In today’s digital economy, data is more than just a byproduct of business operations. It is a critical asset that can drive growth, improve decision-making, and increase your company’s worth. But how do you unlock the true value of your business data? Understanding this can transform how you approach strategy, investment, and competitive advantage. Understanding the Value of Business Data Data is often called the new oil, but unlike oil, it does not deplete when used. Instead, it can be refined, combined, and analysed repeatedly to generate insights and opportunities. The value of business data lies in its ability to inform decisions, optimise processes, and create new revenue streams. For example, customer data can help tailor marketing campaigns, improve product development, and enhance customer service. Operational data can identify inefficiencies and reduce costs. Financial data supports better forecasting and risk management. Each type of data holds potential value that, when unlocked, can significantly impact your bottom line. However, not all data is equally valuable. The quality, relevance, and timeliness of data determine its usefulness. You need to assess your data assets critically and strategically to realise their full potential. Data analysts working in a modern office environment Why the Value of Business Data Matters Recognising the value of your business data is essential for several reasons: Strategic decision-making : Data-driven insights help you make informed choices that align with your business goals. Competitive advantage : Leveraging data effectively can differentiate your business in crowded markets. Investment and funding : Investors and lenders increasingly consider data assets when evaluating companies. Mergers and acquisitions : Data valuation plays a crucial role in determining the worth of a business during transactions. Operational efficiency : Data can reveal areas for cost savings and process improvements. Consider a retail company that uses sales and customer data to optimise inventory levels. By reducing overstock and stockouts, the company saves money and improves customer satisfaction. This example shows how data’s value translates directly into financial performance. Business analytics dashboard showing key performance indicators How to determine the value of data? Determining the value of your data involves a systematic approach. Here are key steps to guide you: Identify data assets : Catalogue all data sources, including customer, operational, financial, and third-party data. Assess data quality : Evaluate accuracy, completeness, consistency, and timeliness. Understand data usage : Analyse how data supports business processes and decision-making. Estimate economic impact : Quantify how data contributes to revenue, cost savings, or risk reduction. Consider legal and compliance factors : Account for data privacy, security, and regulatory requirements. Benchmark against industry standards : Compare your data assets with competitors or similar businesses. This process requires collaboration between data experts, finance teams, and business leaders. Tools and frameworks for data valuation can provide structured methodologies to ensure accuracy and credibility. For instance, a manufacturing firm might find that its sensor data reduces downtime by predicting equipment failures. By calculating the cost savings from avoided downtime, the firm can assign a tangible value to this data. Business meeting focused on data strategy and valuation Practical Ways to Unlock Data Value Once you understand the value of your data, the next step is to unlock it. Here are practical recommendations: Invest in data infrastructure : Ensure you have the right tools and platforms to collect, store, and analyse data efficiently. Enhance data governance : Implement policies to maintain data quality, security, and compliance. Foster a data-driven culture : Encourage teams to use data in everyday decision-making. Monetise data assets : Explore opportunities to sell data insights or create data-driven products. Collaborate with partners : Share data securely with trusted partners to create mutual value. Continuously monitor and update : Data value changes over time, so regular reassessment is crucial. For example, a financial services company might develop predictive models using customer data to offer personalised loan products. This not only improves customer experience but also increases revenue. The Future of Business Data Value The importance of business data will only grow. Emerging technologies like artificial intelligence, machine learning, and blockchain will create new ways to extract value. Businesses that prioritise data valuation and management will be better positioned to adapt and thrive. Moreover, regulatory environments are evolving, making data governance and transparency critical. Understanding the financial value of your data helps you balance opportunity with risk. By unlocking the value of your business data, you gain a powerful asset that supports smarter strategic decisions, attracts investment, and maximises your company’s worth in any transaction. Start today by taking a closer look at your data assets. What hidden value might you discover?

Every founder believes their data is valuable. It’s a reasonable assumption, data underpins growth, customer insight, product development and, increasingly, business valuations. But when it comes to the high-pressure environment of raising capital or negotiating an acquisition, assumptions aren’t enough. Investors notice gaps, inconsistencies, and misjudgements long before many leadership teams do. These are the three data mistakes that quietly undermine credibility, and deals. 1. Overstating data’s role without quantifiable commercial value It’s one thing to claim your data is driving growth, improving retention or informing product development. It’s quite another to prove it in financial terms. Too often, founders rely on qualitative descriptions of their data’s importance, while investors expect a clear, defendable valuation or at least measurable commercial outcomes. When pressed, many leadership teams struggle to demonstrate how their data contributes to revenue generation, cost reduction, or competitive advantage. Vague assertions do not inspire confidence. Sophisticated investors want to see a direct line between data assets and enterprise value. 2. Treating data as infrastructure spend rather than a monetisable asset It’s a common scenario: businesses view their data as an operational or IT issue - a cost centre. They invest in data lakes, analytics tools and compliance processes, but rarely take the next step of treating data as intellectual property that can drive licensing opportunities, inform M&A value, or attract premium investment. By framing data as a monetisable asset rather than just a technical resource, leadership teams can change the tone of investor discussions. Data valuation shifts the narrative from “what we’ve built” to “what it’s worth”. 3. Ignoring compliance risks and governance weaknesses In the excitement of fundraising or exit planning, it’s easy to overlook the regulatory and governance aspects of data ownership and usage. Yet these are precisely the issues that investors, especially those operating across jurisdictions like the UK, EU, and US, are laser-focused on. Poor data hygiene, unclear ownership rights, or a lack of demonstrable compliance can reduce the perceived value of data, or worse, introduce risk that derails a deal entirely. With tightening data regulations and heightened sensitivity to consumer privacy, even minor oversights can become major red flags. The Opportunity: Getting Ahead of Investor Expectations The good news? Each of these mistakes is avoidable. Businesses that approach data strategically - and invest in credible, independent valuation - position themselves not only to meet investor expectations but to exceed them. For founders and leadership teams preparing for funding rounds, acquisitions or strategic partnerships, recognising and addressing these data pitfalls early can be the difference between a strong deal and a stalled conversation. At Data Valuation Partners, we work with clients globally to turn data from an operational talking point into a boardroom-strength asset. Our independent valuations help organisations demonstrate data’s contribution to enterprise value, mitigate compliance risks and drive stronger negotiation outcomes. Discover how we help organisations value their data, confidently: https://www.datavaluationpartners.com/how-it-works

If data’s an asset, why are you pitching it as infrastructure? For all the hype around data, most boardrooms still don’t know how to talk about it. You hear terms like "data is the new oil" or "data-driven growth," but when it comes to actually articulating the value of data in a way that moves the needle on strategic decisions, things tend to get vague. Fast. That’s a problem. Because data isn’t just a technical asset - it’s a financial one. And unless CFOs, CTOs and senior leaders can present it that way, it risks being overlooked in critical conversations around investment, growth, risk and valuation. The Language Barrier One of the biggest challenges in board-level conversations is translation. Technical teams speak in terms of platforms, pipelines and governance. Finance teams speak in numbers. Boards speak in risk, opportunity and strategic narrative. If you’re the CTO, CDO or even the CFO tasked with making the case for data as an asset, the key is bridging that gap. You need to frame data valuation in terms the board recognises : impact on enterprise value, implications for M&A, visibility in financial reporting, risk exposure, and investor expectations. Start With Strategic Relevance Don’t lead with infrastructure. Lead with impact. How is your data supporting product development, enabling commercial partnerships, accelerating time to market or improving customer retention? Better still, what would it cost you to lose that capability? These are conversations that get attention. Boards don’t want a technical audit, they want to know what makes the business more valuable. Data, when presented correctly, does exactly that. Quantify Where You Can Narratives are good. Numbers are better. Data valuation gives you a way to turn a strategic narrative into something measurable. You can quantify: The cost of generating or acquiring data, the revenue it enables (directly or indirectly), Its commercial potential via licensing or partnerships and the market comparables for similar datasets. These aren't just figures - they’re tools to align your data story with the metrics the board already uses to make decisions. Tie It to Risk and Regulation If value doesn't grab attention, risk will. Whether it’s compliance (GDPR, ICO enforcement, sector-specific data mandates) or operational exposure (loss of access, poor data governance), your board wants to understand the downside. Data valuation helps you quantify the financial implications of data loss, misuse or underutilisation, and that makes it real. It shifts data from “tech issue” to board-level risk. Anchor It in Competitive Advantage Boards care deeply about differentiation. If your data helps you understand your customers better than anyone else, operate faster, price more effectively or develop new IP - it’s worth something. Possibly a lot. Framing data in this way shows you understand not just what the asset is, but why it matters commercially. Where This Conversation Is Headed Talking about data in the boardroom isn’t about simplifying, it’s about translating. Valuation is the bridge between technical potential and strategic value. It lets you speak the board’s language, using data not as a footnote but as a financial lever. In a world where intangible assets drive most of the value on the FTSE 100, the ability to talk credibly about data is no longer a niche skill. It’s leadership. Discover the Real Value of Your Data It’s 2025, and data drives everything from boardroom strategy to national policy. So why is yours still being treated like back-office plumbing? In today’s boardrooms - where strategic clarity is expected, not optional - vague claims about being “data-driven” no longer hold water. Whether it’s a funding round, a shareholder presentation, or a cross-border M&A deal, decision-makers want evidence. At Data Valuation Partners , we specialise in independent, commercially credible data valuations that stand up to board scrutiny, investor due diligence, and cross-border regulatory expectations. Our methodology aligns with evolving standards across markets, drawing on real-world benchmarks and rigorous analysis. We're not here to optimise your data stack, we're here to clarify its value. The result? A valuation you can use to inform negotiations, drive investment decisions, and tell a strategic story that resonates where it matters most.

For years, businesses have operated under the assumption that their data is valuable. But when it comes time to prove that value - to investors, buyers, regulators, or boards - most are left relying on instinct, anecdote, or vague benchmarks. It’s a bit like walking into a Dragon’s Den pitch saying “we’ve got loads of data” and hoping someone bites. Spoiler: they won’t. That’s changing. And quickly. As data becomes a core strategic asset across industries, the ability to put a credible, defensible number on it is no longer a luxury. It’s becoming essential. Just look at how data has shaped recent UK debates around NHS digitisation, AI regulation, and the monetisation of public datasets. In a post-Brexit Britain redefining its global role in tech, understanding the value of data isn’t a theoretical exercise, it’s an economic strategy. Why Now? We live in a world where ChatGPT is discussed over coffee, TikTok algorithms are debated in Parliament, and 80% of UK workers interact with data-driven systems daily. The pace of digital transformation is no longer gentle, it’s relentless. And yet, many CFOs and boardrooms still rely on a “gut feel” when it comes to estimating what their data is actually worth. It’s like valuing your car based on how good it looks parked in the driveway, rather than its performance on the road. A formal data valuation changes everything. It’s how you move from anecdote to evidence, from assumption to asset. What Is Data Valuation, Really? It’s not just about analytics or reporting. It’s about understanding data as a financial asset. Properly valued, your data becomes more than a talking point - it becomes part of your strategy. There are multiple approaches. Some assess what it cost to generate the data. Others evaluate its ability to drive income, benchmark it against similar datasets, or even estimate its worth in a hypothetical negotiation. Each method serves a different purpose, but together, they bring clarity to one big question: what is your data really worth? And yes, this is already happening. In recent funding rounds, several UK fintechs credited their rising valuations not to revenue growth, but to proprietary data assets. The message is clear: data value is no longer speculative - it’s shaping valuations and investor sentiment. What’s Driving the Demand? We’re seeing this across the board. M&A deals increasingly revolve around what kind of customer data is being acquired. Investors want transparency. Strategy teams are making major bets on new revenue streams, and the confidence to do that starts with knowing what assets they’re sitting on. And let’s not forget regulation. From GDPR to digital reporting standards, knowing what data you have - and what it’s worth - is fast becoming a compliance essential. From Storytelling to Strategy For years, businesses have used data to support a good story. In 2025 and beyond, data is  the story. Think about the British government’s move towards sovereign AI infrastructure. It’s not just a headline, it’s a signal. Data is being treated as national infrastructure. Forward-looking companies are doing the same. The shift we’re seeing is from narrative to numbers. If you can quantify the role of data in your innovation pipeline, customer retention, or go-to-market strategy, you’re already ahead. What Happens If You Don’t? It’s simple. If you don’t value your data, someone else will, and chances are, not in your favour. Legal disputes over data ownership are on the rise. Buyers are demanding valuations as part of due diligence. And regulators aren’t waiting for you to catch up. The risk isn’t just missing out - it’s being outmanoeuvred by competitors who treat their data like the strategic asset it is. Still relying on instinct? That might have worked a few years ago. But the businesses that lead tomorrow’s economy will be the ones who don’t just collect data - they value it. Formally. Strategically. Transparently. And when the time comes to prove its worth, they won’t blink. Discover the Real Value of Your Data At Data Valuation Partners, we don’t deal in hypotheticals, we deal in hard numbers. Our team helps ambitious organisations move beyond gut feel and into evidence-backed decision-making. Whether you’re raising capital, planning a strategic exit, or simply want to know what your data is really worth, we deliver clear, defensible valuations that stand up to boardroom scrutiny and investor due diligence. No fluff. No filler. Just the real value, finally measured. Curious what your data might be worth? Start here: https://www.datavaluationpartners.com/how-it-works

The everchanging US tariffs  mark more than just a change in trade policy - they represent a broader economic shift that’s placing greater strategic importance on data  than ever before. At Data Valuation Partners , we’re seeing how these developments are accelerating demand for data-led insight. In an environment defined by volatility, disruption and rising costs , the value of high-quality, actionable data is increasing across every industry. Economic Uncertainty: Insight Becomes a Competitive Edge Tariffs introduce friction into global trade, shaking up long-established relationships and increasing business risk. As markets become harder to predict: Real-time data  on consumer behaviour, pricing trends and market conditions becomes essential. Organisations turn to forecasting models  and scenario planning tools  to navigate complexity. Firms with well-managed data assets are better positioned to make confident, informed decisions in the face of uncertainty. Supply Chain Disruption: Data Drives Agility Tariff-related changes in sourcing and manufacturing are forcing companies to rethink operations from the ground up. As they explore new suppliers and logistics models, they rely heavily on: Data identifying alternative sourcing options Insights into supply chain vulnerabilities and resilience Models to support cost-benefit analysis  of new routes In this climate, data is not just operational support, it's a strategic necessity. Inflation Pressures: Consumer Intelligence Gains Value With tariffs increasing the cost of imported goods, many markets are experiencing inflationary pressure. Businesses must now: Track shifts in consumer spending  and price sensitivity Use data to optimise pricing strategies  in real time Balance supply, demand and margin management with confidence Data that informs pricing and inventory decisions becomes especially valuable when consumer behaviour changes quickly. IT Spending Slowdown: Tech-Focused Data Matters More Tariffs are also expected to curb global IT investment , particularly in hardware and infrastructure. In response: Companies are relying on data about adoption trends, supplier costs and investment returns and IT leaders are using analytics to prioritise critical systems  and avoid wasteful spending Here, data becomes a filter - separating strategic investments from unnecessary risks. Macroeconomic Monitoring: Data for Policy and Strategy Governments and large enterprises need high-quality economic data to make effective decisions as the global landscape evolves. Whether for public policy, financial forecasting or trade impact assessments, this type of data enables: More responsive economic planning Evidence-based decisions grounded in real-world conditions Better alignment between business strategy and market trends Why This Matters Now In a rapidly changing environment, data delivers what businesses and governments need most: clarity, adaptability and foresight . The latest tariffs are a clear signal that data is no longer just supportive - it’s a core strategic asset . At Data Valuation Partners , we specialise in uncovering the true value of that asset. Whether you're facing trade disruption, evolving your operations or planning long-term strategy, your data can help drive the way forward. Further Reading Supply Chains Explained: How They Work and Why Tariffs Can Strain Them  – Darden News Navigating Tariff Turmoil with Data-Driven Supplier Relationship Management  – Dun & Bradstreet Why Data is Crucial for Navigating Tariffs  – Supply Chain Digital Curious about the value of your data in this shifting economic environment? Let’s start the conversation.

Our Chief Data Officer, Carl Wier, brings over two decades of experience in data strategy, governance, and monetisation. In this piece, he shares his perspective on a sweeping new U.S. regulation that’s flown largely under the radar. While headlines have focused on tariffs and trade, the real disruption may be unfolding in the world of data. Carl breaks down what the DOJ’s latest move means for data monetisation companies, why it’s a pivotal moment for the industry, and what forward-thinking firms should be doing right now. While the world has been absorbed by headlines on tariffs and their global economic impact, something arguably more transformative is quietly taking shape - this time, in the realm of data. On 8 April 2025 , the U.S. Department of Justice (DOJ) enacted a major regulation: Preventing Access to U.S. Sensitive Personal Data and Government-Related Data by Countries of Concern or Covered Persons While the name may not grab headlines, its implications certainly should. This policy fundamentally reshapes how U.S. data can be sold, shared, and monetised -particularly by companies whose businesses depend on high-volume personal data transactions. As highlighted in Apple News , the regulation is not about trade in goods - it’s a defensive measure aimed at curbing foreign access to personal and government data. But its effect is a kind of “hidden tariff”  on data, one that strikes at the core of the data monetisation industry. What’s Covered and What’s Not The DOJ rule prohibits the sale or transfer of specific categories of data to entities in “countries of concern” or to “covered persons”. These categories include: Biometric data  on more than 1,000 U.S. individuals Precise geolocation data  from over 1,000 devices Personal health or financial data  from over 10,000 individuals Any data related to U.S. government personnel , regardless of volume “Datasets that were once considered commercially routine may now fall under strict federal control.” Low volume thresholds are the key surprise here. Just 100 individuals’ worth of certain types of data may qualify as “bulk” under the rule. This isn’t a minor adjustment, it’s a structural change to how data can legally move across borders. What This Means for Data Monetisation Companies For businesses built around large-scale data aggregation and sales, this is a direct hit. The implications fall into four key buckets: 1. Restricted Access to Bulk Data The commercial viability of selling large datasets has just narrowed considerably. The market for what was once a primary product is now significantly reduced. 2. Compliance Complexity Compliance now requires: Thorough vetting of buyers and end-users Screening for “covered persons” and jurisdictions Careful classification of datasets and metadata The cost of these efforts will be substantial - not to mention the interpretive work required to stay on the right side of an evolving regulatory framework. 3. Reputational and Legal Risk Civil fines:  up to $368,136 per violation or twice the value of the transaction Criminal penalties:  up to $1 million and 20 years in prison With penalties assessed on a per-violation basis , exposure could be enormous for companies that haven’t retooled their compliance strategies. 4. Business Model Disruption This regulation goes beyond operational inconvenience, it calls the entire business model of some data companies into question. The industry will now need to pivot towards privacy-focused, value-driven offerings. So What’s Next? This moment, while disruptive, offers the chance to evolve. To stay relevant (and profitable), data companies need to reframe their offerings and re-engineer their operations. Here’s how: Shift from Raw Data to Insight-Driven Services Selling anonymised insights, analytics, or fraud detection will become more viable - and more attractive to clients facing their own compliance burdens. Focus on Aggregated, Anonymised Data Privacy-compliant datasets remain valuable - if properly anonymised. Investment in differential privacy and similar methods is now essential. Build Compliance Into Your Product Offer clients the tools they need: data screening, audit trails, access controls, and risk scoring solutions. Target Non-Covered Data Segments Demographic or operational data with no sensitive identifiers offers an opportunity to diversify into less regulated categories. Champion Ethical and Transparent Practices “In the age of scrutiny, ethics are not just good policy, they’re good business.” Customers and regulators alike are looking for responsibility. That creates a strategic advantage for those who build trust into their processes. Grow Legal and Regulatory Expertise With policy moving faster than ever, legal insight must become a central function in data monetisation. The Opportunity Beneath the Pressure As pointed out by IAPP and Neudata , the new landscape isn’t all downside. Yes, companies will need to hyper-segment data, assess risk proactively, and manage transactions at a new level of granularity. But that will create demand for: Data compliance services Privacy-first analytics Specialised legal and operational consulting Advanced anonymisation tools The regulation is also likely to result in more - but smaller and more secure - transactions , further increasing the need for scalable, compliant infrastructure. In Summary “The DOJ isn’t just regulating data, it’s redefining the rules of digital trade.” The days of freely buying and selling massive datasets with little oversight are behind us. This new model places national security, privacy, and control  at the centre of data strategy. The challenge is real. But so is the opportunity, for those willing to lead. How We Help at Data Valuation Partners At Data Valuation Partners , we work with data-rich organisations to navigate exactly these kinds of inflection points. Whether you're adjusting your monetisation strategy, building out your compliance capability, or exploring privacy-first product lines, we’re here to help you align with policy while staying commercially strong. Regulation is rising. But so are the companies that embrace it.

With uncertainty surrounding US trade policy , businesses are closely watching potential tariff changes on imports from Mexico and Canada. While some tariffs remain in place, others have been lifted, and new ones have been threatened but not yet enacted. As of today, it remains unclear whether the US will impose new 20% tariffs on key imports, leaving businesses in a precarious position. The lack of clarity is already causing ripple effects across supply chains, from delayed procurement decisions to increased demand for real-time supply chain data. Supply Chain Tariffs: A Data Asset Value Shift Trade uncertainty is not just a logistical headache - it’s a direct challenge to the value of supply chain data. With shifting tariffs, historical pricing data loses relevance  as cost structures fluctuate. Real-time inventory tracking  becomes a critical asset, helping businesses navigate supply shortages and demand surges. Predictive models  that once provided reliable forecasts must be reengineered to factor in political and economic volatility. Alternative supplier data is more valuable than ever , as companies seek to diversify their sourcing strategies to mitigate risks. This isn't just about logistics; it's a financial data reckoning. Businesses that fail to reassess the value and application of their data may find themselves making decisions based on outdated or incomplete information. The DVP Perspective: Data as a Competitive Lever At Data Valuation Partners, we view data as a dynamic financial asset - one that must be continuously reassessed in light of geopolitical and economic changes. The ongoing trade uncertainty highlights the reality that businesses must build flexible, data-driven strategies that allow them to pivot quickly in response to new developments. For instance, companies that leverage real-time data valuation models  can proactively identify risks and opportunities, rather than reacting after the fact. Businesses that monitor alternative supplier costs and lead times  through data analytics are better positioned to secure competitive contracts before shortages hit. Those that integrate real-time pricing intelligence  into their forecasting models can protect their margins while competitors struggle to adapt. In a world where tariff policies remain in flux, companies that treat data as an evolving financial asset  will have a strategic advantage. Contemporary Geopolitical Considerations The trade environment is shifting rapidly. Over the past year, we have seen tariffs on certain steel and aluminum imports lifted , while new threats of tariffs on automotive and agricultural goods from Mexico and Canada  have emerged. Meanwhile, previous tariff disputes with China continue to impact global supply chains , driving companies to reassess supplier relationships and distribution networks. In parallel, the European Union’s evolving carbon border adjustment mechanisms  are adding another layer of complexity, requiring businesses to collect and analyse emissions-related supply chain data. The recent tightening of semiconductor export restrictions  also underscores the need for businesses to evaluate their data strategies in real time. The Future of Supply Chain Data Valuation As trade policy uncertainty continues, businesses that proactively adjust their data strategies will gain a competitive edge. Those that don’t risk being left behind in a landscape where data value is more fluid than ever . At DVP, we help organisations unlock the financial potential of their data assets. The current trade situation is a prime example of why companies need robust data valuation frameworks  that allow them to react swiftly to external shocks. Data isn’t static - it’s an evolving asset.  Businesses that understand its changing worth will be better equipped to navigate uncertainty and emerge stronger. For companies looking to navigate the data challenges of trade uncertainty, now is the time to invest in data valuation. The right insights today will define tomorrow’s market leaders.

In today's fast-paced digital world, data is more important than ever for businesses wishing to stay ahead of the curve. A common myth, however, suggests that certain industries simply don't generate enough data to be valuable. This idea is misleading and misses the vast potential that exists in every organisation, no matter the sector. The truth is that all companies, large or small, collect valuable information. The challenge is knowing how to make the most of it. As we examine this misconception further, we will explore the ways businesses from various industries are creating data, how it can be turned into actionable insights, and the strategic benefits that come from analysing and using this information wisely. Data is Everywhere – Even Where You Least Expect It Even in sectors where data may not seem obvious, companies are continuously gathering crucial information that can impact decision-making and improve operations. Let's take a closer look at different industries to reveal the hidden treasures of data often overlooked. Manufacturing: The Data Hidden in Operations Manufacturers often underestimate the wealth of operational data they gather every day. When analysed effectively, this data can lead to significant improvements across various aspects of production. Production Line Data: By monitoring output, defect rates, and efficiency, companies can identify and address inefficiencies in their processes. For instance, Shanghai Automobile Gear Works (SAGW) implemented a Process Digital Twin using GE Digital’s Proficy Plant Applications. This initiative led to a 20% improvement in equipment utilisation, a 40% reduction in inspection costs, a 30% decrease in inventory, and an 80% reduction in required storage space. Supply Chain Analytics: Tracking supplier performance and inventory turnover can streamline logistics and reduce costs. Butterball, for example, used advanced data analytics to modernise its product offerings and supply chain processes. By upgrading its SAP enterprise resource planning (ERP) system, the company optimised logistics, improved demand forecasting, and increased customer satisfaction, particularly during peak seasons. Predictive Maintenance: Real-time data from equipment sensors can help prevent breakdowns and extend asset lifespan. Wacker Chemical Corporation utilised Asset Performance Management (APM) from GE Digital to extend the scheduled maintenance of critical assets from every two years to a maximum of ten years, saving millions of pounds annually. These examples highlight the transformative potential of data analytics in manufacturing, leading to enhanced efficiency, reduced costs, and improved operational performance. Retail: Turning Customer Insights into Profits ​Retailers often overlook the vast potential of their data assets. By effectively analysing this information, they can significantly enhance decision-making processes and improve customer outcomes.​ Transaction Histories and Purchasing Trends:  Analysing transaction data enables retailers to forecast demand and optimise pricing strategies. For example, Tesco's Clubcard, launched in 1995, revolutionised customer loyalty programmes by collecting detailed purchasing information. This data-driven approach allowed Tesco to tailor promotions effectively, contributing to its rise as the UK's leading retailer.  Loyalty Programmes and Customer Profiles:  By examining customer behaviour through loyalty schemes, retailers can create targeted promotions that boost retention. Tesco plans to expand its use of artificial intelligence to personalise shopping experiences for Clubcard users, suggesting healthier choices and reducing waste by analysing shopping habits. This personalised approach aims to enhance customer loyalty and profitability. ​ Healthcare: Unlocking Patient Insights The healthcare industry generates massive amounts of data, often underutilised. Here’s how to effectively harness this information: Electronic Health Records (EHR):  Analysing EHRs can reveal trends in patient demographics and outcomes. The UK's NHS is considering embracing genetic testing to prioritise illness prevention, aiming to tailor treatments based on comprehensive health records. This approach could transform cardiovascular risk assessment and proactively recommend treatments to high-risk individuals. ​ Wearable Technology:  Health-tracking devices generate continuous data streams that providers can use to personalise care plans. For instance, the Zoe Health Study, initially launched as the COVID Symptom Study, has expanded to log symptoms beyond COVID-19, utilising data from wearable devices to monitor health metrics and improve patient outcomes.  Clinical Trials:  Data from clinical research provides key insights into medication efficacy. The UK Biobank, in collaboration with pharmaceutical companies, has launched a proteomics initiative to utilise AI in understanding and treating diseases. This project aims to enhance drug development processes, potentially reducing timeframes and improving treatment quality. ​ Finance: Data-Driven Decision-Making While finance is often seen as data-rich, there are still underutilised sources worth mentioning: Transaction Monitoring:  Financial institutions monitor transactions for fraud and compliance. Insights gained from this data can also enhance customer experiences. For example, banks that analyse transaction behaviours have reported significant increases in customer service satisfaction, as they can offer personalised financial products and services.​ Risk Assessment Models:  By analysing customer behaviour and market data, companies can improve their risk models. Financial firms that engage in data-driven decision-making often see profit increases, as better insights lead to more informed lending and investment strategies.​ These examples illustrate the transformative potential of data analytics across various sectors, leading to enhanced efficiency, reduced costs, and improved outcomes. Final Thoughts Companies that ignore their data assets risk missing out on significant opportunities for revenue growth and operational efficiency. It's essential for organisations to understand that even if they don't consider themselves "data-rich," they might have a wealth of untapped information waiting to be discovered. By fostering a culture that prioritises data collection and analysis, companies can gain strategic advantages over their competitors. Employing data scientists to interpret the data can reveal insights that enhance not only operational performance but also fuel innovation in products and services. As we navigate this data-driven economy, understanding how to leverage every piece of information will be crucial for sustained growth and success. Organisations in every sector should take the chance to identify, analyse, and monetise their data assets, illustrating that valuable information truly exists everywhere - even in the least expected places. At Data Valuation Partners, we specialise in helping businesses uncover the hidden financial value of their data. Our expertise in data valuation, monetisation strategies, and financial reporting ensures that companies can turn their information into a strategic advantage. Get in touch with us today to start making the most of your data assets.

As we progress further into the digital era, the way we evaluate economic growth is undergoing a significant transformation. For the first time, data is being recognised as a standalone asset in GDP calculations, akin to renewable resources like wind and wave power. This shift, prompted by updates to the United Nations’ System of National Accounts , is pivotal for accurately reflecting contemporary economic activities.  But what does this mean in practical terms? More importantly, how do we determine the value of data?​ The Evolution of Economic Measurement Traditionally, Gross Domestic Product (GDP) assessments have centered on tangible goods and services . While intellectual property and financial assets have been included in economic metrics, data has often remained an unquantified force driving economic changes. The UN’s initiative to incorporate data into national accounts mirrors our swiftly evolving economic landscape, where intangible assets are increasingly vital. ​ By assigning value to data, nations, industries, and companies are entering a phase where they must reconsider how they measure and report economic contributions. Countries with robust digital infrastructures could witness notable enhancements in their GDP as data becomes an integral component of economic evaluations. Moreover, industries centered around data technologies - such as artificial intelligence, cloud computing, and analytics - will receive deserved acknowledgment for their economic impact.​ The Challenge of Valuing Data Valuing data is a complex endeavor. Unlike traditional assets that may depreciate over time, data's value can increase based on its accuracy, relevance, and strategic application.  Identifying appropriate valuation methods is crucial, as existing approaches may not fully capture its economic significance.​ One approach is the Sum of Costs Method , which estimates data's value based on production and maintenance expenses. While this provides a basic financial overview, it may overlook the broader economic growth potential arising from effective data utilisation. For instance, companies that leverage customer data to enhance their marketing strategies have reported increased purchases and reduced customer churn. ​ Another method is the Perpetual Inventory Method (PIM) , which assesses data's value by considering historical investments over time. Although this offers insight into long-term data investment, it might not reflect the dynamic nature of data's influence on the economy.​ Despite these methodologies, accurately assessing data’s contributions remains challenging.  Determining how to value data will influence its integration into GDP calculations and subsequently affect economic policy.​ The Future of Data Valuation As organisations and governments explore optimal methods for valuing data, several critical questions arise: What metrics will define data's worth?  How can we enhance data utilisation processes across various sectors to ensure information leads to innovation and growth?​ One promising approach involves focusing on data usage outcomes.  By examining results from data-driven decisions - such as productivity improvements or enhanced customer satisfaction - analysts can develop models linking data utilisation to measurable economic outcomes. For example, integrating brand and performance marketing has been shown to significantly boost return on investment (ROI) for businesses, with a balanced mix potentially increasing ROI by 25-100%.  Equally important is the development of regulatory frameworks. As data assumes a crucial role in economic assessments, establishing standards around privacy and security becomes essential. Countries emphasising ethical data use and transparency could foster greater public trust, potentially leading to increased data utilisation rates.​ The Road Ahead Recognising data as an economic asset signifies a substantial shift in how we evaluate and comprehend economic growth. The updates to the UN’s System of National Accounts prompt nations worldwide to reassess their operational and reporting frameworks.​ The challenge of valuing data remains intricate.  Through collaboration between businesses and governments to develop innovative valuation methods, the broader implications for economic activity will significantly influence future fiscal policies. As our economy increasingly depends on intangible assets, understanding the value of data will require continuous analysis and refinement. Bridging the gap between this emerging asset class and its economic implications will redefine fiscal reporting and pave the way for future innovations and growth in the digital age. At Data Valuation Partners , we specialise in helping organisations understand, quantify, and defend the value of their data assets. This shift in economic measurement is just the beginning - those who can accurately measure and leverage their data will gain a decisive competitive advantage. Read the BBC’s coverage on this shift here: https://www.bbc.co.uk/news/articles/czedpnen168o For insights on how data valuation impacts your business, get in touch with us at Data Valuation Partners .

In today’s fast-paced digital economy, data is no longer just numbers on a spreadsheet - it’s a powerful asset that shapes the future of business. Companies that harness their data effectively are emerging as key players in mergers and acquisitions (M&A), attracting investors and buyers eager for actionable insights. This shift is driving higher valuations and better deal outcomes for data-driven businesses. This article explores the growing role of data in M&A, key trends shaping the landscape, and what business leaders need to know to stay competitive. The Evolving Role of Data in M&A Traditionally, M&A decisions were driven by physical assets and financial performance. However, the digital revolution has reshaped this approach. Today, data is recognised as a strategic asset with immense potential. Companies that can analyse customer behavior, market trends, and operational efficiencies are now among the most sought-after acquisition targets. A 2022 PwC report found that businesses with strong data analytics capabilities saw their M&A valuations increase by an average of 25%. This underscores a fundamental shift: it’s no longer just about the volume of data a company holds, but how effectively it can leverage that data to drive business decisions. Buyers Prioritising Data-Rich Companies During Due Diligence As M&A due diligence evolves, buyers are placing greater emphasis on the quality and relevance of a target company’s data assets. They want to understand how well a company’s data drives decision-making, improves efficiency, and enhances customer engagement. Consider the case of a tech firm acquired for $300 million - its advanced analytics capabilities and deep customer insights were major factors in the buyer’s decision. Similarly, a recent study revealed that 68% of acquirers believe that a target’s data quality directly correlates with its long-term value. By thoroughly assessing a company’s data landscape, buyers can uncover hidden growth opportunities and potential risks, making informed investment decisions. Data-Driven Companies Command Higher M&A Multiples The financial impact of data-driven decision-making is undeniable. Companies that demonstrate advanced data strategies consistently achieve higher M&A multiples compared to their peers. According to Deloitte, firms that effectively utilise data see M&A valuation premiums of up to 30% higher on average. The ability to present a clear, structured data strategy not only showcases a company’s past success but also highlights its future potential. For business leaders looking to attract investors or acquirers, prioritising data strategy is no longer optional - it’s a competitive necessity. The Rising Demand for Data-Backed Business Intelligence As data valuation gains importance, businesses are increasingly investing in tools that transform raw data into actionable insights. Platforms like Tableau and Power BI have become essential for companies looking to integrate data analytics into their operations. A recent survey found that companies utilising advanced business intelligence tools experience, on average, a 15% boost in operational efficiency. By leveraging data-driven decision-making, organizations can optimise resource allocation, enhance customer relationships, and ultimately increase their appeal to potential buyers. Regulatory Compliance as a Competitive Advantage in M&A With evolving data regulations such as GDPR and CCPA, data governance has become a critical factor in M&A transactions. Companies that maintain strong compliance frameworks are more attractive to buyers, as they mitigate regulatory risks and ensure data integrity. A 2023 report highlighted that organizations with robust data governance structures were 40% more likely to achieve successful M&A outcomes. For sellers, this means that strong compliance practices can significantly enhance valuation and expedite deal processes by reducing due diligence concerns. Integrating Data Valuation into Business Strategy To succeed in today’s M&A landscape, business leaders must integrate data valuation into their broader strategic planning. Cultivating a data-driven culture across all levels of an organisation enhances its ability to extract value from data and positions it as a strong acquisition target. By proactively investing in data analytics, governance, and compliance, companies can differentiate themselves in competitive markets. This strategic focus not only enhances M&A prospects but also drives long-term growth and operational excellence. Conclusion The role of data in M&A is more critical than ever. As businesses navigate an increasingly data-centric world, understanding and leveraging data valuation can be the key to unlocking greater investment opportunities and achieving premium valuations. To stay ahead, companies must: Emphasise data quality and analytics capabilities during due diligence. Invest in business intelligence tools to drive efficiency and insight. Prioritise data governance and compliance to reduce regulatory risks. Integrate data valuation into their overall business strategy. Incorporating a strong data strategy isn’t just about maximizing M&A value - it’s about future-proofing your business for long-term success in an evolving marketplace. Companies that embrace this shift will not only attract investors but also secure a competitive edge in today’s data-driven economy.

Data decay (or data degradation) refers to the incremental aging of data. It is estimated that for B2B companies, data can decay as much as 23% per year. Failure to update your data can result in strategic errors due to decisions being made on irrelevant data in a constantly changing environment. If you desire to use utilise analytics, data science or machine learning for your business, having up-to-date data is essential for making predictions and adjusting to market conditions. Data decay can be both elusive and difficult to understand. Thankfully, at Data Valuation Partners , we have done extensive research on data decay, which includes the following: - Data decay factors: Factors that influence data decay such as decay starting point, rate of decay and other industry-specific factors. - Mathematical formulae: We have multiple ways of representing data decay mathematically based on decay risk factors. - Prevention: We consult on how to reduce data decay both systemically and mechanistically. - Impacts: Understanding more detailed impacts on data decay, from a data value, strategic and reputational perspective. Data Quality is one of the most important factors in determining data value, and data decay is an important component of data quality that is often overlooked. If you want to learn more about data quality, decay and data value then please contact Data Valuation Partners .

If you are involved in Merge and Acquisition activities, do you consider the value of the data held within the business? If not, then read on. You could be leaving money on the table! A client recently verbalised the concept which goes a long way in the revelation the market is going through on recognising data value.  If Newco was formed and bought $100m of data, it would be reasonable to say that on Day 1, that business was worth $100m; $100m in data Value. It's Enterprise Value, multiples of revenue of profit etc. is nil as there is no trading and nothing to value. That same Newco after X years generates a return from the data: If that company was to generate $5m in profit from the data, and 10x profit was the typical multiple used for companies in that sector, then the Enterprise Value would be 10x $5m = $50m. Now ignoring data enhancement and data decay, it would absolutely be reasonable to say that company's value was the Data Value plus the Enterprise Value so $100m + $50m = $150m. The Newco then generates data: Where most companies are today is that they have made or gathered data without the huge inconvenience of acquiring it; maybe through users of a platform or technology. Additionally, their team have gathered data in the day to day operations. If they ended up with the same data set as the newco. and the same financial metrics, then why wouldn't the company be worth $150m! ($100m (Data) + $50m (EV) = $150m). It's just that we are not recognising the $100m!! If you are considering a merger or acquisition, then contact @data valuation partners to gain a defensible financial valuation of the data.