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Insights from the SAP Community: Process Automation Strategies for 2025

Chris Hall
Precisely

With the 2027 deadline for SAP S/4HANA migrations fast approaching, organizations are accelerating their transition plans. According to recent research, 50% of organizations were planning to have migrated or started the migration to S/4HANA by the end of 2024, while an additional 30% plan to make the change in the next two years.

For organizations that intend to remain on SAP ECC in the near-term, the focus has shifted to improving operational efficiencies and meeting demands for faster cycle times. These efforts are essential to maintaining competitiveness while preparing for eventual modernization.

No matter where an organization is in its SAP journey, one theme is clear: The automation of SAP processes is crucial. In order to maintain agility, accelerate the speed of business, and build data integrity, organizations require robust process automation, fueled by accurate, consistent, and contextual data, to drive successful outcomes. Emerging best practices and challenges related to SAP automation will reveal key strategies companies are adopting to optimize their operations.

SAP S/4HANA Migrations Gain Momentum, Despite Ongoing Challenges

In less than three years, the S/4HANA deadline will have arrived and as a result, many organizations are moving forward with plans to start their migration journeys now, if they haven't done so already.

Transitioning from legacy SAP ERP systems to S/4HANA is a notoriously complex process. Oftentimes it requires both legacy and new systems to work in tandem and presents significant data management challenges along the way. The companies getting it right are relying on process automation to accelerate complex SAP business processes.

Process automation solutions are pivotal in expediting SAP migrations by streamlining data transformation and integration tasks. Automated processes enable organizations to create new master data and transaction data in SAP systems, update mass amounts of data throughout the SAP landscape using Excel and perform data migrations from existing systems to S/4HANA. As businesses start with pre-migration assessment and implementation plans, incorporating automation allows for the adoption of a more holistic approach to process redesign, leading to optimized business processes and a smoother transition to S/4HANA.

However, due to data, process, and organizational complexities, the move from legacy SAP ERP systems is often a multi-year process that requires detailed planning and analyses of its impact on business operations. As a result, businesses frequently operate both legacy and new systems in parallel as they work to avoid disruptions during the transition, but this approach can oftentimes compound the complexity of the migration to S/4HANA. While the transition may be difficult at times, the business benefits of this transition — including cloud deployment options, real-time reporting in SAP and a modern user interface — far outweigh the migration challenges

Rise in Automation Adoption Comes with Challenges

Automation is a critical component of any digital transformation strategy, but the implementation of automated solutions hasn't always been quickly adopted. This is particularly true when it comes to complex, and data intensive, SAP-centric business processes which create barriers to success. However, as more organizations realize the benefits of automation, adoption is increasing. In fact, research shows a 15% increase in the use of automation for migrations and digital transformation projects — from 43% in 2023 to 58% in 2024 — indicating that companies considering automation today are likely to begin adopting it soon.

Over the past year, there has been growth in companies maturing their levels of automation adoption, leveraging a mix of manual and automated processes to streamline operations, reduce reliance on manual intervention, and effectively manage high volumes of data. However, a high level of automation adoption remains difficult to achieve. This is due to three factors currently influencing the market:

  • First, the impact of companies migrating to S/4HANA may slow improvements in automation growth and maturity. As organizations complete the migration process, they rationalize the potential impacts of this move on business processes.
  • Next, digital transformation teams recognize that many simple or infrequent processes are more efficiently managed when done manually.
  • Finally, growing recognition that success metrics based on business outcome value for an automation activity or process will vary from use case to use case from an organizational standpoint.

Barriers such as large data volumes and the intricacies of business processes take time to overcome. Many companies continue to cite integration with existing business processes as the biggest challenge when implementing process automation. These challenges are often exacerbated when companies take a case-by-case approach to automation, as this can increase overall complexity.

Scaling Automation Through Citizen Developers and Trusted Data

To navigate these complexities and fully realize the benefits, companies must recognize the value of citizen developers. They play a crucial role in the automation initiative process, leveraging the growing adoption of no-code/low-code platforms that assist business users at every level. Citizen developers also expand the pool of experts who can deploy automation within a company, and a majority of companies believe that these individuals are a crucial part of their organizations. As the use of low-code/no-code platforms grows, citizen developers will continue to drive the evolution of automation.

Despite its challenges, prioritizing best practices in SAP process automation ensures that a company's data is utilized to its full potential, improving business agility and accelerating the organization overall. To achieve this, companies must place automation at the core of their data integrity efforts. Data integrity is key — accurate, consistent, and contextualized data significantly ensures a smooth automation process. For example, ensuring customer records and data are error-free builds trust in the data, enabling the organization to make sound business decisions across all departments.

Automation is becoming a necessity for companies as they embrace digital transformation and the tools required to achieve it. SAP process automation is central to streamlining operational efficiencies. To ensure success, companies must effectively integrate data integrity solutions, as automation cannot succeed without trusted data. The inclusion of no-code/low-code automation tools also supports this goal by enabling broader impacts across the organization. While the automation process is complex, its outcomes — enhanced efficiencies, agility, and greater ROI — are invaluable for driving long-term success.

Chris Hall is Chief Product Officer at Precisely

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

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For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

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Insights from the SAP Community: Process Automation Strategies for 2025

Chris Hall
Precisely

With the 2027 deadline for SAP S/4HANA migrations fast approaching, organizations are accelerating their transition plans. According to recent research, 50% of organizations were planning to have migrated or started the migration to S/4HANA by the end of 2024, while an additional 30% plan to make the change in the next two years.

For organizations that intend to remain on SAP ECC in the near-term, the focus has shifted to improving operational efficiencies and meeting demands for faster cycle times. These efforts are essential to maintaining competitiveness while preparing for eventual modernization.

No matter where an organization is in its SAP journey, one theme is clear: The automation of SAP processes is crucial. In order to maintain agility, accelerate the speed of business, and build data integrity, organizations require robust process automation, fueled by accurate, consistent, and contextual data, to drive successful outcomes. Emerging best practices and challenges related to SAP automation will reveal key strategies companies are adopting to optimize their operations.

SAP S/4HANA Migrations Gain Momentum, Despite Ongoing Challenges

In less than three years, the S/4HANA deadline will have arrived and as a result, many organizations are moving forward with plans to start their migration journeys now, if they haven't done so already.

Transitioning from legacy SAP ERP systems to S/4HANA is a notoriously complex process. Oftentimes it requires both legacy and new systems to work in tandem and presents significant data management challenges along the way. The companies getting it right are relying on process automation to accelerate complex SAP business processes.

Process automation solutions are pivotal in expediting SAP migrations by streamlining data transformation and integration tasks. Automated processes enable organizations to create new master data and transaction data in SAP systems, update mass amounts of data throughout the SAP landscape using Excel and perform data migrations from existing systems to S/4HANA. As businesses start with pre-migration assessment and implementation plans, incorporating automation allows for the adoption of a more holistic approach to process redesign, leading to optimized business processes and a smoother transition to S/4HANA.

However, due to data, process, and organizational complexities, the move from legacy SAP ERP systems is often a multi-year process that requires detailed planning and analyses of its impact on business operations. As a result, businesses frequently operate both legacy and new systems in parallel as they work to avoid disruptions during the transition, but this approach can oftentimes compound the complexity of the migration to S/4HANA. While the transition may be difficult at times, the business benefits of this transition — including cloud deployment options, real-time reporting in SAP and a modern user interface — far outweigh the migration challenges

Rise in Automation Adoption Comes with Challenges

Automation is a critical component of any digital transformation strategy, but the implementation of automated solutions hasn't always been quickly adopted. This is particularly true when it comes to complex, and data intensive, SAP-centric business processes which create barriers to success. However, as more organizations realize the benefits of automation, adoption is increasing. In fact, research shows a 15% increase in the use of automation for migrations and digital transformation projects — from 43% in 2023 to 58% in 2024 — indicating that companies considering automation today are likely to begin adopting it soon.

Over the past year, there has been growth in companies maturing their levels of automation adoption, leveraging a mix of manual and automated processes to streamline operations, reduce reliance on manual intervention, and effectively manage high volumes of data. However, a high level of automation adoption remains difficult to achieve. This is due to three factors currently influencing the market:

  • First, the impact of companies migrating to S/4HANA may slow improvements in automation growth and maturity. As organizations complete the migration process, they rationalize the potential impacts of this move on business processes.
  • Next, digital transformation teams recognize that many simple or infrequent processes are more efficiently managed when done manually.
  • Finally, growing recognition that success metrics based on business outcome value for an automation activity or process will vary from use case to use case from an organizational standpoint.

Barriers such as large data volumes and the intricacies of business processes take time to overcome. Many companies continue to cite integration with existing business processes as the biggest challenge when implementing process automation. These challenges are often exacerbated when companies take a case-by-case approach to automation, as this can increase overall complexity.

Scaling Automation Through Citizen Developers and Trusted Data

To navigate these complexities and fully realize the benefits, companies must recognize the value of citizen developers. They play a crucial role in the automation initiative process, leveraging the growing adoption of no-code/low-code platforms that assist business users at every level. Citizen developers also expand the pool of experts who can deploy automation within a company, and a majority of companies believe that these individuals are a crucial part of their organizations. As the use of low-code/no-code platforms grows, citizen developers will continue to drive the evolution of automation.

Despite its challenges, prioritizing best practices in SAP process automation ensures that a company's data is utilized to its full potential, improving business agility and accelerating the organization overall. To achieve this, companies must place automation at the core of their data integrity efforts. Data integrity is key — accurate, consistent, and contextualized data significantly ensures a smooth automation process. For example, ensuring customer records and data are error-free builds trust in the data, enabling the organization to make sound business decisions across all departments.

Automation is becoming a necessity for companies as they embrace digital transformation and the tools required to achieve it. SAP process automation is central to streamlining operational efficiencies. To ensure success, companies must effectively integrate data integrity solutions, as automation cannot succeed without trusted data. The inclusion of no-code/low-code automation tools also supports this goal by enabling broader impacts across the organization. While the automation process is complex, its outcomes — enhanced efficiencies, agility, and greater ROI — are invaluable for driving long-term success.

Chris Hall is Chief Product Officer at Precisely

Hot Topics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...