Research

Predictive Analytics World 2018

By Bill Franks, Jun 26, 2018

Available to Research & Advisory Network Clients Only

IIA attended the Predictive Analytics World (PAW) show in Las Vegas, June 6–7, 2018. This year the show had a new format called “Mega PAW” where a number of (previously individual) PAW shows were all housed together under one roof. Some of the keynotes were shared by all attendees, while the breakouts were segmented by topic. All of the sessions IIA attended were in the business track. In this event summary, the key points from each session attended will be provided, as will some commentary on IIA’s thoughts about the topic.

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Data Science Engineering

By David Alles, Jun 20, 2018

Available to Research & Advisory Network Clients Only

Reflections from Strata Data Conference 2018 and the emergence of data science engineering

The complexity of deploying advanced analytics and artificial intelligence (AI) into production is changing the nature of analytics and data science. As the size of data continues to expand and the pace of innovation accelerates, new roles are emerging. While advances in AI continued to headline the discussion at O’Reilly’s most recent Strata Data Conference (San Jose, March 5 – 8, 2018), the emergence of data science engineering as a new discipline is a clear trend and the primary focus of this brief. The objective of this report is to highlight and summarize the themes and trends supporting the emergence and importance of data science engineering. This report features a mix of unique IIA perspectives coupled with supporting thoughts from Strata presenters. This report also builds on key takeaways from our last 18 months of technology conference coverage

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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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Applications of AI: The VC Perspective

By Joanne Chen, May 08, 2018

Available to Research & Advisory Network Clients Only

2018 Analytics Symposium – Santa Clara Session Recording

There’s a lot of recent hype around AI and much discussion about what we can expect from these emerging technologies in the next decade. While some fear of the technology’s power, others see it as an opportunity to improve business and even entire industries. As an investor involved in the space, Joanne shared her insights on the enterprise AI landscape, including the critical elements of any startup’s AI strategy, sift through what is hype and what isn’t, and share the most promising business applications of AI. Joanne also zoomed in on conversational AI, sharing examples of chatbots in the real world, the market evolution of the technology, and the implications for your business.

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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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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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Data & Analytics – Enabling Nike’s Digital Transformation

By Gus Weber, May 08, 2018

Available to Research & Advisory Network Clients Only

2018 Analytics Symposium – Santa Clara Session Recording

Gus Weber’s talk jumped into the role of analytics in digital transformation and the Nike Consumer Direct Offense – a new company formation that allows Nike to serve the consumer faster and more personally, at scale. Gus leads the enterprise-wide technology strategy for data and analytics to ensure that Nike maximizes the power of data as a competitive advantage. This includes investments in personalization that leverage machine learning to curate assortments and advancing the role that product plays in unlocking experiences. Partnering, experimenting and fast tracking the greatest opportunities are key to success – envision a future where athletes seamlessly engage through digitally connected products to inform product innovation design, global manufacturing and distribution. Data is the new voice of the athlete.

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Data Science and Critical Thinking

By Alistair Croll, May 08, 2018

Available to Research & Advisory Network Clients Only

2018 Analytics Symposium – Santa Clara Session Recording

The right data, analyzed properly, and acted on wisely, can transform an organization. But the devil’s in the details: How do we know the data is valid? How should we analyze it? What’s legally and morally allowed? And how do we ensure that our analytics turn into business outcomes? The path from data to result is full of potholes, from cognitive bias and bad modeling to unintended consequences and market reactions. In a world awash with data, critical thinking is a vital, often-overlooked skill. In this talk, best-selling author of Lean Analytics and Harvard Business School visiting executive Alistair Croll looked at how to approach data with a critical mindset. Drawing from work with global corporations, early-stage startups, and public organizations, he explored how analytics teams can make the most of data while steering clear of biases and ethical quandaries.

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