Those of us who remember the time before everything went digital can recall how decision-making in business was akin to navigating through a dense fog, with limited visibility and a high risk of veering off course. Data, while recognized as valuable, was often scarce and difficult to collect; transforming it into insights to make informed decisions and create business value was often a formidable challenge. According to the IDC Digital Universe 102 study, “Big Data, Bigger Digital Shadows, and Biggest Growth in the Far East,” the global data supply reached 2.8 zettabytes (ZB) in 2012 — or 2.8 trillion gigabytes (GB) — but just 0.5% of this was used for analysis. The report highlighted the scarcity and complexity of deriving insights from data in the pre-digital age.

The digital world heralded a seismic shift in the way we perceive and use data. With the proliferation of digital technologies, including the internet, social media, and connected devices, the volume, velocity, and variety of data exploded exponentially. In 2023, it was estimated the world created around 120 ZB or about 337,080 petabytes (PB) of datadaily. In context, there are around 5.35 billion internet users globally, meaning each user can create about 15.87 terabytes (TB) of data daily. 

Data abundance is at the heart of what is being called the era of intelligence. In this new era, it will be imperative your business possesses the ability to accurately collect and analyze data and move from insights to intelligence. This capability is now a cornerstone of business success, transforming the way organizations operate, innovate, and compete. Whether you’re a small startup or a multinational corporation, there is immense business value in your data.   

Retaining that value requires vigilance. As such, the role of the board of directors becomes crucial in terms of setting the strategic direction for data initiatives to ensure alignment with overall business outcomes and consideration for risk management. By providing oversight and guidance on data-related matters, boards help organizations maximize the value derived from their data assets while mitigating potential risks and compliance issues. Moreover, boards can foster a culture of data-driven decision-making by championing the importance of data literacy and encouraging collaboration across departments. As stewards of shareholder interests, boards must ensure data is used effectively to create business value and drive sustainable growth. 

Three Ways Data Creates Business Value

Let’s delve into how business leaders and boards can tap the transformative power of data across three key areas: enhancing customer-centric decision-making, improving operational efficiency and productivity, and predicting customer behavior and market trends. 

1. Enhance Customer-Centric Decision-Making: As a business leader, you know decisions can make or break your company. With the today’s volume of data, decision-makers have access to a previously unimaginable wealth of insights. Most of us make 35,000 decisions a day!

Having meaningful insights quickly is essential. We recommend taking a customer-centric approach to decision-making. 

• Netflix analyzes user data, including viewing habits and preferences, to tailor its content recommendations with astonishing accuracy. The personalized recommendations generate 80% of its viewer activity.  
• Similarly, in the B2B sector, Salesforce uses data analytics to empower sales teams. By providing real-time insights into customer behavior and sales trends, the company enables businesses to make informed decisions that drive revenue growth. Salesforce claims companies using its CRM experience a 25% increase in revenue on average

2. Improve Operational Efficiency and Productivity: Data enables organizations to shift to more automated efficient processes and systems, thereby optimizing operations and productivity. Data helps reduce waste and improve collaboration, accuracy, and quality.  

• Amazon analyzes vast amounts of data, including inventory levels, customer demand, and shipping logistics, to minimize delivery times and reduce operational costs. As a result, the company has set new standards for efficiency in the retail industry. 

• General Electric (GE) uses sensor-equipped machines and predictive analytics to monitor equipment performance in real-time to preempt potential breakdowns and optimize maintenance schedules.  

3. Predict Customer Behavior and Market Trends: Data enables businesses to delve into customer behavior and predict market trends with unparalleled accuracy. Behavioral data, for example, enables businesses to personalize marketing campaigns, identify and optimize customer journey breakpoints, and more. 

• Facebook leverages user data to deliver targeted advertising campaigns. By analyzing demographic information, interests, and online interactions, the company helps businesses reach their desired audience with precision. This capability facilitates advertisers experiencing a higher conversion rate on Facebook over other social media channels. 
• Visa harnesses data to detect fraudulent transactions in real-time. Through advanced algorithms and machine learning, the company analyzes millions of transactions per second, identifying patterns indicative of fraudulent activity. As a result, Visa has been able to reduce fraud rates significantly, safeguarding consumers and businesses. According to Visa’s annual report, data analysis prevented approximately $25 billion in fraud in 2023 alone. 

Unlock 10 Steps That Will Convert Data into Business Value

While we’ve used large companies to illustrate how data can be converted into business value, this is a capability every company can build. Realizing the business value of your data requires a strategic approach. Whether you’re a small startup or a multinational corporation, here are 10 actionable steps to harness the power of data and create tangible value: 

1. Define Clear Objectives: This is the starting point for every strategic initiative. Begin by identifying specific business outcomes you aim to achieve through data analysis. Whether it’s improving customer satisfaction, increasing operational efficiency, or driving revenue growth, clarity on objectives will guide your data strategy.
2. Invest in Data Infrastructure: Build a robust data infrastructure that allows for the collection, storage, and processing of data at scale. This may involve implementing cloud-based solutions, investing in data warehouses, or leveraging data management platforms.
3. Gather Relevant Data: Collect data from various sources, including customer interactions, sales transactions, website analytics, and social media engagement. Ensure the data you gather is accurate, relevant, and compliant with data privacy regulations such as GDPR and CCPA.
4. Use Advanced Analytics: Leverage advanced analytics techniques such as predictive modeling, machine learning, and data visualization to derive meaningful insights from your data. Tools like Python, R, and Tableau can aid in analyzing and interpreting complex datasets
5. Empower Decision-Makers: Provide decision-makers at all levels of the organization with access to actionable insights derived from data analysis. Implement performance dashboards, reports, and data visualization tools to facilitate data-driven decision-making processes.
6. Foster a Data-Driven Culture: Cultivate a culture that values data-driven decision-making and encourages experimentation and innovation. Provide training and resources to employees to enhance their data literacy skills and empower them to leverage data in their respective roles.
7. Continuously Iterate and Improve: Data analysis is an iterative process that requires ongoing refinement and optimization. Regularly evaluate the effectiveness of your data strategy, identify areas for improvement, and adapt your approach accordingly.
8. Ensure Data Security and Compliance: Safeguard the privacy and security of your data assets by implementing robust data governance practices. Establish protocols for data access, usage, and sharing, and ensure compliance with relevant regulatory requirements.
9. Foster Collaboration: Encourage cross-functional collaboration between teams such as marketing, sales, finance, and IT to maximize the value derived from data. Break down silos and facilitate knowledge sharing to ensure insights are effectively used across the organization.
10. Monitor Performance and Measure Impact: Establish measures, metrics, and key performance indicators (KPIs) to track the impact of your data initiatives on business outcomes. Monitor measures such as customer experience and engagement, category growth, and operational efficiency to gauge the success of your data-driven initiatives.

By following these steps, your company regardless of size can unlock the full potential of your data assets and drive sustainable growth and innovation in today’s data-driven economy. Have questions about any of these steps?  Use our Advisory Services to secure your answers. 

FAQ:

1. Customer-centric decision-making: Using behavioral and preference data to tailor experiences, reduce friction, and improve relevance—driving acquisition, retention, and lifetime value.
2. Operational efficiency and productivity: Using data to optimize processes, reduce waste, improve quality, and automate intelligently—lowering cost while improving speed and reliability.
3. Predicting customer behavior and market trends: Using analytics to anticipate demand, personalize journeys, identify breakpoints, and forecast risk—enabling proactive decisions rather than reactive firefighting.

1. Define clear objectives tied to outcomes (CX, efficiency, revenue, retention).
2. Invest in data infrastructure for collection, storage, and processing at scale.
3. Gather relevant data across interactions, transactions, web, and engagement—ensuring accuracy and compliance.
4. Use advanced analytics (predictive modeling, machine learning, visualization) to extract signal from noise.
5. Empower decision-makers with dashboards and actionable insights at the point of decision.
6. Foster a data-driven culture through training, resources, and expectations for evidence-based decisions.
7. Continuously iterate and improve—treat analytics as an evolving system, not a one-time project.
8. Ensure security and compliance with governance, access controls, and regulatory alignment.
9. Foster collaboration across marketing, sales, finance, operations, and IT to eliminate silos and increase adoption.
10. Monitor performance and measure impact using KPIs that connect initiatives to business outcomes.