Introduction
SAP Technical upgrades are renowned among SAP users for their time-consuming nature and higher costs compared to upgrades in other systems. However, conveying these complexities to non-SAP consultants, who have experienced faster upgrades elsewhere, can be a challenging endeavor.
This raises important questions - Can we transform SAP upgrades into self-serving experiences for our customers, regardless of Rise? Is it feasible for Gen AI-trained bots to assume control of upgrades in the near future? And ultimately, will human intervention remain necessary for upgrades in the years to come?
The traditional approach to SAP upgrades has heavily relied on human expertise and meticulous planning due to the intricacies of the system. Nevertheless, advancements in AI and automation offer the potential for self-serving SAP upgrades. These AI-driven bots can automate various aspects of the upgrade journey, including system analysis, upgrade impact assessment, testing, and even decision-making.
While automating upgrades is already happening around the world, we still have customers where the process is still very manual. I like to share some of my thoughts on areas of hyper automation that we can do now currently and expand in the future.
Paving the Way for Self-Serving SAP Upgrades
Applying Notes with Precision: Traditionally, applying SAP notes during upgrades has been a time-consuming and error-prone process. However, AI-powered note tools can change this aspect. For example, the SAP Note Assistant[Ameca/Pepper/Sophia/Nadine/Joule 3.0 Humanoid?], powered by AI algorithms, can automate the identification and application and testing and deployment of relevant notes. This streamlines the process, reduces manual effort, and minimizes the risk of errors. Additionally, we can also ensure the accurate implementation of critical security notes, fortifying the SAP system against potential vulnerabilities.
Intelligent OCR Solution for Integration Existing and Upgrade Documentation:One significant side effect of SAP upgrades is that customers often overlook the importance of maintaining accurate and up-to-date documentation, which is crucial in mitigating future legacy debts. For instance, a global manufacturing company implemented an AI-driven documentation tool during their SAP upgrade project. The tool analyzed system logs, identified key changes made during the upgrade, and automatically generated detailed documentation capturing the modifications, configurations, and customizations. Moreover, AI can contribute to effective knowledge management by analyzing and categorizing vast amounts of upgrade-related information. This analysis makes the information easily accessible for future reference, troubleshooting, and overall maintenance.
Risk based Enhancement Testing: It is vital to test the critical bespoke enhancements during the upgrades to ensure that they are working as expected. AI algorithms can identify the most used enhancements, analyze the ABAP enhancement code and generate test cases automatically. Smart Shift Intelligent Automation is a great example of it. By understanding the code structure and logic, AI can identify potential test scenarios and generate comprehensive test data and cases, reducing the manual effort required for test case creation.We can then train the UIPath bots to interact with the ABAP environment, simulate user actions, and validate the expected results.
Automated Regression Tests : Validating system functionality through regression testing is crucial following upgrades. AI can assist in creating regression packs by intelligently selecting test cases based on the impact analysis of upgrade changes and usage patterns. Once Tricentis Live Compare identifies what to test, it tells advanced tool Tosca to prioritize test cases and optimize test coverage and minimize defects. By automating regression testing, a prominent bottling plant successfully completed their upgrade within a shorter timeframe, minimizing disruptions to their business operations.
Natural Language Processing for Conversational User FAQ: During SAP upgrades, user support is crucial to ensure a smooth transition. AI-powered natural language processing (NLP) tools can analyze user queries and provide automated responses, troubleshooting guidance, and self-help resources. This reduces the burden on support teams, improves response times, and enhances the overall user experience during the upgrade.
Strengthening Security Measures: Security breaches pose a significant risk during SAP upgrades. AI Upgrade trained bot can analyze system vulnerabilities, detect potential security threats, and recommend appropriate security measures. For example, AI-powered security solutions like SAP Enterprise Threat Detection can continuously monitor system logs, detect anomalies, and proactively identify potential security breaches.
Performance and Penetration Testing: Optimizing system performance is crucial during SAP upgrades. AI can simulate user loads, analyze system behavior, and identify performance bottlenecks. For instance, tools like SAP LoadRunner by Micro Focus leverage AI algorithms to generate realistic user load scenarios and measure system response times.
Automated Post-Cutover Checks: SAP iRPA or UIPath bots and Active Control can be combined to perform automated checks after the cutover to ensure that critical processes, data, configurations, and integrations are functioning as expected.
Automating Data Archiving:Although many customers invest significant time and resources in system upgrades, data archiving often does not receive adequate attention. It is crucial to recognize that upgrading and decommissioning data are equally important aspects of the process.
Through the utilization of AI algorithms, organizations can effectively identify and classify data for archiving purposes, adhering to predefined rules and criteria. AI also plays a crucial role in data deduplication, identifying redundant or obsolete data that can be safely archived. Furthermore, AI-powered analytics provide valuable insights into data usage patterns, enabling organizations to prioritize archiving based on data relevance and frequency of access. Notable examples of tools that exemplify these capabilities include SNP Outboard ERP Archiving and Proceed Group Archiving.
In summary, while there are already some promising products available in these areas, there are still a significant number of customers who continue to rely on manual intrinsic upgrades. This raises the question of whether we can reshape the future of upgrades. I would be interested to know if you are currently utilizing any additional standard tools or solutions . Your insights and perspectives on this matter would be greatly appreciated as we explore new ideas and possibilities for the future of SAP upgrades.
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