Research

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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Who thought Domino’s Could be a Disruptor?

By Julia Oswald, May 08, 2018

Available to Research & Advisory Network Clients Only

2018 Analytics Symposium – Santa Clara Session Recording

How has Domino’s become such a dominating force in the Quick Serve Industry? Julia Oswald’s presentation shared the key drivers of this success. Domino’s broad strategy is to be a part of the disruption. The company has three key tenants to achieve this strategy:

1) Craft food that they are proud of, 2) Drive growth in the carryout business and 3) Aggressively innovate and invest in digital and in-house analytics. The progression of the Strategy and Insights department has been a crucial element across all three tenants of Domino’s strategy. Julia shared philosophies and some of the details about how the company has and plans to continue to be a disruptor in the category.

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Differentiating Via Data Science

By Eric Colson, May 08, 2018

Available to Research & Advisory Network Clients Only

2018 Analytics Symposium – Santa Clara Session Recording

Companies employ various means of differentiation in order to gain a competitive advantage in the market. Traditional differentiators include network economies, branding, economies of scale, and so on. But the availability of data and compute resources, combined with the emergence of new business models, have enabled data science to become a strategic differentiator. Eric Colson explored what it means to differentiate by data science and explains why companies must now think very differently about the role and placement of data science in the organization. The traditional organization needs to be changed if a company is to differentiate via data science. Data science needs to be a top-level department reporting to the CEO. Further, it needs a completely different workflow. It can’t thrive with top-down requirements or if it is forced to submit to upfront ROI calculations. Data science needs more fluidity, more experimentation, and more iteration.

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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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