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

Regression framework

When you consider the different types of fields in ServiceNow, you might notice that not all fields lend themselves to a classification approach. In addition to assigning categorical values, you may also want to predict numeric field values such as durations, sizes, effort levels, or other measures that vary along some numeric scale. Regression solutions have some distinctive characteristics, which make them very useful as an additional tool for automating processes. To understand these benefits, it is necessary to think about the types of data that we would be predicting and how a person would estimate the number based on inputs. Let’s use the example of estimating the hours that should be estimated for a user story based on some given input text and an assigned team.

The first thing to think about in this situation is whether we should hope for a precisely correct answer each time. If you estimated 30 hours and it turned out to be 28 or 32, you’...