Data Driven Decision Making For Small Businesses

The reader of this book need not be a mathematician. This book is intended for the business-minded individual interested in learning about the strategic advantages which can be obtained from business analytics.Small Business Trends magazine reported that, "you don't need to be a Fortune 500 company with revenue in the stratosphere to benefit from the application of business intelligence. A simple analysis of data your business may already be collecting could hold the answer."Perhaps you would like to reduce your inventory, determine product and customer profitability, gain insight into customer ordering behaviour. Perhaps you would like to know where you are spending your business dollars or how to determine if your cash flow is getting better or worse. Is your business becoming more or less efficient as it grows? Perhaps you would like to predict upcoming retirements to determine the impact of the baby boomer generation on your organization.This book will present some of the simpler approaches to data analysis and will show the value of these analyses to business. The intent is to show the reader what is possible rather than teaching the mathematical techniques. From simple to the more advanced, this book will deliver a series of analytics suitable for anyone wishing to take their business to the next level.I will present a series of real-world case studies from various functional areas, the majority of which will be conducted with every day software that most businesses already possess.The book will go on to examine the advantages and disadvantages of trying to build these capabilities in-house and will provide a realistic view of the challenges associated with analytics in the business world.Finally, I will provide some advice on data analysis and visualization tools. Specifically, I will focus on the tools that are available to the reader for prices that are in line with typical office software.

Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making. In Data Driven, Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals: · The special properties that make data such a powerful asset · The hidden costs of flawed, outdated, or otherwise poor-quality data · How to improve data quality for competitive advantage · Strategies for exploiting your data to make better business decisions · The many ways to bring data to market · Ideas for dealing with political struggles over data and concerns about privacy rights Your company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that.

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

In today's academic environment, the challenge of ensuring lasting commercial and economic success for organizations has become more daunting than ever before. The relentless surge in data-driven decision-making, based on innovative technologies such as blockchain, IoT, and AI, has created a digital frontier filled with complexity. Maintaining a healthy firm that can continually provide innovative products and services to the public while fueling economic growth has become a formidable puzzle. Moreover, this digital transformation has ushered in new risks, from pervasive cybersecurity threats to the ethical challenges surrounding artificial intelligence. In this evolving landscape, academic scholars face the pressing challenge of deciphering the path to long-term organizational prosperity in an era dominated by data. Data-Driven Decision Making for Long-Term Business Success serves as guidance and insights amidst this academic challenge. It is the definitive solution for scholars seeking to uncover the complexities of data-driven decision-making and its profound impact on organizational success. Each meticulously curated chapter delves into a specific facet of this transformative journey, from the implications of modern technologies and pricing optimization to the ethics underpinning data-driven strategies and the metaverse's influence on decision-making.

Accessible and concise, this exciting new textbook examines data analytics from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers. The book successfully combines theory with practical application, featuring case studies, examples and a ‘critical incidents’ feature that make these topics engaging and relevant for students of business and management. The book features chapters on cutting-edge topics, including: • Big data • Analytics • Managing emerging technologies and decision-making • Managing the ethics, security, privacy and legal aspects of data-driven decision-making The book is accompanied by an Instructor’s Manual, PowerPoint slides and access to journal articles. Suitable for management students studying business analytics and decision-making at undergraduate, postgraduate and MBA levels.

This book deals with Business Analytics (BA) - an emerging area in modern business decision making. Business analytics is a data driven decision making approach that uses statistical and quantitative analysis along with data mining, management science, and fact-based data to measure past business performance to guide an organization in business planning and effective decision making. Business Analytics tools are also used to predict future business outcomes with the help of forecasting and predictive modeling.In this age of technology, massive amount of data are collected by companies. Successful companies use their data as an asset and use them for competitive advantage. Business Analytics is helping businesses in making informed business decisions and automating and optimizing business processes.Successful business analytics depends on the quality of data. Skilled analysts, who understand the technologies and their business, use business analytics tools as an organizational commitment to data-driven decision making.

What goes on in a small firm that lives or dies by its capacity to innovate? How are decisions made on new product development, and how does that feed into the ecological, social and financial sustainability of the firm? This book answers the questions through an in-depth look at a small business that manufactures high-end carpet yarn. Using advanced analytical techniques to interrogate rich qualitative data, the book draws together established theories of decision-making and new product development, coupled with thinking about business sustainability to improve our understanding of this important area of business practice. The book further reinforces the importance and role of organizational learning in organizational decision-making, based on novel analysis of empirically developed qualitative data.