Research

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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Inquiry Response: Migrating to New Data Platforms and Data Sources

By Mark Molau, Jun 07, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

I’m interested to discuss methods/options for scaling analytics across our highly matrixed organization. We have done a lot of work building out our analytics strategy, but now need to get more tactical. How can we make this transition while maintaining the current systems, building future systems and constructing a bridge between the two?

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Inquiry Response: Tips for Assessing Talent Readiness

By Jenny Schmidt, May 30, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

How do we assess the readiness of the talent in the organization for our future analytics capability needs?

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Inquiry Response: Galvanizing Enterprise Support for Analytics

By IIA Faculty, May 26, 2017

Available to Research & Advisory Network Clients Only

Inquiry:

We want to improve our analytics capabilities across the organization, but need better ways to justify continued analytics expansion to the enterprise. What are some ways to begin to get buy-in from leadership for our analytics initiatives?

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