Book Image

ServiceNow for Architects and Project Leaders

By : Roy Justus, David Zhao
Book Image

ServiceNow for Architects and Project Leaders

By: Roy Justus, David Zhao

Overview of this book

ServiceNow is the leading enterprise service management platform that enables the effective management of services in a modern enterprise. In this book, you’ll learn how to avoid pitfalls that can challenge value realization, where to focus, how to balance tradeoffs, and how to get buy-in for complex decisions. You’ll understand the key drivers of value in ServiceNow implementation and how to structure your program for successful delivery. Moving ahead, you’ll get practical guidance on the methods and considerations in securely using ServiceNow. You’ll also learn how to set up a multi-instance environment including best practices, patterns and alternatives in the use and maintenance of a multi-instance pipeline. Later chapters cover methods and approaches to design processes that deliver optimal ROI. Further, you’ll receive tips for designing technical standards, designing for scale, ensuring maintainability, and building a supportable instance. Finally, you’ll focus on the innovative possibilities that can be unlocked in a ServiceNow journey which will help you to manage uncertainty and claim the value of being an early adopter. By the end of this book, you’ll be prepared to lead or support a ServiceNow implementation with confidence that you’re bringing not only a solution but also making an impact in your organization.
Table of Contents (17 chapters)
Part 1 – Pursuit of Value
Part 2 – The Checklist
Part 3 – From Success to Innovation

Classification framework

Classification is the task of taking a set of input data, including text or other fields, and using it to output a category, assignment, or other value from a set list of options. In traditional enterprise workflows, simple classification decisions are made with static rules, while more complex classifications rely on expert judgment. ServiceNow’s classification solutions allow the systems to make more complex judgments in an automated way by leveraging information about how data was categorized in the past.

Classification solutions generally outperform simple rules when there are complex relationships between multiple input factors or when there are many examples of high-quality training data for a specific problem. In contrast to this, in a common use case such as setting a priority based on impact and urgency, the relationships between impact and urgency are typically clear and can be captured in a simple 3x3, 4x4, or 5x5 data table. In these...