Mar/Apr 2019

Many organizations haven’t succeeded in making the cultural changes required to become data-driven. Not enough managers are fluent in the language of analytics. So, how can supply chain teams make progress? Start working on three pillars: culture, talent and technology.

• N.S. Krishnan

In Part 1 of this series, we discussed the emerging popularity of neural networks for analyzing more traditional business questions such as customer churn. We outlined an example where a deep learning model was able to outperform a logistic regression on the same data set, in terms of statistical accuracy. In this article, we’ll look more deeply at how we might evaluate two candidate models through an “efficient modeling” lens, and what implications that might have on our business decision.

• Jim Theologes

A new study by the Center for Strategic and International Studies (CSIS) [1] highlights an important factor neglected in the national security digital transformation, a factor that is critical now: the development of what the study’s authors call an “AI Ecosystem.”

• Doug Samuelson

The dream of creating artificial general intelligence has captivated our imagination for generations. Linear reasoning is as common now as it was decades ago, but perhaps linear thinking has been a hindrance to the development of AI.

• Joseph Byrum

The to-do list for a small and midsize business (SMB) owner can be daunting, including myriad administrative and organizational needs relating to accounting and finance, staffing, product and service roadmap for the year and more. In the course of all this productive planning, and as you look to build stronger relationships that drive ROI, consider how you’re responding to customer information. Let’s take a closer look at what small businesses need to know when looking for a CRM – or evaluating their existing solution – in 2019.

• John Oechsle