Analytics For Business Success

Harness the power of analytics to revolutionize your business. Analytics is transforming the business landscape. All over the world, companies are using data to plan, invent, evolve, and gain critical insight into their customers, markets, and operations. The hype around analytics is well justified—but implementing an analytics initiative in practice is no easy task. Most analytics projects never make it to production. Even companies that manage to engineer a workable product prototype can stumble at the last hurdle and fail to realize the benefit of their analytics investment. In Analytics for Business Success: A Guide to Analytics Fitness,TM analytics expert Hema Seshadri diagnoses the challenges that can sabotage analytics product development and operationalization. With her accessible guide, learn how you can boost your company’s analytics fitness and make advanced analytics and AI work for you.

We know HR practices have a significant impact on an organization's bottom line, but too often HR leaders fail to demonstrate direct connections to the business metrics that matter most to executives. Predicting Business Success goes beyond the usual slicing and dicing of HR data to show HR professionals how to definitively connect the dots between people data and business outcomes with a straightforward approach for scaling analytics to all leaders and all levels, detailed strategies for collecting key data elements and making talent profiles predictive, and proven guidelines for harnessing data for selection and recruitment, onboarding, employee surveys, training needs, and much more.

A roadmap to understanding and achieving excellence in business analytics initiatives With business analytics is becoming increasingly strategic to all types of organizations and with many companies struggling to create a meaningful impact with this emerging technology, this book based on the combined experience of 10 organizations that display excellence and expertise on the subject shares the best practices, discusses the management aspects and sociology that drives success, and uncovers the five key aspects behind the success of some of the top business analytics programs in the industry. Readers will learn about numerous topics, including how to create and manage a changing business analytics strategy; align business priorities to technological innovation; quantify and demonstrate tangible business value; implement program processes that balance agility, empowerment, and control; and architecting a business analytics technology solution with future innovation in mind.This is the ideal resource for any organization that wants to learn how a business analytics program can help manage value, employees, and technology to translate strategies into actionable insight and achievement.

Practical introduction to a novel system of performance measurement for a variety of enterprises, written for practitioners and students alike.

We are entering the era of digital transformation where human and artificial intelligence (AI) work hand in hand to achieve data driven performance. Today, more than ever, businesses are expected to possess the talent, tools, processes, and capabilities to enable their organizations to implement and utilize continuous analysis of past business performance and events to gain forward-looking insight to drive business decisions and actions. AI-Enabled Analytics in Business is your Roadmap to meet this essential business capability. To ensure we can plan for the future vs react to the future when it arrives, we need to develop and deploy a toolbox of tools, techniques, and effective processes to reveal forward-looking unbiased insights that help us understand significant patterns, relationships, and trends. This book promotes clarity to enable you to make better decisions from insights about the future. Learn how advanced analytics ensures that your people have the right information at the right time to gain critical insights and performance opportunities Empower better, smarter decision making by implementing AI-enabled analytics decision support tools Uncover patterns and insights in data, and discover facts about your business that will unlock greater performance Gain inspiration from practical examples and use cases showing how to move your business toward AI-Enabled decision making AI-Enabled Analytics in Business is a must-have practical resource for directors, officers, and executives across various functional disciplines who seek increased business performance and valuation.

How does a CEO, manager, or entrepreneur begin to sort out what defines and drives a good customer experience and how it can be measured and made actionable? If you know how well the customer experience is satisfying your customers and you know how to increase their satisfaction, you can then increase sales, return visits, recommendations, loyalty, and brand engagement across all channels. More reliable and more useful data leads to better decisions and better results. Innovating Analytics is also about the need for a comprehensive measurement ecosystem to accurately assess and improve the other elements of customer experience. This is a time of great change and great opportunity. The companies that use the right tools and make the right assessments of how to satisfy their customers will have the competitive advantage. Innovating Analytics introduces an index that measures a customer’s likelihood to recommend and the likelihood to detract. The current concept of the Net Promoter Score (NPS) that has been adopted by many companies during the last decade—is no longer accurate, precise or actionable. This new metric called the Word of Mouth Index (WoMI) has been tested on hundreds of companies and with over 1.5 million consumers over the last two years. Author Larry Freed details the improvement that WoMI provides within what he calls the Measurement Ecosystem. He then goes on to look at three other drivers of customer satisfaction along with word of mouth: customer acquisition, customer loyalty, and customer conversion.

The categorisation of analytical projects could help to simplify complexity reasonably and, at the same time, clarify the critical aspects of analytical initiatives. But how can this complex work be categorized? What makes it so complex? Data Analytics Initiatives: Managing Analytics for Success emphasizes that each analytics project is different. At the same time, analytics projects have many common aspects, and these features make them unique compared to other projects. Describing these commonalities helps to develop a conceptual understanding of analytical work. However, features specific to each initiative affects the entire analytics project lifecycle. Neglecting them by trying to use general approaches without tailoring them to each project can lead to failure. In addition to examining typical characteristics of the analytics project and how to categorise them, the book looks at specific types of projects, provides a high-level assessment of their characteristics from a risk perspective, and comments on the most common problems or challenges. The book also presents examples of questions that could be asked of relevant people to analyse an analytics project. These questions help to position properly the project and to find commonalities and general project challenges.

In a resolutely practical and data-driven project universe, the digital age changed the way data is collected, stored, analyzed, visualized and protected, transforming business opportunities and strategies. It is important for today’s organizations and entrepreneurs to implement a robust data strategy and industrialize a set of “data-driven” solutions to utilize big data analytics to its fullest potential. Big Data Analytics for Entrepreneurial Success provides emerging perspectives on the theoretical and practical aspects of data analysis tools and techniques within business applications. Featuring coverage on a broad range of topics such as algorithms, data collection, and machine learning, this publication provides concrete examples and case studies of successful uses of data-driven projects as well as the challenges and opportunities of generating value from data using analytics. It is ideally designed for entrepreneurs, researchers, business owners, managers, graduate students, academicians, software developers, and IT professionals seeking current research on the essential tools and technologies for organizing, analyzing, and benefiting from big data.