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Data Sources: IT Operations and Development

IT operations and development decide to collect data on the listeners' ages, genders, tastes, moods, and listening times via a questionnaire. They develop an electronic questionnaire that listeners can complete on the radio station's website. The survey is announced and promoted on air, and sponsor prizes are given out via a prize drawing for the participating listeners. The data-collection process enables the creation of new operational data sources in the technically oriented environment, and the process is controlled and managed by developers and operational staff from IT operations and development. Using ETL tools, the database specialist or the ETL developer now continuously transfers the new data source into the data warehouse. Here it is merged with the other databases of the radio station (for instance, the database on past aired radio programs). After having been merged, the data is moved out into a data mart area so that the analyst can access it.

In the analytical environment, the analyst now has access to data and starts to transform the collected and merged data from the data warehouse into information and knowledge. The result of his analytical processes using statistical methods and tools such as data mining shows that the typical listener in the early hours of the morning is a fun-loving 30-year-old woman.

The analyst also has report-developing competencies and has prepared a front-end report with the results from his BA tool, which could be Microsoft Excel. The report contains information and knowledge about listener profiles for different times of the day and for the different programs. The report is released weekly with new numbers to the business's intranet, where it can be accessed and used by business users in the production department. Note that the analytical environment is positioned in the border area between the technically oriented environment and the business-driven environment, and we find people with competencies in both areas. The front-end solution and the report could also be delivered by a report developer from the technically oriented environment, based on results from the analytical processes.

The radio station's operational decision makers, DJs, and newsreaders must now change their daily business processes and actions in such a way that their actions provide better support for the achievement of the strategic targets of the business. As mentioned, the strategic target for the production department is to hold on to listeners for longer with a view to increase market share and ultimately improve ROE. In the morning, they all read the released front-end report to make use of the information and knowledge from the controller's analytical processes.

Before each DJ puts on a song, he looks at the BA report and asks himself the question: "Is a fun-loving 30-year-old woman going to like this music?" If he's about to play a heavy metal CD, it'll probably go back on the shelf. Instead, "Material Girl" by Madonna still might stand a good chance.

Equally, all news will be sorted through by the newsreader. Before reading any news, he now asks himself the question: "Is a fun-loving 30-year-old woman going to find this piece of news interesting?" If the news is about motoring, it'll probably end up in the paper bin, whereas news about either the current economic crises or the latest cinema film is likely to be broadcasted.

What is happening on this radio station is BA: decision support delivered to operational decision makers based on data analysis (creation of knowledge). The purpose of the exercise is to direct the decision makers' daily business processes toward achieving strategic targets.

Today, automatic digitalized decision making, based on analytics, is increasingly used to control and optimize operational processes at Internet radio stations. Data collected from users (e.g., IP addresses, how many people are turned in, the media player they are using, how long they listened, and their computer's operating system) can be used by an robot/algorithm to decide, for example, which shows/tracks to repeat (or skip), the required bandwidth (to support a good user-experience), and advertising content.

Evaluation of the Business Analytics Process

Over the next six months, the radio station succeeds in holding on to its average listener for 9 minutes longer than before, and all three KPIs are improved. (See Exhibit 1.3.)

Following the BA initiative, the radio station's average listener stayed tuned in for an average of 24 minutes (KPI 3). The radio station's market share (KPI 2) went up to 20 percent, and ROE (KPI 1) increased to 12 percent. The business is on its way to achieving its overall strategic targets, and the production department's BA initiative must be said to have been successful. It could not have been done without BA—from strategy to data sources.

Exhibit 1.3 The Radio Station's Dashboard with KPIs after BA Initiative

 
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