Data analytics in business: why you need it and what it lets you see

Data analytics in business has a thoroughly practical purpose: to understand why things happen. Whoever grasps the causes faster — why the margin fell, why sales are growing in one branch but not in another — gains a competitive edge.

Analytics systems do two jobs. First, they let you analyse data held in separate, unconnected systems. Second, they are a powerful tool for presenting data.

Combining data from different sources

These days it is no longer enough to know that certain products are seasonal. Data has to be analysed within individual seasons: which products will be needed at the start of the season, in the middle of it, when it rains or the cold sets in, or while a major sporting event is on.

This is exactly where an analytics system proves its worth — it lets you link data sitting in different places. For example:

• link sales or stock level data from your accounting system with weather forecast data from a public meteorological website;
• forecast sales taking into account the raw material or energy price forecasts published on the market;
• combine accounting data with CRM information on customer activity.

This reveals correlations that simply cannot be seen in separate systems: between sales of different products, between a customer paying invoices late and bad debts appearing later on, and between promotions and the actual change in profit.

Presenting data: from the big picture to a single invoice

The second job is to present data in a way people can understand. In a well-built report you see the big picture, and by clicking on a figure you can drill down: from the annual total to the month, from the month to the branch, and from the branch to a specific product or invoice.

This changes the nature of the conversation in meetings. Instead of “sales fell”, you have “sales fell because of one product group in one branch, and here is when it started”.

Why this beats Excel reports

You can build the same tables in Excel. The difference is automation.

Once built, business analytics reports run by themselves: they pull data straight from accounting, CRM and ERP systems, websites or Excel files, and refresh without any manual work. An Excel report has to be fed new data every month, and every manual step is an opportunity for error.

Secondly, arguments over the numbers disappear: everyone looks at the same source rather than their own version of a file. We have described how to move from manual spreadsheets to automated reports in practice separately.

What data you actually need

A common assumption is that you need to “get your data in order” before you start. In practice, what is already in your accounting system is enough.

You can start with:

• sales and purchase data with dates, customers and products;
• general ledger accounts for income and expenses;
• stock levels, if you trade in goods;
• outstanding balances with payment terms.

Rivilė or Finvalda already collects all of this. Additional sources — CRM, an HR system, a budget in Excel — are added later, once the foundation is working.

The most common mistakes when starting out

From our experience of implementations, a few recurring ones stand out:

• Wanting everything at once. Thirty reports in the first month means none of them gets used. Better five that you actually open.
• No agreement on how a metric is defined. If “margin” means different things to the finance person and the sales manager, the report will not settle the dispute — it has to be settled beforehand.
• The report gets built but nobody owns it. A metric without an owner does not survive. Every report needs someone who looks at it and acts on it.
• Access rights are forgotten. A branch manager usually only needs to see their own site — more on this in our data security article.

Analytics is now within reach of small companies too

Business analytics systems have been around for a long time, but for years they were only available to large companies able to invest in expensive information systems.

That has changed. Microsoft Power BI Desktop is free, and ready-built report packages for Rivilė or Finvalda users start from €59 a month — which means serious data analytics is now within reach of a company of just a few people.

If your data comes from several different systems and you need a bespoke solution, we write about such projects on our Power BI implementation page. And you can see what the ready-built reports look like in the examples.