How Data Collection Services Turn Raw Data into Strategic Business Assets
- Champak Pol
- November 15, 2025
- 6:29 am
Data is no longer just a byproduct of operations. It’s a powerful driver of business growth. Yet many UK enterprises haven’t fully tapped into the value hidden in their data. While global leaders like Walmart and Wolters Kluwer are showing what’s possible, UK-based companies are still finding their footing.
This article offers practical, human-centred guidance for leaders looking to turn raw data into business advantage.
1. The Revenue Opportunity: Why Data Monetization Matters
A 2024 MIT CISR study found that leading companies earn about 11% of their revenue from data, while others average just 2%. For a UK business with £2 billion in turnover, that difference could mean more than £180 million each year.
Globally, the data monetization market is expected to grow from $3.5 billion in 2023 to $14.4 billion by 2032 (IBM Insights). This growth shows how quickly data is becoming a core business asset.
2. What Most Strategies Miss
he financial upside is clear, but many businesses miss important steps in building a solid data strategy. Here are a few areas where UK leaders should pay closer attention
a. Data Quality and Governance
Messy data can quietly drain millions in revenue. Gartner estimates poor data quality costs businesses about 20% of their income. Strong data governance, standardised processes, and clearly defined ownership help ensure that your data is trustworthy and usable.
b. Ethical and Compliant Use
With regulations like GDPR and the upcoming EU AI Act, compliance and transparency aren’t optional. UK companies must have clear policies for consent, anonymisation, and secure data sharing. Resources like the UK ICO and Open Data Institute offer guidance on how to build trust while using data effectively.
c. Culture and Talent
Many businesses invest in data tools but fall short on adoption. While 86% of organizations claim they make data-driven decisions, only 43% actually do, revealing a critical gap between perception and reality. Data literacy and organizational culture emerge as the primary barriers, requiring targeted investment in literacy programs and behavioral change rather than technology alone.
To build momentum, companies need to:
- Offer data literacy training across teams
- Appoint a Chief Data Officer to lead the strategy
- Build cross-functional teams focused on using data to solve real business problems
3. A Roadmap for Turning Data into Value
Data monetization isn’t a one-off project. It’s a journey. Here’s how to build it in stages:
Phase 1: Set the Foundation
- Move to a scalable cloud platform like Azure or Snowflake
- Break down internal data silos
- Organise your data with proper cataloguing and metadata tools
Phase 2: Use Data Internally First
- Build APIs and dashboards that teams can use
- Create an internal marketplace where departments can share and access data
- Define service levels so teams know what to expect from data services
Phase 3: Offer Data Outside the Company
- Package insights for partners and customers
- License anonymised datasets for use in research or industry reports
- Create data-driven tools or services your customers can subscribe to
Phase 4: Make Data Part of the Business Strategy
- Share data performance in company reports
- Link data outcomes to ESG goals, innovation metrics, or brand impact
4. Where Outsourced Data Services Fit In
Not every business needs to build everything in-house. In many cases, outsourced data services can accelerate value while reducing risk. These services help by:
- Consolidating fragmented data sources
- Delivering cleaned, standardised data faster
- Scaling capabilities without increasing internal headcount
- Freeing internal teams to focus on higher-value strategic analysis
When thoughtfully integrated, outsourced data collection services act as an extension of the business, not a replacement. They help organisations transition from siloed, reactive data management to coordinated, insight-driven operations.
5. Common Mistakes to Watch For
Avoiding these pitfalls will help your data strategy stick:
- Prioritising quantity over quality
- Letting technology dictate the approach, instead of starting with business goals
- Ignoring security risks
- Expecting quick wins when the real payoff may take a couple of years
6. Looking Ahead: What’s Next in Data Monetization
a. Generative AI
Clean, structured data is the fuel for effective AI. Businesses with high-quality datasets are in a great position to build custom AI tools. Learn more in Forrester’s 2024 predictions.
b. Data-as-a-Service (DaaS)
More UK organisations are finding value in data sharing across sectors, from Open Banking to NHS health platforms and smart city projects. These models allow for data collaboration while respecting privacy and governance.
c. Data Marketplaces
Platforms like Snowflake Marketplace, Dawex, and Equifax Ignite are gaining traction in sectors like insurance and telecom. Expect to see more companies exploring external licensing and partnerships.
7. Proving the Value of Data
Executives must track data ROI just like they would with any other investment.
You can start by:
- Creating key performance indicators (KPIs) tied to data
- Measuring the return of specific data products or use cases
- Including data metrics in board updates and investor reports
Take inspiration from Wolters Kluwer, which grew its data-based products from 10% to 94% of revenue by focusing on measurement and accountability.
Final Thoughts
Monetising data isn’t just about tools or infrastructure. It’s about mindset, structure, and execution. UK leaders who invest in the right foundations, use data responsibly, upskill their teams, and scale gradually will be well-positioned for long-term gains. Those who delay may find themselves falling behind.
Now is the time to treat data as more than an asset. It’s a product and a strategic one at that.
