"To be honest, we don't really know how this month's sales or gross margins are tracking until accounting aggregates each file in Excel at month-end. Because of that, our executive meetings always focus on last month or the month before that. Our countermeasures are inevitably reactive." This was a consultation we recently received from the executive of a company with about forty employees.
When figures can only be seen after someone aggregates them, management decisions are always reactive. Moreover, the aggregation process itself is laborious, requiring someone to stitch together multiple files manually, placing a heavy burden on staff. By using Looker Studio, Google's free BI tool, you can consolidate data from spreadsheets and GA4 onto a single dashboard and review it in an up-to-date state at all times. In this article, we explain how SMEs can visualize management figures, from our perspective of partnering through custom development and support.
From "viewing after tallying" to "always visible"
First, let us understand the essence of this transition. Looker Studio is a tool that connects data sources like spreadsheets, GA4, advertising, and accounting data, displaying them as charts and tables in a single report. The crucial advantage is that when the source data updates, the dashboard automatically reflects the latest figures.
In other words, the monthly manual grind of gathering files, pasting rows, and building charts is replaced by a setup where you design it once, and it updates automatically thereafter. Executives can simply open the dashboard in a web browser to see current revenue, gross profit, and payment collection status. There is no longer any need to discuss last month's figures in current meetings.
What to put on the initial dashboard
That said, building a dashboard packed with dozens of metrics right from the start will only lead to nobody looking at it. What you should include initially are a few key KPIs focused strictly on the numbers the company cares about daily.
For many SMEs, good starting points include monthly sales, quota attainment, gross margin, receivables and overdue collections, and year-over-year comparisons. You can add web inquiry counts if necessary. The general rule is to narrow metrics down strictly to those that change subsequent behavior once viewed. If you display numbers people merely look at and forget, the dashboard becomes nothing more than a decoration. Grasping what is happening right now is closely linked to our article on dependency inventory for visualizing entire systems and our FinOps article for making cloud costs visible.
The stumbling block is data location, not presentation
This is the area where we receive the most consultations during client development. Building visually appealing charts is not difficult in itself. Projects actually stall when source data is fragmented and not in a state where it can even be connected.
Sales numbers kept in separate spreadsheets by each representative, expense categories named differently from month to month, inconsistent date formats—in such conditions, a dashboard cannot output accurate numbers. That is why, before building visual components, we begin by organizing where data is stored and how it is formatted. We standardize spreadsheet column definitions, establish input rules, and create pipelines to regularly ingest data from accounting or sales software if needed. Once this foundation is cleared, assembling the Looker Studio interface takes very little time. If manual transcription is involved, also consult the concepts in our article on SaaS data integration.
Case study: A company manually aggregating five files every month
Here is a specific example (the company name is withheld). A company consulted us because their accountant was manually copying sales, gross margins, and payment collection data from five separate spreadsheets each month to compile meeting reports. Aggregation took an entire day, occasional copy-paste errors occurred, and confidence in the figures was being undermined.
We standardized the column definitions and entry rules across the five files, organizing them so data aggregated automatically into a single master spreadsheet. We then constructed a Looker Studio dashboard displaying monthly revenue, target attainment, gross profit, and uncollected payments on one screen. Because updates to source data flow through automatically, manual month-end aggregation was eliminated entirely. What made the difference was not sophisticated charting, but "standardizing the data format beforehand and creating an uninterrupted flow of updates."
Establish an uninterrupted update mechanism before building dashboards
Pay attention to the sequence. When adopting BI tools, it is tempting to jump straight into designing an impressive dashboard, but what you must establish first is a mechanism where data gathers automatically, in the correct format, every single day. Once this is ready, dashboards can be added or adjusted freely later. Conversely, skipping this step results in an abandoned dashboard that is used only in the first month and then left stale because updates grind to a halt.
If you only know your revenue and gross profit at month-end, spend hours every month aggregating numbers, or find management decisions lagging because data is scattered across files, please feel free to reach out via GleamHub's Development, AI, and Automation consultation. We will assist you within a realistic scope, from taking inventory of current data to automating aggregation and building executive dashboards in Looker Studio.
