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Embracing Automation Can Drive SAP Improvements

Ritu Dubey
Digitate

SAP is a tool for automating business processes. Managing SAP solutions, especially with the shift to the cloud-based S/4HANA platform, can be intricate. To explore the concerns of SAP users during operational transformations and automation, a survey was conducted in mid-2023 by Digitate and Americas' SAP Users' Group (ASUG) — the largest network of SAP customers, partners, and professionals in the US. The survey group consisted of 153 SAP users in North America across a range of industries, including consumer products, industrial manufacturing, machinery, and components (IM&C), chemicals, and utilities.

Highlighting the Key Challenges

Respondents to the survey identified a number of key challenges that their businesses faced when managing SAP. These included:

Time management: Businesses often spend long hours administering SAP solutions, causing decision-making delays and inefficiencies.

Expensive downtimes: Unplanned outages can be costly, affecting other business areas.

Resource redirection: Addressing downtimes often diverts essential resources, hindering productivity.

Customer frustration: Frequent downtimes can diminish brand trust and customer loyalty.

Reporting hurdles: Many find its complex reporting mechanisms challenging, struggling to derive valuable insights.

Data gaps: Missing or incomplete data can distort results.

Unexpected challenges: Unforeseen system glitches or external factors demand extra troubleshooting.

Manual monitoring: Multifaceted SAP components that customers have modified for their unique needs require manual monitoring.

Human errors: Mistakes can lead to system outages, disrupting operations.

Integration complexity: Connecting SAP to other systems can introduce operational glitches.

Application Downtime Blues

Diving deeper into the results revealed the major concern for respondents was downtime. An overwhelming 90% of the SAP users experienced unplanned SAP application downtime. Furthermore, two-thirds reported that they spent up to 25% of their daily time resolving these unpredictable issues.

While internal downtime impacts were experienced much more than external impacts, business user impacts due to SAP downtime were, unsurprisingly, the overriding concern for respondents. An alarming 69% of businesses reported business user impacts due to downtime, and 56% of those were operational impacts felt internally, while 39% of those surveyed reported a direct impact on customers. External downtime means loss of revenue (28% experienced loss or delay of revenue) and inconvenience for customers.

Integration challenges were identified as the top contributor to unplanned downtime. 40% of businesses cited this as a major problem, which is not surprising given that 60% of organizations use up to 20 tools to monitor different elements of the SAP system. Other significant reported causes of downtime include runtime issues (31%), change requests (25%), and configuration issues (22%)

Furthermore, businesses typically spend four to six hours fixing each downtime problem, leading to less time for other tasks, higher costs, and potential damage to the company's reputation and customer trust.


Operational KPIs and Ticket Resolution

Operational key performance indicators (KPIs) within enterprises are a trusted barometer of the efficiency of SAP operations. Resolving tickets in a timely manner are crucial for overall system health as they impact customer satisfaction, cost control and overall business success. The survey provided some important insights:

■ The KPI of resolving tickets without human intervention is still a distant goal for many, with only 41% reporting they often met it. The largest share of respondents said 10% or less of tickets are resolved automatically. 29% had no tickets resolved automatically.

■ Tickets take an average of three hours to resolve. Long resolution times can upset customers, as delays disrupt services.

■ Ticket requests have grown by 15% year-over-year. This growth indicates more complex SAP operations and can strain IT teams. More tickets can increase operational costs if teams need extra resources.

Leveraging SAP Automation Solutions

Leveraging SAP automation solutions represents uncertainty as almost half of respondents were unable to assess this at their organization. That said, when they were certain, the largest share (42%) responded that their organizations are not leveraging solutions as much as they could. Some of the reasons why organizations are struggling to leverage automation solutions effectively are lack of time and resources, having a plan but no action, and other priorities taking precedence, such as the focus on moving to S/4HANA. There's also a historic resistance to SAP automation solutions, for example, it is seen as too complex or is not yet trusted. Overall, more openness and efforts to adapt new technology, back-end support, and automation across systems are needed to realize benefits.

Automation Can Radically Improve SAP Operations

The survey highlights anticipation for automation to reduce manual processes, with 76% identifying it as crucial for improving SAP operations, and 34% ranking it as the top initiative. Data analytics/dashboard insights and supply chain optimization were also noted as essential technologies/initiatives. While over half recognized the need for automation, only 9% considered it a top priority.

Surprisingly, only 15% currently use artificial intelligence (AI) and machine learning (ML) and monitoring tools, with a third considering it in the future. Despite the momentum towards Generative AI, this remains a low percentage. Notably, 60% use up to 20 tools to monitor SAP systems, indicating a significant opportunity for organizations to enhance business agility and decision-making speed through automated monitoring and AI/ML integration.


So why the disconnect? Why should SAP automation take a back seat?

The survey emphasizes customer focus on automation and SAP S/4HANA. Some are eager to transition for new features, while others must migrate due to mandates.

Businesses see opportunities to enhance SAP operations through technology optimizations, addressing scale, speed, and performance challenges. In the evolving SAP landscape, having the right tools for automation refines operations, reduces human involvement, and minimizes errors, aligning with broader company goals.

Integrating AI/ML and automation into SAP operations drives digital transformation and efficiencies, aided by effective training and suitable tools. Specific tools designed for SAP management tackle challenges, enhancing efficiency, reliability, and agility in day-to-day operations. Offering a comprehensive approach to SAP management, whether it's managing intricate workflows, ensuring data integrity, or optimizing system performance, these tools are well-equipped to confront these challenges head-on, ultimately driving operational excellence.


Ritu Dubey is Global Head of New Business Sales and Market Development at Digitate

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Embracing Automation Can Drive SAP Improvements

Ritu Dubey
Digitate

SAP is a tool for automating business processes. Managing SAP solutions, especially with the shift to the cloud-based S/4HANA platform, can be intricate. To explore the concerns of SAP users during operational transformations and automation, a survey was conducted in mid-2023 by Digitate and Americas' SAP Users' Group (ASUG) — the largest network of SAP customers, partners, and professionals in the US. The survey group consisted of 153 SAP users in North America across a range of industries, including consumer products, industrial manufacturing, machinery, and components (IM&C), chemicals, and utilities.

Highlighting the Key Challenges

Respondents to the survey identified a number of key challenges that their businesses faced when managing SAP. These included:

Time management: Businesses often spend long hours administering SAP solutions, causing decision-making delays and inefficiencies.

Expensive downtimes: Unplanned outages can be costly, affecting other business areas.

Resource redirection: Addressing downtimes often diverts essential resources, hindering productivity.

Customer frustration: Frequent downtimes can diminish brand trust and customer loyalty.

Reporting hurdles: Many find its complex reporting mechanisms challenging, struggling to derive valuable insights.

Data gaps: Missing or incomplete data can distort results.

Unexpected challenges: Unforeseen system glitches or external factors demand extra troubleshooting.

Manual monitoring: Multifaceted SAP components that customers have modified for their unique needs require manual monitoring.

Human errors: Mistakes can lead to system outages, disrupting operations.

Integration complexity: Connecting SAP to other systems can introduce operational glitches.

Application Downtime Blues

Diving deeper into the results revealed the major concern for respondents was downtime. An overwhelming 90% of the SAP users experienced unplanned SAP application downtime. Furthermore, two-thirds reported that they spent up to 25% of their daily time resolving these unpredictable issues.

While internal downtime impacts were experienced much more than external impacts, business user impacts due to SAP downtime were, unsurprisingly, the overriding concern for respondents. An alarming 69% of businesses reported business user impacts due to downtime, and 56% of those were operational impacts felt internally, while 39% of those surveyed reported a direct impact on customers. External downtime means loss of revenue (28% experienced loss or delay of revenue) and inconvenience for customers.

Integration challenges were identified as the top contributor to unplanned downtime. 40% of businesses cited this as a major problem, which is not surprising given that 60% of organizations use up to 20 tools to monitor different elements of the SAP system. Other significant reported causes of downtime include runtime issues (31%), change requests (25%), and configuration issues (22%)

Furthermore, businesses typically spend four to six hours fixing each downtime problem, leading to less time for other tasks, higher costs, and potential damage to the company's reputation and customer trust.


Operational KPIs and Ticket Resolution

Operational key performance indicators (KPIs) within enterprises are a trusted barometer of the efficiency of SAP operations. Resolving tickets in a timely manner are crucial for overall system health as they impact customer satisfaction, cost control and overall business success. The survey provided some important insights:

■ The KPI of resolving tickets without human intervention is still a distant goal for many, with only 41% reporting they often met it. The largest share of respondents said 10% or less of tickets are resolved automatically. 29% had no tickets resolved automatically.

■ Tickets take an average of three hours to resolve. Long resolution times can upset customers, as delays disrupt services.

■ Ticket requests have grown by 15% year-over-year. This growth indicates more complex SAP operations and can strain IT teams. More tickets can increase operational costs if teams need extra resources.

Leveraging SAP Automation Solutions

Leveraging SAP automation solutions represents uncertainty as almost half of respondents were unable to assess this at their organization. That said, when they were certain, the largest share (42%) responded that their organizations are not leveraging solutions as much as they could. Some of the reasons why organizations are struggling to leverage automation solutions effectively are lack of time and resources, having a plan but no action, and other priorities taking precedence, such as the focus on moving to S/4HANA. There's also a historic resistance to SAP automation solutions, for example, it is seen as too complex or is not yet trusted. Overall, more openness and efforts to adapt new technology, back-end support, and automation across systems are needed to realize benefits.

Automation Can Radically Improve SAP Operations

The survey highlights anticipation for automation to reduce manual processes, with 76% identifying it as crucial for improving SAP operations, and 34% ranking it as the top initiative. Data analytics/dashboard insights and supply chain optimization were also noted as essential technologies/initiatives. While over half recognized the need for automation, only 9% considered it a top priority.

Surprisingly, only 15% currently use artificial intelligence (AI) and machine learning (ML) and monitoring tools, with a third considering it in the future. Despite the momentum towards Generative AI, this remains a low percentage. Notably, 60% use up to 20 tools to monitor SAP systems, indicating a significant opportunity for organizations to enhance business agility and decision-making speed through automated monitoring and AI/ML integration.


So why the disconnect? Why should SAP automation take a back seat?

The survey emphasizes customer focus on automation and SAP S/4HANA. Some are eager to transition for new features, while others must migrate due to mandates.

Businesses see opportunities to enhance SAP operations through technology optimizations, addressing scale, speed, and performance challenges. In the evolving SAP landscape, having the right tools for automation refines operations, reduces human involvement, and minimizes errors, aligning with broader company goals.

Integrating AI/ML and automation into SAP operations drives digital transformation and efficiencies, aided by effective training and suitable tools. Specific tools designed for SAP management tackle challenges, enhancing efficiency, reliability, and agility in day-to-day operations. Offering a comprehensive approach to SAP management, whether it's managing intricate workflows, ensuring data integrity, or optimizing system performance, these tools are well-equipped to confront these challenges head-on, ultimately driving operational excellence.


Ritu Dubey is Global Head of New Business Sales and Market Development at Digitate

Hot Topics

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Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

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Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

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