Research

Predictive Modeling at Cleveland Clinic

By Robert Morison, Sep 28, 2017

Available to Research & Advisory Network Clients Only

Headquartered in Cleveland, Ohio, Cleveland Clinic is a nonprofit, multi-specialty academic medical center that integrates clinical and hospital care with research and education. With more than 4,400 beds across the main campus and 10 regional hospitals, plus 18 full-service family health centers, Cleveland Clinic is one of the largest and most respected hospitals in the country.For the last five years, Cleveland Clinic has been deploying progressively more sophisticated and predictive analytics to address one of the organization’s core challenges – optimizing the utilization of operating rooms (OR). The ORs represent significant physical assets and a major source of operational cost. Their scheduling also includes surgeons and other physicians, nurses, anesthesia, and other support teams. That makes scheduling ORs very complex, especially at the main campus where 81 ORs form one of the largest surgery sites in the world. Appropriate utilization of ORs maximizes patient access to surgery and minimizes the direct and opportunity costs of downtime. When the organization is not able to forecast volume accurately and schedule appropriately, ORs get backed up or out of sync, and problems cascade down the line into the ICUs and hospital floors, with repercussions for hospital occupancy and patient throughput.

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Analytics Maturity Powers Company Performance

By David Alles, Sep 21, 2017

Available to Research & Advisory Network Clients Only

Does the development of enterprise analytics capability really drive superior company performance? IIA’s previous research briefs demonstrate that analytics maturity varies significantly between industries and across the top-performing companies in each industry. This follow on research brief uses IIA’s proprietary analytics maturity data – from leading companies like Amazon, Apple, Netflix and Google – and publically available financial and company data, to illustrate the positive association between analytics maturity and superior company performance.

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Inquiry Response: The Bridge Between Internal and External Reporting

By Adam Moore, Sep 11, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

We have an external reporting tool with a certified process and strong governance. Separately, we have management reporting data and analytics data, and for analytics we are standing up a data lake from disparate sources. My challenge is around the external tool and management reporting data. Right now we bridge the management reporting back to the externally reported figures, but I don’t see a need for this tie because the purposes are different. However, senior management has an emotional commitment to the bridge, so I’m wondering if that bridge is really important and whether you are seeing companies diverting from the need to build a bridge.

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Driving Clinical and Operational Performance Through Analytics

By Jack Phillips, David Alles, Aug 02, 2017

Available to Research & Advisory Network Clients Only

As much as any industry today, healthcare sits at the intersection of both technological and societal change. Web, mobile, cloud, and data technologies are being applied to myriad patient-level applications to disrupt traditional patient care methods, and the very way that hospitals operate and compete. Emerging technologies leveraging the Internet of Things (IoT), particularly in the wearables category, will most certainly shift the role of care and wellness from provider to patient. Recent research from the International Institute for Analytics (IIA) has now quantified the significant gap in maturity between all healthcare segments and most other industries. But the research also reveals a discreet set of steps healthcare providers can follow to improve capabilities and move up the analytics maturity curve.

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Inquiry Response: Analytics Trends with an Eye on the Future

By Mark Madsen, Jul 24, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

I lead the technology delivery team for the international business intelligence (BI) division. We’re trying to build a strategy to ensure that we’re at the leading edge with our data and that we can continue to achieve competitive advantage out of our data. We would like your take on where you see analytics going and general trends regarding capabilities that organizations are going to need going forward.

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Saving Retail

By Geoffrey Moore, Jul 18, 2017

Okay, so you know a sector is in trouble when there is a Web page in Wikipedia entitled “The Retail Apocalypse.” This post is not about how much trouble retail is in. This one is about how it can get out.

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Inquiry Response: Key Messages on the Importance of Analytics

By Dave Cherry, Jul 03, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

My organization works with many different business groups and leaders and we need to articulate why they should be thinking about analytics. We often hear from them that they’re already doing analytics, although they’re really just getting some dashboard information. Most of them don’t know what they don’t know.

Questions:

  • How do we make analytics real for them, get them excited and get them to think about data differently?
  • How have others communicated benefits when they just started out and don’t have any internal use cases to reference?
  • How can we explain how things are different in an analytically mature organization?

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Move Your Analytics Operation from Artisanal to Autonomous

By Thomas H. Davenport, May 02, 2017

Many organizations today are wondering how to get into machine learning, and what it means for their existing analytics operation. There are many different types of machine learning, and a variety of definitions of the term. I view machine learning as any data-driven approach to explanations, classifications, and predictions that uses automation to construct a model. The computer constructing the model “learns” during the construction process what model best fits the data. Some machine learning models continue to improve their results over time, but most don’t. Machine learning, in other words, is a form of automating your analytics. And it has the potential to make human analysts wildly more productive.

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IIA 2017 Spring Symposium Event Summary

By Jack Phillips, Apr 13, 2017

Available to Research & Advisory Network Clients Only

IIA hosted its first client-only Symposium of 2017 on March 14, 2017 at the VMware campus in Palo Alto, CA. Over 100 of IIA’s research clients gathered for the Symposium featuring five keynotes and two panel discussions. Given the location in the heart of Silicon Valley, the theme of the Spring Symposium was innovation, disruption, and the growing role of technology in shaping how analytics and data management are executed inside enterprises today.

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Video: Innovation, Disruption, and Enterprise Analytics

By IIA Faculty, Apr 13, 2017

Available to Research & Advisory Network Clients Only

2017 Analytics Symposium - Silicon Valley

This presentation addresses how enterprises of all sizes can adopt a “start-up mentality” to transform their organizations and the industry. Featuring Geoffrey Moore, Author, Thought Leader.

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