Model Management Framework Defines Path to Develop and Deliver Models at Scale for Competitive Advantage

SAN FRANCISCO, Calif.— May 31, 2018 — Domino Data Lab, provider of an open data science platform, today introduced a framework to help organizations become model-driven by systematically developing, validating, delivering, and monitoring predictive and machine learning models at scale. The Model Management framework, substantiated by engagements with hundreds of organizations that run their businesses on models, was revealed during the Rev summit for data science leaders this week. The framework helps organizations create a sustained competitive advantage by embedding models at their business core.

One such company is Moody’s Analytics, a pioneer in financial modeling that has established a competitive advantage by creating analytics based on unique financial data sets and applying them to solve clients’ business challenges. Their large portfolio of models covers everything from small business to large bank credits. “Domino accelerates our speed to delivery, providing a much faster and better return on our modeling investment,” said Jacob Grotta, managing director at Moody’s Analytics. In their first experience using Domino’s framework and platform, Moody’s Analytics delivered an estimated nine-month project in four months.

Models are algorithms whose instructions are induced from a set of data, and are then used to make predictions, recommendations, or generally prescribe some action based on a probabilistic assessment. According to recent studies, at least 80 percent of companies aren’t making extensive use of models. The companies who do have a 9.5 percent profit advantage over those that do not.

Lack of successful, widespread model adoption stems from one root problem: Organizations are trying to manage models like other business assets. They are falling for the Model Myth – the belief that because models involve code and data, they can be managed the same way as software or data assets. Model-driven companies recognize that models are different. They are built with different materials, they are developed with a different research-based process, and they behave differently once deployed.

“The use of data science in leading companies has matured beyond just building models. Organizations are struggling to capitalize on their investments in data science and this is now where they need the most help,” said Stephen Smith, Research Director at Eckerson Group. “Domino has shown unique focus in solving this problem. Their Model Management framework helps organizations manage models as unique assets and enables them to successfully run data science at scale.”

An effective Model Management discipline is comprised of five pillars:

  • Model Technology: The software tooling and infrastructure stack that gives data scientists the agility they need to develop and deploy innovative models.

  • Model Development: Business processes and systems that allow data scientists to rapidly develop models, experiment, and drive breakthrough research.

  • Model Production: The function(s) facilitating the operationalization of data science work from research project to a live product or output that’s integrated into business processes, affecting business decisions.

  • Model Governance: The mechanism and ability to constantly monitor the activity, performance, and impact of models and data science initiatives across the organization. This includes transparency across projects, production models, and the underlying technology infrastructure supporting them.

  • Model Context: At the heart of Model Management, Model Context encompasses all knowledge, insights, and artifacts generated while building or using models. This is often a company’s most valuable IP; the ability to find, reuse, and build upon it is critical to driving rapid innovation and a model-driven culture.

These philosophies have been embedded inside the Domino platform and are driving Domino’s product vision. “After countless engagements with organizations at all stages of data science maturity, we are outlining this new Model Management framework to articulate the best practices of becoming a model-driven business,” said Nick Elprin, co-founder and CEO at Domino. “With our platform, industry-recognized customer experience, and this framework as a guide, companies are weaving models into their business fabric so they can deliver breakthrough innovations and everyday operational efficiencies alike.”

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About Domino Data Lab

Domino Data Lab provides an open data science platform to help companies run their business on models. Model-driven companies like Allstate, Instacart, Dell, and Bayer use Domino to accelerate breakthrough research, increase collaboration, and rapidly deliver high-impact models. Founded in 2013 and based in San Francisco, Domino is backed by Sequoia Capital, Bloomberg Beta, and Zetta Venture Partners. To learn more, visit dominodatalab.com.

Media Contact:

Karina Babcock, Director of Corporate Marketing

E: press@dominodatalab.com

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