Companies save at the expense of their competitiveness

Many companies that successfully manage and map their processes with SAP apply double standards: On the one hand, they pay a great deal of attention to maintaining their SAP infrastructure, which is not least reflected in the form of financial and human resources. On the other hand, they try to make do with narrow-track solutions when transferring the data available in SAP to other systems and writing it back to SAP. A questionable strategy.

In practice, it often turns out that such companies extract the information manually or semi-automatically. The data is selected manually in the SAP system and transferred to the target system. On the other hand, some companies pull SAP data into Excel, for example, where it is again prepared and analyzed manually. Such manual transfer can result in incomplete or duplicate data records being extracted, inconsistencies, or data not being in the correct order.

If the parties involved notice such an error in good time, they can restore the data set, but they have to start integration from the beginning, which takes more time. All subsequent processes are delayed accordingly.

If users fail to register an error in the data set in good time, there is a threat of far more serious consequences. Inefficient inventory management as well as incorrect pricing and product measurement data that have a negative impact on billing and customer relations are just three possible examples.

Strategic decisions based on a poor data foundation, right? Since controllers, division managers, and board members also use SAP-based data links to create analyses and visualizations and use them as the basis for important business decisions, an incorrect data set ensures that decisions are based on incorrect assumptions.

But even if the data set contains no errors, decisions based on manual or semi-automatic data integrations are not optimal. This is because manual integration can take several hours or days, depending on the design of the process. This may be sufficient for certain management areas. In organizations with a high level of digitization and process speed, such retrospective approaches can prove to be a significant competitive disadvantage. 

Fast-growing companies face another challenge: Sooner or later, they realize that manual integration is not a suitable tool for them in the long run. This is because the process proves not to be scalable in such situations as the data load increases. Digital transformation cannot be realized with manual data integration.

Fully automated SAP integration provides a remedy for the disadvantages associated with manual data merging. This refers to the transfer of data and processes from the SAP system to other target environments and writing them back to SAP via an interface. The data is made available directly in a database in different formats, for example. 

The SAP interface is designed to perform these steps in the background without the user noticing it in everyday life. In this way, it enables fast and secure access to SAP data so that the individual departments of the company can use the SAP data in their familiar target environments. There are basically three ways of automated integration.

Self-developed programs

First path: Programs developed in-house. Programs written by companies, which they tailor to their own needs, initially seem to offer a solution. However, they create new problems. The effort required to develop and maintain them is often underestimated.

Especially the lack of maintainability regularly proves to be a proverbial bottomless pit. After years of development, in-house attempts also fail because they do not react flexibly enough to updates, new requirements and other changes in the system environment. Or they do not even make it out of the test phase. 

In the same way, the migration of know-how is an important aspect: as soon as employees who were entrusted with development leave the company, expertise can be lost if there is not enough time for preparation and handover.

SAP's own solutions

Second path: SAP's own solutions. SAP itself offers software for analyzing and processing data. However, this often proves to be less performant, can generate a support overhead that requires a dedicated consultant, and is not the most cost-effective solution. In addition, these applications require more training - they are usually less user-friendly than the software with which users are already familiar. Also, the open standards that SAP has created in the past do not meet the needs of companies and users. 

Many companies also reject a one-vendor strategy because a homogeneous IT landscape entails a high degree of dependency. Especially with regard to mission-critical SAP data, this is not desired in many companies. In principle, they strive for a heterogeneous IT landscape.

Independent interfaces

Third way: Independent interfaces. Independent interfaces enable organizations to extract the most current data for analytics at any time and integrate it into numerous desired target environments. This could be survey and procurement data deployed to the Google Cloud for reporting purposes. Or it may be raw data that is reliably transferred to the Amazon S3 Data Lake to then agilely forecast customer demand for better pricing and availability planning. For the respective departments, automation speeds up workflows enormously and errors are reduced to a minimum. 

The entire range of applications for SAP data integrated via an independent interface is wide: administration in a higher-performance database (cloud and "classic"), enrichment with information from other systems, or visualization of all business-critical data, such as target/actual comparison via a BI tool for sales or production. An interface for data analysis is just as relevant: If not all data from all systems is available, an evaluation is not very meaningful.

However, an independent interface not only ensures a smooth process, but also virtually unrestricted freedom in the selection of application software. Since the IT decision-makers responsible do not have to make any compromises in terms of compatibility, they can focus their attention in the selection process on the other requirement criteria for the best software in each case. The agility of the interface is important. It should be easy to adapt to other required data or new target environments, so that the IT department no longer needs to be involved in any adaptation.

In addition, companies can restrict access to the data in the SAP system to the necessary information, thus improving the security of the system. This provides IT with a holistic tool for linking all systems with each other and also securely integrating future target systems.

The overall costs are also lower with this solution, as in-house development requires a lot of input and manpower, whereas companies use existing systems with a ready-made interface. With such an interface, errors resulting from a lack of experience can also be prevented.

Conclusion

For companies, there is no way around automated SAP integration if they want to ensure scalability, high security standards, the best possible data quality and accurate decisions by their management. Digital transformation can only succeed if the important data is available quickly and flexibly. Management must react just as agilely to a change in the demand for the data to be integrated as it does to a new target environment.

Using SAP integration via an independent interface, companies decide for themselves which data they use in which system and expand their freedom in selecting their software (best-of-breed principle). In this way, they can also easily link new systems with their existing ones and remain flexible and independent in the long term.