Commercialising Your Data: Why Sitting on Valuable Information Is Costing You More Than You Think

Every business is sitting on data. But very few are using it to make money.

Some call it data monetisation. Others say value realisation. Call it what you like. The bottom line is this: if you're not treating your data like an asset, you're leaving serious commercial upside on the table.

And no, this isn't just for the tech giants. Mid-market businesses, professional services firms, industrial operators, and even traditional manufacturers all have commercial data opportunities. You just need to know how to see them.

The problem: businesses treat data like admin

Most businesses collect data because a tool requires it. CRMs, ERPs, quoting systems, timesheets, spreadsheets. It’s entered for compliance, billing, or tracking, but once it’s in, it often goes nowhere.

Ask yourself:

• Is your data helping you find new revenue?

• Is it improving the way you price, sell, or operate?

• Is it being packaged into something customers or partners actually want?

If the answer is no, you’re not commercialising your data. You’re warehousing it.

What does it mean to commercialise your data?

Commercialising your data means turning internal information into external value. That could be direct revenue. It could be cost savings. It could be competitive advantage.

It’s about making your data work for you, not just sit there in reports.

Types of commercial value:

• New revenue streams: Selling or packaging data as a product or service

• Product enhancement: Using data to make your core offering smarter

• Operational savings: Automating decisions or removing waste using data

• Strategic insight: Making faster, more accurate decisions that grow margin

The mindset shift: from cost centre to growth asset

Most IT and data teams are treated like infrastructure. Support functions. They maintain systems and keep things running.

But data is different. It is one of the few assets in your business that gets more valuable the more you use it.

Treating data like a product means:

• Tracking ROI from data investments

• Prioritising what’s valuable to customers or execs

• Designing data outputs with users in mind

• Making quality, access, and reuse a priority

When you stop thinking of data as just reporting and start thinking of it as commercial leverage, everything changes.

Real-world examples of commercialising data

Let’s stop talking theory. Here are examples from real mid-sized businesses:

1. Professional services firm builds benchmarking tools

They were sitting on years of project data across industries. They started offering clients anonymised benchmarking dashboards to show how they compare on pricing, delivery speed, and margin. Now it’s a paid feature.

2. SaaS company monetises feature usage data

By analysing usage patterns, they were able to identify which features predicted upsells. They started charging partners for access to that insight. It also helped drive product roadmap decisions.

3. Logistics provider offers analytics to clients

Rather than just delivering goods, they now provide transport efficiency dashboards to their clients, helping them reduce costs and improve lead times. Clients pay for the added visibility.

4. Manufacturer leverages production data

They used to just track machine performance for internal maintenance. Now they package that data into equipment performance reports for resale to OEMs and engineering partners.

None of these are huge tech unicorns. They’re just businesses that realised data is part of the value chain.

The most common commercial data assets

You don’t need to invent something new. Most of the time, your commercial opportunity is sitting in your operational systems.

Look for:

• Customer behaviour: What people are doing, buying, using, and asking for

• Operational performance: Speed, margin, delivery time, error rates

• Pricing and costing data: Actual vs expected costs, profitable patterns

• Market signals: Patterns across locations, industries, segments

• Product usage: How your service or tool is being used

If this data is structured, accurate, and timely — it can be turned into something useful.

Use cases by business type

For B2B services:

• Package project data into client reports or subscription insights

• Use delivery metrics to feed pricing strategy

• Build internal IP around delivery patterns

For SaaS and digital platforms:

• Offer customer usage trends to partners

• Develop new pricing tiers based on behaviour

• Embed data-driven nudges into the product

For industrials and manufacturers:

• Use machine and sensor data to optimise operations

• Sell performance reports back to vendors or clients

• Benchmark internal sites or suppliers

For retailers or distributors:

• Sell anonymised sales trend data to suppliers

• Identify and monetise bundled buying behaviours

• Use location-based patterns to guide growth

How to start commercialising your data

You don’t need a massive data platform or an army of data scientists. You need to:

1. Identify valuable data assets

   • What data do you have that others care about?

   • What internal metrics drive margin or outcomes?

2. Clean and structure the data

   • If it’s messy, it’s not useful

   • Use simple tools to automate cleaning and consistency

3. Package it for use

   • Dashboards, reports, feeds, APIs

   • Build for the person using it, not the person building it

4. Attach a business model

   • Charge for access

   • Use it to upsell or improve stickiness

   • Build it into your product

5. Set up feedback loops

   • Watch how it’s used

   • Learn what’s valuable

   • Iterate quickly

Overcoming objections

Most of the resistance we see comes from:

• “Our data is too messy” → Good. That means no one else has packaged it either.

• “No one would pay for this” → Have you asked? Clients will often pay for better decisions.

• “It’s not worth the effort” → Then you’re underestimating how much value you’re sitting on.

If you’ve been collecting data for 5+ years and haven’t built a single commercial use case from it, that’s a red flag. You are sitting on untapped value.

The tools you need

You don’t need a huge investment. Most mid-sized businesses can start commercialising data with tools they already use or can access affordably:

• Data warehouse (BigQuery, Snowflake, or similar)

• ETL tools (Fivetran, Stitch, Airbyte)

• BI platforms (Power BI, Looker Studio, Tableau)

• Lightweight APIs or app connectors

It’s not about the tools. It’s about the mindset.

Final thought: Data is your product now

You already paid to collect it. You already paid to store it. You already paid to maintain it. Why are you not using it to grow your business?

Every organisation that invests in data should be asking one question: what commercial value can we create from what we already know?

Because if you don’t, someone else will.

Data is not just an asset. It’s inventory. Start packaging it. Start selling it. Start building with it.

Commercialising your data is no longer optional. It’s where your next margin boost is going to come from.