Research

Don’t Be Hit by the Analytics Backlash

By Thomas H. Davenport, Jun 19, 2018

Analytics leaders and practitioners need to be prepared both to defend analytics and AI where appropriate, ensure that you’re not contributing to issues like how to prevent algorithmic bias, what industries would be least likely to do harm with analytics, and how to reduce the societal damage from AI.

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There are two serious crises looming over our workforce at present. The one getting all the attention is the threat of artificial intelligence to eliminate vast numbers of jobs. The one lurking in the corners is a pervasive lack of engagement among workers from all sectors of the economy. What people are neglecting to note is that the two are related.

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Inquiry Response: Building Your Analytics Community

By IIA Expert, Jun 04, 2018

Available to Research & Advisory Network Clients Only

Inquiry:

We want to create a community among the analysts spread throughout the enterprise. How can we best foster collaboration and encourage shared knowledge and resources?

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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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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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