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Idriss Patel

EPM with IBM Planning Analytics: the GPS that steers your company’s performance

Discover how Enterprise Performance Management, combined with IBM Planning Analytics, turns planning into a navigation system capable of adjusting your trajectory in real time.

For a long time, finance teams navigated with a sextant, static maps and annual budgets frozen in Excel spreadsheets. In a volatile world, that is like travelling without a GPS. Enterprise Performance Management (EPM) acts as a navigation system for your company: it centralizes data, compares your current position with the plan and helps recalculate the route when conditions change. With IBM Planning Analytics, performance management becomes more continuous, more collaborative and better aligned with operational reality.

EPMAIPerformance Management
8 min
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Stephane Malho
Stephane Malho

Understanding REST APIs simply: from the web to SQL and JSON data

What is an API? What are REST, HTTP, CRUD, URLs, response statuses, and JSON used for? This progressive guide explains the fundamentals clearly, first for non-technical readers, then with concrete examples connected to SQL and modern data exchanges.

The word API appears everywhere: web applications, business software, ERP, CRM, cloud tools, automation, artificial intelligence, and data integration. Yet for many people, the concept still feels unclear. An API can seem technical, abstract, and reserved for developers. In reality, it can be understood very simply. An API is first and foremost a standardized entry point that allows one system to request or send information to another. More concretely, a company can expose certain data or services in a controlled way so that other applications or authorized users can access them to answer a specific need. In this article, we start with a broad and accessible view, then move step by step toward a more technical reading by connecting APIs to SQL queries, JSON responses, and the differences between relational and document-oriented models.

APIREST APIHTTP
10 min read
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David Boublil
David Boublil

EPM & AI: unlocking the hidden value of your data to support business decisions

Discover how artificial intelligence transforms EPM data into clear, actionable insights that create value for FP&A teams.

Companies have never had so much data. Yet decision-making often remains complex, slow, and uncertain. Why? Because data, no matter how reliable, is useless without context and interpretation. The rise of artificial intelligence in EPM environments is fundamentally changing this reality by turning raw data into strategic decision-making levers.

EPMIBM Planning AnalyticsFP&A
6 min
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David Boublil
David Boublil

Without context, data is nothing: from raw information to strategic decision-making

Financial data alone is not enough to make decisions. Discover why context is essential to interpret your indicators and manage performance effectively.

In finance departments, data is often seen as a source of truth. Yet an isolated figure has no meaning on its own. Without context, it can be misinterpreted and lead to poor decisions. Understanding performance requires placing each piece of data back into its economic, operational, and strategic environment.

FinanceDataFP&A
5 min
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David Boublil
David Boublil

Enrich your EPM: when external data adds depth to performance

Discover how to integrate external data into your EPM to improve analysis, anticipate risks, and make better decisions.

EPM systems help manage internal performance. But to truly understand that performance, it is essential to enrich it with external data. Market conditions, inflation, current events, or competition: this information provides the context needed to turn traditional reporting into a strategic tool.

EPMPlanning AnalyticsData Integration
6 min
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Idriss Patel

M&A and FP&A: why connecting an ERP to IBM Planning Analytics accelerates post-acquisition integration

In an M&A context, connecting an ERP to IBM Planning Analytics helps groups integrate new entities faster, harmonize financial data, track synergies, and secure group reporting without waiting for a heavy ERP transformation.

Mergers and acquisitions almost always add another layer of complexity to group financial steering. Each acquired entity comes with its own systems, chart of accounts, reporting habits, KPIs, and sometimes its own definition of performance. In that context, connecting an ERP to an FP&A platform such as IBM Planning Analytics becomes a strategic lever. This architecture helps accelerate integration, strengthen consolidation, and manage synergies without waiting for a long and risky ERP migration. SAP and SAP S/4HANA remain very common cases, but the rationale goes far beyond one ERP stack.

M&AERPSAP
6 min read
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Idriss Patel

Why connect an ERP to IBM Planning Analytics? Benefits for finance and business teams

Connecting an ERP to an FP&A platform like IBM Planning Analytics separates transaction processing from analytics while keeping data reliable, current, and usable. It is especially relevant for CFOs, controllers, IT teams, and business managers who need faster and better-informed decisions.

In many organizations, the ERP already sits at the core of billing, procurement, payroll, accounting, and operational flows. But when finance teams need to simulate scenarios, produce a reliable rolling forecast, shorten the budget cycle, or steer performance across multiple dimensions, the ERP on its own quickly reaches its limits. This is where a connection with IBM Planning Analytics becomes valuable. The goal is not to replace the ERP, but to complement it with a dedicated FP&A layer so that transaction processing and analytics remain clearly separated without breaking data continuity. SAP and SAP S/4HANA are very common cases, but the logic applies much more broadly.

ERPSAPSAP S/4HANA
6 min read
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Thomas Leduc
Thomas Leduc

Best FP&A software in 2026: complete comparison of financial planning tools

IBM Planning Analytics, Anaplan, Oracle Cloud EPM, Jedox, OneStream, Pigment, and Workday Adaptive Planning are among the most frequently shortlisted FP&A platforms. This comparison reviews their positioning, strengths, and trade-offs to help finance leaders choose the right fit for their organization.

Finance teams are expected to plan faster, work with more data, run more scenarios, and support decisions with greater confidence than ever before. In that environment, FP&A platforms have become a core part of the finance technology stack. They help organizations strengthen budgeting, accelerate forecasting, connect finance with operations, and move away from spreadsheet-driven processes that no longer scale. The challenge is that the market is crowded and the leading solutions often appear similar at first glance. This guide offers a clearer 2026 market view in a comparison format inspired by software review pages, but adapted to AEXIS's advisory perspective.

FP&AIBM Planning AnalyticsAnaplan
7 min read
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Thomas Leduc
Thomas Leduc

IBM Planning Analytics vs Workday Adaptive Planning vs Anaplan: which xP&A platform should you choose?

When Excel-based planning reaches its limits, three names often come up in FP&A and xP&A projects: IBM Planning Analytics, Workday Adaptive Planning, and Anaplan. The right choice depends less on a universal ranking than on your level of complexity, your modeling needs, your cloud trajectory, and your ability to industrialize planning processes.

Many organizations reach a point where spreadsheets are no longer enough to manage budgets, forecasts, and scenarios. Data volumes grow, models become more complex, security controls are no longer sufficient, and collaboration between finance and business teams becomes fragile. This is typically when IBM Planning Analytics, Workday Adaptive Planning, and Anaplan enter the discussion. All three address the same modernization challenge, but they do so with different design philosophies. This updated version of the comparison is meant to make the decision framework clearer and more practical.

IBM Planning AnalyticsWorkday Adaptive PlanningAnaplan
6 min read
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Thomas Leduc
Thomas Leduc

What are the differences between Microsoft Power BI and IBM Planning Analytics?

Power BI and IBM Planning Analytics share some reporting and data connectivity capabilities, but they do not solve the same problem. One is primarily a business intelligence tool, while the other is a platform for planning, simulation and performance management.

Many companies, including many of our clients, use Microsoft Power BI as part of their Microsoft environment. Power BI is an excellent tool, easy to adopt, familiar to Excel users, and able to connect to many data sources. We are often asked how it compares with IBM Planning Analytics. In reality, they are two different solutions designed for different purposes, even if they have several overlapping features. In this article, we look at what they have in common, where they differ, and in which contexts each one brings the most value.

Power BIIBM Planning AnalyticsBusiness Intelligence
4 min read
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Thomas Leduc
Thomas Leduc

Getting multiple AI agents to work together: the real value of multi-agent orchestration

The future of AI agents in the enterprise does not rely on a single assistant that is supposed to know everything. It relies on the ability to make multiple specialized agents collaborate, coordinated through a clear and governed orchestration logic.

When an organization discovers AI agents, the temptation is strong to create a single agent capable of addressing every need. In practice, this logic quickly reaches its limits. Business use cases combine different rules, different tools, and different skills. A strong agentic setup therefore looks less like an omniscient agent and more like an organized team. watsonx Orchestrate makes it possible to design this kind of architecture by enabling several specialized agents to cooperate within a shared workflow. For AEXIS, this approach is particularly compelling because it aligns far better with the operational realities of companies than the simplistic promise of a universal assistant.

Multi-agentwatsonx OrchestrateAI Agents
4 min read
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Thomas Leduc
Thomas Leduc

Create, improve, and make AI agents more reliable with watsonx Orchestrate AI Builder

Creating a useful agent is not about writing a longer prompt. With watsonx Orchestrate AI Builder, the challenge becomes defining a clear role, relevant tools, and explicit guardrails to obtain an agent that is truly usable in the enterprise.

In many AI projects, the first version of an agent looks convincing for a few minutes, then quickly shows its limits as real-world cases become more precise. A rule is missing, a tool is missing, a constraint is missing, a business rewording is missing, or a guardrail is missing on what the agent is allowed to infer. watsonx Orchestrate AI Builder is interesting precisely because it structures this improvement phase. It allows you to create an agent from an intention, refine its instructions, revise its definition, and progressively make it more robust. For AEXIS, this logic is essential: an agent only has value if it becomes reliable, understandable, and manageable in a real business context.

AI Builderwatsonx OrchestrateAI Agents
4 min read
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Thomas Leduc
Thomas Leduc

MCP server and watsonx Orchestrate: connect your AI agents to IBM Planning Analytics

The real shift does not come only from the model, but from the connection to tools. With an MCP server connected to IBM Planning Analytics, watsonx Orchestrate can transform a conversational agent into one capable of interacting with real TM1 capabilities.

AI in the enterprise becomes truly useful when it can act beyond the chat window. In an EPM environment, that means understanding a business need, accessing Planning Analytics objects, running a query, using a view, or triggering a targeted process according to context. This is precisely where the MCP model becomes strategic. By connecting watsonx Orchestrate to IBM Planning Analytics through an MCP server, the agent is no longer limited to a textual assistant role: it can rely on tools exposed in a structured way to interact with the TM1 environment. For AEXIS, this is a particularly strong direction because it brings agentic AI closer to real finance, controlling, and planning use cases.

MCP serverwatsonx OrchestrateIBM Planning Analytics
4 min read
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Thomas Leduc
Thomas Leduc

Why watsonx Orchestrate is a game changer for enterprise AI agents

With watsonx Orchestrate, AI is no longer limited to answering questions. The platform makes it possible to create agents able to use tools, collaborate with one another, and integrate into enterprise processes within a governed framework.

Many AI projects stop at the conversational demo stage. The answers can be impressive, but they remain disconnected from real execution. As soon as multiple steps need to be chained together, a tool must be called, the task must be handed to the right actor, or access to data must be framed, the difficulty changes scale. watsonx Orchestrate addresses precisely this transition: moving from an assistant that comments on work to a platform of agents that actually participate in how the enterprise operates. At AEXIS, we see this evolution as a practical lever to industrialize intelligent automation without losing control, clarity, or governance.

watsonx OrchestrateAI AgentsOrchestration
4 min read
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Thomas Leduc
Thomas Leduc

IBM watsonx Orchestrate: manage AI agents with AEXIS

IBM watsonx Orchestrate makes it possible to move beyond the isolated chatbot and orchestrate AI agents capable of acting in your business tools, chaining multi-step tasks, and remaining governed within an enterprise framework.

Many AI initiatives remain stuck at the demonstration stage because they answer, but do not execute. With watsonx Orchestrate, the challenge becomes different: connecting agents to applications, structuring their role within a process, framing access, and making their actions observable. AEXIS supports this shift by turning automation ideas into guided, integrated, and industrializable use cases.

IBM watsonx OrchestrateAI AgentsAutomation
3 min read
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Frédéric Mallaval, Pre-Sales Consultant and IBM TM1 Expert at AEXIS
Frédéric Mallaval

Structuring and Securing the Budgeting Process with Planning Analytics

IBM Planning Analytics goes beyond performance monitoring. It structures the entire budgeting process—data entry, validation, allocation, and finalization—to enable a collaborative, secure, and auditable budget.

An efficient budget relies as much on the robustness of the process as on its flexibility. Contributor coordination, simulations, validations, and traceability are essential to securing financial commitments. IBM Planning Analytics provides a structured framework for managing the entire budgeting process.

IBM Planning AnalyticsTM1Budgeting process
1 min
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Frédéric Mallaval, Pre-Sales Consultant and IBM TM1 Expert at AEXIS
Frédéric Mallaval

Driving Budget and Performance with IBM Planning Analytics

IBM Planning Analytics enables organizations to move beyond static budgeting and continuously manage financial performance. Dashboards, variance analysis, and forecasting provide a clear view to support earlier and more confident decision-making.

In an uncertain economic environment, an annual budget is no longer sufficient. Finance leaders need real-time visibility that compares budget, actuals, and forecasts to anticipate deviations and adjust course. IBM Planning Analytics addresses this challenge by providing a unified platform for performance management, analysis, and projection.

IBM Planning AnalyticsTM1Performance management
1 min
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Bernice van Merksteijn
Bernice van Merksteijn

IBM Controller & IBM Planning Analytics: an integrated chain from consolidation to decision-making

IBM Controller and IBM Planning Analytics form an integrated analytical chain that connects financial consolidation, multidimensional analysis and performance management around a single source of truth.

Many organizations today rely on powerful tools for financial consolidation and analysis, but struggle to connect them into a coherent end-to-end chain. The result is data breaks, manual rework and delays in decision-making. The combination of IBM Controller and IBM Planning Analytics addresses these challenges by building an integrated chain from source data to decision support, without disruption or re-entry.

IBM ControllerIBM Planning AnalyticsEPM
4 min read
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Thomas Leduc
Thomas Leduc

IBM Planning Analytics: foundations, use cases and value drivers

IBM Planning Analytics goes beyond the limitations of Excel and traditional EPM tools to sustainably structure planning, forecasting and financial simulation across the enterprise.

In many organizations, financial planning still relies on complex Excel files that are difficult to maintain and poorly suited to today's governance, collaboration and simulation requirements. IBM Planning Analytics provides a structured response to these challenges by offering an EPM platform capable of centralizing data, industrializing planning processes and improving decision reliability. This article presents the solution's fundamentals, its main use cases and the tangible value drivers observed in real-world implementations.

IBM Planning AnalyticsEPMTM1
3 min read
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Thomas Leduc
Thomas Leduc

10 best practices for modern and high-performing financial planning

In a context of uncertainty and accelerating economic cycles, financial planning must evolve. Here are 10 key best practices to structure a modern, agile and decision-oriented FP&A function.

Financial planning is no longer limited to building an annual budget. In an unstable economic environment marked by rapid change and growing performance management requirements, finance leaders must rethink their approaches. A high-performing FP&A function today relies on continuous processes, appropriate tools and close collaboration with the business. This article presents ten essential best practices to sustainably modernize financial planning.

FP&AFinancial PlanningRolling Forecast
3 min read
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Thomas Leduc
Thomas Leduc

EPM vs BI: differences, use cases and real complementarity

EPM and BI serve fundamentally different yet complementary objectives. Understanding their respective roles is essential to building truly effective performance management.

For a long time, EPM and BI solutions evolved in separate ecosystems, driven by different use cases, teams and objectives. Financial planning and analytical reporting required distinct tools that were difficult to align. Today, this boundary is gradually fading. More mature organizations no longer seek to oppose EPM and BI, but to intelligently articulate them in order to connect planning, performance management and decision analytics.

EPMBIPerformance Management
3 min read
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Thomas Leduc
Thomas Leduc

Planning Analytics for Excel: accelerating decision performance with Excel

Planning Analytics for Excel transforms Excel into a true financial and strategic performance management tool. Discover how PAFE enables faster planning, simulation and decision-making through real-time data.

In an economic environment marked by uncertainty, market volatility and the proliferation of data sources, organizations must rely on tools capable of turning information into actionable decisions. Planning Analytics for Excel (PAFE) fully addresses this need. By combining the power of the IBM Planning Analytics (TM1) engine with the familiarity of Microsoft Excel, PAFE delivers a modern, flexible and high-performing approach to financial planning and analysis. This article explores the foundations of PAFE, its key use cases and the strategic value it brings to performance-driven organizations.

Planning AnalyticsPAFEEPM
4 min read
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Thomas Leduc
Thomas Leduc

Improving the reliability of margin management in the banking sector

In a demanding regulatory and economic environment, banks must strengthen margin management by linking planning, forecasting, profitability and risk management.

Active risk and return management has never been more critical for financial institutions. Banking planning can no longer be limited to an annual exercise disconnected from operational and regulatory realities. With the emergence of standards such as expected credit losses and mandatory stress tests, banks must rethink their forecasting processes. When properly structured, these constraints become an opportunity: transforming planning into a true lever for improving the reliability of profit projections and overall performance.

BankingMargin ManagementFinancial Forecasting
5 min read
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Thomas Leduc
Thomas Leduc

Why Rolling Forecast is becoming the new standard in financial performance management

In the face of economic uncertainty and accelerating decision-making cycles, Rolling Forecast is emerging as an alternative to the annual budget for continuous financial performance management.

Budgeting and financial performance have always been central concerns for organizations. However, in a rapidly changing economic environment, relying on a fixed annual budget is no longer sufficient. Even when forecasts are updated monthly, their time horizon gradually shortens as the year progresses. Rolling Forecast addresses this limitation by offering a continuous, forward-looking planning approach aligned with operational reality.

Rolling ForecastFinancial TransformationFinancial Planning
3 min read
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Thomas Leduc
Thomas Leduc

Harmonizing financial planning across a multi-entity group

How an international organization structured its financial planning to improve forecast reliability, shorten budgeting cycles and align finance and business teams across the group.

Many organizations operating across multiple countries face similar challenges: heterogeneous planning processes, excessive reliance on Excel, long budgeting cycles and limited consolidated visibility. This use case illustrates how a multi-entity group redesigned its financial performance management to harmonize practices, improve forecast reliability and strengthen decision-making at all levels of the organization.

Use CaseFinancial PlanningMulti-Entity Group
2 min read
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Last updated on May 18, 2026

AEXIS Blog - Insights on Planning Analytics & Financial Transformation