Excel is the most important evaluation tool in almost every company, and for good reason. It is flexible, anyone can use it, and for many questions it is just right. But at some point the relationship ends: The monthly report lasts three days, two departments name different sales figures, and the file on which everything hangs, only one person understands. When the switch to a business intelligence solution is worthwhile depends less on the company size than on a few clear signs.
Why Excel works well for so long
It would be wrong to denigrate Excel. For ad hoc analyses, calculations, planning calculations and everything a person evaluates for himself, a spreadsheet is hard to beat. It needs no project, no training, and no IT department. Whoever has a question answers it himself.
It only becomes problematic when Excel becomes an infrastructure. Then the table is no longer a tool, but a system based on decisions, and it is maintained like a tool: manually, without versioning, without testing. This transition is rarely noticed on a given day. You notice him by the symptoms.
Five Signs It's Time
- Reporting takes more time than analysis. If someone spends days every month exporting, copying, and formatting data from ERP, CRM, and accounting before anyone even looks at the numbers, the bottleneck is not with the evaluation, but with the data collection.
- There are several truths. Sales and controlling come up with different sales figures because they exported at different times, filtered differently or treated credits differently. The meeting then turns to the question of which number is correct, rather than the question of what to do.
- Knowledge depends on a person. The central file has nested SVERWIS formulas, hidden sheets, and macros that only its creator can see through. If this person fails, the reporting is available.
- The figures come too late. Monthly reports, which are available in the middle of the following month, are suitable for review, but not for control. Those who need stocks, incoming orders or open items on a daily basis cannot cope with manual exports.
- The file reaches technical limits. Long loading times, crashing workbooks, data that needs to be distributed across multiple files. At the latest then you work against the tool.
If two or more of these points are true, it is worth taking a closer look. If they are all true, the status quo probably already costs more than a solution.
What makes a BI solution different
The real difference is not in the diagrams. Dashboards can also be built in Excel. The difference lies in this: in an automated data link that regularly fetches the data from the source systems, cleans them and merges them into a uniform model. Key figures such as turnover, contribution margin or delivery reliability are defined there once and then apply equally to all reports.
The question of which number is correct disappears. Anyone who looks at sales in sales sees the same number as the management, only filtered differently. Permissions govern who is allowed to see what, and the update runs automatically overnight or even several times a day.
A BI solution does not replace Excel. It replaces copying. Anyone who wants to continue computing in Excel can do so, but on a common, tested database.
In fact, Excel remains in use in most companies after introduction. Power BI, for example, can be queried directly from Excel. This is not a compromise, but usually the most sensible division: standard reports and key figures come from the BI solution, individual analyses are still created in the table, only with reliable figures.
What Introductions Fail
Technology is rarely the problem. A tool like Power BI is set up quickly, and the first dashboards are in days. It gets difficult in two places.
The first is the data itself. If customer numbers in ERP and CRM do not match, article groups have been rebuilt over the years or master data is incomplete, the most beautiful dashboard shows incorrect numbers. The BI introduction brings such problems to light, which in Excel someone has quietly corrected by hand. This is unpleasant, but valuable, and it takes time to plan.
The second is the definitions. What is an active customer? Does an order with incoming order or with delivery count towards sales? Such issues are technical, not technical, and must be decided before the reports are built. Projects that skip this provide several truths again in the end, only in a more expensive tool.
How to Start Small
A BI project does not have to start with an enterprise-wide data warehouse. The start has proven itself via a concrete report that costs a lot of manual work today, such as the monthly sales report or the liquidity overview. For this one report, the sources are connected, the key figures are defined and the route is automated. This takes weeks, not months, and it quickly shows whether the approach is contributing.
Then the solution grows report by report. Every new source and every new indicator ends up in the common model, and the effort decreases because the basis already stands. From the outset, it is important to have a clean data link instead of direct connections from each report to each source. How we build such routes, we describe on the page to Business Intelligence and ETL.
Conclusion
The right time for the switch does not depend on a number of employees. It is achieved when obtaining the numbers takes more time than evaluating, when different departments name different numbers or when the reporting depends on a single person. Then it is worth getting started with a concrete report that shows what an automated database does. If you want to check whether and how this can be implemented in your company, we support you in the Launch of Power BI and Microsoft Fabric. Talk to us.
Would you like to implement this in your company? We support you pragmatically – from the idea to the operation.