For years, finance leaders have debated when the time would come to embed Artificial Intelligence (AI) into their operations. That time is no longer in the future. AI has become a business imperative—a driver of efficiency, agility, and competitive advantage for CFOs under mounting pressure to deliver more with less.

This is not just theory. It’s happening today. And Rinnai Australia is a standout example.

In just 12 months, Rinnai has modernised its finance platform, embedding IBM Planning Analytics (PA) with support from Octane Software Solutions. The result? A finance function that has freed up 40 hours per week of manual effort, cut reporting cycles from weeks to four days, reduced reliance on spreadsheets by 50%, improved staff morale, and positioned the business for AI-driven forecasting, predictive models, and even faster M&A integration.

This story, and what other CFOs can learn from it, will be at the centre of the upcoming CFO Lunchtime Live Webcast, hosted by CFO Magazine’s James Solomons, featuring Dilend Chawda (Rinnai Australia), Darksha Nadesewaran (IBM ANZ), and Amendra Pratap (Octane Software Solutions).

The Starting Point: Fragmented, Manual, and Complex

Like many growing businesses, Rinnai faced the challenge of fragmented finance processes. Over the years, the organisation had grown in complexity through multiple subsidiaries and M&A activity. Finance was juggling different tools—from Cognos and TM1 to Essbase and Oracle OACS—with high spreadsheet dependency for budgeting and reporting.

The result was:

• Long reporting cycles: Subsidiaries took weeks to close, delaying group-level insights.

• Spreadsheet chaos: Dozens of versions, late-night reconciliations, and version-control headaches.

• 3-month budgeting cycles: A bottom-up approach involving countless files, links, and manual inputs.

• Staff fatigue and low morale: Finance teams were bogged down in reconciliation and data wrangling rather than analysis.

The system simply wasn’t fit for a fast-moving organisation that needed real-time insights, scenario planning, and agility in the face of market volatility.

The Transformation Journey

1. Building a Modern Platform with IBM Planning Analytics

In mid-2024, Rinnai partnered with Octane SoftwarIn mid-2024, Rinnai partnered with Octane Software Solutions to modernise its finance platform with IBM Planning Analytics. Within weeks, the first modules were live:

• August 2024: Group month-end reporting (P&L, Balance Sheet).

• October 2024: Product profitability reporting—allocating operating profit down to individual products.

• November 2024: Logistic demand planning—12-month SKU-level forecasting.

• December 2024: Budget suite for 2025—integrated with sales, costing, workforce, capex, and manufacturing recovery cubes.

• June 2025: Subsidiaries fully integrated—Xero trial balances from subsidiaries consolidated into group reporting.

This was a swift, phased deployment that made transformation tangible within months, not years.

2. Quantifiable Benefits Delivered

The outcomes have been both immediate and measurable:

• 40 hours/week saved: Automation of data consolidation and reporting removed manual wrangling.

• Reporting cycle cut to 4 days: Down from weeks for subsidiaries.

• 50% fewer spreadsheets: Dramatically reducing version errors and reconciliation headaches.

• Budgeting accelerated: From a painful 3-month cycle to a streamlined, collaborative process.

• Staff morale uplift: Finance staff moved from data entry to analysis, improving job satisfaction and retention.

• 10% targeted inventory reduction: Through AI-enabled demand planning, reduce warehouse costs while ensuring sales coverage.

The shift has not just been technical—it has been cultural. Finance is no longer the bottleneck, but the enabler.

3. AI Foundations and Next Steps

Rinnai’s transformation has built the foundation for AI adoption. Already, the company is:

• Running predictive models for working capital management.

• Leveraging IBM PA Assistant (built on watsonx) for natural language queries, commentary automation, and outlier analysis.

• Piloting agentic AI assistants (Watson Orchestrate) to automate workflows.

• Experimenting with generative AI in Planning Analytics and Oracle—using natural language prompts for “Ask Rinnai” use cases.

Lessons for CFOs

From Rinnai’s journey, there are clear takeaways for other finance leaders:

1. Be bold and act early: Legacy systems will only get more expensive and harder to fix.

2. Start with a strong foundation: Modernising reporting, budgeting, and forecasting enables AI to scale.

3. Quantify benefits: Measure and communicate outcomes like hours saved, cycle time reduced, and morale lifted to keep momentum.

4. Embed governance and culture: AI adoption requires upskilling teams and embedding robust controls.

5. Think strategically: Modern platforms don’t just support finance—they enable faster M&A integration, strategic planning, and long-term growth.

The Bigger Picture: Finance as a Strategic Partner

What stands out most from the Rinnai story is how the role of finance has shifted. With automation and AI taking on manual processes, the finance team is now focused on:

• Providing forward-looking insights through predictive analytics.

• Partnering with the business on strategy, pricing, and resource planning.

• Supporting growth through faster M&A integration.

• Driving continuous improvement through new AI features and enhancements.

Finance has moved from a reactive scorekeeper to a proactive strategist.

Final Word

The Rinnai story proves that AI in finance is not a distant dream—it’s a present reality. With vision, leadership, and the right partners, CFOs can deliver faster, smarter, and more resilient finance functions that directly enable business growth.

The question is not if finance leaders should adopt AI, but how quickly they can embed it into their organisations.

Don’t wait until it’s harder and more expensive. Join us for this webcast and see how you can start your journey today.

WATCH RECORDING HERE

 

IBM Planning Analytics has introduced new features that make development and administration tasks much easier. Two of the most impactful improvements are the ability to see variable values while debugging TI processes and the enhanced Database Explorer.

1. Hover to See Variable Values in TurboIntegrator Debugger

Debugging TI processes used to mean adding log statements and rerunning processes just to see variable values. With the new hover help, simply move your mouse over a variable in the debugger, and its value is displayed (e.g., sCube = 'Asset_Input').

✅ Benefit: Makes debugging much faster, eliminates extra logging, and helps you quickly confirm whether variables are behaving as expected.

Figure 1: Hovering over a variable shows its value instantly in the TI debugger

2. Database Explorer: A Smarter Way to Navigate Your Environment

Managing a Planning Analytics server or instance often involves checking how many objects exist—be it cubes, dimensions, processes, chores, or control objects. Previously, administrators and developers had to dig through folders or rely on TI scripts to gather this information. Now, with the Database Explorer, everything is accessible in one clean interface.

Key features include:

• Quick Object Counts: Instantly see how many cubes, dimensions, processes, and chores are available.
• Process Data Source Types: Displays what data source a process is using (e.g., Cube, ODBC, or 'No data source').
• Organised View: Objects are grouped into categories, reducing clutter and making navigation straightforward.
• Centralised Actions: Access logs, import/export, manage users, refresh security, or check server version from one place.

✅ Benefit: The Database Explorer improves transparency and efficiency, helping both administrators and developers work faster by providing a unified view of objects and their data sources.

Figure 2: Navigation through the Database Explorer menu

Figure 3: Object counts displayed in Database Explorer

Figure 4: Shows Data source when clicked on Processes

Small Changes, Big Impact

These updates may seem minor, but they greatly improve user productivity. From instantly checking variable values in debugging to exploring databases more efficiently, IBM Planning Analytics is now smarter and more user-friendly.

 

 

In an age where AI is often synonymous with machine learning, one of the most powerful, but often overlooked, tools in the AI toolbox is optimisation. At the heart of many real-world, high-stakes decisions lies a mathematical engine built to deliver the best possible outcome. And IBM ILOG CPLEX continues to be that engine of choice. 

As we move deeper into 2025, one hot trend is hybrid AI, the combination of predictive models with prescriptive optimisation. Why predict what might happen if you can also decide what should happen? That’s where CPLEX shines.

Real-world impact: From supply chains to smart grids 

Whether it’s dynamically routing fleets, allocating resources under uncertainty, or scheduling energy consumption during peak hours, organisations are leveraging CPLEX not just as a solver, but as a strategic decision engine.

Here are a few standout use cases:

• Retail & E-Commerce: Predicting customer demand using ML, then using CPLEX to optimise fulfilment across a decentralised warehouse network. 

• Utilities: Combining real-time sensor data with CPLEX-based scheduling to balance load in smart grid systems. 

• Finance: Creating portfolio allocations that meet regulatory requirements and maximise return, all while adapting to market volatility. 

Cloud-native optimisation: Scaling with IBM Cloud Pak for Data

Another major shift? Optimisation in the cloud. IBM's Cloud Pak for Data is helping companies operationalise CPLEX models in ways that were unimaginable just a few years ago. Think seamless integration with data lakes, real-time dashboards, and API-first deployment models.

Why It Matters

As business environments grow more complex, the ability to make data-driven, optimal decisions in real-time becomes a true competitive advantage. CPLEX brings mathematical certainty to uncertain times, and when combined with machine learning, it offers a full-spectrum AI approach that’s both predictive and prescriptive. 

Are you exploring optimization as part of your AI strategy? Let’s connect, happy to exchange thoughts on where prescriptive analytics is heading next.

💬Talk to us: media@octanesolutions.com.au

 

In today’s fast-moving business environment, automation isn’t just a nice-to-have — it’s essential. IBM Watsonx Orchestrate has already helped many organisations streamline tasks, save time and improve productivity across teams. However, with the introduction of the Agentic version of Watsonx Orchestrate, a noticeable shift is occurring in how companies approach automation.

Unlike the Classic version, which relies on well-defined rules and task sequences, the Agentic approach introduces intelligent agents that understand goals, adapt to changing inputs, and even make decisions in real-time.

So, what’s the practical difference between the two versions? And more importantly, which one should you be using?

Let’s walk through it.

Classic vs. Agentic: A different approach to getting things done

The Classic Watsonx Orchestrate setup works exactly how you’d expect a traditional automation tool to work. You build a step-by-step workflow — for example, “If form is submitted, send it to Person A, then update System B.” It’s reliable, consistent and ideal for tasks that rarely change, like data entry or approval chains.

Agentic Watsonx Orchestrate flips that on its head.

Instead of just executing steps, it starts with a goal — say, “onboard this new employee” — and figures out the best way to achieve that outcome. It plans, adjusts and even asks for help when needed. It’s built to handle the real world, where not everything goes according to plan.

In other words, Classic is scripted. Agentic is strategic.

How They Make Decisions: One Follows Rules, One Thinks for Itself

This is where things start to diverge.

• Classic orchestration follows predefined rules. If X happens, do Y. It’s fast and efficient — as long as everything goes as expected.

• Agentic Orchestrate, on the other hand, understands context. If the usual input is missing or something unexpected comes up, it doesn’t just fail — it adapts. It learns from interactions and updates its plan as needed.

This kind of dynamic decision-making makes Agentic a better fit for processes where flexibility, personalisation, or real-time problem-solving are required.

When to Use What: It Depends on the Complexity

Not every process needs a thinking agent. Many don’t.

Here’s a simple guide:

Use Case	Best Fit
Leave requests, form approvals	Classic
Employee onboarding	Agentic
Performance reviews, coaching	Agentic
Simple helpdesk responses	Classic or Agentic

 

If your process is straightforward and repeatable, Classic is a solid choice. But if there’s variation, personalisation, or a need for real-time judgment, Agentic wins hands down.

What’s the Real Impact?

Let’s talk numbers for a second. Organisations that have started using Agentic Orchestrate are seeing:

• Up to 50% faster HR processing

• 30–60% quicker onboarding

• 25% higher satisfaction from employees using automated support services

That’s because these agents don’t just check boxes — they respond in real-time, offer suggestions and help both employees and managers stay on top of their goals. Think of it like having a digital colleague who understands what you're trying to achieve.

Classic automation answers “What needs to be done?”
Agentic automation answers “Why are we doing this, and what’s the best way to get there?”

How to Choose What’s Right for You

If you’re just starting out with automation, or if you want to get some quick wins by automating simple tasks, the Classic version will serve you well.

But if your goal is to rethink how your business operates — especially in areas like HR, IT, or customer support — the Agentic version is where you’ll start seeing transformative results.

In most cases, the best approach isn’t either/or. It’s both. Use Classic for structured processes and Agentic for the ones that benefit from adaptability and intelligence.

The Future: Smarter, Self-Improving Automation

Agentic Orchestrate isn’t just an upgrade — it’s a complete evolution in how we think about automation. With its ability to learn, adapt and personalise at scale, it opens the door to:

• Workflows that improve over time

• AI agents that respond based on real-world context

• Better support and alignment across teams

This is where automation is headed — not just faster, but smarter.

Ready to Explore What Agentic Orchestrate Could Do for You?

Whether you’re trying to modernise HR, improve service desk responsiveness, or simply reduce the manual load across departments, Agentic Watsonx Orchestrate gives you tools that work like partners — not just programs.

Let’s start a conversation. The future of intelligent work is here — and it’s Agentic.

What is ASCIIOutputOpen

In IBM Planning Analytics (TM1), TurboIntegrator (TI) processes are essential for automating data operations. One of the most useful functions in TI scripting is ASCIIOutputOpen, which allows you to open a file for writing ASCII data. Whether you need to create a new file or append data to an existing one, this function provides the flexibility to control file access and modifications efficiently.

 

Key Features of ASCIIOutputOpen

• Append or Overwrite: Choose whether to overwrite an existing file or add new data to the end.  

• Shared Read Access: Enable other processes or users to read the file while it’s being written.  

• Supports Multiple File Types: Works seamlessly with .csv and .txt files, making it ideal for various data export needs.  

Syntax Breakdown 

The basic syntax for ASCIIOutputOpen is:  

ASCIIOutputOpen(FileName, OpeningMode);

Parameters Explained 

1. FileName  

   • The full path and filename (including extension) where data will be written.  

   • Example: "C:\Data\Report.csv"  

2. OpeningMode  

   • A numeric code that determines how the file is accessed.  

Mode	Description	Behaviour
0	Overwrite without shared read access	Creates or overwrites the file; no other process can read simultaneously.
1	Append mode without shared read access	Adds data to the end of the existing file; no sharing.
2	Overwrite, shared read access enabled	Overwrites if the file exists; allows other processes to read concurrently.
3	Append, shared read access enabled	Adds data to the end; allows other processes to read the file simultaneously.

 

Related Functions 

For more granular control, you can also use:  

• FILE_OPEN_APPEND() – Opens a file in append mode.

• FILE_OPEN_SHARED() – Opens a file with shared read access.
  

Combining these functions can provide finer control over file operations. 

Practical Examples

Example 1: Overwriting a File with Shared Read Access  

If you want to generate a new CSV report (overwriting any existing version) while allowing others to read it:  

ASCIIOutputOpen("C:\\Reports\\SalesData.csv", 2);

  

Example 2: Appending Data with Shared Access  

If you need to add new records to an existing file without locking it:  

ASCIIOutputOpen("C:\\Reports\\SalesData.csv", 3);

Conclusion 

ASCIIOutputOpen is a powerful function in TurboIntegrator that helps manage file exports efficiently. By understanding its different modes, you can ensure seamless data operations—whether you're generating reports, logging data, or integrating with external systems.  

Pro Tip: Always verify file paths and permissions before running TI processes to avoid errors!  

Have you used ASCIIOutputOpen in your projects? Share your experiences in the comments! 🚀  

Big news for Indian enterprises: IBM Planning Analytics as a Service is now officially available on AWS in India. This means faster performance, stronger data sovereignty, and AI-powered insights—all on a scalable cloud platform. At IBM India Services, together with Octane Software Solutions, we're excited to help you harness this opportunity.

Why this AWS India expansion changes everything

• Ultra-low latency for real-time planning & analytics

• Local data residency for compliance with India's DPDP Act

• IBM Planning Analytics on AWS - cloud-powered FP&A at scale

• AI-enhanced insights through IBM's agentic AI capabilities

Meet Octane Software Solutions: India’s trusted IBM Planning Analytics experts

Octane Software Solutions is a leading IBM implementation partner, known for deep expertise in financial analytics and enterprise planning. Here’s why Indian enterprises trust Octane:

• Home to 3 IBM Champions: Recognised by IBM for outstanding technical leadership and contribution to the global IBM community.

• Winner of the 2025 IBM Partner Plus Award: A testament to Octane’s excellence in delivering high-impact, scalable solutions with IBM technologies.

• Local expertise for Indian businesses: Deep understanding of compliance, data localisation, and sector-specific requirements in India.

• Proven delivery methodology: A structured, risk-free approach that covers everything from cloud migration and solution customisation to training and optimisation.

Why choose IBM + Octane?

• Best-in-class technology (IBM)+ 🛠️ Best-in-class implementation (Octane)

• End-to-end journey support—from planning to ongoing success

• Customisable, AI-powered FP&A solutions built for your needs

• Security and compliance assurance for Indian regulatory standards

Take the next step today

Whether your business is:

• Planning to modernise financial systems

• Exploring AI-powered forecasting and analytics

• Seeking to optimise cloud infrastructure and cost efficiency

Let’s make your vision a reality—quickly, securely, and intelligently.

📧 Contact Octane Software Solutions at hello@octanesolutions.com.au
Let’s build a customised roadmap to transform your planning and analytics on IBM Cloud + AWS India.

 

Looking for ways to monitor the health and status of your IBM Planning Analytics (PA) Application and Server?

Here are some methods for automating monitoring and receiving alerts whenever issues arise in the backend of your PA applications.

Before enabling these alerts, it's important to understand the key areas to monitor. Monitoring these aspects ensures your PA applications remain healthy, stable, and optimised for performance.

NOTE: Your Access role should be Administrator to view and perform all the below.

1. Database Health Monitoring

To assess the health of your PA applications and databases, follow these steps:

1. Log in to IBM Planning Analytics Workspace.

2. Navigate to Administration and click Databases.

3. Under Databases, select the desired PA application.

4. On the right-hand side of the page, click on Details to view the status and health metrics.

This provides a quick overview of the database’s performance and any potential issues that may require attention.

Sample Screenshot:

 

You will see various status icons that indicate the current health of the PA application. Here's what each icon represents:

 Indicates that the PA application is healthy and running without any issues.

Indicates that the PA application is at risk of moving into a critical state. Proactive attention may be required.

 Indicates that the PA application is in a critical state and may potentially
                                 lead to a system failure or downtime if not addressed immediately.

To set up automatic alerts for your PA application:

1. On the right-hand side of the application's detail page, click on Alerts.

2. From there, you can configure the threshold values that will trigger alerts based on system performance or issues.

3. To enable the Alerts, click on the respective  button, which changes to  indicate it's enabled.

This allows proactive monitoring by notifying you when predefined conditions are met.

Sample Screenshot:

5. We can define the Warning threshold and Critical threshold values based on the size and memory utilised by the PA application under stable conditions.

6. Apart from that, we have options to define Critical Threshold values for factors such as –

• Max thread wait time: we can set the Critical Threshold for maximum thread wait time for the respective PA Application to make sure the PA instance is not slowing down as we can kill thread as soon as possible.

• Thread in run state: we can set the Critical Threshold to make sure the threads are not in Run state for more than expected in the respective PA Application, which has the possibility of slowing down the server.

• Database unresponsive: we can set the Critical Threshold to note if Database/PA application is not responsive which helps us to action it as soon as possible.
  

6.  We can enable the Database Shutdown Alert to enable notifications on the PA Application Stop/Downtime and Start/Restart activity.

7.  We can add multiple email IDs to receive the notifications of the enabled Alerts, separated by a comma (‘, ’) in the Notify email IDs text box.

8.  Click Apply to save the change made to the Alerts.

2. Agent/PA Server Health Monitoring

To assess the health of your PA Server/Agent, follow these steps;

1.    Log in to IBM Planning Analytics Workspace.
2.    Navigate to Administration and click Databases.
3.    Under Agents, select the desired Agent.
4.    On the right-hand side of the page, click on Details to view the status and health metrics.

This provides a quick overview of the database’s performance and any potential issues that may require attention.

Sample screenshot:

To set up automatic alerts for your PA Server:

1.    On the right-hand side of the application's detail page, click on Alerts.
2.    From there, you can configure the threshold values that will trigger alerts based on system performance or issues. 
3.    To enable the Alerts, click on the respective   button, which changes to   indicates it's enabled.

Sample Screenshot:

4.    We can define the Warning threshold and Critical threshold values based on the size and memory utilized by the PA application on stable conditions.
5.    We can add multiple emails IDs to receive the notifications of the enabled Alerts separated by a comma (‘ , ’) in the Notify email IDs text box.
6.    Click Apply to save the change made to the Alerts.

As the role of the CFO evolves from financial steward to strategic architect, the expectations have never been higher. 

CFOs today are expected to: 

• Deliver rapid, accurate close cycles.  

• Ensure compliance across a complex regulatory landscape. 

• Provide forward-looking insights that drive executive decisions. 

• Lead finance transformation in a data-driven world. 

This shift demands more than spreadsheets and legacy consolidation tools. It calls for intelligent automation, real-time transparency, and strategic control. 

This is where IBM Controller steps in as a financial consolidation platform and a strategic lever for modern CFOs. 

Why CFOs need more than just a close process

Financial close is no longer just a back-office routine; it’s a board-level priority. Late or inaccurate reporting can erode stakeholder trust, disconnected systems can slow you down, and manual errors open the door to audit risks. 

With IBM Controller, CFOs move from reactive to proactive by: 

• Accelerating the close cycle without compromising accuracy. 

• Ensuring compliance across multiple GAAPs, IFRS, and local statutory rules. 

• Reducing manual effort with automated intercompany eliminations, minority interest handling, and ownership calculations. 

• Maintaining full audit trails to satisfy internal and external audits effortlessly.
  
  Speed + Accuracy + Control = Confidence at Every Close. 

From static numbers to strategic narratives 

Today’s executive team needs more than a balance sheet. They need answers: 

• What’s driving margin erosion? 

• How are subsidiaries impacting group performance?

• Where should we invest next?

IBM Controller delivers real-time insights, not just reports. When integrated with IBM Planning Analytics, CFOs can: 

• Drill down into entity, region, or line-of-business level performance. 

• Compare actuals vs. budget with clear variance explanations. 

• Model multiple financial scenarios in the same ecosystem. 

This empowers CFOs to shift the narrative from “what happened” to “what’s next”, backed by data that leadership can trust. 

Built-in compliance, without the complexity 

The regulatory landscape is only getting tougher, taxonomies are changing, ESG requirements are emerging, and cross-border regulations are becoming more intricate. 

IBM Controller helps CFOs stay ahead by: 

• Supporting multi-GAAP reporting and localisation. 

• Offering governance frameworks with role-based controls and data lineage. 

• Providing full auditability and traceability of financial data. 

• Enabling continuous compliance—not just at quarter-end. 

This isn’t just regulatory peace of mind, it’s risk mitigation at scale. 

Scalability that matches business growth 

CFOs aren’t just managing today, they’re preparing for tomorrow. Whether it’s a merger, acquisition, spin-off, or expansion into new markets, the finance function must scale fast. 

IBM Controller delivers the agility to: 

• Seamlessly onboard new entities and the chart of accounts. 

• Adjust the consolidation logic as ownership structures evolve. 

• Adapt to new taxonomies, KPIs, and compliance requirements. 

With a flexible, rule-driven architecture, IBM Controller grows as your business grows without rewriting your finance playbook. 

Cloud-powered, CFO-friendly 

Modern CFOs are embracing the cloud not just for IT efficiency, but for strategic advantage. 

IBM Controller on Cloud offers: 

• Lower total cost of ownership, no infrastructure or heavy IT dependency.
• Always-on availability, global scalability, and robust security.
• Faster upgrades, with immediate access to new features and enhancements.
  

This allows finance teams to focus on what matters- strategy, performance, and growth, not system maintenance. 

One source of truth. Many paths to insight.

With IBM Controller, the CFO gains more than visibility, they gain command. 

The solution becomes a single source of truth for the office of finance. Whether you're reporting to the board, regulators, or investors, the numbers always align, no recon, no surprises. 

And with powerful integration to tools like IBM Planning Analytics, Cognos Analytics, and Excel, you’re not just seeing the past. You’re shaping the future

The Strategic Payoff: A CFO’s Competitive Advantage

Let’s be clear, IBM Controller isn’t just a tool for the finance team. It’s a strategic platform for CFOs who want to:

• Close faster, with fewer errors

• Ensure regulatory compliance across borders

• Gain real-time visibility into performance

• Scale finance operations with business growth

• Drive executive decisions with confidence 

In an era where data is your most valuable asset and insight is your sharpest edge, IBM Controller puts you at the helm of financial command.

"Be the CFO who leads, not just reports"

You’re not just responsible for the numbers, you’re shaping the story they tell. 

With IBM Controller, you gain the speed, clarity, and control to lead with impact every quarter, every decision, every time. 

The need for agile financial planning

In today’s rapidly evolving business landscape, organisations face unprecedented volatility, supply chain disruptions, fluctuating demand, inflationary pressures, and geopolitical uncertainties. Traditional financial planning methods, reliant on static spreadsheets and manual processes, are no longer sufficient. Businesses need real-time insights, predictive foresight, and the ability to pivot quickly in response to changing conditions.

Enter IBM Planning Analytics with Watson’s AI Assistant, a cutting-edge solution that combines multidimensional modelling with conversational AI. This solution is transforming how enterprises approach budgeting, forecasting, and performance management. This isn’t just an incremental improvement; it’s a paradigm shift in financial planning and analysis (FP&A).

What is IBM Planning Analytics with AI Assistant?

IBM Planning Analytics, built on the powerful TM1 engine, has long been recognised for its:

• In-memory computing for lightning-fast calculations

• Multidimensional modelling for complex scenario analysis

• Seamless Excel integration for user-friendly analytics

Now, with the AI Assistant, the platform goes beyond traditional analytics by embedding Watson-powered artificial intelligence directly into the planning workflow. This AI-driven co-pilot enables users to interact with their data conversationally, uncovering insights that would otherwise require deep technical expertise.

How does the AI assistant work?

Think of it as a data-savvy colleague who can:

• Answer complex financial questions in natural language (e.g., *“Why did Q2 profitability decline in the Asia-Pacific region?” *)

• Automatically detect anomalies and suggest corrective actions

• Generate predictive forecasts based on historical trends and external factors

• Run instant what-if scenarios (e.g., “What happens if raw material costs increase by 15%?”)

Unlike traditional BI tools that require users to write queries or build complex models, the AI Assistant democratizes analytics, making advanced insights accessible to finance teams, business leaders, and operational managers alike. 

Key Benefits of IBM Planning Analytics with AI Assistant

Natural language queries – No coding required

Gone are the days of struggling with MDX or complex formulas. Users can simply ask questions in plain English, such as:

• “Show me sales performance by region last quarter.”

• “Why are operating expenses higher than forecast?”

• “Predict next quarter’s revenue based on current trends.”

The AI Assistant interprets intent, retrieves relevant data, and presents answers in interactive dashboards, charts, or drill-down reports, eliminating the need for IT intervention.

Real-time cognitive insights

The AI Assistant continuously monitors data patterns, flagging anomalies and suggesting corrective actions before they escalate into bigger issues. For example:

• “Inventory turnover in the Northeast is 20% below target, recommend adjusting procurement orders.”

• “Marketing spend is exceeding budget due to higher-than-expected digital ad costs.”

This proactive intelligence helps businesses stay ahead of risks and opportunities.

Instant scenario modelling & what-if analysis

Strategic planning no longer takes weeks. With AI-powered scenario modelling, finance teams can:

•  Test multiple business conditions in seconds (e.g., “What if interest rates rise by 2%?”)

• Compare outcomes side-by-side

• Adjust assumptions dynamically

This capability is invaluable for risk management, capital allocation, and growth planning

Democratised analytics for cross-functional teams

The AI Assistant breaks down data silos, allowing:

• Finance teams to explore profitability drivers

• Sales leaders to assess pipeline impacts

• Supply chain managers need to optimise inventory levels

By making analytics self-service, organisations reduce dependency on IT and accelerate decision-making.

Explainable AI: Not just predictions, but reasons

Many AI tools provide forecasts but fail to explain why a trend is occurring. IBM’s AI Assistant goes further by:

• Highlighting key drivers behind variances (e.g., “Q3 revenue dipped due to delayed product launches in Europe.”)

• Suggesting actionable recommendations (e.g., “Consider reallocating budget to high-growth markets.”)

This transparency builds trust in AI-driven insights.

Real-world use case: Transforming a CFO’s workflow

Imagine a CFO who starts their day with an AI-generated briefing:

“Good morning. Last week, operating margins in the retail division fell by 8% due to higher logistics costs. Supplier X increased rates by 12%. Recommended actions: Renegotiate contracts or explore alternative vendors. Additionally, Q4 demand forecasts suggest a 15% increase, consider ramping up production.”

This level of automated, intelligent guidance enables faster, more informed decisions, reducing planning cycles from weeks to hours.

Seamless Integration with Existing Tools

IBM Planning Analytics doesn’t operate in isolation. It integrates with:

• Microsoft Excel (for familiar spreadsheet-based planning)

• Power BI & Tableau (for advanced visualisations)

• ERP systems (SAP, Oracle, NetSuite) for real-time data synchronisation

The AI Assistant acts as a universal translator, bridging gaps between disparate systems and delivering unified insights.

The future of work: Augmented, not automated

A common fear is that AI will replace human jobs. However, IBM Planning Analytics is designed to augment—not replace, FP&A teams.

• AI handles data processing, anomaly detection, and predictive modelling.

• Humans focus on strategy, stakeholder collaboration, and creative problem-solving.

The result? Higher productivity, deeper insights, and more strategic impact.

Is your organisation ready for AI-driven planning?

Adopting IBM Planning Analytics with AI Assistant requires:

• A shift from manual to automated processes

• Trust in data-driven decision-making

• Willingness to experiment with AI-powered insights

For companies that embrace this transformation, the rewards are substantial:

• Faster, more accurate forecasts

• Proactive risk mitigation

• Empowered teams with self-service analytics

Start your AI-powered planning journey

The best way to experience the power of IBM Planning Analytics with AI Assistant is to run a pilot project. Begin with a single department, finance, sales, or operations and measure the impact.

Your planning process will never be the same.

📅 Ready to explore how AI can revolutionise your financial planning? Contact us for a demo and learn more.

 

In a world where speed, scale, and trust define success, Octane has emerged as a leader in enterprise AI-driven transformation. Honoured with the 2025 IBM Partner Plus Award in APAC for automation, Octane’s groundbreaking use of IBM Watsonx Orchestrate is setting a new benchmark for how intelligent automation can empower business users and scale human productivity.

The Award: Increasing performance through automation

The IBM Partner Plus Award for Automation celebrates business partners who are delivering new levels of performance with speed, scale and security, enabling systems, business processes, and people to be more efficient.

For Octane, this means:

• Speed: Accelerating workflows by over 70% through AI orchestration.

• Adaptability: Designing solutions that flex with business demands.

• Security: Ensuring compliance through enterprise-grade automation guardrails.

“This award reinforces our belief that automation should be intuitive, intelligent, and human-first,” said Amendra Pratap, Managing Director. “Our collaboration with IBM brings this vision to life.”

IBM Watsonx Orchestrate: A new paradigm in intelligent automation

Watsonx Orchestrate is IBM’s enterprise-ready solution that helps create, deploy, and manage AI assistants and agents. It blends AI and workflow automation, enabling users to interact with systems using natural language prompts, representing a powerful step toward fully autonomous agentic AI systems. It enables multi-step, goal-driven task orchestration and integration with existing business systems, connecting to multiple proprietary and third-party AI models and automation tools.

How Octane leverages Watsonx Orchestrate:

• Skill-based AI execution: Prebuilt “skills” automate repetitive actions—like sending emails, updating records, or scheduling interviews.
• No-code integrations: Plug-and-play connections to enterprise tools like SAP, Salesforce, and Workday.
• Conversational interface: Users trigger complex workflows through Slack, Teams, or email with simple prompts.

“Watsonx Orchestrate isn’t just for building chatbots—it’s an AI-powered teammate,” says Amendra Pratap, Managing Director, “Watsonx Orchestrate is your next hire. By orchestrating tasks across various assistants, agents and systems, it helps boost workforce efficiency and reduces manual load by surfacing the right tools when you need them."

Real-world impact:

What we achieved:

What sets Octane apart: Augmented intelligence, not just automation

Traditional automation follows rules. Octane uses AI to understand goals, context, and next best actions.

With Watsonx Orchestrate, Octane delivers:

• Adaptive workflows: Adjusts based on real-time data (e.g., re-routing approvals during outages).
• Multi-agent collaboration: Skills collaborate (e.g., sentiment analysis + ticket escalation).
• Continuous learning: Models improve from feedback to streamline operations over time.

“We don’t just automate tasks—we augment thinking,” says Steny Sebastian, Principal - Data and AI Platforms. “That’s how we deliver smarter outcomes, not just faster ones.”

Ready to orchestrate intelligence into every workflow?

 Explore how Octane’s award-winning AI solutions can help you scale with confidence.

Learn how advanced your organisation is with AI adoption and how Orchestrate can help. - Take the next step. Try IBM Watsonx Orchestrate at no cost, or book a consultation with an expert

Learn more about the IBM Partner Plus Awards: https://www.ibm.com/partnerplus/awards

#AgenticAI #EnterpriseAutomation #OctaneSolutions #WatsonxOrchestrate #IBMPartnerPlus #DigitalTransformation

There’s nothing quite like starting a new role at the forefront of innovation. My first week at Octane Software Solutions was nothing short of electrifying—the highlight was a full-house customer event buzzing with energy, visionary ideas, and the promise of AI-driven transformation. 

The focus?

 IBM AI Platform,  Watsonx Orchestrate, is poised to redefine how businesses harness automation, AI agents, and predictive intelligence to unlock unprecedented efficiency. Let me take you through this exhilarating journey and why Watsonx Orchestrate, paired with Octane’s expertise, is the future of work.  

As we close out 2024, a year that has been revolutionary for AI adoption, let’s pause to reflect on the data driving this transformation. Companies have spent 2023-2024 experimenting with generative AI, deploying AI assistants, and running pilots, many of which have evolved into concrete plans for 2025. Now, the focus shifts to finding the right partner to turn these blueprints into reality. 

These statistics aren’t just metrics; they prove that AI is fulfilling its promise to amplify productivity while elevating outcomes. Here’s how Watsonx Orchestrate’s AI agents are reshaping enterprises: 

1. Enhanced User Experience 
   
   AI agents deliver intelligent, multi-turn conversational experiences that solve complex tasks seamlessly. For instance, integrating Watsonx Orchestrate with tools like IBM Planning Analytics (TM1) allows finance teams to automate data reconciliation while maintaining compliance.

2. Reduced Total Cost of Ownership (TCO) 
   
   By leaning on AI to automate tasks at scale, enterprises cut costs while boosting efficiency. Watsonx Orchestrate’s pre-built Skills and low-code studio let businesses extend existing Gen AI investments—like chatbots or co-pilots—without overhauling systems.

3. Agility & Future-Proof Flexibility 
   
   AI agents enable organisations to pivot rapidly as markets shift. With Watsonx Orchestrate’s autonomous orchestration, businesses adapt workflows in real-time, whether rerouting customer inquiries during peak demand or updating financial forecasts using TM1.

If below is what you are thinking: 

• How do you integrate AI agents into your existing digitised workflows?
• How do you maximise ROI from current AI tools?
• How do you retain control as AI evolves?

Octane: Is Your Partner for Scaling Customer-Centric AI

While many providers offer AI tools, Octane stands apart as a force for customer-centric innovation. Here’s why: 

We don’t believe in one-size-fits-all solutions. Together with IBM, Octane’s team works side-by-side with clients to:

• Map AI use cases to your unique customer journey.
• Integrate Watsonx capabilities with niche tools  
• Prioritise ethical AI practices, ensuring transparency and trust at every interaction. 

Octane: Delivering Real-World Impact with Watsonx Orchestrate—An Airline’s Journey to AI-Driven Intelligence 

Let’s cut through the hype and dive into a tangible example of how IBM Watsonx Orchestrate, implemented by Octane, transformed operations for a global airline—a case study that exemplifies the platform’s power to turn data chaos into strategic clarity. 

The Challenge: Manual Mayhem in Business Intelligence 

The airline’s Business Intelligence (BI) and Finance teams were drowning in manual processes: 

• 2-3 days wasted monthly on report generation, with analysts manually cleaning, reconciling, and validating data in IBM Planning Analytics (TM1).
• Knowledge bottlenecks: Executives relied on BI teams for real-time insights during critical meetings, creating delays and frustration.
• Human errors: Manual calculations led to costly rework, while commercial decisions were stalled by a 3-week data validation cycle. 

The stakes? Missed deadlines, strained resources, and executives flying blind in a competitive market. 

The Solution: Watsonx Orchestrate in Action

Octane partnered with the airline to integrate Watsonx Orchestrate with their existing IBM Planning Analytics deployment. In just two weeks, we automated workflows and unleashed AI-driven efficiency:

Automated Data Cleaning & Reconciliation 

• AI-Powered Automation: 

• Manual data cleaning reduced from 2-4 days/month to minutes. 

• Data reconciliation slashed from 3-4 hours/month to 1 minute. 

• Self-Correcting Workflows: 
  Watsonx Orchestrate’s AI agents flagged inconsistencies, auto-corrected errors, and validated datasets, ensuring 99% accuracy in financial reports. 

Empowering Executives with NLP-Driven Insights

• Natural Language Queries: 
  Executives could now ask, “Show me Q3 revenue trends vs. forecasts” in plain language. Watsonx Orchestrate generated real-time insights, reducing reliance on BI teams by 90%. 

• Faster Decisions: 
  Monthly reports that once took 2-3 days were generated in 10 minutes, accelerating commercial decisions from weeks to hours. 

Eliminating Knowledge Silos

• Democratized Data Access: 
  By codifying tribal knowledge into AI workflows, the airline mitigated key-person risk and ensured continuity during staff turnover. 

• Scalable Governance: 
  Octane embedded compliance checks into automated processes, aligning with IBM’s enterprise-grade LLMs for audit-ready outputs. 
  

Business Outcomes: From Friction to Flight 

"With Octane and Watsonx Orchestrate, we’re not just surviving data chaos—we’re soaring above it." - Fortune 500 Airline Client

Three Pathways to AI Transformation 

1. Test-drive Watsonx Orchestrate on our dedicated platform  

2. Client Briefing: Dive deep into a 2-4 hour session to align AI strategy with your goals.

3. Pilot Program: Co-develop a 1-4 week proof-of-concept with Octane’s AI engineers. 

The Future is Autonomous—Let’s Build It Together

Reflecting back on the event, the energy in the room was infectious. Attendees left inspired by Watsonx Orchestrate’s ability to blend autonomous AI with human ingenuity. By automating the mundane, enhancing precision, and scaling seamlessly, this platform isn’t just a tool—it’s a productivity revolution. 

As I begin my journey with Octane, I’m energised by the possibilities. Whether you’re optimising finance with TM1, Anaplan, transforming employee productivity with SAP, or reimagining customer service with Salesforce / ServiceNow, IBM Watsonx Orchestrate—powered by Octane—is your catalyst for growth. The future of enterprise productivity isn’t just automated—it’s augmented. With AI Agents handling the grind, your team can focus on what humans do best: innovating, strategising, and delivering exceptional value.

Ready to turn your 2025 AI vision into reality?

Contact Octane to discover how Watsonx Orchestrate can accelerate your journey—with the stats to back it up. 

Steny Sebastian
Principal - Data and AI Platforms
Octane Solutions 🗓️ Book me
https://www.octanesolutions.com.au/

In today’s fast-paced business environment, companies are constantly looking for ways to streamline their operations, improve decision-making, and stay ahead of the competition. One of the tools that has gained significant attention in the world of business intelligence and analytics is IBM Planning Analytics, which harnesses the power of AI to enhance financial planning, forecasting, and reporting. One of the standout features of IBM Planning Analytics is its AI Assistant, an innovative tool that leverages artificial intelligence to provide smarter, more efficient planning and analytics capabilities.

In this blog, we’ll dive into the key features of the IBM Planning Analytics AI Assistant and explore how it is transforming business planning for organisations around the world.

What is IBM Planning Analytics AI Assistant?

IBM Planning Analytics is a cloud-based solution designed to help businesses automate their planning, budgeting, forecasting, and analysis processes. The AI Assistant embedded within the platform brings cognitive capabilities to the table, making it more intuitive and user-friendly.

The AI Assistant uses natural language processing (NLP) and machine learning algorithms to understand and respond to user queries in plain language, enabling business users—whether financial analysts, planners, or executives—to interact with the system more naturally. Instead of relying on complex formulas or spending hours running reports, users can simply ask questions like, "What was our sales growth in Q3?" or "How much did our expenses increase year-over-year?" The AI Assistant then processes these requests and provides quick, data-driven insights.

Key Features of IBM Planning Analytics AI Assistant

1. Conversational analytics

   One of the most impressive features of the AI Assistant is its ability to enable conversational analytics. Traditionally, getting insights from business intelligence tools involved navigating through multiple layers of data, setting up reports, or writing complex queries. The AI Assistant eliminates this complexity by allowing users to ask questions in natural language, just like they would talk to a colleague or consultant.

   For example, a user can ask, "What were our sales for last quarter?" and the AI Assistant can instantly pull up relevant data, graphs, or reports. This conversational interface makes it easier for non-technical users to engage with analytics and access valuable insights without having to be data experts.

2. Data-driven decision-making

   The AI Assistant doesn’t just provide static answers—it actively helps users analyse trends, identify anomalies, and make data-driven decisions. For instance, the Assistant can compare historical data, identify seasonal patterns, and even suggest potential adjustments to forecasts based on changing market conditions. This empowers decision-makers to quickly assess different scenarios and make informed choices.

   Additionally, the Assistant can provide context behind the data, such as explanations of why certain numbers are trending upward or downward. This deeper level of understanding enables organisations to plan with greater confidence.

3. Predictive analytics and forecasting

   In addition to assisting with retrospective analysis, the AI Assistant is also equipped to help users with predictive analytics. Using historical data, market trends, and other variables, the Assistant can generate forecasts for various business aspects like sales, revenue, and operational costs.

   For instance, planners can ask the AI Assistant, "What is the projected revenue for the next quarter based on current trends?" The Assistant then leverages machine learning models to provide accurate, forward-looking forecasts. By incorporating AI-driven insights, businesses can improve their planning accuracy and reduce the risks associated with manual forecasting.

4. Automated insights and recommendations

   One of the standout benefits of AI in business planning is its ability to go beyond simple reporting. The IBM Planning Analytics AI Assistant is capable of delivering automated insights and recommendations that are tailored to the needs of the organisation. By analysing past performance, the Assistant can highlight areas of opportunity or potential risk that may require attention.

   For example, if expenses are increasing faster than revenue, the Assistant might recommend strategies for cost-cutting or optimising operations. These automated recommendations allow planners and analysts to quickly address potential issues and capitalise on emerging opportunities.

5. Seamless integration with IBM Planning Analytics Workspace

   The AI Assistant is fully integrated with the IBM Planning Analytics Workspace, which is the central hub for business users to manage and analyse data. This integration ensures that users have a smooth experience when interacting with their data, whether they are leveraging the AI Assistant for ad-hoc analysis or using the broader tools available in Planning Analytics for long-term strategic planning.

   The seamless integration between the Assistant and the workspace also means that businesses can continue to rely on traditional data management and reporting workflows while taking advantage of AI-powered insights without disruption.

Benefits of IBM Planning Analytics AI assistant

• Faster Decision-Making

  The AI Assistant accelerates decision-making by delivering insights in real-time. Users can ask questions and get answers instantly, without having to manually sift through large datasets or run complex queries. This speeds up planning cycles and ensures that decisions are based on the latest data.

• Empowerment of Business Users

  With the AI Assistant, business users who may not have deep technical expertise can now access analytics and make informed decisions. This democratisation of data ensures that all teams—finance, marketing, operations—are equipped to contribute to planning processes and drive organisational success.

• Reduced Errors

  Since the AI Assistant uses machine learning models to predict and analyse data,  the likelihood of human error in forecasting and planning is significantly reduced. Automated insights and recommendations are based on sophisticated data analysis, helping to eliminate mistakes caused by manual data handling.

• Scalable Insights Across Teams

  The AI Assistant enables businesses to scale their analytics capabilities across teams and departments. Whether a team is working on financial forecasts, sales targets, or operational efficiencies, the Assistant can be used to generate insights that are relevant to each department’s specific goals and objectives. This scalability ensures that AI-powered decision-making benefits the entire organisation.

Real-World Use Cases

1. Finance Teams

   For finance teams, the AI Assistant is a game-changer in managing budgets, forecasting, and scenario planning. It can quickly identify deviations from expected results, recommend corrective actions, and forecast the financial outlook based on real-time data.

2. Sales and Marketing Teams

   Sales and marketing teams can use the Assistant to gain quick insights into customer behaviour, sales trends, and marketing ROI. By understanding which campaigns are driving results and which aren’t, they can adjust strategies on the fly and optimise their efforts.

3. Operations and Supply Chain

   Operations managers can use the AI Assistant to forecast demand, optimise inventory, and predict potential supply chain disruptions. By understanding these dynamics earlier, businesses can mitigate risks and improve operational efficiency.

Conclusion

The IBM Planning Analytics AI Assistant represents a significant leap forward in the world of business analytics. By combining artificial intelligence, natural language processing, and predictive analytics, it transforms the way businesses plan, forecast, and make decisions. With its ability to provide faster insights, automate recommendations, and empower users across the organisation, the AI Assistant is not just a tool—it’s a strategic asset that helps businesses become more agile and data-driven in their operations.

As businesses continue to face increasingly complex challenges, tools like IBM Planning Analytics AI Assistant will become indispensable for navigating the future of planning and decision-making.

Ready to take AI to the next level? Talk to us! 

The world of finance is evolving rapidly, and AI is no longer a futuristic concept—it’s a practical tool that can transform how finance teams operate. But for many organisations, the idea of integrating AI into their workflows can feel overwhelming. Where do you start? How do you ensure success? The answer lies in taking a gradual, strategic approach. With Watson Orchestrate and IBM Planning Analytics, you can start small, prove the value, and confidently scale your AI initiatives. At Octane, we guide you through this journey, from exploring use cases to delivering impactful projects.

 

Why Start Small with AI in Finance? 

AI has the potential to revolutionise finance by automating repetitive tasks, enhancing decision-making, and improving accuracy. However, diving headfirst into a full-scale AI implementation can be risky. Starting small allows you to test the waters, build confidence, and demonstrate tangible results before committing to larger investments. This is where Watson Orchestrate shines—it’s designed to integrate seamlessly with your existing tools, like IBM Planning Analytics, and automate specific tasks without disrupting your workflows. 

Step 1: Explore Use Cases with Octane’s Workshops 

The first step in your AI journey is identifying where it can add the most value. We work closely with IBM client engineering team and run interactive workshops to help you explore potential use cases for Watson Orchestrate within your finance team. These workshops are designed to: 

• Understand Your Pain Points: We work with your team to identify repetitive, time-consuming tasks that are ripe for automation, such as data consolidation, report generation, or budget reconciliation. 

• Brainstorm Solutions: Together, we brainstorm how Watson Orchestrate can address these challenges, leveraging its AI capabilities to automate processes and enhance efficiency. 

• Prioritise Opportunities: Not all use cases are created equal. We help you prioritise the ones that offer the quickest wins and the highest impact. 

Step 2: Prove the Value with a Proof of Concept (POC) 

Once we’ve identified promising use cases, the next step is to validate them through a Proof of Concept (POC). A POC allows you to see Watson Orchestrate in action, delivering real results in a controlled environment. Here’s how it works: 

• Define Success Metrics: We work with you to define clear objectives and success metrics for the POC, ensuring that the results are measurable and aligned with your goals. 

• Build and Test: Our team builds the POC, integrating Watson Orchestrate with IBM Planning Analytics to automate the selected use case. We test the solution rigorously to ensure it meets your requirements. 

• Evaluate Results: After the POC, we evaluate the results together. Did it save time? Improve accuracy? Enhance productivity? These insights help you decide whether to move forward with a full-scale implementation. 

Step 3: Deliver the Project and Scale 

If the POC demonstrates value, we move into the  project delivery phase. Our team works closely with yours to implement the solution, ensuring it’s tailored to your specific needs and integrated seamlessly into your workflows. Once the initial project is delivered, you can scale the solution to address additional use cases, gradually expanding the role of AI in your finance operations. 

Real-World Impact: A Gradual Approach to AI 

Many organisations have successfully adopted AI in finance by starting small and scaling strategically. For example, an airline participated in one of Octane’s workshops and identified report generation as a key pain point. Through a POC, they automated the process using Watson Orchestrate, reducing the time required from 2 days to just 30 minutes. Encouraged by the results, they expanded the solution to automate budget reconciliation, achieving even greater efficiencies. 

Why Choose Octane? 

At Octane, we specialise in helping organisations like yours navigate the complexities of AI adoption in Finance teams. Our phased approach—starting with workshops, moving to POCs, and then delivering projects—ensures that you can dip your toes into AI without taking on unnecessary risk. We bring deep expertise in Watson Orchestrate and IBM Planning Analytics, along with a commitment to delivering measurable results.  

Take the First Step Today 

AI is no longer a distant dream—it’s a practical tool that can transform your finance team. By starting small with Watson Orchestrate and IBM Planning Analytics, you can explore the potential of AI, prove its value, and scale your initiatives with confidence. Ready to get started? Contact Octane today to schedule a workshop and begin your AI journey. Email us at  media@octanesolutions.com.au  to learn more. 

The future of finance is AI-powered, and the journey starts with a single step. Let Octane guide you every step of the way. 

Today, we’re excited to explore a game-changing function that enhances the versatility of your Planning Analytics platform. Imagine a tool that not only streamlines your data processes but also connects your Planning Analytics seamlessly with external systems. This innovation allows you to execute HTTP requests directly within your TurboIntegrator (TI) processes, transforming your Planning Analytics into an integral part of your interconnected ecosystem. Join us as we delve into the possibilities this function brings and how it can elevate your data management strategies to new heights.

Why Execute HTTP Request is a Game-Changer

What makes this function truly versatile is its ability to connect with any external system that supports APIs. The only limit is your imagination and the capabilities of the APIs you wish to connect to. Integrating Planning Analytics with external systems allows developers to break free from traditional limitations and extend the functionality of their applications.

This session will include practical demonstrations of several use cases that highlight the power of the Execute HTTP Request. By the end, I hope to inspire you to explore how you can leverage this function to enhance your TM1 applications and workflows.

Demo 1: Hot Promotion of Objects Between Instances

Let's dive into our first demonstration on how to perform hot promotion of objects from one instance to another. Traditionally, migrating objects between instances involved shutting down the target server. However, using the Execute HTTP Request, we can do this in real-time.

1. Setting Up the TI Process:
    
   • Open the workbench in your workspace and create a new TI process.
   • Declare necessary constants and set your source and target instances (e.g., SmartCo to Demo Server).
2. Use of HTTP Execute Request:
    
   • Fetch dimensions from the source instance and check for their existence in the target instance.
   • For non-existing dimensions, save them as JSON files and use the HTTP Execute Request to migrate them to the target instance.

Let’s execute this process! Once completed, you’ll see that the dimensions have been successfully migrated.

Demo 2: Executing a Process Across Instances

Next, we'll demonstrate the ability to execute a process from one instance in another:

1. Migrate TI Processes:
    
   • Similar to dimension migration, retrieve the TI process (like Sample TI) from the source instance and save it as a JSON file.
2. Execute the TI Process:
    
   • Use the Execute HTTP Request to trigger execution from the target instance while utilising its response to capture status codes and log outputs.

After running this process, you should see that both the processes have been migrated and executed successfully.

Demo 3: Loading Currency Conversion Rates

In this demo, we will load real-time currency conversion rates from a website using its API:

1. Call the API:
    
   • Set up an HTTP GET request to retrieve USD conversion rates.
2. Extract and Utilise Data:
    
   • Capture the JSON response and extract required currency rates using JSON functions.

Run the process, and you will observe the real-time conversion rates being fetched and displayed.

Demo 4: Sending Teams Notifications

Next, I’ll show you how to send automated notifications to Microsoft Teams:

1. Integrate with Microsoft Power Automate:
    
   • Set up a Power Automate flow to send notifications.
2. Trigger Notification from System:
    
   • Use Execute HTTP Request to trigger alerts in Teams based on process execution results.

After execution, you should see notifications appear in your Teams channel.

Demo 5: Sending Emails via HTTP Requests

Finally, we'll explore how to send emails:

1. Power Automate for Email Notifications:
    
   • Again, set up Power Automate to manage email sending through appropriate HTTP requests.
2. Dynamic Email Content:
    
   • Utilise dynamic fields for subject and body based on execution results.

After executing this process, you will receive the email in your mailbox.

Conclusion

Today, we have unlocked the extensive capabilities of the Execute HTTP Request function in IBM Planning Analytics. We showcased hot promotion between instances, cross-instance process execution, real-time data fetching, as well as integration with Microsoft Teams and email notifications. 

Thank you all for attending this session. I hope you found it beneficial and feel inspired to explore the functionality of Planning Analytics further. Let’s move toward a more integrated and dynamic future in our analytics processes!

The holiday season is a time for joy, relaxation, and quality time with loved ones. However, for many finance teams, it’s also a period of intense activity. Year-end closings, budgeting, and reporting deadlines can pile up, creating a stressful and demanding environment.

Imagine spending your holiday season worrying about potential system outages, data load failures, or urgent user queries. It’s a scenario that can disrupt your well-deserved break and compromise your team’s productivity.

Leverage Dedicated TM1 Support During the Holidays

• Engage a reliable TM1 support partner to handle system maintenance, troubleshooting, and year-end processes so your team can enjoy a well-deserved break without stress.

Automate Routine Tasks and Processes in TM1

• Use TM1’s automation capabilities to schedule recurring tasks like data loads, reconciliations, and report generation, ensuring everything runs smoothly while minimizing manual effort.

Ensure Proactive Monitoring and Downtime Prevention

• A TM1 support team can proactively monitor your environment, identify potential issues before they escalate, and ensure critical systems remain up and running during the festive season.

Outsource Last-Minute Reporting and Forecasting Support

• Avoid scrambling to meet year-end deadlines by outsourcing TM1 reporting tasks to a team that can handle changes, corrections, and urgent requests with expertise and speed.

Plan Ahead with a Holiday Support Coverage Model

• Partner with a TM1 managed services provider who offers holiday-specific coverage, ensuring your team has access to skilled resources when needed, without disrupting workflows or personal time.

Why TM1 support (Octane Blue) is the Perfect Solution 

That’s where Octane Blue comes in. Our comprehensive support service is designed to alleviate your holiday stress and ensure business continuity. With 40 hours of dedicated support, you can rest easy knowing that your TM1 environment is in expert hands.

What Does Octane Blue Offer? 

1. Proactive System Monitoring: Our team will keep a watchful eye on your TM1 environment, identifying and resolving potential issues before they escalate. 

2. Rapid Incident Response: Should any issues arise, our experienced support engineers will be on hand to diagnose and fix them promptly. 

3. Data Load and Reconciliation Support: We’ll assist with data load processes, ensuring accurate and timely data integration.

4. Security and Access Management: Our team will help maintain the security of your TM1 environment and manage user access rights. 

5. Security and Access Management: Our team will help maintain the security of your TM1 environment and manage user access rights.

6. Technical and Functional Support: We’ll provide expert guidance on a wide range of TM1 topics, from technical troubleshooting to functional best practices.

7. User Support: Our team will be available to assist your users with any questions or issues they may encounter. 

Frequently Asked Questions

How many hours of support are included in Octane Blue? 

• 40 hours. 

What happens if I don’t use all 40 hours during the festive season? 

• Unused hours will be rolled over for one additional month. 

Do I need to be an existing Octane client to sign up for Octane Blue? 

• No, Octane Blue is available on any TM1 site. 

Do I need to sign a long-term contract? 

• No, you can purchase Octane Blue on a one-time basis or as needed. 

How much does Octane Blue cost? 

• https://www.octanesolutions.com.au/tm1-support#switch

How do I purchase Octane Blue? 

• Purchase now

Can I schedule a meeting to discuss Octane Blue further? 

• Book a meeting with us

Don’t let the holiday season stress you out. Let Octane Blue take care of your TM1 environment so that you can enjoy a peaceful and productive holiday. 

The past few weeks have been a whirlwind, a high stakes balancing act that tested the limits of our team's resilience and expertise. We simultaneously managed two major client migrations. Both were for high profile large clients and part of their IBM Planning Analytics Modernisation initiative:

The clients

News Corp - News Corp Australia tells the stories that matter to 18.2 million Australians every month as an important part of News Corp, a diversified global media and information services company. From breaking news in the morning to deciding dinner that night, Australia trusts our brands to inform, inspire and delight across the day – including The Australian, The Daily Telegraph, Herald Sun, The Courier-Mail, The Advertiser, Mercury, NT News, Townsville Bulletin, The Cairns Post, Gold Coast Bulletin, Geelong Advertiser, news.com.au, Vogue, GQ, Kidspot, taste.com.au and plenty more. More here https://www.newscorpaustralia.com/

A long-time TM1 user was looking at refreshing its application and modernise it by going to the cloud and utilising new dashboarding capabilities of the workspace and starting some testing on AI capabilities for the Finance team. TM1 is one of the core applications within the Finance team and they could not afford to run the risk of a prolonged upgrade to the cloud.

BlueScope They are a global leader in metal coating and painting products for the building and construction industries, providing vital components for houses, buildings, structures, vehicles, and more.

They have built a solid foundation for growth with a diverse portfolio of businesses in some of the largest and fastest-growing economies of the world. They are headquartered in Australia, with our people and operations spread across North America, Australia, New Zealand, the Pacific Islands, and throughout Asia. More here https://www.bluescope.com/

BlueScope is also a long-term TM1 user with the application used for a number of areas including demand planning, forecasting and Reporting in the Finance teams. They were on an older version of on–prem TM1 and upgrading to the latest version of on-prem IBM Planning Analytics TM1

A Perfect Storm

Both projects presented unique challenges. NEWS's migration required significant user training and change management, while BlueScope's upgrade involved complex technical configurations and intricate coordination with multiple stakeholders. To make matters even more challenging, both go-lives were scheduled for the same day!

Overcoming the Odds

How did we navigate this perfect storm?

• Strong Leadership: Clear and decisive leadership was crucial in keeping the projects on track. By setting clear expectations, prioritising tasks, and making timely decisions, we were able to mitigate risks and ensure smooth execution.
• Effective Teamwork: Our team demonstrated exceptional teamwork and collaboration. By working closely together, we could share knowledge, support each other, and address challenges proactively.
• Agile Methodology: We adopted an agile approach, breaking down the projects into smaller, manageable phases. This allowed us to adapt to changing circumstances and deliver value incrementally. We have built up a comprehensive checklist for our upgrade TM1 upgrades and this makes upgrades easier and risk free.
• Robust Communication: Open and transparent communication was key to keeping all stakeholders informed and aligned. Regular status updates, clear documentation, and effective problem-solving ensured a smooth transition.

Lessons Learned

These experiences have taught us valuable lessons:

• Prioritise and Plan: Careful planning and prioritization are essential, especially when managing multiple projects simultaneously.
• Embrace Flexibility: Be prepared to adapt to unexpected challenges and changes in scope.
• Build Strong Relationships: Strong relationships with clients and team members are crucial for successful project delivery.
• Learn from Mistakes: Analyse past projects to identify areas for improvement and avoid repeating errors.

Successful outcomes for both clients

The upgrade was successful for both clients and went live on the same day. This was a testament to my team’s technical ability and tenacity to ensure we followed our upgrade checklist. All testing and end-user training went well. One of our key tenets of upgrades is to ensure that client communication around changed functionality and look and feel is explained, trained and tested. The stakeholders from our client side were great and the whole team went above and beyond during the upgrade and deployment.

Both the upgrade took under 6 weeks to complete with minimal disruption to the business.

A huge shoutout goes to Alpheus and Rajan for their stellar work on the NEWS migration, ensuring a smooth transition to the Cloud, and to Baburao for expertly managing the BlueScope upgrade, and overcoming every hurdle that came our way.

Your Turn

Have you faced similar challenges in managing multiple simultaneous projects? How did you overcome them? Share your experiences and insights in the comments below.

If you are looking to modernise or upgrade your IBM Planning Analytics, then contact us and we would be happy to guide you. 

Attending IBM TechXchange in Mandalay Bay, Las Vegas was an exhilarating experience that showcased the cutting-edge IBM technologies shaping various industries today. The conference brought together technologists, IBM Champions, thought leaders, industry experts, and innovators eager to share insights and explore the latest advancements in IBM's technology portfolio. From AI to cloud computing, the event highlighted how these tools are transforming businesses, making operations more efficient, and ultimately driving better decision-making.

As an IBM champion we were treated as VIPs with row seats in all keynote sessions, special champions lounge and special dinners and networking sessions. It was great to see IBM champions sporting the blue jackets throughout the conference.

One of the standout moments for me was the opportunity to present alongside Ashika Singh from Fiji Airways. Our session focused on their usage of IBM Planning Analytics, which allowed Fiji Airways to navigate the challenges posed during the COVID-19 shutdown. The pandemic created unprecedented obstacles for the airline industry, with travel restrictions and safety concerns leading to a dramatic decline in passenger numbers. However, Fiji Airways leveraged IBM Planning Analytics to make data-driven decisions that prepared them for the eventual reopening of global travel.

During our presentation, we shared how the airline utilised forecasting and scenario planning capabilities in the tool to assess various outcomes and devise strategies for recovery. By analysing all drivers and generating up to 60- what-if scenarios at a time, Fiji Airways was able to predict future demand and align their resources accordingly. This proactive approach not only ensured they were ready when the skies reopened but also positioned them to adapt quickly to changing circumstances, ultimately enhancing their resilience. This led to numerous awards and Fiji Airways is now ranked 14^th in the world in Skytrax ranking 2024. They have overtaken Qantas and Air New Zealand which traditionally dominated the rankings in the region.

The discussions throughout the conference were incredibly enlightening. Industry leaders spoke about the importance of digital transformation and how organizations must prioritise agility and innovation to thrive in today's fast-paced environment. There was a strong emphasis on how leveraging AI and analytics can unlock new opportunities, streamline operations, and create a more personalized customer experience. These insights resonate deeply, especially in sectors like travel and hospitality that have been profoundly affected by global events.

Networking opportunities were plentiful at TechXchange, allowing me to connect with other professionals who share a common goal of harnessing technology for business growth. Conversations flowed about the challenges and triumphs faced during the pandemic, highlighting how collaboration and knowledge-sharing have played vital roles in overcoming adversity. Each conversation reinforced the idea that we are all part of a larger community that supports each other's journeys toward transformation. There were lots of opportunities to network with other TM1 specialists from around the world.

The event was also filled with hands-on labs and demonstrations, showcasing IBM's latest products and solutions. Exploring new functionalities and engaging with the technology firsthand enhanced my understanding of how these tools can be applied in various contexts. It was exciting to envision how businesses can harness these innovations to optimize their operations and improve overall performance. IBM also used the conference to announce the launch of the Granite 3.0 AI model. (Read more here Granite 3.0)

Looking back on my experience at IBM TechXchange, I am inspired and optimistic about the future. Planning Analytics has a range of new functionality to improve performance, deployment options and integration of IBM AI onto the platform will cement its position as a leader in the XP&A space. Presenting with Ashika was a highlight that illustrated not only the adaptability of Fiji Airways but also the potential of data-driven decision-making for all of our clients. There was a lot of interest in how we integrate Watson Orchestrate with Planning Analytics to boost the AI functionality in finance teams.

In conclusion, attending IBM TechXchange has provided a great platform to see where IBM is going in the future – and it's looking exciting. As AI becomes more mainstream and use cases continue to evolve it was interesting to see how our peers and IBM are harnessing this technology to deliver business value for clients. The dates for 2025 Techxchange in Orlando are already announced and Octane will once again attend along with our clients. (More details IBM Techxchange conference)

 

 

Planning Analytics Workspace (PAW) offers a robust suite of visualizations, enabling users to create rich and compelling reports and dashboards with remarkable flexibility. However, even with these capabilities, you may occasionally encounter requirements that push the limits of what PAW provides out of the box. 

One such scenario I encountered was the need to create a column chart comparing Actual vs Budget variance. The twist? Any negative variance should be highlighted with a red bar, while positive variance should be displayed in green, as shown below: 

PAW’s default settings don't currently offer this kind of custom conditional formatting for visualizations. However, with a little MDX magic and a few formatting tweaks, you can achieve this effect in just five simple steps. 

Step-by-Step Guide to Creating Custom Visualizations in PAW 

Step 1: Position the Version Dimension in the Column 

Start by positioning the Version dimension in the column of the Exploration view. This is where we will apply the MDX logic to derive the desired results. 

Step 2: Use MDX to Create Calculated Members 

Next, you'll need to update the MDX query by creating three calculated members to represent Actual vs Budget (AvB), Positive Variance, and Negative Variance. 

Here’s the MDX code: 

MDX code: 

WITH  

MEMBER [Version].[Version].[AvB] AS [Version].[Version].[Actual] - [Version].[Version].[Budget]  

MEMBER [Version].[Version].[Positive] AS IIF([Version].[Version].[AvB] > 0, [Version].[Version].[AvB], "") 

MEMBER [Version].[Version].[Negative] AS IIF([Version].[Version].[AvB] < 0, [Version].[Version].[AvB], "") 

Note: The AvB calculation could also be done using a consolidated member in the Version dimension, where the Budget has a negative weight. 

Step 3: Replace the MDX in the Row Axes 

Now, replace the MDX in the Row Axes relating to the Version dimension to show only the Positive and Negative calculated members, while excluding the AvB calculation (and any other member): 

MDX code: 

{ 

    EXCEPT( 

        { 

            [Version].[Version].[AvB], 

            [Version].[Version].[Positive], 

            [Version].[Version].[Negative] 

        },  

        { 

            [Version].[Version].[AvB] 

        },  

        ALL 

    ) 

} 

This MDX will generate a view that displays only Positive and Negative members in the Version dimension, leaving the non-relevant member (whether positive or negative) as blank, depending on the AvB value. 

Step 4: Convert the Exploration View into a Column Chart

Once the MDX has been applied, convert the Exploration view into a Column Chart. By default, PAW will show the columns for positive and negative values with its standard color scheme.  

 

Step 5: Apply a Custom Color Palette 

To finalize the visualization, we’ll apply a custom color palette. Navigate to the visualization properties and create a color palette that includes only two colors: green for positive values and red for negative values. 

Conclusion 

With just a few lines of MDX and a bit of customization, you can significantly enhance PAW visualizations. This technique allows you to move beyond the standard out-of-the-box options, giving you the flexibility to create more intuitive and visually effective reports. Whether you're comparing Actual vs Budget or any other metrics, these methods help you build visuals that not only convey the necessary information but do so in a way that is easy to interpret at a glance. 

By leveraging MDX and PAW’s formatting tools, you can push the boundaries of your reporting and create dynamic, insightful dashboards tailored to your business needs. 

 

In this blog post, we will showcase the process of exposing the transaction logging on Planning Analytics (PA) V12 on AWS to the users. Currently, in Planning Analytics there is no user interface (UI) option to access transaction logs directly from Planning Analytics Workspace. However, there is a workaround to expose transactions to a host server and access the logs. By following these steps, you can successfully access transaction logged in Planning Analytics V12 on AWS using REST API.

Step 1: Creating an API Key in Planning Analytics Workspace

The first step in this process is to create an API key in Planning Analytics Workspace. An API key is a unique identifier that provides access to the API and allows you to authenticate your requests.

1. Navigate to the API Key Management Section: In Planning Analytics Workspace, go to the administration section where API keys are managed.
2. Generate a New API Key: Click on the option to create a new API key. Provide a name and set the necessary permissions for the key.
3. Save the API Key: Once the key is generated, save it securely. You will need this key for authenticating your requests in the following steps.

Step 2: Authenticating to Planning Analytics As a Service Using the API Key

Once you have the API key, the next step is to authenticate to Planning Analytics as a Service using this key. Authentication verifies your identity and allows you to interact with the Planning Analytics API.

1. Prepare Your Authentication Request: Use a tool like Postman or any HTTP client to create an authentication request.
2. Set the Authorization Header: Include the API key in the Authorization header of your request. The header format should be Authorization: Bearer <API Key>.
3. Send the Authentication Request: Send a request to the Planning Analytics authentication endpoint to obtain an access token.

Detailed instructions for Step 1 and Step 2 can be found in the following IBM technote:

How to Connect to Planning Analytics as a Service Database using REST API with PA API Key

Step 3: Setting Up an HTTP or TCP Server to Collect Transaction Logs

In this step, you will set up a web service that can receive and inspect HTTP or TCP requests to capture transaction logs. This is crucial if you cannot directly access the AWS server or the IBM Planning Analytics logs.

1. Choose a Web Service Framework: Select a framework like Flask or Django for Python, or any other suitable framework, to create your web service.
2. Configure the Server: Set up the server to listen for incoming HTTP or TCP requests. Ensure it can parse and store the transaction logs.
3. Test the Server Locally: Before deploying, test the server locally to ensure it is correctly configured and can handle incoming requests.

For demonstration purposes, we will use a free web service provided by Webhook.site. This service allows you to create a unique URL for receiving and inspecting HTTP requests. It is particularly useful for testing webhooks, APIs, and other HTTP request-based services.

Step 4: Subscribing to the Transaction Logs

The final step involves subscribing to the transaction logs by sending a POST request to Planning Analytics Workspace. This will direct the transaction logs to the web service you set up.

Practical Use Case for Testing IBM Planning Analytics Subscription

Below are the detailed instructions related to Step 4:

1. Copy the URL Generated from Webhook.site:
   • Visit siteand copy the generated URL (e.g., https://webhook.site/<your-unique-id>). The <your-unique-id> refers to the unique ID found in the "Get" section of the Request Details on the main page.

2. Subscribe Using Webhook.site URL:
   • Open Postman or any HTTP client.
   • Create a new POST request to the subscription endpoint of Planning Analytics.
   • In Postman, update your subscription to use the Webhook.site URL using the below post request:

• In the body of the request, paste the URL generated from Webhook.site:

{
 "URL": "https://webhook.site/your-unique-id"
}
<tm1db> is a variable that contains the name of your TM1 database.

Note: Only the transaction log entries created at or after the point of subscription will be sent to the subscriber. To stop the transaction logs, update the POST query by replacing /Subscribe with /Unsubscribe.

By following these steps, you can successfully enable and access transaction logs in Planning Analytics V12 on AWS using REST API.

In the realm of digital transformation, the concept of digital labor has emerged as a game-changer for businesses seeking efficiency, agility, and innovation. IBM WatsonsX Orchestrate, a powerhouse in the AI and data orchestration space, takes center stage in this digital evolution. This blog explores the pivotal role played by WatsonsX Orchestrate in reshaping digital labor and how it empowers organizations to harness the full potential of artificial intelligence (AI) and data science.

Orchestrate allows you to add and train new automations from a variety of sources, enabling users to easily work across existing systems using a single UI.

 

Understanding Digital Labor:

Digital labor refers to the use of digital technologies, including AI, automation, and robotics, to augment or replace human tasks and processes. It's a paradigm shift in how work is done, leveraging technology to enhance productivity, reduce errors, and enable humans to focus on more strategic and creative aspects of their roles.

"Companies that effectively apply intelligent automation across the enterprise expect to outshine peers in profitability, revenue growth, and efficiency over the next 3 years."

IBM WatsonsX Orchestrate and Digital Labor:

1. Workflow Automation for Operational Efficiency: One of the key pillars of digital labor is workflow automation, and WatsonsX Orchestrate excels in this domain. By automating intricate AI and data science workflows, the platform significantly reduces manual effort, streamlining processes and enhancing operational efficiency. This allows organizations to accomplish more with less, freeing up human resources for high-value tasks.

2. Collaboration for Enhanced Productivity: Digital labor is not about replacing human workers but augmenting their capabilities. WatsonsX Orchestrate fosters collaboration among cross-functional teams, bringing together data scientists, developers, and domain experts. This collaborative environment accelerates problem-solving, decision-making, and innovation, creating a synergistic relationship between digital labor and human expertise.

3. Scalability to Meet Growing Demands: As organizations scale their digital labor initiatives, scalability becomes a critical factor. WatsonsX Orchestrate provides the flexibility to scale horizontally and vertically, ensuring that the platform can seamlessly adapt to the growing demands of AI and data science projects. This scalability is essential for organizations aiming to expand their digital labor capabilities without compromising performance.

4. Model Monitoring and Management for Continuous Improvement: In the era of digital labor, continuous improvement is paramount. WatsonsX Orchestrate includes robust tools for monitoring and managing AI models in production. This ensures that digital labor processes based on AI models deliver consistent and reliable results over time. The platform's capabilities contribute to the iterative refinement of digital labor processes, optimizing outcomes and enhancing overall performance.

5. AI Explainability and Ethical Digital Labor: Transparent digital labor practices are crucial for building trust and ensuring ethical use of AI. WatsonsX Orchestrate provides tools for explaining AI model decisions, addressing the interpretability challenge often associated with complex AI systems. Additionally, the platform includes features for detecting biases, aligning digital labor practices with ethical standards and promoting fairness in decision-making.

   
   

   

   There are more than 2,000 activities that make up 800 full-time occupations that are part of knowledge work. However, only 5% of these full-time occupations could be fully automated using existing technology. That means that the 95% of remaining occupations require cognitive abilities.

Benefits for Businesses:

1. Accelerated Time-to-Value: By automating and streamlining AI and data science workflows, organizations can significantly reduce the time it takes to move from ideation to deployment, ultimately accelerating their time-to-value for AI initiatives.

2. Improved Collaboration: The collaborative features of WatsonsX Orchestrate facilitate better communication and knowledge sharing among teams, leading to more effective and impactful AI solutions.

3. Enhanced Governance and Compliance: The platform provides robust governance and compliance features, ensuring that organizations can meet regulatory requirements and maintain a high standard of data ethics.

4. Cost-Efficiency: With the ability to scale and the flexibility of deployment options, WatsonsX Orchestrate helps organizations optimize costs by aligning infrastructure with project requirements.

In the era of AI and data-driven decision-making, IBM WatsonsX Orchestrate stands out as a powerful solution for organizations looking to harness the full potential of their AI and data science initiatives. With its automation capabilities, collaborative environment, and emphasis on ethical AI, WatsonsX Orchestrate is poised to become a key player in the journey towards building intelligent, transparent, and scalable AI solutions. As businesses continue to navigate the complexities of the digital age, platforms like WatsonsX Orchestrate provide the tools needed to turn data into a strategic asset and drive innovation in the ever-evolving landscape of AI.

One of the standout features of Planning Analytics Workspace (PAW) is its ability to create calculations in the Exploration view. This feature empowers users to perform advanced calculations without the need for technical expertise. Whether you're using PAW or PAfE (Planning Analytics for Excel), the Exploration view offers a range of powerful capabilities. The Exploration view supports a variety of functions, such as aggregations, mathematical operations, conditional logic, and custom calculations. This means you have the flexibility to perform complex calculations tailored to your specific needs. 

This enables users to create complex financial calculations and business rules within the views, providing more accurate and tailored results for analysis and planning. All this can be done by the business users themselves without relying on IT or development teams, enabling faster and more agile reporting processes. This enables creating ad hoc reports and performing self-service analysis on the fly with a few simple clicks. This self-service capability puts the control in the hands of the users, eliminating the need for lengthy communication processes or waiting for IT teams to fulfill reporting requests.

In this blog post, we will focus on an exciting aspect of the Exploration view: creating MDX-based views that are dynamic and automatically update as your data changes. The beauty of these dynamic views is that users no longer need to manually select members of dimensions to keep their formulas up to date.

Similar to the functionality of dynamic subsets in dimensions, where each click in the set editor automatically generates MDX statements that can be modified, copied, and pasted, the exploration views in Planning Analytics Workspace also generate MDX statements. These MDX statements are created behind the scenes as you interact with the cube view. Just like MDX subsets, these statements can be easily customized, allowing you to fine-tune and adapt them to your specific requirements.

By being able to tweak, copy, and paste these MDX statements, you can easily build upon previous work or share your calculations with others.

Currently, the calculations are not inherently dynamic, however, there are techniques that can be employed to make the calculations adapt to changing time periods.

A classic example we can look at is performing variance analysis on P&L cube where we wish to add a variance formula to show the variance of current month from the previous month. There are many more calculations that we can consider from but we will focus on this analysis in this blog.

If we take our example, the current month and previous month keep changing every month as we roll forward and they are not static. When dealing with changing months or any member in your calculation, it's important to ensure that your calculations remain dynamic and adaptable to those changes. 

To ensure dynamic calculations that reflect changes in months, you have several options to consider:

Manual Approach: You can manually update the column dimensions with the changing months and recreate the calculations each time. However, this method is time-consuming, prone to errors, and not ideal for regular use.

Custom MDX Approach: Another option is to write custom MDX code or modify existing code to reference the months dynamically from a Control cube. While this approach offers flexibility, it can be too technical for end users.

Consolidations Approach: Create consolidations named "Current Month" and "Prior Month" and add the respective months to them as children. Then, use these consolidations in your view and calculations. This approach provides dynamic functionality, but you may need to expand the consolidations to see the specific months, which can be cumbersome.

Alias Attributes Approach: Leverage alias attributes in your MDX calculations. By assigning aliases to the members representing the current and previous months, you can dynamically reference them in your calculations. This approach combines the benefits of the previous methods, providing dynamic calculations, visibility of months, and ease of use without excessive manual adjustments.

In this blog post, we will focus on the alias attributes approach as a recommended method for achieving dynamic calculations in PAW or PAfE. We will guide you step-by-step through the process of utilizing alias attributes to ensure your calculations automatically adapt to changing months. By following this approach, you can simplify your calculations, improve efficiency, and enable non-technical users to perform dynamic variance analysis effortlessly.

To create dynamic calculations for variances between the current and prior month, you can follow these steps:

• Step 1: Ensure you have an alias attribute available in your Month dimension. If not, create a new alias attribute specifically for this purpose.
• Step 2: Update the alias with the values "Curr Month" and "Prior Month" for the respective months.
• Step 3: Open the exploration view in PAW and select the two months (current and prior) on your column or row dimension. 
• Step 4: Create your variance calculation using the exploration view's calculation capabilities. This could involve subtracting the P&L figures of the prior month from the current month, for example.
• Step 5: Open the MDX code editor and replace the actual month names in the MDX code with the corresponding alias values you updated in Step 2. You can copy the code in Notepad and use the "Find and Replace" function to make this process faster and more efficient.

By replacing the month names with the alias values, you ensure that the calculation remains dynamic and adapts to the changing months without manual intervention. When you update the alias values in the Month dimension, it will reflect in the exploration view. As a result, the months displayed in the view will be dynamically updated based on the alias values. This ensures that your calculations remain synchronized with the changing months without the need for manual adjustments.

Important Note: When selecting the months in set editor, it is crucial to explicitly select and move the individual months from the Available members' pane (left pane) to the Current set pane (right pane). This step is necessary to ensure that unnecessary actions, such as expanding a quarter to select a specific month, are not recorded in the MDX code generated in the exploration view which can potentially lead to issues while replacing the member names with alias values. 

This approach of using alias attributes to make calculations dynamic can be extended to various other calculations in Planning Analytics Workspace. It provides a flexible and user-friendly method to ensure that your calculations automatically adapt to changing dimensions or members.

That being said, it's important to note that there may be certain scenarios where alternative approaches, such as writing custom MDX code or utilizing a control cube, are necessary. Each situation is unique, and the chosen approach should align with the specific requirements and constraints of the calculation, however the proposed approach should still work for a wide variety of calculations in IBM Planning Analytics.

As the world moves towards more data-driven decision-making, businesses are increasingly looking for effective planning and budgeting solutions. IBM Planning Analytics is the go-to for businesses looking for a comprehensive set of tools to help them manage their budgeting and planning process.

With Planning Analytics, businesses can access powerful analytics to make more informed decisions, leverage advanced features to create complex models, and gain better insights into their financial data.

IBM is constantly improving the functionalities and features of the IBM Planning Analytics components. This includes Planning Analytics Workspace (PAW), Planning Analytics for Excel (PAfX), and Planning Analytics with Watson. With these updates, businesses can take advantage of new features to help them manage their budgeting and planning process more effectively.

In the last 12 months, IBM has released several updates to its Planning Analytics components.

In PAW, users can now access advanced analytics such as forecast simulations, predictive models, and scenario analysis. They can also perform in-depth analysis on their data with the new Visual Explorer feature. In addition, users can now access a library of planning and budgeting models, which can be customized to fit the needs of their organization. (download PDF file to get the full details)

download PDF file to get the full details

 

download PDF file to get the full details

In PAfX, users can now access advanced features such as SmartViews and SmartCharts. SmartViews allows users to visualize their data in various ways, while SmartCharts allows users to create interactive charts and graphs. Users can also take advantage of the new custom formatting options to make their reports look more professional.

download PDF file to get the full details

 

download PDF file to get the full details

Finally, with Planning Analytics with Watson, users can access powerful AI-driven insights. This includes AI-driven forecasting, which allows users to create more accurate forecasts. In addition, Watson can provide insights into the drivers of their business, allowing users to make more informed decisions.

 

download PDF file to get the full details

 

Overall, IBM’s updates to the Planning Analytics components provide businesses with powerful tools to help them manage their budgeting and planning process. With these updates, businesses can take advantage of the latest features to quickly access data-driven insights, create more accurate forecasts, and gain better insights into their financial data.

Download the PDF file below to get the full version of each IBM Planning Analytics components.