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TM1 is never the Problem. Support is.

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Why most TM1 environments underperform — and the four-step blueprint to fix it. When a finance team tells me their TM1 environment "doesn't work", I've learned to listen carefully — because the platform is rarely the real issue. What they actually mean is one of four things: Excel is creeping back in. Enhancements are taking months instead of days. The system goes down at the worst possible ...

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Why most TM1 environments underperform — and the four-step blueprint to fix it. 

Support

When a finance team tells me their TM1 environment "doesn't work", I've learned to listen carefully — because the platform is rarely the real issue. 

What they actually mean is one of four things: Excel is creeping back in. Enhancements are taking months instead of days. The system goes down at the worst possible moment — mid-budget cycle or during month-end close. Or, most dangerously, the entire environment is held together by one or two people, and a single resignation away from a crisis. 

The root cause of all four problems is the same: the operating model is reactive, knowledge is trapped, and improvements never get prioritised. In short, TM1 is not the problem. Support is.

The Four Support Models and Where Each One Breaks

Most organisations fall into one of four support models. The first step to improving your environment is recognising which one you are.

Model 1: The In-House Specialist 

You have one or two TM1 experts who own the environment. It works well when things are stable, and they're content. The breaking point arrives when they leave, or when the backlog grows faster than one person can manage. This is what the IT industry calls the "bus factor", what happens when the key person gets hit by a bus? It is not a strategy.

Model 2: Finance as the Admin

Finance has taken on the pseudo-admin role either because it was cheaper, more convenient, or gave them greater control. This works reasonably well in small deployments. It breaks when FP&A spends more time maintaining TM1 than using it for insights. The tool that was supposed to free finance ends up creating a new administrative burden, and Excel creeps quietly back in. 

Model 3: Ad Hoc Consulting

You call a vendor or consultant when things break. This is common — especially after a difficult implementation. The problem is structural: you pay to fix the same issues repeatedly, there is no knowledge transfer, no improvement, and you are essentially funding someone else's consulting pipeline by never resolving the root cause.

Model 4: Hybrid or Managed Support (Where You Should Be Heading) 

A model built for modernisation: clear governance, defined SLAs, mixed-maturity handling, peak-load capability, and measurable KPIs. This is the model that transforms support from a cost centre into a genuine business enabler.

 

What Modern TM1 Support Actually Looks Like

Not the brochure version. The operational reality.

Modern support is built around five pillars:

  • Coverage and Response. Defined SLA targets — not best effort. You know what Priority 1 means, when the clock starts, and what happens next. Communication is transparent.

  • Single Intake Funnel. No artificial split between support, development, and training. If it helps the business, it goes into one queue. No out-of-scope conversations.

  • Prevention Over Firefighting. The goal isn't faster ticket closure — it's eliminating the ticket in the first place. Every resolved issue is reviewed: Is  this recurring? If so, it goes into a problem backlog and gets a permanent fix.

  • Reporting and Accountability. Monthly KPI reports, backlog trends, and SLA compliance data. You can see what's happening and hold your support partner accountable.

  • A Live Road Map. Structured improvement with capacity built into every engagement. Not a list of hopes an actual plan with milestones.

The key mindset shift: modern support is not about faster ticket closure. It is about predictable cost, reduced risk, and continuous improvement — a model that prevents recurring pain rather than profits from it.

The Prevention Imperative

This is where most support models genuinely fail. In a reactive model, organisations pay to fix the same problem every month. In a prevention-led model, you invest once in understanding the root cause — and then it's gone. 

Based on our experience across client sites, more than 50% of ongoing support spend is going into repeatable issues that could be fixed once and automated. Think about that: half your support budget is fixing things that shouldn't be happening. 

Effective prevention involves three things:

  • Recurring ticket elimination: Identify the patterns and close them permanently.

  • Proactive health checks: Log hygiene, performance baselines, and chore execution validation — run fortnightly or monthly before problems surface, not after.

  • Automation of manual issues: Every repeatable manual task is flagged for automation. As the environment stabilises, ticket volumes drop, and human intervention decreases. 

Three Real Clients. Three Consistent Outcomes

The following outcomes come from actual client engagements — three different environments, three different sizes and industries, but strikingly consistent results.

Case Study 1: Large Media Group 35% Cost Reduction

A complex multi-entity TM1 environment with a heavy reporting load, mid-way through a cloud migration. By moving from a reactive break-fix model to a governed, predictable support structure with defined SLAs, this client eliminated their top five recurring issues within 90 days, reduced ticket volume by 40%, and completed their cloud migration with zero disruption to BAU operations including through a live budget cycle. 

The lesson: The 35% cost saving is the headline. The mechanism predictable cost, removal of key-person risk, and proactive maintenance are what actually drove it.

Case Study 2: Large Financial Services Group: 10-Week Budget Cycle Reduction 

Close to a thousand users, 50 rolling forecasts, and heavy allocation and scenario modelling workloads. The budget cycle was cut by ten weeks. Scenario modelling extended to a 60-month horizon. Finance shifted from process-heavy administration to genuine analysis. 

The lesson: None of this came from a new module or feature. It came from platform stability. When the system isn't crashing, when changes don't take weeks, the team can actually start using it. That is what stable support contributes to planning transformation.

Case Study 3: Global Retailer Zero Spreadsheets, 120 Hours Saved Monthly

A finance team managing reporting across 15 to 20 offline spreadsheets. Reports that previously took weeks now take five minutes. 120 hours saved per month — roughly equivalent to one full-time finance analyst returned to the business for actual analysis. And zero offline spreadsheets remaining. 

The lesson: For the CFO, eliminating spreadsheets was the most significant outcome not the time saving. Every uncontrolled spreadsheet is a version-control risk and an audit exposure. Stable TM1 support is not just an efficiency gain; it's a governance improvement.

The Support Maturity Curve: Where Are You?

  

Most organisations, if honest, sit at Level 1 or Level 2. Here is the full picture:

  • Level 1 — Reactive: Fix things when they break. Knowledge lives in people's heads. No road map. 

     

  • Level 2 — Stable: The environment is reliable. A support model exists, even if imperfect. Recurring issues are managed but not eliminated. 

     

  • Level 3 — Optimised: Prevention is active. Telemetry is live. Ticket volumes are declining. Finance is spending more time on analysis than administration. 

     

  • Level 4 — Innovation Ready: The platform is a genuine competitive advantage. Planning is automated. AI tools are actively in use. Finance is leading the organisation forward as a true business partner. 

The opportunity is not moving from Level 1 to Level 4 overnight. It is taking the next step. Levels 2 to 3 are where organisations see the biggest returns. 

The 6–12 Month Road Map

Months 1–3: Stabilise

Audit the environment. Fix the top five recurring issues. Stand up a single intake queue. Get telemetry and reporting live within 48 hours. Most organisations attempt to modernise before they have stabilised — that is backwards. Worse still, many implement another tool because the current one feels broken. Changing the tool will not solve a support model problem. 

Months 4–6: Optimise

Telemetry is fully deployed. Minor requests are automated. SLA reporting live. The knowledge base is built out. Around this period, support ticket volumes will begin to decline noticeably.

Months 7–12: Modernise

If you are still on-premises, cloud migration should be a key consideration here (IBM Cloud or AWS, depending on your scale and environment). Legacy models decommissioned. Finance has shifted from process work to analysis. If you are on an older version, anything 10.2 or below, IBM ended support for those versions in April 2024. You are running unsupported software. This conversation is urgent.

The True Cost of Poor Support

  

Most organisations measure support costs as consultant invoices. The real cost is much broader: 

  • Finance time wasted managing the tool instead of using it

  • Audit risk from uncontrolled spreadsheet use

  • Delayed forecasting and planning cycles

  • A platform too unstable to build upon

  • AI projects that cannot move forward because the data foundation is unreliable

That last point is increasingly critical. If your organisation has an AI strategy that involves TM1 data, and TM1 is crashing every month, you will have no confidence, nor will the AI team or the board in using those cubes as a foundation. Stable support is not the end goal. It is the prerequisite for everything else. 

Where to Start 

Ask yourself ten questions about your current support model:

  • During peak periods, is the system fast and reliable or slow and crashing?

  • How many recurring bugs or tickets do you handle every month?

  • What happens to unused support hours? Are they lost, or rolled forward?

  • Can your support model handle development work without a separate commercial fight?

  • How long does it take to deliver a critical finance report days, hours, or instantly?

  • Do you have performance monitoring on stats control cubes to spot regressions early?

  • Are your TM1 logs monitored so that accumulation doesn't silently pressure the server?

  • Who controls the ticket priority: finance, IT, or whoever shouts loudest?

  • Is there a knowledge base or runbook being actively maintained and shared?

  • Do you have an active road map aligned to IBM's support lifecycle?

Score one point for each yes. If your total is under seven, your support model is introducing meaningful risk into your finance function. 

The good news: this is entirely fixable. The road map is clear, the outcomes are proven, and the first step is simply understanding where you are. 

Ready to assess your TM1 support model?

Contact the Octane Solutions team for a complimentary five-question health check assessment, or reach out to Amendra directly on LinkedIn. We work with organisations globally from Australia, New Zealand, and the Pacific through to India, the Middle East, and North America on a flexible, no lock-in basis.

Learn more and get started: www.octanesolutions.com.au/tm1-support

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Modernising TM1: Why Cloud Migration Alone Doesn’t Solve the Problem

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IBM Planning Analytics (TM1) remains one of the most powerful planning and modelling engines used by Finance teams worldwide. Yet many organisations eventually experience frustration with their TM1 environments — slow performance, painful upgrades, rising support costs, and the quiet return of Excel.

Contrary to popular belief, these challenges are rarely caused by TM1 itself.

They are symptoms of a modernisation gap.

The Hidden Drift Problem in TM1 Environments

TM1 models often start clean, efficient, and purpose-built. Over time, however, incremental changes accumulate:

  • New dimensions added without structural discipline

  • Rules layered onto legacy logic

  • TI processes expanded beyond their original design

  • Reporting logic intertwined with source data

  • Upgrade cycles deferred

  • Risk and compliance requirements

  • Upgrade tolerance

  • Internal IT capabilities

  • Cost predictability objectives

  • Metadata-driven logic instead of hard-coded processes

  • Modular cube design separating input, calculation, and reporting

  • Decoupled reporting layers

  • Performance-first feeder strategies

  • Cloud-aware security models

  • Structured change management practices

  • Issues detected late

  • Knowledge concentrated with individuals

  • Upgrades treated as disruptive events

  • Costs becoming unpredictable

What emerges is not a broken system — but a fragile one.

Performance declines. Change cycles slow. Complexity rises.

The Common (But Incomplete) Response: “Move to Cloud”

When issues surface, organisations frequently default to infrastructure decisions:

Move from on-premise to cloud
Adopt SaaS
Change hosting providers

While these shifts reduce infrastructure management overhead, they do not automatically modernise the model.

A poorly structured TM1 architecture behaves the same way regardless of where it is hosted.

Better infrastructure cannot compensate for design inefficiencies.

True TM1 Modernisation Requires Three Pillars

Sustainable TM1 environments align three interdependent areas.

1. Infrastructure Modernisation

Infrastructure choices should reflect:

Cloud platforms reduce maintenance effort — but they are only the foundation.

2. Architecture Modernisation (The Critical Lever)

Architecture modernisation is where the largest gains are realised.

Modern TM1 models typically prioritise:

Without architectural evolution, cloud migration simply relocates existing constraints.

3. Support Model Modernisation

Traditional break-fix support models introduce systemic risk:

Modern support approaches focus on:

Proactive monitoring
SLA-driven response models
Continuous optimisation
Upgrade lifecycle management
Knowledge transfer

This operating philosophy underpins Octane Blue, our proactive TM1 managed services model.

Why This Matters for Finance Leaders

Modernised TM1 environments typically deliver:

Faster budgeting and forecasting cycles
Lower data errors
Safer upgrade paths
Reduced operational friction
More predictable support costs

Most importantly, Finance teams regain time, stability, and confidence.

Final Perspective

Cloud migration is valuable — but it is not modernisation by itself.

Real TM1 modernisation redesigns how the model scales, performs, and evolves with the business.

📘 Download the TM1 Modernisation Roadmap (PDF) 
📊 Request a Free Upgrade & Risk Estimate 

 

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Tips on how to manage your Planning Analytics (TM1) effectively

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Effective management of Planning Analytics (TM1), particularly with tools like IBM’s TM1, can significantly enhance your organization’s financial planning and performance management. 

TM1 newsletter

Here are some essential tips to help you optimize your Planning Analytics (TM1) processes:

1. Understand Your Business Needs

Before diving into the technicalities, ensure you have a clear understanding of your business requirements. Identify key performance indicators (KPIs) and metrics that are critical to your organization. This understanding will guide the configuration and customization of your Planning Analytics model.

2. Leverage the Power of TM1 Cubes

TM1 cubes are powerful data structures that enable complex multi-dimensional analysis. Properly designing your cubes is crucial for efficient data retrieval and reporting. Ensure your cubes are optimized for performance by avoiding unnecessary dimensions and carefully planning your cube structure to support your analysis needs.

3. Automate Data Integration

Automating data integration processes can save time and reduce errors. Use ETL (Extract, Transform, Load) tools to automate the extraction of data from various sources, its transformation into the required format, and its loading into TM1. This ensures that your data is always up-to-date and accurate.

4. Implement Robust Security Measures

Data security is paramount, especially when dealing with financial and performance data. Implement robust security measures within your Planning Analytics environment. Use TM1’s security features to control access to data and ensure that only authorized users can view or modify sensitive information.

5. Regularly Review and Optimize Models

Regularly reviewing and optimizing your Planning Analytics models is essential to maintain performance and relevance. Analyze the performance of your TM1 models and identify any bottlenecks or inefficiencies. Periodically update your models to reflect changes in business processes and requirements.

6. Utilize Advanced Analytics and AI

Incorporate advanced analytics and AI capabilities to gain deeper insights from your data. Use predictive analytics to forecast future trends and identify potential risks and opportunities. TM1’s integration with other IBM tools, such as Watson, can enhance your analytics capabilities.

7. Provide Comprehensive Training

Ensure that your team is well-trained in using Planning Analytics and TM1. Comprehensive training will enable users to effectively navigate the system, create accurate reports, and perform sophisticated analyses. Consider regular training sessions to keep the team updated on new features and best practices.

8. Foster Collaboration

Encourage collaboration among different departments within your organization. Planning Analytics can serve as a central platform where various teams can share insights, discuss strategies, and make data-driven decisions. This collaborative approach can lead to more cohesive and effective planning.

9. Monitor and Maintain System Health

Regularly monitor the health of your Planning Analytics environment. Keep an eye on system performance, data accuracy, and user activity. Proactive maintenance can prevent issues before they escalate, ensuring a smooth and uninterrupted operation.

10. Seek Expert Support

Sometimes, managing Planning Analytics and TM1 can be complex and may require expert assistance. Engaging with specialized support services can provide you with the expertise needed to address specific challenges and optimize your system’s performance.

By following these tips, you can effectively manage your Planning Analytics environment and leverage the full potential of TM1 to drive better business outcomes. Remember, continuous improvement and adaptation are key to staying ahead in the ever-evolving landscape of financial planning and analytics.

For specialized TM1 support and expert guidance, consider consulting with professional service providers like Octane Software Solutions. Their expertise can help you navigate the complexities of Planning Analytics, ensuring your system is optimized for peak performance. Book me a meeting

Got a question? Shoot!

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