Intelligent controlling not only of purchasing and ordering processes

Within the framework of Industry 4.0, the focus is on the optimization and automation of production and logistics processes. Increasingly, AI is also to be used for administrative, scheduling and planning processes in marketing, sales and management.

Purchase and order processes are a very good example where AI can optimize and improve many things. The processes from ordering to financial settlement are ideal for this. Many purchase and order processes are still handled manually by companies, although the processing is already digital. Orders are filed and processed manually and invoices are written, printed and sent on paper. AI-supported technologies help companies ensure that orders and invoices are not forgotten, and that payments are processed or sent on time. Any errors that occur can be corrected automatically and ensure continuous operation.

Beyond the simple handling of payment and receipt processes, AI-enabled systems can also identify the best customers. The intelligent software can identify whoever pays on time, makes regular purchases or focuses on specific products. With this information, companies can create personalized incentives for their customers and expand their perception.

Machine-learning analyses help to identify customer requirements, problems or product defects and to optimize these for all parties involved. AI systems help companies to keep an eye on their customers and ensure that processes are processed on time and without losses. Optimal interaction creates added value for all parties involved.

AI can also help to ensure that the controlling department is significantly supported by a company. Controlling departments are interested in using the added value of advanced AI methods for their planning, analysis and budgeting. Sophisticated machine learning algorithms refine the integrated planning, analysis, reporting and consolidation solution using artificial intelligence. Since AI systems can recognize patterns and anomalies in transactions, financial planning and annual reports, they support ongoing operations, e.g. in planning cycles, the integration of subplans or the auditing of annual financial statements. In doing so, they not only facilitate the planning process itself, but also expand the breadth and depth of information.

The algorithms of the AI can provide answers and suggestions and can be an innovation tool for competitive advantages. Based on an AI-defined infrastructure, information and its contents extend the possibility and power of statements. Important is an open and dynamic application landscape as well as a seamless extension and connection possibility up to the CPM programs.

There are no limits to the possible applications of intelligent systems in controlling and are only limited by non-existent data. The goal must be to let all information in the company communicate with each other in order to better understand the business, to react to deviations and peculiarities, and to obtain reliable information about processes and movements. Existing processes can be significantly improved and expanded and new opportunities in your own business can be identified.

So far, so promising. However, the AI is not yet ready to recognize on its own where optimization is possible and which approach will bring the most benefit. For each of the approaches described above a data model has to be formulated, a potential for improvement has to be found and the AI algorithm for solving the problem has to be found.  And this is where the human component comes into play - as long as the positronic brain (who does not know it yet: -> Isaac Asimov, "I Robot") is not invented, the intelligence of humans in controlling needs to identify and raise this potential.

The tools for implementation are already there and are developing rapidly:

AI in controlling today

Even though AI is currently known as a new technology trend, AI has been around for quite some time. With today's technical means, however, it can be used and applied much better. These include:

  • Cloud & PaaS with access to faster computing

  • Big Data with the ability to store and explore a vast amount of data

  • IoT, search algorithms & mobile devices with data generation directly at the source

Today, cognitive intelligence already offers detailed analyses of data that reveal information that is partly hidden from the human eye. Statistical methods are used to evaluate the data with cognitive intelligence. Another example are controlling dashboards that are supplemented with automatically generated data. In addition to the actual presentation, they also contain rules and algorithms for a meaningful forecast.

Intelligent controlling with an AI approach is the future of every company - plug and play can only exist to a limited extent - every company is different and must be viewed individually. This makes a flexible platform for modelling and integration all the more important: CoPlanner's software can be operated completely cloud-based and covers the requirements for AI-capable and flexible corporate performance management software.

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