Business Analytics for Managers. Thorlund Jesper

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      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 target is for the business to show a profit of $1.3 million after taxes, or whether the target is to be perceived as the most innovative enterprise – the two different targets require a completely different analytical approach and information deliverables. In data warehousing, the database specialist and the ETL developer won't know which data sources to retrieve, merge, enrich, and deliver to data marts (data prepared in the data warehouse for business use). IT operations and development won't be able to contribute by creating new data sources, since they don't know which new information and knowledge are required by the business. In other words, the whole thing becomes a messy affair without focus. One way of avoiding such a chaotic situation is to create a business analytics competency center (BACC), perhaps as a virtual organizational unit. We'll take a closer look at BACCs in Chapter 7.

      Of course, this is what we've always been doing or tried to do – but it's the first time I am able to put it into words and see our endeavors in a useful analytical model.

       Case Study: How to Make an Information Strategy for a Radio Station

      Now that we've introduced our theoretical model, let's apply this information to a concrete example in order to understand it better. This case study features the BA initiative of a large radio station that broadcasts nationwide. The case study is a simplified and somewhat creative version of real events, and its objective is merely to outline a BA process. Its focus is on the helicopter perspective, an improved conceptual СКАЧАТЬ