Do you ever find yourself at odds with what you think you know versus the data you are reviewing? When that happens, do you decide to go with your gut or listen to the data? While experience and gut feelings have their place, ignoring data can lead to catastrophic outcomes. History is full of examples of companies that had the data they needed to succeed but chose to follow their instincts instead, with devastating results. We’ll review a few, identify how guts and feelings resulted in disastrous decisions, and suggest six data categories every company should access and use to drive strategy and decisions.

Four Examples of the Heavy Price of Ignoring Data

Data-driven decision-making is good business and good for business. There have been numerous studies over the past two decades on the business benefits of using data. For example, a McKinsey study found organizations that use data to make decisions are 23 times more likely to acquire customers, 19 times more likely to be profitable, and six times more likely to retain customers than those that don’t.  

Yet, despite the clear advantages, some of the most successful companies in history have ignored data at crucial moments, relying instead on intuition or past successes. Kodak, Blockbuster, Nokia, and Yahoo are familiar examples that provide good lessons for all of us. 

Kodak’s Missed Opportunity: Kodak was once synonymous with photography. At its peak, it commanded 90% of the film market in the United States. But Kodak’s leadership made a fateful mistake: they ignored the data that showed the inevitable rise of digital photography. In the 1970s, Steve Sasson, a Kodak engineer, invented the first digital camera. Even though it was clear digital photography was the future, Kodak’s leadership feared embracing digital technology would cannibalize the company’s lucrative film business. They decided to shelve the project, confident film would remain dominant. 

Of course, we all know the outcome. By the time Kodak finally adopted digital photography, it was too late. The company filed for bankruptcy in 2012, overtaken by competitors like Canon and Sony, and even newer entrants like Apple, whose iPhone revolutionized photography.  

Blockbuster’s Fall from Grace: Blockbuster’s story is another stark reminder of the dangers of ignoring data. In the early 2000s, Blockbuster was the undisputed leader in video rentals, with over 9,000 stores worldwide. Data was beginning to show a shift in consumer behavior toward online streaming and mail-in rentals, a trend Netflix was quick to capitalize on. Netflix approached Blockbuster with a partnership offer, suggesting Blockbuster could handle the physical side of the business while Netflix focused on digital. But Blockbuster’s leadership, confident in their brick-and-mortar model, declined. They believed customers would always prefer the in-store experience. 

This decision proved catastrophic. By 2010, Blockbuster filed for bankruptcy, while Netflix, having listened to the data, grew into a global entertainment giant. Today, Netflix has over 200 million subscribers worldwide while Blockbuster is a memory.

Nokia’s Decline: Nokia was once the world’s largest mobile phone manufacturer, with a market share of over 40% in 2007. The company had data showing the growing importance of smartphones with touchscreens and advanced operating systems. While Apple introduced the iPhone in 2007 and Google launched Android, Nokia continued to focus on feature phones and its Symbian operating system. Unfortunately, Nokia’s leadership relying on their experience and dominance underestimated the significance of the shifting market.  

The result was a rapid decline in Nokia’s market share, and by 2013, its phone division was sold to Microsoft. Nokia’s failure to listen to the data and adapt to the changing market led to its downfall as a leader in the mobile phone industry.

Yahoo’s Costly Mistake: In the late 1990s, Yahoo was one of the biggest names on the internet. Did you know the company had a chance to buy Google for $1 million in 1998 when Google’s data-driven search engine was already showing promise? Yahoo’s leadership turned down the deal, believing search was just a small part of the internet experience and their broader portal strategy would keep them on top. It was a costly mistake. As Google’s search engine grew in popularity, driven by its data-focused approach, Yahoo struggled to keep up. By the time Yahoo realized the importance of search, Google had become the dominant force in the industry and Yahoo was left trying to catch up. In 2017, Yahoo sold its core business to Verizon for $4.5 billion, a fraction of its former value.  

The Data You Need to Listen To 

These examples highlight a common theme: even the most successful companies can falter when they ignore data. Each of these examples reflects a different type of data the companies had at their disposal and should have listened to: 

• Kodak: For Kodak, market and technology data were critical. The market data showed a shift toward digital photography, while the technology data, including internal R&D data, highlighted the potential of digital cameras. Kodak ignored this data out of fear that digital technology would disrupt its film business, focusing instead on maintaining the status quo. 

• Blockbuster: Blockbuster had access to consumer behavior data. This data indicated a growing preference for convenience, such as mail-in rentals and online streaming. The company ignored it, believing their customers’ habits would not change and the in-store experience was irreplaceable. 

• Nokia: For Nokia, the key data was related to product trends and consumer demand. Data showed consumers were gravitating toward smartphones with advanced capabilities but Nokia’s leadership clung to their success with feature phones, underestimating the pace of change in consumer preferences. 

• Yahoo: Yahoo ignored strategy data regarding the value of search technology and the potential of Google’s data-driven approach. The company had data showing the increasing importance of search in internet usage but it chose to prioritize its existing portal strategy, missing out on the opportunity to dominate the search market. 

Leaders often rely on intuition or past experiences, believing they understand their industry better than anyone else. These examples illustrate why this approach is risky. 

Yes, experience and intuition are valuable but they should complement, not replace data. Data provides the objective insights needed to validate or challenge assumptions, identify trends, and make informed decisions. As leaders and boards of directors, we cannot risk making decisions based on outdated or incomplete information.

The Six Most Important Data Every Company Should Collect 

To avoid the pitfalls Kodak, Blockbuster, Nokia, and Yahoo encountered, we advise business leaders and boards of directors to prioritize the collection and analysis of six key types of data: 

1. Market Data: This includes data on market trends, competitive analysis, and consumer preferences. Market data helps your company stay competitive and customer focused. Use it to ensure you are meeting market demands and customer expectations. When you stay attuned to market changes, it is easier to adapt your strategy to stay relevant. 
2. Customer Data: Understanding your customers is crucial. This includes demographic data, buying behavior, and voice of customer data. Customer data allows your company to tailor your products and services to meet the evolving needs of your current and prospective customers, ensuring long-term engagement, advocacy, and loyalty. 
3. Product and Technology Data: Companies must track data related to product performance, innovation, and technological advancements. This data allows you to innovate and stay ahead of technological advancements, preventing obsolescence. Use this data to stay ahead of the curve and avoid being blindsided by new technologies or shifts in customer preference. 
4. Financial Data: Financial data, including sales figures, profit margins, and cost structures, provides insights into the health of your business. Financial health is what enables you to make a strategy based on investments to drive growth. Regularly analyze your financial data to make informed decisions about resource allocation, pricing strategy, and investment opportunities. 
5. Operational Data: This includes data on supply chain efficiency, production processes, and operational costs.Operational data helps you optimize your processes, reduce costs, and improve overall efficiency. Use this data to help you achieve a stronger bottom line. 
6. Strategic Data: Strategy based on data encompasses long-term forecasts, risk assessments, scenario analysis, and strategic planning. This data is important for aligning short-term actions with long-term outcomes, ensuring you, your board of directors, and your team can react to immediate needs and prepare for future challenges. 

To effectively collect and use this data, companies should invest in robust data analytics tools, the insights supply chain, and processes. This includes implementing customer relationship management (CRM) systems, leveraging big data analytics and strategy, and fostering a data-driven culture where insights are regularly reviewed and acted on. Regularly update and analyze your data to ensure your business remains agile and responsive to market and customer changes. If you don’t have a data inventory, now is the time to create one. 

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What is the Future of Your Data-Driven Customer-Centric Decision-Making?

The importance of data-driven decision-making is only growing. As businesses collect more data than ever before, the ability to analyze and act on that data is becoming a critical competitive advantage. A McKinsey study found companies using data-driven B2B sales-growth engines report above-market growth and EBITDA increases in the range of 15 to 25%.  

We believe companies that leverage data effectively are better positioned to serve customers, adapt to changing market conditions and customer preferences, identify new market and product opportunities, and mitigate risks. Yet, the Data Quality 2023 Study revealed while most companies focus on data, only about 16% are “data-driven,” with data being fully integrated into those processes at all organizational levels.  

What is your plan for using data to make more customer-centric decisions? We hope you intend to access and use the data you need to make the right decisions. It is our deepest wish that your company doesn’t fall into the trap of ignoring data, resulting in lost market share, missed market and customer opportunities, or even complete business failure. 

As leaders, we must learn to balance intuition with data, using both to inform our decisions. We encourage you to prioritize the collection and analysis of market, customer, product, financial, operational, and strategic data. Make sure your company isn’t the next statistic. As experts in using data to make customer-centric decisions, we’re here to help.  

FAQ:

• Kodak: Ignored market and technology data signaling the rise of digital photography because it feared cannibalizing film revenue.
• Blockbuster: Discounted consumer behavior data showing a shift toward convenience and streaming, clinging to the store-based model.
• Nokia: Underestimated product and demand data pointing to smartphones and touchscreen ecosystems, staying anchored to feature phones and Symbian.
• Yahoo: Misread strategic data about the value of search and the trajectory of data-driven discovery, passing on Google early and losing category leadership.
  The common pattern is not “lack of data.” It is leadership choosing comfort over evidence.

1. Market data: Trends, competitive moves, category shifts, and changing preferences.
2. Customer data: Demographics, buying behavior, Voice of Customer, retention signals, and journey friction.
3. Product and technology data: Product performance, adoption, usage patterns, innovation pipeline, and technology shifts.
4. Financial data: Revenue drivers, margins, cost structure, pricing performance, and investment capacity.
5. Operational data: Supply chain performance, process efficiency, quality, cycle times, and cost-to-serve.
6. Strategic data: Forecasts, risk assessments, scenario analysis, and strategic planning inputs that connect near-term actions to long-term outcomes.