Research

Organizing Analytics

By Robert Morison, May 16, 2018

Available to Research & Advisory Network Clients Only

This research brief describes and offers guidance on:

  • The fundamental goals of organizational structure
  • Six basic models for organizing analytics
  • Mechanisms for coordinating across organizational boundaries
  • Design variables that enable or constrain organizational shape
  • How analytics organizations commonly evolve
  • How to assess readiness for greater centralization
  • Structural variations driven by technological and business change
  • Questions to ask in planning your next structural move

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Inquiry Response: Hiring for Rotational Development Programs

By IIA Expert, May 14, 2018

Available to Research & Advisory Network Clients Only

Inquiry:

We’re starting a rotational development program aimed at master’s level grads in the data science arena. The program is three years long with three one-year rotations in different business areas. We’re struggling with the program’s design and recruiting efforts and are hoping for some insights.

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Will Data Scientist Continue to Be the Sexiest Job?

By Thomas H. Davenport, May 08, 2018

Back in 2012 I wrote (with D.J. Patil, who went on to become the Chief Data Scientist in the White House) an article in Harvard Business Review called “Data Scientist.” Nobody remembers the title or much about the content of the article, but many remember the subtitle: “Sexiest Job of the 21st Century.” At the time (and still today), these jobs paid well, were difficult to fill, and required a very high level of analytical and computational expertise. But a more accurate subtitle might have been “Sexiest Job of the 2010-2019 Decade,” because I am not sure how much longer data scientists will be in great demand.

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Burtch Works decided to survey hiring managers to see if the shifts among professionals were reflected in employers’ hiring intentions for the beginning of 2018. Periodically we send out “flash surveys” to our network with a few questions, and so we used this method to gather some data from our network of quantitative hiring managers.

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Inquiry Response: Managing Model Maintenance Tasks

By IIA Expert, Apr 23, 2018

Available to Research & Advisory Network Clients Only

Inquiry:

One of our challenges is that once we’ve deployed a model, it must be monitored and fed data. Unfortunately, the important work of model maintenance isn’t seen as a high priority within the enterprise and isn’t seen as a glamorous job by our analytics talent.

Do you have any advice for helping evolve the culture so that model maintenance work is acknowledged as valuable and can attract and retain high quality talent?

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Inquiry Response: Understanding Cybersecurity Roles

By IIA Expert, Apr 16, 2018

Available to Research & Advisory Network Clients Only

Inquiry:

Given the competitiveness in the cybersecurity (CS) space, we want to update our CS job descriptions and compensation to bring them in line with the industry. How should we approach this?

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Most people will agree that interviewing is one of the most difficult and least enjoyable professional activities in which we engage. Given the recent demand for data analytics and data scientist skills, it has become an increasingly daunting task for managers to adequately test and qualify candidates. Our team at TCB Analytics has interviewed hundreds of individuals with various backgrounds over the years and needed a more efficient way of quantifying technical and cultural fit. This led us to design a deceptively simple data exercise, which reveals a surprising amount of information about the interviewees.

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Inquiry Response: Career Development for the Analytics Team

By IIA Expert, Apr 02, 2018

Available to Research & Advisory Network Clients Only

Inquiry:

We’re working on our career development and career paths for our data science and analytics team. We have forty people, and we’re growing. Our concerns include low attrition and the fact that not everyone wants to be a manager.

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Do You Need a Ph.D. to Run Analytics or Data Science?

By Thomas H. Davenport, Doug Gray, Mar 22, 2018

While we are supportive of companies’ efforts to hire quantitative Ph.D.’s to practice data science, we believe that most firms are better off hiring people with other types of training and general management skills to manage analytics and data science groups. Why? Because there are a series of traits that make for effective managers of such groups, and most Ph.D.’s don’t tend to have them. We describe ten of those traits in this blog, and the reasons why they are unlikely to be found in the average doctoral degree holder. The list of traits may be useful for anyone seeking to hire a leader of analytics or data science functions-whether they are considering Ph.D.’s or not.

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Is the analytics and data science market starting to settle down? Our recent analysis of job change and tenure shows an interesting new development, which certainly suggests that things are leveling out a bit.

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