The steep cost of a poor data management strategy

It’s a time-tested truth: Getting a head start improves outcomes. In sprint races, it’s not always the fastest runner that wins, but the one with the best start. And marathoners know that how they run their first few miles often determines how they finish. And before runners even enter a race—whether a sprint or a marathon—they have prepared with months or years of training. The same is true in education. In one study, an MIT economist found that attending preschool increased college attendance by 18%. That’s an almost 20-year head start. 

But head starts don’t need to take years to make a difference, especially in the fast-moving world of technology where the window of opportunity is much shorter. In technology, hesitate, and you may not be able to catch up to your competitors. The important point is to start and keep moving. As the Chinese proverb wisely suggests, “The best time to plant a tree was 20 years ago. The second best time is now.”

Such is the case with a data management strategy. It reigns as one of the most commonly missed, foundational opportunities in technology today, creating a growing gap in capabilities. That gap is becoming increasingly apparent because of artificial intelligence’s (AI) dependence on effective data management. Without it, businesses incur steep costs, but the downside, or costs, are often unclear because calculating data management’s return on investment (ROI), or upside, is a murky exercise. 

For many organizations, the real challenge is quantifying the ROI benefits of data management in terms of dollars and cents. Unlike other business investments, the returns may not be immediately apparent because the benefits accrue over time. This places a major focus on the initial investment instead of the potential outcomes and ROI, often disguising data management’s incredible value. Let’s look at how we can resolve this—while there is still time to do so.

Data dependency

Regardless of your industry, data is central to almost every business today. Leveraging that data, in AI models, for example, depends entirely on the accessibility, quality, granularity, and latency of your organization’s data. Without it, organizations incur a significant opportunity cost. A few years ago, Gartner found that “organizations estimate the average cost of poor data quality at $12.8 million per year.’” 

Beyond lost revenue, data quality issues can also result in wasted resources and a damaged reputation. Data management underpins many other transformational capabilities and competencies that can elevate business outcomes, making it a crucial enabler of modern business operations.

Consider wind turbine operation. Data management enables the use of multiple data sources for real-time monitoring of a wind turbine’s operating condition. This allows predictive maintenance, which helps prevent unplanned downtime for more consistent energy production. Avoiding wind turbine repairs is vital. Repairs can require on-site cranes that are large and expensive to use, costing $10,000-50,000 a day to rent. And, it takes about 20 truckloads traveling about 600 miles per day, to transport one crane, comprising 50% of the crane-related costs. That’s why preventing the need for crane-related repairs in the first place is a big cost saver—the ROI of which depends on effective data management.

Wind turbines are just one example. The benefits of data management are universal. 

Data management defined

You may be wondering what data management means. Simply put, data management is a sophisticated process involving various stages, such as data storage, processing, analysis, and visualization. Data management requires dedicated resources, specialized software, and skilled personnel that collect, organize, store, analyze, and protect data.

That’s a lot of capabilities and they require investment and time to achieve. However, the benefits of effective data management can far outweigh the costs, providing businesses with a competitive advantage, insights into customer behavior, and improved decision-making capabilities. The cost of not doing so creates a competitive advantage gap over those with a head start.

That gap can make a difference in human health as well. For example, smart hospitals employ effective data management strategies. Streaming data helps to capture patient vitals and monitor patients more efficiently and effectively. This helps to improve real-time care, hasten the availability of patient rooms and accelerate better patient outcomes.

Data management’s ROI

Customers often ask me how to “make the case” for data management. To derive data management’s ROI, your organization can use your relevant key performance indicators (KPIs). This includes metrics beyond traditional financial and operational measures, including customer retention and advocacy, employee satisfaction and productivity, societal and environmental factors, and ethical outcomes. 

To give you a head start, here are some of the organizational KPIs that help capture data management’s ROI:

1. Improved operational efficiency: Effective data management can streamline business processes, reduce manual labor and improve the accuracy of data-driven decision-making.

2. Increased revenue: By using data to identify new opportunities, improve customer engagement and optimize pricing strategies, businesses can increase their revenue and profitability.

3. Reduced costs: Data management can help businesses identify hidden inefficiencies and reduce wasteful spending, leading to cost savings.

4. Enhanced customer satisfaction: Businesses can personalize their offerings by using customer data to improve customer support and enhance the overall customer experience.

5. Reduced risk: Effective data management can help businesses mitigate risks, such as data breaches, compliance violations, and reputational damage.

Your data management head start

Data management is a critical aspect of modern business operations. Despite its potential benefits, many organizations grapple with having real ROI conversations about a data management strategy. To maximize the value of data management, we must shift our focus from the cost of implementation to the potential value it can provide—and the opportunity cost of not doing so. By identifying and measuring the key performance indicators that matter most, you can make informed decisions about your data management investments and gain a head-start competitive advantage in today’s data-driven world.

Learn more about data architectures in my article here.

Read about Dell Technologies Data Management here.

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Dell Technologies and Intel are helping organizations advance data management strategies. 

“Generating actionable insights is very challenging, and now, more than ever, it’s critical to harness data to drive real-world solutions. Intel is proud to be working with Dell to deliver modern data and analytics solutions that help organizations unlock the untapped value of their data.”  Gilberto Vargas, Intel Corporate Vice President and General Manager, Data Center, and AI Sales & Marketing.