Business Analytics for Managers

Taking Business Intelligence Beyond Reporting

Gert H. N. Laursen, Jesper Thorlund

• Publisher: Wiley
• Year: 2016
• ISBN:
  9781119302537
• Edition: 2
• Topic: Business
• Subtopic: Decision Making
• Index: Business

The intensified used of data based on analytical models to control digitalized operational business processes in an intelligent way is a game changer that continuously disrupts more and more markets. This book exemplifies this development and shows the latest tools and advances in this field

Business Analytics for Managers offers real-world guidance for organizations looking to leverage their data into a competitive advantage. This new second edition covers the advances that have revolutionized the field since the first edition's release; big data and real-time digitalized decision making have become major components of any analytics strategy, and new technologies are allowing businesses to gain even more insight from the ever-increasing influx of data. New terms, theories, and technologies are explained and discussed in terms of practical benefit, and the emphasis on forward thinking over historical data describes how analytics can drive better business planning. Coverage includes data warehousing, big data, social media, security, cloud technologies, and future trends, with expert insight on the practical aspects of the current state of the field.

Analytics helps businesses move forward. Extensive use of statistical and quantitative analysis alongside explanatory and predictive modeling facilitates fact-based decision making, and evolving technologies continue to streamline every step of the process. This book provides an essential update, and describes how today's tools make business analytics more valuable than ever.

• Learn how Hadoop can upgrade your data processing and storage
• Discover the many uses for social media data in analysis and communication
• Get up to speed on the latest in cloud technologies, data security, and more
• Prepare for emerging technologies and the future of business analytics

Most businesses are caught in a massive, non-stop stream of data. It can become one of your most valuable assets, or a never-ending flood of missed opportunity. Technology moves fast, and keeping up with the cutting edge is crucial for wringing even more value from your data— Business Analytics for Managers brings you up to date, and shows you what analytics can do for you now.

Chapter 1
The Business Analytics Model

The most important thing in a large and complex project with a large number of people and competencies involved is to create an overview of the project from a helicopter perspective as quickly as possible.

This chapter focuses on the business analytics (BA) model, which will help provide that overview. The model provides an outline for understanding—and creating—successful BA in any type of organization. The purpose of the model is to give the organization a single common frame of reference for an overall structure in the creation of successful BA; the model clarifies the roles of the individual contributors and the interaction in the information generation and information consumption process, which is what BA is, too. The model is the pivot of the rest of the book; the five layers of the model are subsequently explained in detail, with each layer allocated a separate chapter.

If your job is to make an information strategy, for example as a CIO, the model comprises all the stakeholders and processes on which you should focus. The model also gives clues about why most BA projects fail, which is simply because it is a large cross‐organizational activity. You can compare it to a chain that is only as strong as its weakest link; if one of the departments involved lacks the skills or resources, or if the knowledge handover between departments fails, your project will fail.

OVERVIEW OF THE BUSINESS ANALYTICS MODEL

The BA model in Exhibit 1.1 illustrates how BA is a layered and hierarchical discipline. Arrows show the underlying layers that are subject to layers above. Information requirements move from the business‐driven environment down to the technically oriented environment. The subsequent information flow moves upward from the technically oriented environment toward the business‐driven environment.

Exhibit 1.1 The BA Model

As illustrated by the BA model in Exhibit 1.1, there are many competencies, people, and processes involved in the creation of BA. In the top layer of the model, in the business‐driven environment, the management specifies a strategy that includes which overall information elements must be in place to support this strategy. In the second layer, the operational decision makers' need for information and knowledge is determined in a way that supports the company's chosen strategy. In the middle layer of the model, analysts, controllers, and report developers create the information and knowledge to be used by the company's operational decision makers with the purpose of innovating and optimizing their day‐to‐day activities. In the second layer from the bottom, in the technically oriented environment in the data warehouse, the database specialist or the ETL (extract, transform, load) developer merges and enriches data and makes it accessible to the business user. In the bottom layer, in the technically oriented environment, the business's primary data generating source systems are run and developed by IT professionals from IT operations and development. Successful BA processes should have a fixed structure that always begins with the specification of the information strategy, which is derived from the objectives of the business strategy.

Strategy Creation

All underlying contributions and activities must submit to the chosen information strategy, as specified in the business‐driven environment at the top of the model. This information strategy is decided at this level based on the organization's or the business area's overall business strategy (vision, mission, and objectives). Normally, these strategies will result in a number of key performance indicators (KPIs) with the purpose of measuring the degree of progress and success. The contents of the KPIs will depend on which underlying business process we want to control. The KPIs could, for instance, relate to profitability, return on equity (ROE), or different types of sales targets. The information strategy is often specified by the top management of the organization, by functional managers, or by business process owners. Large organizations may have an actual business development function, which is responsible for the formulation of the strategy for the entire group. How this is undertaken will be explained in detail in Chapter 2.

Business Processes and Information Use

Once the strategy, along with the overall strategic KPIs, is in place, a framework, focus, and objectives are established for the operational business processes and initiatives. The information and analysis shown in the underlying layers of the model must be directed at changing and managing business processes toward the strategic objectives made visible by the KPIs. The operational decision makers' desired behavior and the subsequent information and knowledge requirements to bring about this behavior are specified and outlined in this layer.

As mentioned, the objective of BA initiatives is to change business processes and actions so that they are targeted toward achieving the organization's strategic objectives. For example, operational decision makers from sales, marketing, production, general management, human resources (HR), and finance can use information and knowledge to optimize their daily activities. In Chapter 3, we'll look at what this means specifically for the various functions of the company.

Types of Reporting and Analytical Processes

In the analysis and reporting development environment in the middle of the model, analysts specify which information and data are necessary to achieve the desired behavior of operational managers and digital processes in the business environment. This is where information and knowledge are generated about the deployment of analytical and statistical models, which are typically deployed on data from the data warehouse. The requirements for front‐end applications, reporting, and functionality are also specified in detail here, all with the purpose of meeting the demands from the higher layers and levels of the model. Note that the analysis and reporting development environment is placed in the bordering area between the business‐driven and the technically oriented environment, and that the team in this area usually has competencies in both areas. Chapter 4 covers more about the methodical work in the analytical and reporting environment.

Data Warehouse

Database specialists and ETL developers receive requirements from the analytical environment about data deliveries. If the required data is already in the warehouse, the process will be to make this data accessible to the front‐end applications of the business. If data is not stored, the data warehouse will need to retrieve data from one or more operational data sources in the organization's environment. Alternatively, data can be purchased from an external supplier, or the IT department may be asked to implement a new infrastructure with a view to create a new operational data source. Chapter 5 focuses on methods and systems for storing, merging, and delivering data.

Data Sources: IT Operations and Development

IT operations and development must meet the requirements from the data warehouse about the delivery of data from the primary operational data sources or the development of new data sources. The different primary data sources in a company's environment and the data created are covered in Chapter 6.

As previously noted, a large number of people, competencies, and processes are involved in the creation of BA. Large organizations sometimes have several hundred people on all levels involved at the same time. In smaller companies, controllers and analysts must have a wider range of competencies to be able to carry out BA initiatives on their own.

It is important to realize that if something goes wrong in one of the layers of the BA model, the investment in BA may well be lost. If the management, in the top layer of the model, does not define one overall strategy, operational decision makers will not have a goal to work toward. The analyst won't know which analyses are required. It makes a big difference, for example, for the analyst to know whether the overall targe...