Budgeting and Planning

Plan Smarter – with Power BI

Modern sales budgeting doesn’t have to mean complex Excel spreadsheets and time-consuming coordination. Intelex’s solution allows you to enter budget data directly into Microsoft Power BI, where it integrates seamlessly with your existing analytics model. This means budgeting, updating forecasts, and comparing results all happen in one visual and user-friendly environment—without switching between platforms.

The solution is built on the Microsoft Fabric platform and leverages Azure cloud services, ensuring scalability, security, and smooth integration with your current systems. It’s designed for businesses that want to plan faster, respond more flexibly, and make confident decisions.

Curious how this works in a retail context?
Check out our blog post “Sales Budgeting That Works – Intelex’s Smart Solution for Retail Companies”, where we explain how rolling forecasts help you respond quickly to market changes, keep costs under control, and improve sales performance.

Want to see how it could work for your business?
Book a consultation and discover how our solution can turn budgeting into a strategic advantage.

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Planning solution helps with

  • Faster planning process

    A modern budgeting and planning solution speeds up the budgeting and forecasting process.

  • Collaboration

    People can enter data at the same time, and the data entered is automatically aggregated into a single result.

  • Model forecasts

    A faster and simpler process allows you to create different scenarios and model what to do in a crisis.

  • Better management decisions

    Good forecasting helps to make the right decision at the right moment (in a crisis). The future of the company may depend on it.

  • Advanced planning

    Constant comparison with actual results highlights the accuracy of forecasts. If forecasts do not match reality, they or the process itself can be adjusted.

  • Comparison with reality

    The value of budgeting and forecasting comes to the fore when the data are actually used. Forecasting in BI links forecast data to actual data and allows them to be compared.

Budgeting and planning with BI

Why budget and plan at all?

Does the owner insist? Has planning been taught in school and does everyone else do it? Often the process of budgeting tends to be a tedious chore done once a year, put in a drawer and that's it. We approach the budget as a management tool. It's about setting objectives and monitoring whether they are being met. Whether it's financial budgeting, sales forecasting or even production planning, for example.

Traditional budgeting in Excel spreadsheets is clumsy, requires a lot of work and ultimately someone from 10 different departments has to collate the information into one big spreadsheet. But what if you could make the process simpler, quicker and do it from the start so that the budget is comparable to the reality?

You can also budget more simply

Intelex has created a standalone solution for budgeting that allows you to enter data directly into the BI data model. As the BI solution already contains the actual data of the company, there is a nice functionality where the budget entry structure is created on top of the existing data structure and the budget/forecast entrant is left to fill in the necessary fields. Budgets from different departments are automatically consolidated, budgets can be pre-determined according to the rules from previous periods and budgets can be compared with reality all the time.

So, with a good solution, the process of entering the budget will become simpler and faster, the budget can be compared with reality and budgeting can be used as a modern forecasting and management tool, which also allows to react quickly to different challenges.

Main functionalities:

  • budget input directly into the data model

  • rolling budgeting, i.e. budget numbers can be changed on the fly to react to a changing environment.

  • locking of budget versions and comparison of different versions

  • automatic consolidation, e.g. department managers each enter their own unit budget and it is consolidated into the budget of the whole organisation.

  • pre-budgeting, e.g. based on the results of previous periods, pre-budgeting of new periods using statistical and machine learning algorithms.

  • hierarchical distribution from higher to lower levels (e.g. increasing the annual number by 10% also increases the monthly numbers by 10% in proportion, the same logic applies to the departments of the whole company etc.).

✺ Frequently asked questions ✺

  • Most of our clients use Microsoft's business analytics platform, and according to the client's needs, this generally means:

    -> Azure cloud services

    -> MS SQL Server with SSIS and SSAS services.

    -> on-premise solutions with Power BI Report Server

    -> Microsoft Power BI business analytics platform for data visualization.

    As our solutions are designed according to industry best practices, they can be made compatible with other BI platforms, for example, we have customers using Power BI and Tableau in parallel, as well as Power BI and QlikSense.

  • We've done so many different business analytics solutions that we have a pretty good idea of how much work needs to be done to create different solutions. First, you need to describe the data source (input data) and the desired end result (output). From this, we can give a pretty accurate volume estimate.

    For more complex solutions, it is sometimes wise to do a little analysis and identify the key nuances, but we will approach this as appropriate.

  • Our main technology partner is Microsoft, so we recommend using Microsoft SQL as the data warehouse platform. This can be deployed through cloud-based solutions from Microsoft Azure or through the classic MS SQL Server. In addition, we have also developed data warehouses on PostgreSQL and Vertica platforms.

  • It is possible to import data from virtually any digital data source, including Excel spreadsheets. To do this, the Excel file must be available for the data warehouse query, either in a shared directory or in the cloud.

    If possible, we recommend using a medium other than an Excel spreadsheet as a data source. The main risk with Excel is the potential errors that can occur when modifying the data, as Excel does not usually have any data quality rules.

    Nevertheless, Excel spreadsheets are sometimes a necessary source of information to ensure the integrity of the data in the data warehouse.