BARC Spotlight EPM on Your Data Platform
BARC Spotlight EPM on Your Data Platform: Unlocking Flexibility & AI Dokumentum letöltéseBARC Spotlight
EPM on Your Data Platform:
Unlocking Flexibility & AI
Authors: Robert Tischler, Kelley Lynn Kassa
Publication: December 2025
Provided by
EPM on Your Data Platform:
Unlocking Flexibility & AI
Authors: Robert Tischler, Kelley Lynn Kassa
Publication: December 2025
Provided by
2BARC Spotlight: EPM on Your Data Platform: Unlocking Flexibility & AI
Table of Contents
Why EPM data management has reached a breaking point ....................................................................................... 3
The cost of data duplication in planning databases ....................................................................................................... 5
Formal structures constrain AI capabilities and drive spreadsheet sprawl ............................................................ 6
Storing planning data where analytics already lives ........................................................................................................7
Shared data foundations reduce effort and accelerate action ....................................................................................7
Success requires performance, usability, and organizational commitment .......................................................... 8
About BARC..................................................................................................................................................................................... 9
About SAP .......................................................................................................................................................................................10
Table of Contents
Why EPM data management has reached a breaking point ....................................................................................... 3
The cost of data duplication in planning databases ....................................................................................................... 5
Formal structures constrain AI capabilities and drive spreadsheet sprawl ............................................................ 6
Storing planning data where analytics already lives ........................................................................................................7
Shared data foundations reduce effort and accelerate action ....................................................................................7
Success requires performance, usability, and organizational commitment .......................................................... 8
About BARC..................................................................................................................................................................................... 9
About SAP .......................................................................................................................................................................................10
3BARC Spotlight: EPM on Your Data Platform: Unlocking Flexibility & AI
Why EPM data management has reached a
breaking point
Enterprise performance management (EPM) evolved out of the basic use of spreadsheets for financial
planning and budgeting. While spreadsheets are still widely used for planning, larger and/or more so-
phisticated organizations have adopted specialized software for these purposes. The promise of EPM is
to extend the knowledge of and discipline around “the numbers” beyond the purview of finance and
into other departments across the enterprise.
Data provisioning is the process of preparing, integrating, and delivering data in the right format, at the
right time, to the users and systems for corporate planning, reporting, analytics, and more. Data provi-
sioning is a critical component to successful EPM implementations. However, it often feels like an uphill
battle – sometimes up a very steep one. BARC research consistently confirms this fact.1 Companies need
master data to define planning hierarchies and actuals to have orientation for plans. Planning figures
must also be accessible by reporting software to communicate results or to trigger further actions. But
often a seamless flow cannot be taken for granted.
Twenty years ago, vendors promised to reduce data management workload for business users. However,
data volumes and planning scope have exploded instead. Two underestimated driving forces cause
much of the pain we feel today.
• Today, data is captured at astronomical volumes, and the number of internal source systems
delivering it has exploded – and that’s not even considering external data.
• The other factor is pretty well summarized by this: “Appetite comes with eating.” If you have
better software that increases your efficiency, you end up doing more “stuff” than before. You
plan more areas (subplans), run more simulations and forecasts2, and deliver more extensive
reports to your management.
We have reached a point where we can no longer follow the current trajectory. Many struggle to inte-
grate all relevant data into a dedicated planning system. The three main drivers further reinforce the
pressure exerted.
• Companies are moving from doing predominantly financial planning (FP&A) to widening their
scope to what is called extended planning (xP&A) or integrated planning. This requires lever-
aging data from more sources beyond core financial and cost accounting systems, databases,
and enterprise resource planning (ERP) solutions. It also magnifies the challenges around data
provisioning, quality, and management.
• The second trend that requires organizations to extend the capabilities of their planning systems
is artificial intelligence (AI). Automated forecasts, predictions and simulations use machine
learning (ML), also known as “traditional AI,” which requires large amounts of data. The aggre-
gated values often used in planning lack the necessary depth and signals. AI/ML relies on de-
tailed data in wide tables, which is not the type of data assets that a typical planning system can
easily process.
1 49% of companies are planning to invest in “Data management and data integration” within the next 12 months – ranking it number
2 among all software investment priorities. Its importance to companies with heterogeneous data landscapes has increased noticeably.
“The CFO Agenda 2025”, BARC 2025
2 49 percent have increased the frequency of their planning and forecasting cycles to achieve greater planning resilience. “Resilient
Planning in Volatile Markets”, BARC 2025
Why EPM data management has reached a
breaking point
Enterprise performance management (EPM) evolved out of the basic use of spreadsheets for financial
planning and budgeting. While spreadsheets are still widely used for planning, larger and/or more so-
phisticated organizations have adopted specialized software for these purposes. The promise of EPM is
to extend the knowledge of and discipline around “the numbers” beyond the purview of finance and
into other departments across the enterprise.
Data provisioning is the process of preparing, integrating, and delivering data in the right format, at the
right time, to the users and systems for corporate planning, reporting, analytics, and more. Data provi-
sioning is a critical component to successful EPM implementations. However, it often feels like an uphill
battle – sometimes up a very steep one. BARC research consistently confirms this fact.1 Companies need
master data to define planning hierarchies and actuals to have orientation for plans. Planning figures
must also be accessible by reporting software to communicate results or to trigger further actions. But
often a seamless flow cannot be taken for granted.
Twenty years ago, vendors promised to reduce data management workload for business users. However,
data volumes and planning scope have exploded instead. Two underestimated driving forces cause
much of the pain we feel today.
• Today, data is captured at astronomical volumes, and the number of internal source systems
delivering it has exploded – and that’s not even considering external data.
• The other factor is pretty well summarized by this: “Appetite comes with eating.” If you have
better software that increases your efficiency, you end up doing more “stuff” than before. You
plan more areas (subplans), run more simulations and forecasts2, and deliver more extensive
reports to your management.
We have reached a point where we can no longer follow the current trajectory. Many struggle to inte-
grate all relevant data into a dedicated planning system. The three main drivers further reinforce the
pressure exerted.
• Companies are moving from doing predominantly financial planning (FP&A) to widening their
scope to what is called extended planning (xP&A) or integrated planning. This requires lever-
aging data from more sources beyond core financial and cost accounting systems, databases,
and enterprise resource planning (ERP) solutions. It also magnifies the challenges around data
provisioning, quality, and management.
• The second trend that requires organizations to extend the capabilities of their planning systems
is artificial intelligence (AI). Automated forecasts, predictions and simulations use machine
learning (ML), also known as “traditional AI,” which requires large amounts of data. The aggre-
gated values often used in planning lack the necessary depth and signals. AI/ML relies on de-
tailed data in wide tables, which is not the type of data assets that a typical planning system can
easily process.
1 49% of companies are planning to invest in “Data management and data integration” within the next 12 months – ranking it number
2 among all software investment priorities. Its importance to companies with heterogeneous data landscapes has increased noticeably.
“The CFO Agenda 2025”, BARC 2025
2 49 percent have increased the frequency of their planning and forecasting cycles to achieve greater planning resilience. “Resilient
Planning in Volatile Markets”, BARC 2025