Research

Scaling Analytics at Instacart

By Che Horder, May 08, 2018

Available to Research & Advisory Network Clients Only

2018 Analytics Symposium – Santa Clara Session Recording

The Data & Analytics team at Instacart is responsible for delivering meaningful analyses that impact the decisions we make as a company. The team is at the center of an extremely data-driven company culture and there is nothing more important to the team than helping the company learn and make great data-driven decisions. The team found that over time, they accumulated chronic issues or obstacles in the environment that were hampering their ability to scale and deliver on our mission. These obstacles were monopolizing their time and reducing capacity to focus and be productive on Instacart’s core mission. Che discussed 1) what his team’s obstacles were, 2) why it is was critical to address them, and 3) how they have removed them.

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The “Last Mile”:  Keys to Successfully Embedding Analytics in Core Organizational Processes

By Blake Johnson, May 08, 2018

Available to Research & Advisory Network Clients Only

2018 Analytics Symposium – Santa Clara Session Recording

The critical capability for analytics organizations today is the ability to seamlessly integrate analytics into high-value, large-scale organizational processes. This “last mile” to major business impact depends on two cross-functional “bridging” capabilities: 1) establishing leadership by senior business executives, who are the only people capable of driving change in core organizational processes, and 2) carefully designing analytics so that they can be “embedded” into current organizational processes and IT systems, which is required for them to be executable at scale. Blake described best practices for establishing these capabilities identified in a recently completed two-year study, and the rapid scaling of analytics business impact they make possible.

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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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Deploying AI in Mobile-First Consumer-Facing Financial Products – A Tale of Two Cycles

By Jike Chong, May 08, 2018

Available to Research & Advisory Network Clients Only

2018 Analytics Symposium – Santa Clara Session Recording

What opportunities does anytime, anywhere access of financial services on mobile devices enable? How can we use AI to capture these opportunities to create better financial services for everyone? Jike dove into AI in the context of two fundamental business cycles in financial services: the intelligent acquisition of customers, and the intelligent sustaining of customer relationships. These two business cycles can be broadly applied to a variety of traditionally off-line service industries. Six areas of opportunities were highlighted where AI technologies are being readily deployed today.

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84.51° Builds a Machine Learning Machine for Kroger

By Thomas H. Davenport, Apr 24, 2018

Machine learning is a great way to extract maximum predictive or categorization value from a large volume of structured data. The idea is to train a model on a one set of labeled data and then use the resulting models to make predictions or classifications on data where we don’t know the outcome. The approach works well in concept, but it can be labor-intensive to develop and deploy the models. One company, however, is rapidly developing a “machine learning machine” that can build and deploy very large numbers of models with relatively little human intervention.

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Enterprise AI Primer: Build on Your Strengths

By Thomas H. Davenport, Kris Hammond, Apr 16, 2018

Available to Research & Advisory Network Clients Only

This brief is based on the premise that there’s a general confusion when it comes to AI impact, strategy, investment options, and even terminology. A significant factor is that for many companies, AI can and should be viewed as a natural progression of their existing business analytics capabilities. We believe that positioning AI as a natural evolutionary outgrowth of analytics, thus benefitting from already established analytics capabilities, provides the best and easiest path for most companies to successfully “step into” AI.

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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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Inquiry Response: Working the Right Business Problems

By IIA Expert, Apr 09, 2018

Available to Research & Advisory Network Clients Only

Inquiry:

We have our data lake in order so that we can perform more forward-looking analytics to drive business value. Now we’re struggling with how to start and what to prioritize first—any ideas?

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Operationalizing Analytics for Intelligent Fraud Detection and Case Management

By Michael Ames, Robert Morison, Jan 31, 2018

Available to Research & Advisory Network Clients Only

Fraud is widespread and continues to grow, especially online. It’s a major problem in a variety of industries and government agencies far beyond the familiar areas of financial and retail fraud, where credit card information is compromised and fraudsters use it for online purchases. The problem worsens as criminals get more organized and technologically sophisticated and operate at greater scale. As fraudsters innovate and scale up, fraud prevention and investigation become more challenging, and advanced analytics become a bigger part of the solution.

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Improving Analytics Measurement Part 5 of 5 – Analytics Health

By Robert Morison, Dec 20, 2017

Available to Research & Advisory Network Clients Only

Analytics Health metrics address the question, “Are we maintaining and building the right capabilities to meet business demand and perform better in the future?” These capabilities can include people and skills, processes for execution and management, technologies and techniques, and data assets for analytics.

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