November 7, 2023
Predictive analytics is a powerful business tool. Backed by the SAP platform—a standalone enterprise resource planning (ERP) system enabled by AI-SAP integrations—SAP analytics can deliver just about anything. This ranges from modeling consumer behaviors and generating insights into cash flow and staffing levels to assessing risk and managing supply chain logistics.
An emerging set of best practices is helping companies extract maximum value from AI- and SAP-powered predictive analytics.
In late 2022, the Silicon Valley-based tech developer OpenAI publicly released its landmark ChatGPT tool, to global acclaim. By taking generative AI to the next level, ChatGPT quickly drew attention because of its potential to revolutionize the technological side of business management. Organizations have since sought to integrate ChatGPT and similar AI tools with SAP analytics.
Here, we’ll examine potential challenges—and possible solutions—in the realm of predictive analytics, as well as the competitive edge that this technology brings.
Predictive analytics draws on large volumes of historical data to make projections about potential future outcomes. Here, specific business applications include:
To extract maximum value from these applications, businesses also need to anticipate some challenges associated with integrating AI with SAP analytics. Key examples include:
Finally, keep in mind that predictive analytics algorithms are both highly specific and complex. As such, you need to choose the right algorithms for your intended application to generate optimal results.
ChatGPT and other generative AI tools rely on a technique known as natural language processing (NLP). NLP equips computerized tools with the ability to understand the details, nuances, and complexities of language and its context.
Human users can train AI on specific data, improving its ability to extract and refine targeted analytical insights. NLP has strong synergy with SAP analytics, given the dynamic robustness of the SAP platform and its application development potential. The two technologies complement each other. To illustrate, carefully trained AI harnesses a deep set of powerful and customized insights from SAP analytics data. Furthermore, it can also automate simple communication tasks, improving customer service and allowing businesses to make more productive use of their human resources.
Additional benefits of integrating AI with SAP analytics include:
With AI integration, SAP analytics can deliver actionable, data-driven insights in real time. ChatGPT’s advanced NLP features support the immediate generation and refinement of customized visualizations and reports. These capabilities can particularly help businesses with deep reliance on supply chains—as well as those dealing with shifting consumer needs and demand patterns.
AI has the ability to streamline data entry and reporting tasks, thus reducing the need for human labor and its associated costs.
Businesses often integrate AI with SAP analytics to assist proactive decision-making processes. It’s an area where AI can dramatically enhance the efficiency, accuracy, and depth of business forecasting, generated by intelligence-focused analytics.
A case study performed by the Eindhoven University of Technology on data from UWV, a major Dutch employee insurance agency, highlights the potential of AI-powered real-time analytics. The study logged usage patterns among various customer contact channels and analyzed the channels most often used by customers in specific situations—such as registering concerns or complaints.
This analysis aimed to identify ways in which businesses could address incoming customer queries without forcing them to switch to different channels. It involved heavy, detailed analyses of channel transition, including behavioral and demographic data, among other variables.
With the help of ChatGPT in analyzing data, the study identified ways to:
The results indicate the powerful potential of combining AI with SAP analytics to dramatically improve both operational efficiency and the customer experience.
Generative AI tools like ChatGPT can provide data and recommendations that enhance the accuracy of insights harvested from master data. For example, AI can quickly classify and organize data based on its defining attributes, enabling precise and targeted application of adjunct SAP analytics tools.
In addition, AI can extract data from documents almost instantaneously. This optimizes the routing and management of customer service tickets, reduces manual labor needs across multiple accounting processes, and minimizes processing errors. These features also improve the cost efficiency profile of AI-powered approaches to SAP analytics.
Organizations across a broad cross-section of industries already use the SAP HANA multi-model relational database tool to store, organize, and retrieve data. The next step is to integrate ChatGPT or other AI tools with SAP HANA.
Once businesses have identified a precise and carefully defined use case, they can then select an appropriate algorithm for the intended application. A case in point is regression algorithms, which excel at projecting continuous numeric values. There are also classification algorithms, which group data into pre-selected categories, and time-series algorithms that analyze historical data to forecast future values. Depending on your intended use case, one or more of these algorithm types may figure into your plans.
From there, you can refine your models to improve their depth and accuracy. This may require:
Generative AI tools like ChatGPT can yield powerful performance-boosting results when integrated with SAP analytics. This is where expert guidance can help you extract maximum value from your efforts and investment.
Approyo offers deep support to businesses seeking to integrate generative AI with SAP analytics to build competitive advantages. Clients can purchase an expertly authored ebook to learn more about the integration process, or contact Approyo to arrange a personalized consultation.
