Title: Business analytics for managers: taking business intelligence beyond reporting / Gert H. N. Laursen, Jesper Thorlund.
Description: Second edition. | Hoboken: Wiley, 2016. | Series: Wiley & SAS business series | Revised edition of the authors's Business analytics for managers, | Includes index.
Identifiers: LCCN 2016028271 (print) | LCCN 2016029032 (ebook) | ISBN 9781119298588 (hardback) | ISBN 9781119302520 (ePDF) | ISBN 9781119302537 (ePub) | ISBN 9781119302520 (pdf) | ISBN 9781119302537 (epub)
Subjects: LCSH: Business intelligence. | BISAC: BUSINESS & ECONOMICS / Decision-Making & Problem Solving.
Classification: LCC HD38.7 .L39 2016 (print) | LCC HD38.7 (ebook) | DDC 658.4/033 – dc23
LC record available at https://lccn.loc.gov/2016028271
Cover Design: Wiley
Cover Image: © Michael Mann/Getty Images, Inc
Foreword
This book provides more fuel for this era of strategic and unified views of business analytics for value creation. In the same vein as Competing on Analytics and Analytics at Work, Business Analytics for Managers: Business Intelligence beyond Reporting adds another interesting and worthwhile perspective on the topic. In times of rapid change and growing complexity, rapid learning becomes more valuable. This book provides the strategic view on what's required to enable rapid learning and ultimately value creation.
Making decisions using huge, noisy, messy data requires business analytics. It is important to have a true appreciation of and advocacy for the analytical perspective on the whole of business analytics – on data (a strategic asset), on methods and processes (including refinement and optimization), and on people (the diverse skills it takes to formulate and execute on a well‐thought‐through strategy).
It starts with an analytical view of data: What is being measured, and is it what matters? Measurement (data generation and collection) is itself a process – the process of manufacturing an asset. When data is viewed this way, the analytical concepts of quality improvement and process optimization can be applied. The authors essentially ask, “What are you doing with your data? How are people in your organization armed to make better decisions using the data, processes, and analytical methods available?”
Business analytics, as portrayed by these analytical thinkers, is about value creation. Value creation can take different forms through greater efficiency or greater effectiveness. Better decisions to reduce costs, reveal opportunity, and improve the allocation of resources can all create value. The authors provide valuable business analytics foundational concepts to help organizations create value in a sustainable and scalable way.
Why business analytics? Even though some have tried to expand the definition of the relatively aged term business intelligence (BI), there is no real consistency, so a new term reflecting a new focus is warranted. Further, through promotion of a process view, we break out of some of the silothink and see the importance of closing the loop – on data (to monitor data quality and measure what matters), on process (to continuously learn and improve), and on performance (to make the best decisions, enable the best actions, and measure impact). How many organizations continue producing text‐heavy, tabular reporting on old and perhaps out‐of‐date metrics that few take the time to consume? How old are some of the processes driving key decisions in organizations? What opportunity costs are you incurring, and how could you be creating more value?
This book provides a synthesized view of analysis, traditional BI, and performance management, all of which are connected and need to be orchestrated strategically for maximum impact. The chapter advocating a shared strategic resource – a competency center or center of excellence – is an excellent way to drive best practices and create more value, making the case for treating data as a strategic asset and investing in the appropriate analytic infrastructure to maximize value.
Wherever you may be on your business analytics journey, you will find worthwhile thinking, shared expertise, and solid practical advice in this book to help you create more value in a sustainable and scalable way. The book is not just about analytics as a step in any given business process, but about the analytical perspective on any process that is key to understanding what it takes to drive continuous learning and improvement.
Introduction
Imagine a company. It could be an American manufacturer of home computers. Try to imagine, too, all the things such a company must be able to do: purchasing from suppliers, assembling and packaging the parts, preparing manuals and marketing plans, selling the products. The company also has a large number of support functions. Someone must look after the well‐being of its employees, new staff must be hired, people must be paid, the place must be cleaned, and a canteen must work to feed everyone. There is an entire financial function, ensuring that the crediting and debiting of banks, suppliers, owners, and customers runs smoothly. Finally, there are all the planning processes related to product lines and customer groups on which the company has chosen to focus.
Now imagine how much of this the company could outsource. Without too much effort, all production could be moved to East Asia. That could probably bring huge advantages since assembling computers is typically salary‐heavy and standardized production work. Others could handle the logistic side of things. The company could get professionals to write and translate the manuals. In addition, the company wouldn't need its own outlets; its products could be sold through some of the major retail chains. Alternatively, a Web shop could be commissioned to create an Internet site where customers could order the products they want. There is no real need for the company to have its own warehouse for parts and computers, from their arrival to their delivery to the customers. A lot of the support functions could be outsourced, too. Many companies outsource the process of recruiting the right people. Routine tasks such as paying salaries, developing training plans, and executing them in external courses could be outsourced, once the company has put the routines in place. Cleaning, the running of the canteen, refilling vending machines, and mowing grass are functions that are already, as a rule, outsourced by large IT companies.
By now, there is not much left of our company. We have removed all the functions that others can do almost as well or, in some cases, even better. What we have left is what we call the company's core competencies. These competencies are the things that the company is especially good at and that can secure its survival in the future, provided it is capable of developing these so that they continue to meet the requirements in the marketplace.
As shown in our example, core competencies have little to do with the physical world. Machinery, warehouses, and distribution can be outsourced. A company's core competencies lie in knowing how to handle internal processes, and knowing what customers want now and in the future. In other words, the key is to have the right knowledge in the company. More specifically, what the company needs is for the right people to have the right data and information at the right time. When that happens, we have rational decision making that meets strategic, operational, and market conditions. And this is exactly the first half of this book's business analytics (BA) definition:
Definition 1: Delivering the right decision support to the right people at the right time.
In this definition, we have chosen the term decision support, because BA gives you, the business user, data, information, or knowledge, that you can choose to act upon or not. Here's a familiar example: An analysis of check‐out receipts can inform the manager of a 7‐Eleven store which products are often purchased together, thus providing the necessary decision support to guide the placement of goods on the shelves to increase cross‐selling.
There is a saying that “people don't buy drills; they buy holes,” and this definition of BA points out that “people don't buy servers, pivot tables, and algorithms; they buy the ability to execute, monitor and control their business processes, along with insights about how to improve them.”
Regardless of whether predictive models or forecasting is