Finance usually has no shortage of figures. The challenge is that actuals, budgets, forecasts, liquidity, and operational information are spread across different accounting systems, other systems, and files.
Bringing financial and operational data together creates a single, reliable view of what happened, why results differ, and what to expect going forward.
There is usually plenty of financial data. The challenge is that actuals, budgets, forecasts, liquidity, and operational information are spread across accounting systems, ERP systems, planning tools, and separate files. As a result, reporting requires extensive manual work and does not automatically provide a single, reliable view.
In practice, we mainly see the following issues:
Figures are collected from different accounting systems, reports, and spreadsheets, then checked and reworked. As a result, every reporting cycle involves a great deal of recurring work and remains prone to errors, version discrepancies, and unclear traceability.
Differences between accounting systems, missing mappings, and inconsistent definitions often become apparent only during the period close. As a result, Finance spends considerable time on reconciliation and corrections before the figures can be shared.
Budgets and forecasts are often maintained in separate files or applications. This makes it difficult to identify variances in time, update expectations, and compare different scenarios.
The profit and loss statement shows that revenue, costs, or results differ from expectations, but not always why. Without links to customers, products, projects, employees, orders, and other operational data, Finance remains dependent on additional analyses and separate explanations.
Revenue, costs, margins, results, and other KPI metrics are not always calculated consistently. This leads to discussions about the figures when the conversation should really focus on causes, expectations, and corrective action.
A financial report is only reliable when its underlying data, definitions, and mappings are aligned. In practice, general ledger structures, cost centers, accounting entities, and revenue definitions often differ by system or business unit.
By modeling financial data centrally, these differences are made explicit and resolved in a controlled way. Totals remain traceable to the underlying entries, while the same definitions are used for management reporting, analysis, and detailed review.
This creates not just a single report, but a data foundation that Finance can rely on.
A fully reconciled dashboard starts not with the visualization, but with definitions that are also correct under the hood.
Good Finance analytics shows not only what has happened, but also what is likely to happen next.
Annual financial statements and monthly reporting remain important, but up-to-date expectations are just as relevant for day-to-day management. Finance needs to see how actuals are developing against budget and forecast, which assumptions are changing, and what that means for profit and liquidity.
By linking financial data to operational developments, forecasts can be adjusted sooner. Data-entry and planning applications also allow budgets, rolling forecasts, scenarios, and explanations to be recorded in a controlled way and compared directly with actuals.
This shifts Finance from retrospective reporting to analysis, forward planning, and targeted advice.
Where does profit vary, and what causes the variance?
Analyze revenue, costs, profit, and balance sheet items by accounting entity, company, department, cost center, or general ledger account. Compare periods, years, and organizations using the same structure.
Compare actuals with budget, forecast, and the previous year. Drill down from the total to the category, account, and transaction details to identify the source of a variance more quickly.
What do we expect, and which assumptions underpin those expectations?
Track actuals against budget and the current forecast. Maintain plans by accounting entity, department, cost center, account, or other relevant dimensions.
Explore what different assumptions about revenue, costs, staffing, prices, or investments mean for profit and liquidity. Where needed, we add data entry, writeback, and explanations.
Are the figures traceable, and does the financial position remain healthy?
Monitor current liquidity positions, trends over time, and differences between bank accounts. Where possible, combine actual cash positions with expected income and expenses.
Check totals across accounting entities and drill down into transactions, documents, customers, suppliers, and posting details. This keeps reports verifiable and traceable.
Financial information is rarely stored in one place. The general ledger and subledgers reside in ERP and financial systems, budgets and forecasts may be kept in spreadsheets or planning tools, liquidity data is held by banks, and the drivers behind results are found in operational systems.
We combine data from systems including AFAS, Exact Globe, Exact Online, SAP, Microsoft Dynamics 365 Business Central, Dynamics AX and NAV, Unit4, CCH Tagetik, Reeleezee, Excel, and custom systems. Data from CRM, order management, HR, projects, and other operational sources can also be included.
This creates one coherent view of:
The value does not lie in adding yet another standalone integration, but in properly aligning definitions, general ledger structures, and processes. When accounting entities and reports interpret revenue, costs, or results differently, even a technically correct report remains open to debate.
A period close is often delayed not by one major problem, but by many small reconciliation differences. Subledgers do not reconcile directly with the general ledger, mappings differ between accounting entities, and checks are performed manually in spreadsheets.
By centrally documenting definitions, mappings, and checks, exceptions can become visible earlier. Reports remain traceable from the management level down to the general ledger account, document, and individual posting. This makes it easier to investigate differences and avoids having to rebuild the same checks every month.
Finance retains responsibility for processing and approval. The analytics solution makes the required information available faster, easier to verify, and more consistent to apply.
Closing faster usually starts with identifying reconciliation differences earlier.
Planning becomes useful when assumptions, inputs and actuals come together in the same environment.
In many organizations, budgets and forecasts still reside in separate spreadsheets. This leads to version differences, makes it unclear which assumptions were used and makes consolidation time-consuming.
Input and planning applications allow users to record budgets, rolling forecasts, scenarios and explanations in a controlled manner. This can be done by accounting entity, department, cost center, project, account or month, for example. In Qlik, we regularly implement this using Inphinity.
New projections can be compared directly with actuals, the previous year and earlier forecast versions. This reveals which assumptions are changing, who is responsible for the inputs and what a revised scenario means for profit and liquidity.
A financial variance is usually the result of something happening elsewhere in the organization. Revenue changes due to volumes, prices and discounts. Personnel costs change due to staffing levels, contractors and absenteeism. Project results change due to hours, progress and scope. Logistics costs change due to volumes, routes and deliveries.
Connect revenue, costs and margin with customers, products, projects, employees, orders, locations and other relevant dimensions. This allows Finance to drill down from a variance into the processes contributing to it.
Finance can spend less time gathering explanations and discuss sooner with budget owners and management what is changing, which actions are needed and what their expected financial impact will be.
Reliable financial management requires both clear management information and a data foundation aligned with Finance’s daily processes. Finance Management, Financial Control and FP&A each take a different perspective, but they must be able to work from the same figures and assumptions.
Finance Management wants to know how the organization is performing financially, which risks are emerging and where adjustments are needed. This includes:
Financial Control and FP&A ensure that reporting, analysis, and planning are reliable and repeatable. This includes:
This creates a single shared view for Finance, management, and the rest of the organization. Instead of everyone working from their own exports or definitions, they use the same figures and an auditable data foundation.
Effective financial management does not start with a standard dashboard, but with the questions Finance needs to report on, analyze, and forecast more effectively. We then bring processes, definitions, and data sources together and build a solution that fits the existing organization.
We start with the most important financial questions. Where do actual results deviate from expectations? How are costs and liquidity developing? How reliable are the budget and forecast? Which analyses currently require a lot of manual work?
We also agree on definitions for revenue, costs, results, margin, budget, forecast, and liquidity, among other things. This prevents different reports from continuing to present their own version of the truth.
We connect financial systems such as AFAS, Exact, SAP, Business Central, Dynamics AX and NAV, Unit4, Tagetik, and Reeleezee with planning systems, banks, and relevant operational data sources.
We account for accounting entities, general ledger structures, cost centers, currencies, periods, posting groups, consolidation, and access rights. Spreadsheets, budget files, and custom systems can also be included.
Based on this foundation, we develop dashboards, analyses, and planning applications for areas including:
Where needed, we use Inphinity to add data entry, writeback, rolling forecasts, commentary, and planning, so the solution not only looks back but also actively supports forward planning and course correction.
Depending on the existing environment, we work with Qlik, Power BI, Microsoft Fabric, TimeXtender, or a combination of these.
If you already have an analytics environment, we build on it when that makes sense. We can improve existing models and reports, add new accounting entities, harmonize definitions, or support a migration. If you have doubts about the current approach, a Second Opinion Data & Analytics can be a good first step.
After delivery, we can also support and manage the environment, allowing new accounting entities, data sources, reports, and planning processes to be added in a controlled way.
For Medux, we helped build a central data foundation that brings together data from multiple source systems. A key starting point was streamlining and accelerating the financial revenue close. Consistent definitions and reusable data models help reports align more closely and make figures comparable across different business units.
For a national occupational health service provider, we developed financial reports covering multiple accounting entities. The solution combines the income statement, budget, forecasting, and liquidity insights. Users can analyze data by period, accounting entity, and general ledger category, while access to financial data is secured separately for each accounting entity.
For an insurance intermediary, we developed a Finance solution for booked and expected commissions, underwriting commissions, and fees. Finance and management can analyze revenue and net retention by client, advisor, intermediary, insurer, and period, including comparisons with last year and forecasts for the current year.
Financial data rarely resides in a single system. We combine data from ERP, financial administration, budgeting and planning systems, banks, spreadsheets, and operational sources into a single coherent view.
Many organizations already have financial systems, spreadsheets, dashboards, and periodic reports. The question is usually not whether everything needs to be replaced, but where the current information falls short and which improvement will deliver the most value.
For example, we can:
Even when the data still needs work, an initial analysis can be valuable. It reveals which discrepancies, missing mappings, and quality issues have the greatest impact on the reliability of reports and forecasts.
A good Finance solution does not have to start big. Above all, it should improve the reporting, analysis, or planning that currently takes the most time or creates the most uncertainty.
That depends on the questions you want to use to guide decisions. We often combine general ledger and subledger data with budgets, forecasts, cash flow data, and relevant operational data. Financial data may be sufficient for an income statement or balance sheet. To explain and predict trends, data on customers, products, projects, employees, orders, and capacity utilization is often valuable.
Yes. We have experience with systems including AFAS, Exact Globe, Exact Online, SAP, Microsoft Dynamics 365 Business Central, Dynamics AX and NAV, Unit4, CCH Tagetik, and Reeleezee. Databases, APIs, spreadsheets, and custom systems can also be used as data sources. Replacing existing financial systems is not an automatic starting point.
Yes. We can combine financial data across multiple entities, companies, and business units. Where necessary, we harmonize general ledger structures, cost centers, periods, and other dimensions. The solution can provide both a consolidated overview and detailed analysis for each entity.
Yes. In addition to reporting on existing budgets and forecasts, we can build data entry and planning applications. In Qlik, we regularly use Inphinity for this purpose. It allows users to enter budgets, rolling forecasts, scenarios, assumptions, and notes in a controlled way and compare them directly with actuals.
Yes. This connection often makes financial analyses more valuable. For example, we can link revenue and costs to customers, products, orders, projects, locations, employees, or other business processes. This shows not only that a financial KPI deviates, but also which developments are likely contributing to it.
We can mainly speed up data collection, reconciliation, validation, and reporting. This can include centrally managing definitions and mappings, automated checks, and reports that can be traced back to transaction level. How much time this saves depends on the current processes and the causes of delays.
Yes. We can assess and improve existing dashboards, data models, and definitions. This may involve missing entities, inconsistent KPI definitions, manual steps, slow reports, or insufficient alignment between financial and operational results. If you are unsure, a Second Opinion Data & Analytics can be a good first step.
That depends on the existing environment, information needs, and desired solution. We work with technologies including Qlik, Power BI, Microsoft Fabric, and TimeXtender. We prefer to build on what is already in place.
No. A clearly defined question or an initial application can be a sensible starting point. Examples include budget versus actuals, cash flow insights, an income statement across multiple entities, or automating a periodic report.
That depends on the number of entities and data sources, data quality, differences in general ledger structures, and the desired level of detail. A clearly defined report can be delivered through a manageable project. A broader solution involving multiple entities, operational sources, planning, and writeback requires more analysis, modeling, and coordination.
Yes. Different entities or business units do not need to use exactly the same chart of accounts. We can create mappings and reporting structures that map local general ledger accounts to a shared management structure.
The original transactions and local structures remain available, allowing users to drill down from a consolidated overview to the source data at any time.
Yes. Dashboards can be configured so users can drill down from a total or variance to the general ledger account, journal, document, customer, supplier, and individual transaction. The details available depend on the data exposed by the source system.
Yes. We can analyze current and historical liquidity data for each bank account and track developments over different periods. If expected receipts and payments are also available, they can be used to extend the view further into the future.
Yes. Access can be tailored by accounting entity, company, department, or other organizational structure. This allows management to see a consolidated view, while other users only see the financial data for which they are responsible.
No. Finance analytics can support consolidation, planning, and management reporting, but it does not automatically replace a specialized solution for statutory consolidation, financial statements, audit trails, or complex intercompany eliminations.
For each business need, we determine which functionality logically belongs in the analytics environment and where a specialized financial platform should remain the primary system.
Do you want to speed up reporting, better understand where results differ, or track budgets, forecasts, and liquidity from a single reliable data foundation? Barry and Eric would be happy to discuss your current environment, information needs, and a logical next step. In half an hour, you will know whether we are a good match. Email us, call us, or schedule a call right away.
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