianalytics.com 503-467-0210 www.iianalytics.com LET IIA BE YOUR GUIDE

    ×