Presented By
O’Reilly + Cloudera
Make Data Work
29 April–2 May 2019
London, UK
Please log in

Executive Briefing: Why managing machines is harder than you think

Pete Skomoroch (Workday)
12:05–12:45 Wednesday, 1 May 2019
Executive Briefing and best practices, Strata Business Summit
 Location: Capital Suite 13
Secondary topics:  AI and machine learning in the enterprise, Open Data, Data Generation and Data Networks
Average rating: ****.
(4.70, 10 ratings)
Download slides (PDF)

Who is this presentation for?

  • Product managers, vice presidents, directors, C-suite executives, and CTOs

Prerequisite knowledge

  • Familiarity with product management
  • An understanding of high-level concepts related to machine learning

What you'll learn

  • Explore a practical roadmap for machine learning in the enterprise, including a deep dive into an effective product management process for AI

Description

Companies that understand how to apply machine intelligence will scale and win their respective markets over the next decade. That said, delivering on this promise is much harder than most executives realize. Without large amounts of labeled training data, solving most AI problems isn’t possible. The talent and leadership to bridge the worlds of product design, machine learning research, and user experience are scarce. Many organizations will tackle the wrong problems and fail to ship successful AI products that matter to their customers.

Pete Skomoroch explains how to navigate these challenges and build a business where every product interaction benefits from your investment in machine intelligence.

Topics include:

  • Who defines the data vision and roadmap in your organization? Who is accountable for building and expanding your competitive moat?
  • Investing in foundational data infrastructure, training, logging, and tools
  • Fostering executive support for exploration and innovation, including user-facing data product and algorithm development
  • How to evaluate new machine intelligence projects and develop a portfolio that delivers
  • How AI product management differs from traditional product management
  • How to bridge the worlds of design and machine learning to get to product-market fit
  • Defining a framework for trading off investments in data quality, machine learning relevance, and other business objectives
Photo of Pete Skomoroch

Pete Skomoroch

Workday

Pete Skomoroch is the former head of data products at Workday and LinkedIn. He’s a senior executive with extensive experience building and running teams that develop products powered by data and machine learning. Previously, he was cofounder and CEO of venture-backed deep learning startup SkipFlag (acquired by Workday in 2018) and a principal data scientist at LinkedIn, the world’s largest professional network, with over 500 million members worldwide. As an early member of the data team, he led data science teams focused on reputation, search, inferred identity, and building data products. He was also the creator of LinkedIn Skills and LinkedIn Endorsements, one of the fastest-growing new product features in LinkedIn’s history.