The time has come to unlock the full potential of your (SAP) data
Transform Insights into Action with Smarter Data Management
In the fast-paced world of modern business, companies must continually innovate and adapt to stay ahead of the competition. Digital transformation has shifted from a strategic advantage to an essential requirement for success. Companies must boost operational efficiency, enhance customer experiences, and respond to market changes with agility.
Economics and market volatility demand for flexible solutions
To keep up with this volatility, decision-makers need up-to-date, and often real-time, insights delivered in a clear, easily consumable format. While traditional BI -mainly focused on reporting historical data and comparing budgets and plans- remains relevant, it no longer meets all requirements, particularly where quick actions are essential.
As a result, analytics is shifting from traditional BI, which largely examines the past, toward predictive and even prescriptive analytics that leverage AI and GenAI for automated, actionable insights.
Self-service analytics is no longer a new trend, but it remains essential as business users demand greater flexibility, speed, and analytical tools as well as actual and consumable data to act on insights. Yet, it often remains an unmet or inconsistently addressed need, limiting users’ ability to interact with data freely.
Moreover, use cases beyond finance, such as supply chain optimization and 360-degree customer view, are becoming critical for maintaining competitive advantage. Also emerging concepts like data products are opening up new market and monetization opportunities that every business should explore.
But all these initiatives rely on a robust, trusted data foundation—a task that consumes roughly 80% of BI and analytics project efforts.
Unlocking new market opportunities drives additional requirements on data (management)
Besides classic data integration and management tasks all above mentioned trends and use cases require new concepts and technologies to provide businesses with needed insights. To only name a few examples:
- Rising amounts of data, for instance, is not a net new trend and is already addressed by different software solutions and data architecture concepts. However, rather still unsolved is combination of structured data with text (processing) or formats such as videos or pictures. Often, use cases involving semi-structured and unstructured data are solved as standalone scenarios not really integrated into an overall data strategy or architecture, and therefore available for selected decision makers only.
- Moreover, faster decisions mostly require more up-to-date information. Business users have often demanded real-time data but today more than ever, esp. in operational use cases. Of course, old architectures struggle to meet this requirement, but also modern architectures often do not solve this problem appropriately and especially cost-effectively.
- Use cases, such as data products, data monetization or embedding, put additional pressure on overall scalability and multi-tenancy of modern data architectures.
- Finally, combing back to business users, those still require adequate and consumable view on data which is often spread across multiple products and still require lot manual search and ingestion to find the right data which fulfils the needs.
Modernization of (SAP) systems is inevitable
Demands and opportunities are high, but the reality for many companies, including buyers of SAP software, looks quite different: legacy software and inefficient business processes, complex data models, and inappropriate organizational structures have resulted in long to-do lists for CEOs and CIOs. Therefore, a large number of SAP customers are now undertaking modernization initiatives to upgrade their operational systems, such as ERP, and take these projects as a chance to rethink and optimize their data and analytics environments, ensuring employees have timely access to the data they need for informed decision-making. Optimizing SAP data integration and management requires initiatives across the entire data chain—from operational systems to data & analytics—making also cross-departmental collaboration crucial for success.
Optimization of operational and analytical systems require besides process optimization and data movement from A to B, well thought-out concepts for the time of the journey and beyond. That means, that such huge undertakings are done with a big bang. In fact, they are implemented within months or even years depending on the size and dimensions of the system landscape. A thoroughly planning is then key to success: Customers should certainly concentrate on a future vision and its execution, however, the road to accomplishment and how its executed and can be supported by software should be designed as well.
Moreover, competitors and decision makers do not wait during this period. That said, although the companies are caught in modernization projects, they still have to scan for market opportunities and work on improvement of efficiency and productivity to stay competitive.
Modernization of SAP landscape starts with data
Therefore, it’s not surprising that these endeavors lead to large multiple projects, each demanding careful planning and management. As part of these strategic initiatives also cloud should be considered and discussed. Moreover, modern data management and pipelining products help companies accelerating and automating data provisioning, integration and orchestration tasks to meet data-related challenges and provide business users with requested data. These products also help customers with common challenges SAP users typically face when it comes to integration or interaction with SAP data such as:
Access of SAP data and metadata
- Some SAP systems have complex structures and interfaces for data access and ingestion. Customers should evaluate carefully which interfaces can be used and which data as well as metadata is required and how can it be accessed as well as processed.
- Customers should scan the market for pre-defined solutions which help them executing this complicated task and accelerate its execution.
Combination of data formats as well as SAP and non-SAP data sources to build up a trusted foundation
- Many SAP customers not only face same challenges that all companies have with arising trending topics and new data formats but also have rather traditional challenges of data combination.
- As some SAP systems are not easy to “read”, blending of SAP and non-SAP data typically becomes a challenge as well. Also, here not only appropriate software, but also architectural concepts are key to fulfil individual requirements.
- Real-time data availability is crucial for businesses that need timely insights for rapid decision-making, like detecting trends or responding to operational changes:
- Many use cases require real-time data and therefore data ingestion.
- Especially, traditionally built system architectures often struggle to meet this requirement. When modernizing a system landscape companies should examine whether these requirements are in place and where real-time data ingestion can provide them with benefits.
- Today, the data & analytics market can provide both software and concepts to process data in real-time if needed.
Automation is the next logical step
- Automation is not only discussed in the business departments to free up the hands of power users and allow them to focus on higher-value tasks but also for data engineers and developers which can provide increased business user support through won time
- Moreover, with streamlined, automated data movement, teams access insights faster, enabling quicker time-to-market for data-driven products and decisions, a competitive edge for businesses in fast-paced industries.
These projects present valuable opportunities to streamline business processes, establish forward-looking data strategies and architectures as well as company-wide data cultures. Businesses should plan accordingly, search for expertise and modern software solutions which support them during this transformation journey.
Author
Larissa Baier is Senior Analyst Data & Analytics at BARC. She specializes in front ends for dashboarding, reporting, analysis, planning, data discovery and in self-service BI and analytics. As part of the BARC Advisory practice, Larissa supports companies in their software selection processes and in strategic decisions regarding their BI front end portfolio including architecture and usage scenarios. She is also an expert in landscapes and requirements of SAP customers. In the area of research, she is responsible for the BARC Score product line and acts as product manager for “BARC Score Enterprise BI & Analytics Platforms”.
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