The highlights of this article:
- Business Intelligence - the classic reporting, a look into the past
- Predictive analytics – looking into the future
- Prescriptive Analytics - modeling and simulation of the future
AI (artificial intelligence), analytics, robotic process automation or IoT are buzzwords in many companies and are often used when simple reporting is no longer sufficient or when you want to describe your own company as digital and innovative. However, most companies set up isolated solutions that are difficult to use across all levels in a digital and networked company or group of companies. In order to ensure an efficient and effective implementation of the above domains, it is advantageous to deal with the procedures and their temporal reference. At this point we are happy to support you. Contact us for an individual offer.
While Business Intelligence is mainly on an operational level, Predictive and Prescriptive Analytics are on the strategic level. This article aims to provide you with clarity and a deeper understanding
Business intelligence
Business Intelligence, also referred to as classic reporting, refers to the current and already created data in the ERP or other sources. For example, it characterizes the questions: How was my turnover in the last quarter? How many products have we sold in which segment? Most companies judge the key financial figures as the ultimate and measure their own success against them. However, financial key figures represent a time-delayed result of key figures from others, such as production key figures or HR key figures. If a plant fails in any part of the world, which cannot be compensated for by other production plants, this is immediately reflected in the production key figures , but not immediately in the financials. An analogy, as the title of this article already describes, is driving a car: Would you maneuver your car blindly using the rear-view mirror? We recommend pursuing a holistic view of BI and will help you take your reporting to the next level.
predictive analytics
Current technical developments offer companies the opportunity to take a look into the future. Various types of analyzes can be used to make predictions for the future if the data has been cleaned or enriched beforehand. For example, sales developments can be created in the form of corridors or corporate planning and, consequently, control can be designed more precisely. A classic example is the decision tree, which is divided according to certain parameters and is run through once for the situation. For example, an ordering process can be more targeted and more accurate. If you run an online shop, the classic example is a shopping cart analysis and the resulting generation of product suggestions. Assuming that customers often buy products A, B and C in combination, it can be concluded that if a customer has products A and C in their shopping cart, a suggestion for product B at this point represents a strong sales promotion measure and may reflected in turnover and sales. To take up the analogy of the vehicle: Would you use the classic paper map and calculate the journey time manually, or would you prefer the digital route and have it directly predict when you will arrive at your destination under what conditions?
Prescriptive Analytics
The prescriptive analyzes deal with the optimization and simulation of situations related to the business environment. In this way, simulations can be set up with existing internal and external data sources and various scenarios can be analyzed using parameters. A risk assessment, for example of a machine that has failed or a production failure due to the weather, can be analyzed and, if necessary, its effects can be estimated in advance and a number of measures can be defined. This is how a classic risk management can be operated, but with an exact statement about the effects. Alternatively, external qualitative risks can be simulated, for example by legislation. If the legislature changes certain restrictions in some business areas, it can be advantageous to provide for this in a capacity or financial plan for the individual business areas and to have simulated your transactions in the individual fields in advance. Under certain circumstances, this can result in a competitive advantage. But what exactly does that have to do with driving a car? Before a new vehicle is bought from the factory, one deals intensively with one's wishes and "What if?" situations. Is the steering wheel heating still in the budget or rather not? By adding or omitting the steering wheel heating, the change in price is simulated. Finally, two scenarios, one with and one without steering wheel heating, are simulated and the effects are discussed in detail. If one does not deal with it, the options and the effects would not be exhausted at all.
