Summit 2016: Agenda

Non-Technical Summit Tech Level non-technical | BeginnerSummit Tech Level Beginner | Intermediate Summit Tech Level Intermediate | Advanced Summit Tech Level Advanced

BI in 2016: What's New and What's Changed in 12 Months?

Howard Dresner, Dresner Advisory Services, LLC
Tech Level: Summit Tech Level non-technical
Wednesday 8:30AM - 9:30AM
In this interactive session, veteran industry analyst Howard Dresner shares a market update, and will include audience input (bring a Smartphone!) to compare trends and perspectives. Key topic areas will include: chief data and chief analytics officers, success with business intelligence, goals/objectives for BI, strategic technologies and initiatives, user adoption and penetration, BI drivers/targets, the state of data/governance, and the state of BI collaboration.

Building a Culture of Accountability, Transparency, and Performance Excellence

Aimee Kaslik, City of Irving
Tech Level: Summit Tech Level non-technical
Wednesday 2:45PM - 3:45PM
As a 2012 Malcolm Baldrige National Quality Award winner, the City of Irving, TX is known for excellence in leadership, strategic planning, customer and workforce focus, process improvement, and performance management. Key components of this success are ensuring accountability, full transparency, and relying on data in the decision-making process when allocating available resources and determining areas of focus. Attendees can learn how the City uses Performance Management Framework (PMF) to ensure a high level of accountability, including how the agency organizes and presents data to staff, council, and customers; how PMF serves as the hub for carrying out its strategic plan, and how individual departments rely on it to track key processes and initiatives.

Clinical Data Exchange Through Omni-Payer: Development, Delivery, and Impact

Jason Gordon, BlueCross BlueShield of Tennessee
Tech Level: Summit Tech Level non-technical
Wednesday 1:30PM - 2:30PM
Attend this session to hear how BlueCross BlueShield of Tennessee and Information Builders worked together to build and implement Omni-Payer, a solution to obtain, master, and update clinical data from provider electronic medical records. Supplemental data through Omni-Payer impacts quality reporting and opens the door to a host of collaborative possibilities between the payer and the provider.

Global Standardization

Donald Northcote, Ford Motor Company
Tech Level: Summit Tech Level non-technical
Wednesday 4:00PM - 5:00PM
Attend to hear Ford Customer Service Division's (FCSD) strategies to drive and measure its global growth plans. FCSD pushes key performance indicators (KPIs) to every level of the organization to equip 90 percent of its staff offices, field operations, and dealers with globally standardized KPIs and performance analytics. Global data analytics enhance operational transparency, driving process improvement and growth. See how the new FCSD Global Dashboard 2.0 provides value to the dealer sales process and service performance.

Governing and Preparing Data for Analytics and Business

Mark Smith, Ventana Research
Tech Level: Summit Tech Level non-technical
Tuesday 4:00PM - 5:00PM
As business becomes more self-sufficient in accessing and putting data to work for analytics, there are many steps that are circumvented that can jeopardize the quality of business decisions. While it might seem easy to do one-off data preparation cycles that create analytic silos, the importance of placing governance on the data and users is essential to ensure accuracy of information used by business. The solution for these challenges can be addressed by applying effective processes and systems that are shared across business and IT. In this presentation, you'll will learn the latest best practices and steps to increase data governance and preparation processes that will shorten the time to efficiently connect users and data at any time.

Making the Right Choices When Choosing Cloud Analytics

Lyndsay Wise, Enterprise Management Associates
Tech Level: Summit Tech Level non-technical
Wednesday 11:00AM - 12:00PM
Cloud analytics and cloud platforms now represent more viable options for organizations that want to bring their analytics projects to the next level. With big data, IoT, and agility, the ability to develop a flexible information management ecosystem provides organizations with the competitive advantage they require to gain business value from their analytics infrastructure. The cloud market is now mature enough to provide insights into general trends relating to adoption patterns and overall use. Luckily, organizations considering cloud can now look at earlier adopters to identify whether and how they should take advantage of cloud analytics. This presentation will discuss: cloud trends, including the intersection of big data and IoT within cloud infrastructures; the benefits and challenges of cloud analytics adoption; cloud analytics adoption trends; best practices and considerations for cloud adoption; and pitfalls to avoid.

The Keys to Enterprise BI and Analytics Adoption: How to Optimize Data Access, Delivery, and Insights

Wayne Eckerson, Eckerson Group, LLC
Tech Level: Summit Tech Level non-technical
Tuesday 1:30PM - 2:30PM
Business intelligence (BI) adoption is the holy grail of BI. It?s represents the culmination of everything a BI team does. This session will discuss the key factors that contribute to high levels of BI adoption, including techniques for operationalizing BI and governing self service. BI managers who pay close attention to these factors will steer their BI programs in the right direction. Those who don?t will experience lackluster user adoption and put their BI programs at risk.

Turning Big Data Into Actionable Insights

Boris Evelson, Forrester Research
Tech Level: Summit Tech Level non-technical
Tuesday 2:45PM - 3:45PM
Although many companies are beginning to leverage the power of Hadoop and other big data technologies to supplement their existing BI platforms, turning data into actionable insights remains a challenge. This presentation will review lessons learned and pitfalls to watch out for when using big data for analytics, as well as ways to ensure that big data provides the value needed to live up to its expectations.