ASX-Listed Industrial Services Group Case Study: Financial Consolidation, Forecasting & ESG Reporting

Post author By Tim Bryden
Post date

As finance environments grow through acquisitions, legacy systems, and expanding reporting requirements, spreadsheet-led processes often reach a breaking point.

That was the situation facing this ASX-listed industrial services group. With 31 entities operating across multiple general ledger systems, the finance team needed a more reliable way to manage financial consolidation, improve forecasting and planning, compare entities consistently, and support broader group reporting. Since then, the group has expanded to 58 entities, making the need for a scalable finance platform even more important.

Working with Brydens BI and Calumo, the business moved from a fragile, spreadsheet-driven process to a more controlled, scalable, and database-driven reporting model. The result was a dramatic reduction in month-end effort, stronger controls, improved visibility, and a reporting platform that scaled as the business grew.

The challenge: 31 entities, 6 GL systems, and a fragmented month-end process

Before the project, the finance team was struggling to produce a consolidated view of the whole group and relevant subgroups of businesses. It was also difficult to compare entities consistently, even though this was increasingly important for group finance and executive decision-making.

The complexity was significant. The group included 31 entities using 6 different general ledger platforms: Xero, MYOB, Sage, Pronto, IFS, and TechnologyOne. Even where businesses used the same GL software, those systems were often configured differently, creating inconsistency in reporting structures and limiting comparability across the group.

To produce consolidated reporting, the finance team relied on a large and complex Excel workbook. Each month, trial balance files from across the group were manually inserted, mapped, checked, and consolidated. The process was slow, cumbersome, and highly vulnerable to error. A single incorrect row insertion, broken formula, or formatting issue could disrupt the workbook and require significant rework.

Month-end effort was fragmented and frustrating, requiring around 20 hours spread across 5 days. Manual intervention was ad hoc and cumbersome, and adding a new entity or updating mappings could take hours or even days.

This approach created several problems:

Consolidated reporting took days to complete
Manual rework was common when files, formulas, or formats were incorrect
Reporting flexibility was limited once the workbook structure was set
Answering management questions was often slow and cumbersome
Comparing entities and business groupings consistently was difficult
Adding new entities required significant manual effort

For a growing group finance function, this was becoming increasingly difficult to sustain.

The approach: standardised exports, controlled imports, and centralised mapping

The solution was to replace spreadsheet-led consolidation with a database-driven model designed for consistency, control, and scale.

From each source GL, a trial balance export or full transactional export was established. In most cases, these standard exports already existed and could be adopted without major system changes. Real-world formatting issues such as subtotals, page breaks, and inconsistent headers were handled within the import design, allowing source systems to remain unchanged.

A key design principle was consistency with minimal manual intervention. With 6 different GL platforms in use, it was important that entities using the same software adopted the same export approach and structure, even where underlying account structures differed. This created a more standardised and scalable process across the group.

As part of the Calumo implementation, Brydens BI implemented single-click imports supported by detailed validation controls. These checks ensured that files matched the correct period, company, and expected format before loading. This reduced risk and gave users a much more controlled import process.

The solution also introduced centralised mapping from all subsidiaries to a single master chart of accounts. New accounts are automatically identified during import and flagged for mapping through a simple interface. Rather than relying on manual spreadsheet logic, users select the appropriate mapping from a drop-down list, making maintenance significantly easier and more controlled.

Where required, segregation controls were introduced to ensure that users from one subsidiary could not see or influence another subsidiary’s data.

The new operating model was built on:

Standardised exports from source GL systems
Validated single-click imports
Centralised mapping to a master chart of accounts
Minimal manual handling
Controlled security and user segregation
A scalable structure for new entities and acquisitions

The outcome: month-end reduced from 5 days to under 1 day as the group grew from 31 to 58 entities

The impact was immediate and substantial.

What had previously required around 20 hours spread across 5 days can now be completed comfortably within 1 day. More importantly, the actual consolidation effort now takes less than 1 hour once subsidiaries have closed their books.

This significantly reduced manual effort and rework risk, while giving the finance team a more dependable and repeatable monthly process.

The solution also scaled with the business. What began with 31 entities now supports 58 in the consolidated group. Most new entities have been added by the business itself, with no consulting support required. That is a strong indicator that the model is not just effective, but practical and sustainable for internal teams to maintain.

Manual intervention has been reduced to near zero, with the main exception being the mapping of new accounts to the master chart of accounts through a controlled drop-down process. If management accounting adjustments are required, they can be added directly in Calumo with a full audit trail and are automatically consolidated as appropriate.

The business also gained a much stronger visibility layer. Once imported, subsidiary data is immediately available across consolidated reports, subgroup reporting, dashboards, and executive-level views. Instead of spending time maintaining fragile spreadsheets, finance can focus more on analysis, visibility, and decision support.

Beyond consolidation: forecasting, dashboards, and broader management reporting

The value of the platform extended well beyond month-end consolidation.

With cleaner, more structured finance data available in a governed environment, the group was also better positioned to improve forecasting, planning, and broader management reporting. Calumo provided a more flexible foundation for consolidation, reporting, and planning, with outputs tailored to the needs of different stakeholders across the business.

Planning, including both annual budgeting and periodic forecasting, followed a similar path. Each subsidiary can now easily import and export budgets and forecasts, improving consistency across the group and reducing the manual effort previously required to support planning cycles.

The ability to create timely, tailored dashboards for different business groupings and executive users added further value, helping finance move beyond data preparation and toward more effective analysis and decision support.

Extending the model into ESG reporting

Calumo enables emission factor tracking by region, scope and unit type.

Once the consolidated general ledger capability was in place, the business turned its attention to another reporting challenge: ESG reporting and sustainability data collection.

The ESG process was experiencing many of the same problems that had previously affected finance consolidation. Data collection was fragmented, manual, and inconsistent. Inputs were gathered from different parts of the business, checked manually, and processed outside a well-controlled and scalable framework.

Because the finance consolidation model had already established a more structured reporting platform, the business was well positioned to apply the same principles to ESG reporting. The goal was not simply to collect more data, but to create a more repeatable and controlled process for ESG data capture, validation, calculation, and reporting.

This meant extending the same practical disciplines that had improved finance reporting:

More consistent data collection across the group
Reduced manual handling and spreadsheet dependency
Clearer validation and control over inputs
A more scalable foundation for ongoing reporting requirements
Improved visibility for management and group-level reporting

In this sense, ESG reporting became a natural extension of the broader transformation. Once the group had a stronger and more governed foundation for financial reporting, it made sense to apply the same model to ESG data and calculation.

Positioning for AI-enabled analysis

By bringing together financial, operational, and emissions data into a single governed platform, Calumo creates a governed data foundation for AI-enabled finance analysis. Brydens BI can extend this capability by applying AI models informed by finance domain expertise and business context, supporting pattern detection, scenario simulation, and narrative insight generation across the group.

Because these models operate within defined financial rules and reporting structures, resulting insights remain more explainable, auditable, and aligned with executive reporting standards.

Why this mattered strategically

For a growing multi-entity group, this was not just about making month-end easier. It was about creating a more controlled and scalable reporting foundation.

By reducing spreadsheet dependency, standardising data capture, improving visibility, and enabling internal teams to add new entities without external consulting support, the business became better equipped to support acquisitions, strengthen executive reporting, and respond more quickly to changing information needs.

The extension into ESG reporting also demonstrated the broader value of the approach. Once a consistent and governed reporting foundation was established, the same model could be applied to adjacent reporting challenges that were previously manual, fragmented, and difficult to scale.

For finance leaders managing complexity across multiple systems and entities, that kind of foundation becomes increasingly important as the business grows.

How Brydens BI helps

Brydens BI helps finance teams move beyond spreadsheet-led consolidation and manual reporting processes by implementing practical, scalable solutions using Calumo and the Microsoft-based finance data warehouse approach.

For businesses operating across multiple entities, inconsistent source systems, and growing reporting demands, the goal is not just to produce reports faster. It is to build a stronger finance and reporting model that improves control, visibility, and decision support across the business.

Why CFOs Are Choosing Calumo for Consolidation, Reporting & Planning

Post author By Tim Bryden
Post date

Modern CFOs are under pressure to close faster, forecast more accurately, and deliver sharper insight across increasingly complex finance systems. For many teams, that still means managing multiple GLs, manual eliminations, disconnected spreadsheets, and growing reporting demands without growing headcount. That is exactly why more CFOs are turning to Calumo.

1. Consolidation Without the Chaos

For any CFO managing multiple entities, acquisitions, or international operations, consolidation can quickly become a bottleneck. Calumo cuts through that complexity by acting as a unified finance data warehouse and consolidation engine. Rather than wrestling with disconnected GLs and manual journal spreadsheets, finance teams use Calumo to automate eliminations, allocations, adjustments and currency conversions, reducing close cycles from days to hours.

At Brydens BI, we have worked with dozens of large, complex clients to centralise finance and operational data in Calumo, standardise chart-of-account structures, and map multiple ledgers into a single model. Whether a business runs on Xero, NetSuite, Sage Intacct, Acumatica, Oracle, GP, Microsoft Dynamics F&O, or numerous other systems, Calumo brings them all together into one harmonised environment.

As one example, Brydens BI was engaged by a major private construction firm to bring together data from multiple GLs into a single, coherent finance view. The objective was not only to consolidate reporting across the business, but to enable finance and operational leaders to see the full financial position of each project by combining related data from both systems. This was achieved in Calumo through a unified model that allows the client to select any project and view that combined picture in near real time. For the business, this has represented a meaningful step forward in visibility, control and decision support, while also creating a stronger foundation for future analysis and performance improvement.

For larger and more complex groups, the value can be even greater, particularly where multiple entities, currencies and source systems must be brought together into a single reporting and planning model.

For CFOs, this means fewer errors, faster closes and far more reliable reporting, especially as the business grows or acquires new entities.

Calumo’s architecture provides the flexibility and scalability required to support evolving organisational structures. As new entities or data sources are introduced, whether through organic growth or acquisitions, the platform will integrate them without disrupting existing processes. It is designed to manage complex consolidations involving hundreds of entities and multiple sub-consolidation layers with ease. Centralising consolidation logic alongside reporting, budgeting, and forecasting reduces operational risk, streamlines governance, and lowers overall financial-system complexity.

2. Reporting That Actually Keeps Up With the Business

Traditional reporting tools often leave CFOs stuck in a cycle of exporting, reconciling, and manually assembling management packs. Calumo flips the script by giving finance teams live, drill-through reporting directly on top of consolidated data. Executives finally get real-time visibility into performance, and finance teams regain hours previously lost to spreadsheet gymnastics.

Because Calumo integrates across GLs, HR systems like Employment Hero, CRM systems like Microsoft Dynamics, Salesforce and Hubspot, and operational databases, it produces a single source of truth that supports everything from board reporting to operational dashboards. Many Brydens BI clients cite the ability to run ad hoc analysis directly in Calumo, with no waiting on IT and no data wrangling, as something they now consider a must-have.

Calumo gives CFOs and their teams the agility to answer critical questions on demand, backed by reliable data they can trust. And because Calumo is built on Microsoft SQL Server in Azure, finance teams benefit from a secure, scalable platform that unlocks Microsoft’s AI and analytics capabilities. At the same time, the Calumo Excel add-in provides a live connection to the Calumo model, letting teams keep working natively in Excel with enterprise-grade power behind every cell.

3. Planning and Forecasting, Without the Spreadsheet Pain

Budget season shouldn’t feel like a crisis. Yet many finance teams still depend on giant Excel workbooks full of fragile formulas and version-control nightmares. Calumo replaces this with a structured budgeting and forecasting framework that supports 3-way rolling forecasts, scenario analysis, employee planning models, workflow, and driver-based modelling.

Some clients even use Calumo as their allocation engine, transforming allocation runs that once took days into automated processes completed in minutes. For finance teams, that means more time spent analysing results, adding real business value and less time manipulating spreadsheets.

Well-structured, trusted data also creates the right foundation for emerging capabilities such as AI forecasting. When financial and operational data is centralised, governed and consistently modelled in Calumo, finance teams are far better placed to apply AI in a practical, controlled way. Rather than relying on fragmented spreadsheets and disconnected source systems, they can build on a reliable data foundation that supports more explainable forecasting, stronger scenario analysis and better decision-making. Learn more about AI Forecasting.

A Strategic Investment in Financial Control

In an environment where data volumes are expanding, stakeholder expectations are intensifying, and finance is increasingly expected to act as a strategic partner to the business, Calumo represents a meaningful step-change in financial capability. By unifying disparate systems, strengthening reporting integrity and automating core planning processes, it enables finance teams to redirect effort from manual data preparation to higher-value analysis and decision support.

For organisations seeking to reduce operational complexity, enhance transparency, and scale their financial operations with confidence, Calumo functions not merely as a reporting tool but as a strategic platform that provides a single, reliable view of performance and supports more informed, timely, and enterprise-wide decision-making.

To learn more about Calumo, contact Brydens BI, or check out some of our brief Calumo Client stories.

About the Author

Tim Bryden is Founder and Director of BrydensBI, a finance-led business intelligence consultancy focused on reporting, forecasting, consolidation and governed data foundations. BrydensBI is also a contributor to ForesightXL, an AI forecasting assistant built to help finance teams create clearer, more explainable forecasts in Excel.

Connect with Tim Bryden on LinkedIn

Building a Future-Ready Finance Function: Data Lakes, Calumo and the Finance Data Warehouse

Post author By Tim Bryden
Post date

CFOs today face rapidly rising expectations: more reporting, faster reporting, accurate rolling forecasts, ad hoc analysis, and increasing pressure to deliver AI-ready data across the organisation. To meet these demands, high-performing finance functions are adopting a Finance Data Warehouse for delivering trusted, finance-ready reporting, planning, and governance. At the same time they are supporting the idea of an enterprise-wide data lake for capturing raw, enterprise-wide data at scale. Together, these complementary tools provide the breadth needed for advanced analytics and the precision required for reliable financial management.

1. Why This Matters and What Works

Brydens BI supports clients across Australia, Asia and North America. Across our clients, typically with revenues between $100M and $500M (although several are much larger), we see consistent themes:

Automatic consolidation and the ability to easily slice and dice trusted financial numbers and key operating metrics are a given.
Forecasting needs to be more reliable, and numbers supported by operating metrics understood by the business are much more meaningful.
Reporting must be delivered faster, and the breadth of reporting is growing. It helps when insights are spelled out with commentary, and the reports need to look good online and be easy to push to Excel or PDF.
Planning processes need modernisation and automation.
AI readiness is becoming an expectation from Boards and CEOs
Finance Teams need to provide more. ESG Reporting anyone?

These themes make sense. The finance teams we work with have already implemented a Finance Data Warehouse (which we do as part of their Calumo implementation). They are unlocking value, have the tools to unlock more value, and understand the value of data. This often leads to questions like, should the business implement a Data Lake? or if the business wants a Data Lake, whether this will, or whether it should, replace the Finance Data Warehouse? All reasonable questions.
In our view, it’s essential to understand what each of these things are, the role they play, and what the actual cost and effort of each is. Ideally, most businesses should have both; they are complementary.

2. What a Data Lake Actually Is, and What CFOs Need to Know

A Data Lake is a highly scalable, low-cost environment where an organisation can store data of any type in its raw form. Nothing needs to be cleaned, modelled, or shaped before it’s captured. Examples might include ERP data, CRM and sales activity, Web clickstream data, Call centre transcripts, Construction photos and drone footage, Historical archives and third-party data. Pretty much anything and everything.

That’s the simple definition. But by itself, it adds no value. To get the value the Data Lake needs:
Good data governance – data is accurate, only available to the right people, consistent, and used the right way;

Good metadata management – it tracks what the data means, where it comes from, and how to use it;

It’s curated and transformed into usable, business-ready layers (raw data is generally not that useful). Ideally, relevant subsets might even get fed into Calumo (and vice versa). We do this with several clients, and yes, sometimes we enrich the data further to make sure it works from a Finance perspective.

A key takeaway is that the data lake is not a project in itself; it is an enabler of other projects. Its value lies in helping with decisions, enabling automation, or improving performance.

Why a Data Lake Matters to CFOs

A well-implemented Data Lake gives you:

A single repository for all enterprise data;
Scalable storage, which should be at a very low cost (but keep a close eye on this!);
Data at a granularity suitable for AI and machine learning (probably with a bunch of additional effort, but having the data in one place helps!);
The potential for earlier visibility of risks, opportunities, and operational drivers, and to generate Cross-department insights that previously may have been very time-consuming or impossible

A Data Lake is not about today’s reporting; it’s about preparing the organisation for future analytics, automation, and AI-driven decision-making. It’s an investment.

3. What a Calumo Finance Data Warehouse Is, and Why It’s Essential

A Calumo Finance Data Warehouse, built on leading Microsoft technology, is the Finance team’s single source of truth. Where a Data Lake stores everything raw, a Finance DWH is highly curated and structured. Typically, we see most clients integrate data directly from their ERP(s) or General Ledger Systems, Payroll/HR systems, and relevant subsets of data from internal operational and external sources. Links are typically via API or Linked Servers with scheduled and on-demand updates to facilitate key month-end processes. Teams then use Calumo to automate consolidations and allocations, generate board-ready reports (using Excel as the authoring tool), and manage rolling forecasts and budgets that leverage relevant operational data. Because Calumo is so flexible, we have many examples of it being used to solve very business-specific challenges. If you have any finance or business processes that take up a lot of resources, or involve lots of spreadsheets or old databases, it’s likely Calumo can modernise them.

Why this matters for Finance

A Finance DWH delivers immediate, tangible benefits

Faster, cleaner month-end
Reduced reconciliation effort
Consistent numbers across Finance, Executive, and Operations
Reliable management reporting and board packs
Stronger scenario modelling and forecasting
Governance, auditability, and transparency

Because it runs on SQL Server in Microsoft Azure, Calumo integrates natively with Microsoft’s AI ecosystem. At Brydens BI, we can extend the solution to enable

AI-assisted forecasting, automated variance detection, automated commentary and insights, and data quality automation. The results of AI forecasting or insights are far more valuable if the underlying financial data is trustworthy, and the Finance DWH provides precisely that.

4. How the Two Can Work Together (Not Against Each Other)

Many CFOs initially assume that the Data Lake and Finance Data Warehouse compete with each other. In practice, they are complementary layers of a modern data architecture.

Data Lake	Finance Data Warehouse (Calumo)
Raw, granular, enterprise-wide data	Finance-ready, curated, audited data
Potential for AI, ML, and data science	Ideal for reporting, planning, and specific AI use cases
Ingests everything	focuses on finance-centric data and generating periodic management reporting
Flexible and exploratory	Largely structured and rule-driven
Operational breadth	Financial precision

In short, the Data Lake widens what you can do; the Finance Data Warehouse makes sure you can trust what you see.

5. The Hidden Effort Behind a Data Lake: Technology Is Easy. Meaning Is Hard.

While a data lake provides scalable, low-cost storage and a unified place to consolidate enterprise data, the true effort and ongoing cost is not in the platform itself but in the work required to make data usable, accurate, and trusted.

The most significant investment lies in building and maintaining the metadata, mapping rules, and business logic that define how data from different systems relates to projects, products, customers, cost centres, regions, or operational activities. This work requires deep organisational knowledge, coordination across departments, and continuous upkeep as the business changes.

Without this layer, a data lake accumulates raw files with limited shared meaning, risking inconsistent reporting, conflicting definitions, and a “data swamp” rather than a source of truth.

In discussions with people from the trenches, it seems that 10–20% of the cost is technology, while 80–90% is the ongoing effort to model data, maintain master data, apply governance, and evolve rules as new projects, codes, systems, and reporting needs appear.

In short, a data lake’s value comes from disciplined data management, not effortless storage. The real work is giving the data meaning, and keeping that meaning current over time.

6. The Reality of a Finance Data Warehouse: The Logic Is the Hard Part

At Brydens BI, we work with over 30 different businesses, and for each one, we’ve designed and now maintain a dedicated Finance Data Warehouse. The technology, in most cases, is the easy part. The real work, and the real value, is in how we structure the financial and related operational data, apply the lessons we’ve learned across industries, and customise everything to fit the way each specific business actually operates while taking account of how far along they are on the data journey. It also helps that everyone on the team has worked extensively in Finance.

Every warehouse, and the reporting and interfaces we build in Calumo to interact with it, requires clear definitions: how your chart of accounts works, how cost centres roll up, which period rules apply, how consolidations and eliminations are handled, how each source system maps into a single, trusted view, the list goes on.

Once that’s in place, your reporting becomes fast and dependable. But as your business changes, the warehouse must change too. New entities, restructures, acquisitions, ERP changes, and even the loss of key staff all impact the warehouse and the reporting, forecasting, and similar processes tailored for your business. The software is the container; the structure and processes are what make the numbers trustworthy. Calumo then brings this structure to life, making reporting, automation and planning simpler and more powerful.

Top 5 Takeaways for CFOs

A Data Lake provides scalable, low-cost storage for raw, enterprise-wide data. It can open the door to more sophisticated analytics, including AI and machine learning, when your organisation is ready.
A Finance Data Warehouse, built on Microsoft SQL Server and with a front-end like Calumo, delivers structured, curated, auditable financial data that supports consistent reporting, faster month-end processing, and reliable forecasting.
A Calumo implementation includes the Finance Data Warehouse, which brings it to life by enabling automated consolidations, board-ready reporting, scenario modelling, and planning directly from the trusted dataset.
Data Lake and Finance Data Warehouse technologies are complementary, not competing: the Data Lake broadens analytical possibilities, while the Finance Data Warehouse ensures precision and trust in financial outputs.
The significant effort in both environments lies in the business logic, master data, mappings, and governance needed to keep data meaningful and aligned with a changing organisation, not in the underlying technology.

Why Finance Teams Struggle with External Statutory and Sustainability Reporting and How the Right Software Can Help

Post author By Tim Bryden
Post date

Brydens BI works with many different finance teams (refer Clients) and often meets with staff from many others. Many Finance teams, especially those in larger and more complex businesses, are under immense pressure, navigating increasingly complex statutory and sustainability reporting requirements.

Reporting has evolved beyond traditional financial statements, integrating broader ESG (Environmental, Social, and Governance) disclosures that now significantly influence stakeholder decisions and regulatory scrutiny. Despite these evolving responsibilities, many finance teams, for external reporting, continue relying on manual processes and outdated tools, resulting in inefficiencies, increased risk, and heightened stress during reporting cycles.

Addressing these challenges using specialist software can significantly improve accuracy, reduce risks, and empower finance teams to deliver strategic value to their organisations.

Why Finance Teams Face Growing Reporting Challenges

Finance teams consistently face common frustrations: data scattered across multiple systems, unclear reporting requirements, and reliance on manual reconciliation processes. Uncertainty about what specific data needs capturing, particularly for emerging ESG standards, further compounds these difficulties. This ambiguity creates additional pressure, leading to last-minute data collection and increased risk of inaccuracies.

Emerging standards such as AASB S1 and S2, alongside traditional financial reporting frameworks, mandate comprehensive disclosures around financial performance and climate-related financial risks. The increased complexity requires finance teams to maintain stringent controls, accuracy, and transparency, all within tight deadlines and resource constraints.

Imagine this scenario: Your team is attempting to finalise year-end financial and ESG disclosures yet finds itself struggling with disconnected datasets and unclear instructions about required disclosures. This situation creates last-minute confusion, magnifies error risks, and significantly escalates stress and audit scrutiny.

What Effective Reporting Software Must Provide

Finance teams need robust reporting software that meets today’s complex regulatory demands and enhances efficiency. An ideal solution should:

Integrate Financial and ESG Data: Centralise reporting data within a unified platform that is accessible across departments, eliminating fragmented and inconsistent data.
Embed Regulatory Compliance Frameworks: Offer ready-to-use, adaptable templates pre-configured for relevant accounting standards and ESG disclosure requirements, automatically updating as standards evolve.
Streamline Workflows and Governance: Clearly define roles, automate task tracking, and provide robust version control, significantly reducing manual effort and error risks.
Ensure Comprehensive Audit Trails: Capture detailed change logs, offer transparent validation processes, and simplify the audit process, enhancing confidence and accuracy.
Automate Data Integration and Reporting: Seamlessly connect with existing ERP or BI systems, automate data extraction, calculations, and narrative reporting, significantly streamlining the reporting process.

Quick Assessment: Is Your Reporting Solution Meeting Expectations?

Integrates financial and ESG data effectively?
Automatically manages compliance updates?
Provides clear, automated, and controlled workflows?
Delivers detailed, transparent audit trails?
Efficiently automates data integration and reporting?

Real Benefits for CFOs and Finance Teams

Using modern, specialist software with the right support will provide substantial benefits. You’ll achieve shorter reporting cycles, improved accuracy, and significantly reduced audit-related stress. Reliable and transparent reporting strengthens board and stakeholder confidence, while streamlined processes foster better collaboration across finance, sustainability, and risk management functions.

Fundamentally, the right software, with the proper support, reduces risk.

Next Steps

The complexity of external statutory and sustainability reporting continues to grow. If your finance team struggles with fragmented processes and manual data management associated with external reporting, it’s essential to reassess your current tools and practices. Adopting structured, integrated solutions will not only simplify compliance but enhance overall organisational effectiveness. Now is the time to proactively refine your reporting approach, ensuring your team remains efficient, compliant, and strategically positioned for future regulatory demands.

What software do we recommend for External Statutory and Sustainability Reporting

First, we would start by saying that different businesses have different needs. Sometimes, simple is best (think Excel auto-populated from Calumo and Word). In other cases, especially for complex entities, more sophisticated solutions like CDM (Certent Disclosure Management) that some of our clients use, or the purpose-built OmniDisclose that leverages Excel and AI, are appropriate.

If you have questions, get in contact, our team have all worked in Finance and understand the challenges.

Generating Multiple Scenarios in Budgeting and Forecasting: A Game Changer for CFOs and FP&A

Post author By Tim Bryden
Post date

In the dynamic world of finance, the ability to anticipate and plan for various future states is critical. Financial Planning and Analysis (FP&A) Managers and their CFOs not only need to create comprehensive budgets and rolling forecasts, they also need the ability to rapidly create What If-style analysis.

This capability is not just a luxury—it is a critical component of strategic financial management. The creation of full scenario copies, especially those incorporating detailed models for revenue, direct costs, and employee costs, offers a suite of benefits that can significantly enhance decision-making processes. Moreover, integrating all relevant data into a single Finance Data Warehouse simplifies these operations, making scenario generation efficient and comprehensive.

Brydens BI works with various private and listed companies, where finance users routinely make full working scenario copies. We do this primarily with SQL Server and often use Calumo as the front-end tool, as it works in Excel and has excellent online finance-style reporting.

Why is being able to create Multiple Budget and Forecast Scenarios Important?

Several years ago (as COVID started to impact everything), a frantic CFO called me; I had designed, built and continued to support their budgeting and forecasting solution. I did not normally have much to do with the CFO, as the business was large, he was busy, and his FP&A manager was really good. The solution was reasonably sophisticated, with a driver-based revenue model (updated from their internal data warehouse) and an employee model (updated from their payroll system). A small capital and funding model was also used, and other expenses were updated via direct writeback. The whole model was also 3-way in that it auto-generated most balance sheet and cash entries based on a range of cash and GST rules. Anyway, they had recently finalised their budget and were in the middle of a leadership strategic offsite. The FP&A Manager was holidaying overseas. The discussion at the offsite was all about potential COVID impacts, and the CFO was tasked with generating a range of different budget outcomes based on changes in key operations. As I said, he was frantic and breathlessly asked how long it would take to create three new budget scenarios. I thought for a second and replied… “Probably 3 to 5”… he cut me off. “No”, he said, “3 days is too long… I need this tomorrow.” I took a quick breath and said, “Sure… I was going to say 3 to 5 minutes”. He went silent, confirmed he had heard me right and was a bit stunned. To cut a long story short, I showed the team how to create the copies, discussed with the CFO what the differences between the scenarios should be and oversaw the relevant updates. That evening, the CFO reviewed them and, the next morning was able to present the draft budget options. A very happy client.

The above hit home for me. As a former CFO who has stepped in to help businesses in tough times, I understood the power of rapidly generating what-if scenarios, modelling outcomes, and proving numbers with underlying data. Obviously, this is not trivial to do in a rolling forecast scenario unless things are set up well. This is a key reason I gravitated toward solutions that use SQL Server and have an Excel and Online front-end. Below are five (of the many) advantages of setting up a Finance Data Warehouse in SQL Server and using a tool like Calumo for Budgeting and Forecasting, management reporting and automation, with a focus on Multiple Scenarios.

Scenario planning also becomes even more valuable when paired with Context-Driven Forecasting, which adds AI-informed forecasting insight alongside annual budgets and rolling forecasts.

Five key advantages of using a tool like SQL Server with Calumo for Budgeting and Forecasting with Multiple Scenarios:

Enhanced Decision-Making Agility
Being able to quickly generate and compare multiple financial scenarios gives CFOs, FP&A and business leadership the agility to make informed decisions in response to changing market conditions. This agility is crucial for maintaining competitive advantage and financial health.
Improved Risk Management
Multiple scenarios allow for thoroughly examining potential risks and opportunities and their financial implications. A better understanding of impacts can help develop more robust risk mitigation strategies.
Strategic Allocation of Resources
With detailed scenarios that include revenue models based on operational data and employee cost models based on staff information, organisations can strategically allocate resources to optimise outcomes. This level of precision in planning helps to prioritise investments and provides Executives with much clearer guideposts.
Increased Forecast Accuracy
Using sophisticated models that draw on a wide range of operational and employee data leads to more accurate forecasts. Rapidly showing what-if scenarios, especially when M&A is discussed, or a new product or business line is being contemplated, in the context of real operational data helps build trust and promote rapid decisions.
Streamlined Planning Processes
Centralising all relevant financial data in a single Finance Data Warehouse not only makes the creation of scenario copies relatively straightforward but also significantly streamlines the planning process. This efficiency can lead to cost savings and more time for value add and, of course, helps lay the foundation for the adoption of AI. If you have read this far, I’m sure you wondered when AI would be mentioned.

A Finance Data Warehouse that includes planning models and the ability to generate multiple scenarios quickly and without issue revolutionises how companies approach budgeting and forecasting. This paradigm shift enables a more proactive, data-driven strategy for financial planning and analysis. Tools like Calumo make using these intuitive and are ideal for many Finance reporting and automation needs. At the same time, data can also be easily curated for use in reporting-focused tools, such as Power BI to remove many of the data-related issues typical when using these tools.

In conclusion, the capacity to generate multiple scenario copies rapidly, especially when integrated with detailed operational and employee cost models, is transforming the landscape of financial planning and analysis. For CFOs and FP&A Leaders, embracing these capabilities can lead to more informed decision-making, enhanced strategic planning, and, ultimately, greater organisational success.

If you are interested in learning more, please reach out to us.

Maximising Finance Data Warehouse Value with Calumo and Power BI

Post author By Tim Bryden
Post date

In today’s finance environment, owning a dedicated finance data warehouse is increasingly important. It provides a governed foundation for actuals, budgets, forecasts, commentary, and operational data structured around finance needs. Establishing that foundation can be complex and often takes weeks, particularly where internal IT teams have limited finance-specific experience. With Calumo and specialist implementation support, finance teams can implement that foundation more efficiently and use it for reporting, planning, analysis, automation, and future AI initiatives.

Understanding the Finance Data Warehouse:

At its core, a Finance Data Warehouse serves as the nerve centre of financial data management. It acts as a centralised repository, aggregating financial data from various sources, including General Ledger systems, budgeting and forecasting tools, operational databases, relevant external sources, and manual input and commentary. By consolidating data at a granular level, the Finance Data Warehouse enhances the contextual understanding of financial information, facilitating automation, comprehensive reporting and analysis.

The Role of Calumo in the Finance Data Warehouse:

Calumo is the primary finance platform; Power BI is an optional complementary visualisation layer.

Calumo transcends traditional reporting and budgeting tools by offering a comprehensive solution that includes creating a tailored Finance Data Warehouse in Microsoft SQL Server using a dimensional model approach. This Finance Data Warehouse is then expanded over time to further empower finance.

Calumo uses cubes that can be viewed and queried online for fast, self-service analysis, while data can also be accessed directly from the Finance Data Warehouse where required. This gives finance teams flexibility in how they report and analyse information, with reports authored in Excel so users can work in a familiar environment. Calumo also supports writeback, commentary capture, and a range of finance-specific modelling and automation needs, including allocation journals, commission calculations, eliminations, and other controlled processes.

Calumo includes charting capabilities and can leverage Excel charts, while Power BI can serve as a complementary visualisation layer when more specialised dashboards are needed. Tailored, updatable datasets can be delivered to Power BI directly from the finance data warehouse, making it easier to build targeted dashboards while maintaining a single source of truth. This reduces data wrangling and avoids unnecessary DAX complexity for finance teams.

Challenges in Establishing a Finance Data Warehouse:

Establishing and maintaining a finance-centric data warehouse poses unique challenges, especially for IT teams who may not be deeply familiar with the specific needs and nuances of the finance domain, may have limited or no prior experience in developing and managing finance-specific data warehouses, and, like any good IT team, may have many competing priorities.

This knowledge gap underscores the importance of partnering with a specialised consultancy like Brydens BI. With a wealth of experience in developing and managing complex Finance Data Warehouses, Brydens BI is a trusted ally, leading and guiding organisations through every implementation stage, always being available and providing ongoing support as an extension of the Finance team.

A good Finance Data Warehouse is data source agnostic. Over several years, Brydens BI has had many clients change source systems, staff, buy and sell businesses, and work through reorganisations. The only constant is the Finance Data Warehouse, with Calumo as its key interface. Several finance leaders have made implementing Calumo an early priority after joining a new business because they are accustomed to working with timely, reliable finance information rather than navigating an Excel quagmire or tools not specifically designed for finance.

How Calumo works with Power BI and Excel

Calumo’s Finance Data Warehouse and finance-friendly reporting and modelling provide the foundation. Power BI can then add visualisation and ad hoc analytical capability where required, while Excel remains familiar for report authoring and day-to-day finance use. With Brydens BI’s implementation experience and support, organisations can get up and running more quickly and make more effective use of these tools for reporting, analysis, and decision-making.

Frequently Asked Questions:

How does Calumo differentiate itself from traditional budgeting tools?

Calumo goes beyond traditional budgeting tools by providing a broader finance platform built on a tailored finance data warehouse. Rather than focusing only on budget input, it supports reporting, planning, analysis, commentary, and writeback in a governed finance environment.

Because Calumo links directly to a finance data warehouse built on Microsoft SQL Server using a dimensional model approach, it gives finance teams a stronger foundation for working with actuals, budgets, forecasts, and relevant operational data in one place. Reports are authored in Excel, allowing users to build on familiar skills while working from governed, well-structured datasets.

This foundation also helps finance teams become more AI-ready by creating cleaner, more consistent, and better-governed data for future automation, modelling, and AI initiatives. Where Power BI is used, tailored datasets can also be provided from the finance data warehouse, making it easier to build dashboards without placing unnecessary data wrangling or transformation effort on finance teams.

What specific advantages does linking Power BI with Calumo offer finance teams?

Many staff will have experience with Excel and Power BI. Linking Power BI with tailored datasets from the Finance Data Warehouse that underpins Calumo ensures a single source of truth, removing key data sourcing and data transformation issues associated with Power BI. It also means Finance teams get the best of both worlds, including the enhanced visualisation capabilities of Power BI and the data management, modelling, and finance-friendly reporting capabilities of Calumo.

How does Brydens BI support clients with their Finance Data Warehouse and Finance needs?

Brydens BI offers specialised expertise in designing, implementing, and supporting Finance Data Warehouse and analytics capabilities, drawing from its extensive experience with a range of large private and listed companies. Given its Finance and IT knowledge, combined with its depth of experience, a typical implementation requires only limited input from client-side resources.

Collaborating closely with clients, Brydens BI actively provides options, suggests best practices and delivers tailored solutions that address unique needs and challenges. As client businesses grow and change, Brydens BI remains available to ensure the underlying data warehouse and any associated applications and automation stay current. This allows the Finance team to focus on adding value and driving efficiency, accuracy, and strategic decision-making.

Beyond Spreadsheets: Why Every Modern CFO Needs a Finance Data Warehouse

Post author By Tim Bryden
Post date

In today’s fast-evolving business environment, the role of CFO has transformed dramatically. No longer confined to traditional bookkeeping or fiscal management, the modern CFO is at the helm of strategic decision-making, harnessing the power of data analytics to drive the business forward. One tool, in particular, stands out in this new era of financial management: the finance-specific data warehouse. In our view, beyond the familiarity of spreadsheets lies a tool that offers a magnitude of benefits tailored for the contemporary CFO.

1. Finance Specific Data

Central to successful financial decision-making is the availability and integration of relevant financial and operational data. Although spreadsheets were apt for a time when data existed in isolated silos, contemporary businesses thrive in a profoundly interconnected environment. Having critical financial and operation information tailored for finance in an intuitive and easy-to-use central data warehouse removes significant risks, makes any reporting and/or ad-hoc analysis faster, and means the Finance function is positioned to add value.

Apart from the obvious General Ledger, Finance often need broader business data for specific Finance use cases and/or to answer particular Finance style questions such as regulatory reporting or forecasting. Finance must control their data and directly influence how it is structured and maintained. Although broad business-wide datalakes or data warehouses are to be applauded and are often a very useful data source, they should not negate the need for a tailored finance-specific data warehouse whose primary purpose is to support Finance reporting, forecasting and efficiency.

2. Scalability and Performance

As organizations grow, so does their financial and related operational data volume. Spreadsheets, albeit convenient, have limitations in managing vast quantities of data, often leading to performance issues. A finance data warehouse, however, is inherently designed to handle large datasets, ensuring that CFOs can retrieve and analyze information rapidly, irrespective of its volume. Importantly, if the data warehouse is finance-centric and well-designed, the enormous amount of time wasting associated with using Excel to ‘format’ or ‘pivot’ the data also becomes redundant.

It also means that other popular tools become more effective. Tools like Power BI become far more useful when the underlying data sets are clean, trusted and designed for Finance.

3. Enhanced Data Accuracy and Reliability

In the world of finance, precision is non-negotiable. Manual data entries on spreadsheets are prone to human error, potentially leading to significant financial discrepancies. Data warehouses automate much of the data aggregation process and can include their own controls and reconciliations. This dramatically reduces the risk of errors and enhances data integrity.

In addition, as businesses evolve and new accounts get added or new cost centres are introduced, a well-designed finance-specific data warehouse (and associated reporting) will automatically handle these changes. If ‘manual’ management accounting adjustments, eliminations or allocations are required, then having these set and centralised in the Finance data warehouse and fully controlled by Finance will save significant time, reduce risk and increase accuracy. For instance, it is not uncommon for Brydens BI clients to have their CALUMO solution auto-generate cost allocations based on rules they define and have these form part of their management reporting with the option to generate an actual journal also available.

Similarly, reports set up in Power BI are far more effective if the team trusts the underlying data and knows that the underlying database is dynamically updating.

4. Timely Financial Insights and Forecasts

Businesses are moving faster. Waiting for month-end reports or quarterly analyses no longer suffices. Modern companies demand up-to-date data, and timely insights to respond swiftly to market dynamics. A finance-specific data warehouse that is connected to critical finance and operational data sources can provide essential reporting and advanced analytics in near-real time. This allows CFOs to oversee agile and informed decision-making. It also means that rolling forecasts become a standard tool, underpinned and automatically informed by models tied to actual financial and operational data.

Many Brydens BI clients have monthly rolling forecasts as standard. As we have implemented rolling forecasts and then continue to support them, it becomes clear that these businesses become much more forward-looking, and Finance becomes far more central to decision-making,

5. Advanced Analytical Capabilities and Automation

Beyond mere data storage, finance data warehouses are equipped with powerful analytical tools and centralise things like mapping to avoid the tedious use of VLOOKUPs often repeated across Excel workbooks. Brydens BI has designed, set up and continues to support dozens of Finance-specific data warehouses. By leveraging code and the power of databases, we see these being leveraged to run complex financial models, predictive analyses, and the automation of once time-consuming processes like allocations, consolidations, and eliminations. We also see CFOs continue to push the boundaries as they leverage their finance-specific data warehouse to answer challenges or key process challenges specific to their business.

This approach also lends itself to adopting Artificial Intelligence and Machine Learning, with several Bryden’s BI clients now using these technologies to understand better what might happen next and/or identify areas that need greater scrutiny.

Whether using sophisticated tools like Calumo, reporting in Power BI or even exposing data in Excel, ensuring the Finance team (and broader business) is using the same, trusted (and enhanced) finance data from a central finance-centric data warehouse removes significant risk from the business, saves time and unlocks much potential.

6. Data Security

In an era where data breaches can spell monumental crises, ensuring the security of key financial and operational data is paramount. Data warehouses can leverage robust security protocols to minimise the risk of unauthorized access or breaches.

Closing Thoughts

The digital transformation wave has left no stone unturned, and the finance function is no exception. As businesses hurtle towards an increasingly data-driven future, the tools of yesteryears — no matter how cherished — must give way to more advanced, efficient, and strategic solutions. This does not mean that broad business-wide data warehouses are unnecessary, nor does it mean that Excel will die; instead, how they are used will evolve. For the modern CFO tasked with steering the financial ship amidst volatile waters, the finance data warehouse is not just a tool; it’s an imperative.

Incorporating a finance data warehouse into the strategic toolkit is the forward leap that today’s CFOs must take to ensure their organizations remain competitive, resilient, and ever-evolving. Brydens BI supports businesses on this journey, primarily with CALUMO, Power BI and Excel. This includes an SQL Server-based data warehouse designed and supported by us (ex-finance staff) tailored to each client and their specific needs.

The journey beyond spreadsheets is not just a technological upgrade; it’s a paradigm shift in financial leadership.

Scenario Planning Enhanced: Leveraging the Finance Data Warehouse for Robust Employee Forecasting

Post author By Tim Bryden
Post date

In today’s complex and rapidly evolving business landscape, financial leaders are not just number crunchers but strategic decision-makers. Central to this transformation has been the rise of the Finance Data Warehouse (or finance data mart) designed for and owned by Finance. A centralised repository for detailed financial data and relevant operational data that underpins analytics, decision-making, and future planning.

One compelling application of the Finance Data Warehouse is in the domain of employee forecasting. In nearly all businesses, employee costs are significant. Understanding and accurately forecasting these costs and changes in FTE and Headcount becomes vital.

Employee Forecasting made easy.

Nearly all Brydens BI clients have a sophisticated Employee Planning model that is informed daily or monthly of actual changes via automated (API) connections or monthly file uploads, along with a simple interface to manage all future forecast changes. This level of automation and control becomes critical as clients reach hundreds or thousands of employees. Due to its ease of writeback, Calumo is typically the front-end tool used by clients who no longer have dozens of Excel files with employee data. Being able to rely on a central source of truth that they control reduces risk, saves time and makes Finance more relevant. In addition, with central, clean and trusted data, reporting with other tools, such as Power BI or Excel, becomes easier and more useful. Several Brydens BI clients leverage the Finance Data Warehouse that underpins Calumo to generate specific datasets tailor-made for Power BI.

The Finance Data Warehouse automatically updates rolling forecasts with new employees, terminations, and salary or cost centre changes. This automation saves significant time and reduces risk. Importantly, it also provides key business users with up-to-date, by-employee data they can discuss with Finance and use to make decisions. Being able to discuss variances and quickly drill to employees makes everything easier.

Using the Finance Data Warehouse to budget and forecast employees and all related costs, such as salaries, superannuation, and payroll taxes, simplifies core forecasting challenges. In addition, and where relevant, headcount or new starters can be used to model other relevant costs automatically. This also means that what-if style forecasting is straightforward.

Employee Forecasting is just the beginning.

In addition to Employee forecasting, once the General Ledger, HR Systems, and other relevant operational systems are linked to the Finance Data Warehouse, more possibilities are unlocked. For some clients, Brydens BI calculates and reports commissions, provides workforce planning capability, automates allocations (based on FTE and other metrics), and generates employee analytics and related visualisations through Calumo or Power BI.

In conclusion, the Finance Data Warehouse is not just a tool; it’s a game changer. By harnessing its capabilities, finance leaders can ensure more robust, accurate, and strategic employee forecasting while empowering their teams, removing significant unproductive work and providing the foundation for additional value-add. A finance-centric data warehouse also means monthly report packs and annual reporting, especially when linked to a tool like CDM (Certent Disclosure Management), becomes faster with less risk.

Brydens BI works with clients around Australia and worldwide. Because of our extensive finance experience, we often become an extension of the finance team and provide advice and support as required. Feel free to reach out if you want to know more.

Strategic Financial Planning: Navigating Change with Annual Budgets and Rolling Forecasts

Post author By Tim Bryden
Post date

The annual budget and the rolling forecast are critical deliverables for Finance. Historically, executing these effectively has posed a considerable challenge for many organisations. Some businesses would take months to produce a budget without even attempting monthly rolling forecasts. However, with bespoke solutions and adept support, this daunting task transitions into an opportunity, amplifying business value and redefining finance department significance.

Brydens BI works with many organisations and has helped them transition to rolling forecasts and far less painful annual budget processes.

The annual budget and rolling forecasts serve distinct yet complementary purposes, offering organisations the benefits of stability and adaptability in a dynamic business environment.

The Annual Budget: Setting the Course for the Year Ahead

The annual budget acts as an organisation’s fiscal compass. It remains static, instils fiscal discipline, establishes benchmarks for performance assessment, and helps define critical capital allocation decisions.

For many enterprises, the annual budget only focuses on the Profit and loss (P&L) statement. Yet others adopt a comprehensive three-way methodology, incorporating Balance Sheet and Cash Flow. At Brydens BI, we champion both approaches and have developed methodologies to streamline and tailor them to each client.

The Monthly Rolling Forecast: Adapting and Looking Further Ahead

Contrasting the static nature of the annual budget, the monthly rolling forecast thrives on adaptability, continuously adjusting in response to internal shifts and external influences. Brydens BI recommends setting up core models around employees, revenues and direct costs and would typically leverage CALUMO and its underlying Finance Data Warehouse to achieve this.

Each model, uniquely crafted to fit individual business needs, syncs seamlessly with pivotal operational data. This synchronisation ensures that when a month “rolls,” updates to the models mirror both operational and financial realities, enhancing the forecast’s pertinence while eliminating redundant tasks like copying and pasting data or updating a range of Excel workbooks. Brydens BI has clients who have built various complex models, including within Funds Management (with all the complexities around costs and hurdles by Fund), Equipment Lease and Term Loan Models, and Construction and Development Models. Clients have full control in all cases and typically extend and modify models as their businesses evolve (always with our support, if needed). These models become central to forecasting, especially as they are linked to real operational data and automatically update monthly or in line with business needs.

The strength of the monthly rolling forecast is its continual evolution and ability to inform business strategy. In our experience, Rolling Forecasts typically extend for three to five financial years (although we manage some that extend further). When done well, Rolling Forecasts equip businesses to anticipate challenges and spot burgeoning opportunities. Importantly, Finance and the company can discuss these as they evolve.

Combining Annual Budgets and Rolling Forecasts

An effective and timely annual budget and monthly rolling forecast equips organisations to define, evaluate, and recalibrate their fiscal goals. This dynamic allows for a harmonious blend of setting foundational expectations and making agile, informed strategy modifications in response to live data and emerging trends.

Notably, a high-quality monthly Rolling Forecast is the starting point of the Annual Budget process. In some cases, Brydens BI has seen clients reduce time spent on Annual Budgets from close to three months to under two weeks. Finance teams, who start with a rolling forecast informed by up-to-date operational data that Executives are familiar with, effectively have a draft Annual Budget (even multi-year) when they start.

Equipped with the right tools and support, focusing on insightful analysis rather than mere execution elevates the finance function’s stature. Brydens BI partners with numerous finance teams to set up and support monthly rolling forecasts and annual budgets. This is achieved through years of experience designing, implementing and managing robust Finance Data Warehouses that support Finance in these and other related tasks. To learn more, simply reach out.