Data Insights — Business & Supply Chain

Investing in Data Analytics

The Real Business Case for SMEs

Rob den Otter April 2026 3 minute read Business & Finance

What you'll take from this

The biggest cost of data analytics is usually not the investment — it's what you lose by not having it.

Four areas deliver measurable ROI: inventory, revenue, marketing, and purchasing. This article builds the case for each.

For a business with €1M in stock and €2M in purchasing volume, the calculable savings easily exceed €150,000 per year.

Power BI doesn't create this value as a first step. It makes visible what's already leaking.

Inventory

The Asset Illusion — your warehouse is eating your margin

The problem

A persistent misconception in logistics: inventory costs equal the purchase price. In practice, total inventory carrying costs — interest, storage, risk, and obsolescence — run between 20% and 30% of inventory value per year. A €1 million inventory costs €200,000 to €300,000 per year. Just to own it.

The fix

In Excel, identifying dormant stock across thousands of lines is nearly impossible. A Power BI inventory dashboard connects directly to your ERP and shows real-time turnover by item group — including automatic alerts for products that have been sitting idle for more than 90 days and are therefore costing money rather than generating it.

€100K–150K

working capital freed
on €1M inventory

10–15%

inventory level
reduction

€20K–30K

lower operating costs
per year, structural

Revenue

The No-Reflex — the price of stockouts

The problem

Stockouts destroy customer loyalty and cost revenue directly. Sales reps say "no" because they think something isn't available — or say "yes" when stock is already reserved for another customer. Both cost revenue. Both are preventable.

The fix

Power BI makes Available to Promise (ATP) logic possible. It combines physical inventory, open purchase orders, and reserved sales orders into one clear figure. The sales team sees not just what's in stock — but what's available for sale, now and in the coming weeks.

+3%

direct revenue increase from
reducing stockouts 5% → 2%

€150K

additional revenue at €5M turnover —
without extra marketing spend

Marketing

The Halving — from shotgun to sniper

The problem

Everyone knows the line: half your marketing budget is wasted, you just don't know which half. Data lives in silos — Google Ads in Google, customer data in the CRM, sales data in the ERP. The true ROI of any campaign stays invisible.

The fix

Power BI's strength is its connectivity. It pulls data from Google Analytics, advertising platforms (LinkedIn, Meta), and the financial system, and overlays them. Instead of optimising for clicks and impressions — vanity metrics — you steer on Customer Acquisition Cost (CAC) and Customer Lifetime Value (LTV). You see exactly which campaigns generate paying customers.

25–30%

reduction in
cost-per-lead

€12,500

additional value on a
€50K marketing budget

Purchasing

Maverick Buying — stop leaving money on the table

The problem

Purchasing data is fragmented, and maverick buying — purchasing outside agreed contracts — is a common drain. Without centralised visibility, buyers often don't know that colleagues are ordering from the same supplier at different rates. Off-contract purchases typically cost an average of 20% above the agreed price.

The fix

A Spend Analysis dashboard in Power BI automatically categorises all purchase invoices. You immediately see how many suppliers you use for the same product group (consolidation opportunities), whether the same product is bought at different prices across locations, and who is buying outside contracts.

5–15%

purchasing savings via
consolidation and data

€40K

additional profit on
€2M purchasing volume

The conclusion: this is not an IT project

The four profit drivers above are independent of each other. But a business with €1M in inventory, €5M turnover, €50K marketing budget, and €2M purchasing volume can, on the benchmarks above, structurally improve €200,000 to €300,000 per year. Not by hiring more people. By seeing what was already there.

Den Otter Solutions helps Dutch SMEs make this hidden profit visible through Power BI dashboards built by Rob den Otter, an Analytics Translator with 25+ years of executive experience in supply chain, finance, and operations.

Frequently asked questions

Does Power BI work if our data is in Excel or Google Sheets?

Yes. Excel and Google Sheets are some of the most common starting points and works well as a Power BI data source. A daily scheduled export from your ERP or accounting system delivers 90% of the value — without complex live connections. Most clients start here and only move to a direct ERP connection later if needed.

How quickly do we see results after implementation?

Most businesses see actionable insights within the first week — specifically which inventory, purchasing flow, or campaign to tackle first. Structural returns (lower costs, higher margin) develop over the following months as decisions consistently move from gut feel to data.

Do we need an in-house data analyst?

No. Den Otter Solutions' Analytics as a Service fills exactly this role — as a flexible external data partner for SMEs without an internal data team. You get the expertise of a Business Controller and Power BI specialist, without the fixed staffing costs.

What does it cost to have these dashboards built?

Den Otter Solutions always works with a fixed price after a free scoping conversation — so you know upfront what the investment is and what it delivers. Contact us for a no-obligation conversation about your specific situation.