In a world marked by exponential growth and digital transformation, companies are in need of intelligent software solutions that enable them to bridge the gap between data science, IT teams, and lines-of-business across the entire enterprise.
And, with its robust automation capabilities and cutting-edge algorithms, SAP Machine Learning empowers organizations to extract valuable insights, automate business processes, and make data-driven decisions as business intelligence needs grow and change over time.
This article will take a deeper dive into the world of machine learning, offer valuable insights into the key capabilities and advantages of machine learning in SAP, and help you understand where our team of SAP consultants can come in to help.
Read on to learn more!
What is Machine Learning?
Machine learning is a subset of artificial intelligence (AI) focused on teaching computer systems to learn from input data and improve functionality through experience rather than explicit programming.
Machine learning applications are designed to leverage patterns and trends in company data to improve the accuracy of predictive algorithms, automate tasks, and promote better decision making across the entire organization.
How Does Machine Learning Work?
Machine learning algorithms allow AI tools to process both internal and external data sources and leverage deep learning functionality to build advanced neural networks that simplify pattern recognition, analysis, and learning across their core business applications.
With various different types of machine learning models, including supervised models, unsupervised models, and semi-supervised models, companies are enabled to leverage advanced algorithms and techniques to classify data sets, find patterns, and predict outcomes.
ML algorithms can be used by themselves or combined to improve the accuracy and efficiency of core business processes, especially when complex or unpredictable data is involved. Let’s take a closer look at the key phases involved in building and maintaining functional machine learning models…
- Input data, including information from current and historical data sources
- Develop a model for machine learning capabilities
- Train (and retrain) ML models for improved process automation and efficiency
- Analyze and test each model to ensure proper functionality
- Launch defined machine learning models into the production environment
Main Types of Learning Within SAP Applications
SAP Machine Learning encompasses a wide range of techniques and algorithms that enable intelligent automation and data-driven decision-making within the SAP ecosystem.
Each of these learning models plays a crucial role in empowering SAP systems to extract insights, uncover patterns, and optimize processes, ultimately driving efficiency and innovation across solutions. Here are the main types of machine learning in SAP…
Supervised Learning
An iterative learning process lies at the core of supervised machine learning algorithms, driving advancements in a wide range of applications, from image and speech recognition to fraud detection and everything in between.
In supervised learning models, the machine is taught by example, allowing them to make predictions or decisions based on the patterns and relationships observed in the training data. With the supervised algorithm, the system compiles training data over time to determine similarities and differences across sources, and eventually predict answers on its own.
The process of teaching machines in supervised learning involves the following steps:
- Preparation of training data
- Selection of machine learning models
- Training for selected MI algorithms
- Prediction of data inputs and customer behavior patterns
- Evaluation and iteration of the trained model
Semi-Supervised Learning
Because data isn’t always labeled and structured before it is input into a system, semi-supervised learning algorithms offer a more flexible solution for business users to input, manage, and analyze large amounts of raw, unstructured data across the enterprise.
With this model, companies can input small amounts of labeled data over time to improve unlabeled data sets and improve the speed and accuracy of management and learning processes for current and past data sources. This allows the machine to analyze each SAP data set and apply correlative properties to the unlabeled data.
Unsupervised Learning
In unsupervised learning algorithms, the machine analyzes unstructured and unlabeled input data and leverages accessible, relevant data to identify correlations and trends, all without a pre-defined answer key. This allows users to leverage business intelligence, intuitive tools, and machine experience to group different data together more efficiently.
As machines “experience” (i.e., input and access larger amounts of data) more over time, their ability to categorize data and identify relevant information improves, making it easier to leverage SAP Data Intelligence and Machine Learning functionality.
Reinforcement Learning
While the reinforcement model doesn’t provide an answer key, it does allow machines to input actionable rules, actions, and potential end states, enabling them to learn by both experience and “reward” over time. A “reward” in reinforcement learning algorithms refers to a numeric value that is programmed into the algorithm as something for the system to collect.
4 SAP Applications that Use Machine Learning Capabilities
Within the SAP ecosystem, various different applications harness the power of machine learning to unlock valuable insights, streamline processes, and drive intelligent automation.
The SAP applications that leverage integrated machine learning capabilities empower organizations to gain a competitive edge by enhancing operational efficiency, enabling predictive analytics, and facilitating data-driven decision-making.
From intelligent chatbots and recommendation systems to demand forecasting and anomaly detection, these applications demonstrate the versatility and wide-ranging impact of SAP machine learning across industries, paving the way for advanced innovation and optimization.
1) SAP Leonardo
SAP Leonardo is a digital innovation infrastructure designed to integrate existing services and technologies into a single system, making it easier for companies to scale their business operations to keep up with growth and store data in a comprehensive repository.
With machine learning capabilities, companies can integrate their SAP Leonardo solution with any on-premise or cloud-based applications and help data scientists (or non-data scientists) train, adapt, and retrain pre-trained routines across their SAP data landscape.
2) SAP CoPilot
SAP CoPilot is a digital assistant tool and bot integration hub that helps users personalize their own experiences across the SAP landscape and leverage intelligently-structured data to improve business results over time.
It uses machine learning algorithms and connectivity to the SAP HANA Cloud to simplify customer-facing processes and allow users to focus on more strategic tasks.
3) SAP Predictive Analytics
With SAP Predictive Analytics, companies can analyze both historical and external data more efficiently, find patterns that offer better insights into customer behavior, and predict system maintenance to reduce the amount of downtime in the long run.
This solution uses machine learning functionality to analyze correlations between machine and operational data and create predictive models to identify otherwise hidden relationships between each data source across the system.
4) SAP Intelligent RPA
SAP Intelligent Robotic Process Automation (RPA) leverages software bots to imitate human action and interaction, including the replacement of manual clicks, offering end-user process recommendations, and reading text-rich communications.
And, with machine learning tools, companies can replicate routine activities across the SAP system to improve digital transformation efforts and accelerate time-to-value for customers.
How Can We Help?
Whether you’re brand new to the SAP Analytics Cloud or you’ve been working in the SAP ecosystem for years, our team at Surety Systems has the knowledge, skills, and experience needed to lead you to success through any implementation, integration, or upgrade project.
Our team of senior-level, US-based SAP consultants has what it takes to prepare your internal team for new machine learning operations, automate repetitive tasks, maximize the potential of your intuitive SAP products, and improve the overall customer experience.
Your technology. Your priorities. Our expertise. That’s the name of the game at Surety.
Getting Started with Our Team
Interested in learning where our team of expert SAP consultants can fit in your organization?
Ready to start leveraging machine learning capabilities across your SAP solutions, but don’t just where to begin or who to turn to for help?
Contact us today for more information about our SAP consulting services!
