Research

Inquiry Response: Engaging for Digital Transformation

By Mark Molau, Aug 14, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

How can we approach structuring our digital transformation so they can get some real traction? We are a very analytically siloed organization, and struggle with data transparency/access across the enterprise. We are working to figure out how our analytics initiatives fit within the larger organization, and how to engage everyone, CIO and business units, in our digital transformation.

  • How can we approach structuring our digital transformation in a way to get some real traction and change the culture?
  • How can I best communicate why it’s necessary to directly align our analytics initiatives with the business?

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Inquiry Response: Approaching EDW and Analytics for Hospitals on Epic

By Gwen O’Keefe, Aug 07, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

We’re considering integrating Caboodle and would like to learn from other healthcare organizations using Caboodle if it is their core enterprise data warehouse (EDW), or if other solutions have been supplement to meet their needs.

  • What role does Caboodle play in your overall enterprise data strategy?
  • Does Caboodle operate as your core enterprise warehouse, or are supplemental solutions being used?
  • What data are you collecting in Caboodle as opposed to supplemental systems?

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Inquiry Response: Tips for Building Your Analytics Toolbox

By Mark Molau, Jul 31, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

We are considering having our analysts use the same set of tools and are considering MicroStrategy because it is readily accessible. What should we take into consideration when selecting analytics tools to support the business?

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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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Inquiry Response: Suggestions for Getting Data Scientists to Embrace Agile Methods

By Mark Haseltine, Jul 17, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

Our company has recently adopted a Scrum/Agile framework, which has caused some hiccups with our data scientists, who are used to managing their projects themselves. They tend toward perfectionism, which takes longer. Our goal is to build model minimum viable products (MVPs) faster, using two-week sprints for testing/incrementing the models. Part of the problem is that the data scientists don’t fully trust the process because of the loss of control to the Scrum master and also because of the continued perception that they have to produce perfect models the first time out. How can we get our data scientists to embrace the Agile process?

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Inquiry Response: Building a Data Science Team, Recruitment and Hiring

By Rumman Chowdhury, Jul 10, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

We’re a major player within a massively complex industry with a three-year mandate to build a data science practice to help us drive competitive advantage. How do we assess the gaps in our current talent pool and what are the considerations for new hiring and recruitment?

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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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Inquiry Response: Path Toward Advanced Analytics for the End User

By Mark Molau, Jun 27, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

Everyone talks about dashboards and tools, but tools often produce a one size fits all solutions. Our quest is to produce a solution that appeals to multiple end users, effectively socialize the benefits, and push for adoption. We hope to use predictive analytics for process optimization – our integrated delivery systems are heavy on processes – so optimization here could yield great value.

Questions:

  • How do you start to move into a more predictive analytics culture and encourage the application of advanced analytics?
  • Where should we start to ensure the different end user audiences are receiving useful information/insights in a way that is most valuable for them?
  • What approach should we take to ensure that the tools we create get socialized, engaged, and adopted?

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Inquiry Response: Data Warehouses Versus Data Lakes

By Josh Gray, Jun 19, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

We have fragmented data everywhere, much of it traditionally structured but using dozens of different ERP systems and data warehouses and data sources. How might we proceed so we can actually make timely use of all this data? Would we be better off with a data lake rather than a traditional data warehouse?

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Inquiry Response: Considerations for Rotational Training Programs

By IIA Faculty, Jun 12, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

We would like to create a rotational training program for our in-house analytics professionals. New hires would rotate through various other business units to gain a broader view of the overall business, while bringing the data science perspective into those units.

Questions:

  • Would a rotational program like this appeal to recent analytics and data science graduates?
  • How does a rotational training program for analytics professionals benefit business?
  • What are some best practices for rolling out a successful rotational training program for analytics professionals?

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