Business Intelligence: 5 Reasons Why it is so Important for Digitization

Business Intelligence: 5 Reasons Why it is so Important for Digitization

For many companies, digitization is currently the most important modernization project in decades. Nothing can go wrong. However, digitization pressure on companies, industries, and entire economic sectors is not growing linearly. Instead, it intensifies day by day in view of the global competitive situation. In the strategic planning and implementation of digitization projects, business intelligence is an elementary success factor. This article gives five reasons for using business intelligence tools when building digital business models.

1. Documentation of the status quo using business intelligence

Many existing processes grow historically. Often situationally, spontaneously, and without appropriate planning documents and documentation. However, these are essential for the preparation of process digitization. Without an overview of the process landscape, the basis for its digitization is missing. The more businesses use manual processes, the more difficult it is to collect reliable key figures. Business intelligence agency helps to merge available data and create the most objective picture of the current situation possible at this early stage.

2. Analysis of the status quo

In the second step, all current processes must be put to the test for honest and self-critical analysis. Only from the deep understanding of the strengths and weaknesses of existing processes can the course be set for their successful digitization. Or, the replacement by new, more suitable digital processes. BI programs use KPI measurements to show to what extent processes contribute to the strategic specifications. Thus, they can analyze their value.

3. Definition of the digitization strategy

On the basis of these findings, a digitization strategy suitable for the respective company, the business model, and process landscape hits the design phase. Here, too, business intelligence provides the necessary process transparency. Businesses analyze and hierarchize processes according to their importance and the benefit factor for the company. This then decides the order of the digitization steps. The digitization strategy also includes process selection. Identify and eliminate processes that are unsuitable, superfluous, or even obstructive during critical examinations. This avoids unnecessary effort for the digitization of these processes and at the same time optimizes the process chain.

4. Operational implementation of the digitization strategy

In the subsequent digitization practice, business intelligence analyzes the company-critical and most useful processes as a central measuring and control instrument. You will receive the greatest priority, which will then be followed successively by further processes less relevant to the company's success. At the same time, however, this digitization work at the core of the company also bears the greatest risk. Therefore, it makes sense to use the principle of low-hanging fruits. With BI tools, businesses can select relatively simple, manageable processes with set collateral effects for digitization.

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5. Process automation using business intelligence

Digitization not only opens up new ways of automating processes - it's one of the biggest advantages of it. Business intelligence provides the necessary information on the extent to which the user actually exploits the potential efficiency, error reduction, and speed effects of process automation. Since it is particularly demanding, it should not be right at the beginning, but should be part of the digitization strategy from the outset.

Show the status of digitization measures with business intelligence

For the technical-operational implementation in the digitization of business models, BI tools are indispensable indicators and control instruments for measuring and controlling the operational impact of digitization measures. By analyzing the key figures on sales and marketing, customer service, and internal processes and resources, they reliably indicate the state of digitization progress or omissions and provide information on the potential for improvement. Selection criteria for a targeted BI tool include flexible adaptability and expandability for specific requirements and future updates. As well as an open data model for data analysis and evaluations. Plus, standardized interfaces for interaction with legacy systems and other software tools.

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