Many companies today claim to be “data-driven,” but what does this buzzword actually mean? After all, companies have always had access to data (whether it’s digital or analog) that they’ve used for decision-making. What’s different about data today?
The answer lies primarily in the magnitude and richness of the data involved. Companies now have access to vast pools of information and tools to explore the depths therein for insights. From that data, they’re able to extract actionable, previously invisible insights that can be applied in all sorts of decision-making.
Rather than relying on intuition, clairvoyance, or hunches, data-driven decision-making utilizes empirical insights to inform the course of action. It’s the difference between flying blind versus charting a course. And though an optimal outcome is never guaranteed, informed decisions increase the likelihood of positive outcomes far above operating without data as the driver. Considering that 58% of respondents to a BI survey say their companies base at least half of regular business decisions on intuition, clarity on informing decisions with data is ever more important.
Data-Informed, Data-Driven, and Data-Centric Classifications
Many of the companies claiming to be data-driven understand and aspire to the concept but fall short in execution. More often, they’re better described as “data-informed;” they systematically collect and store data, and decision makers know where to access it when needed. This is a strong first step. However, there are crucial depths still to be explored.
Being legitimately data-driven (versus being data-informed) means a scientific approach has been operationalized. Data-driven companies have professionals on staff who know how to collect, organize, and analyze data based on what the decision makers need. Data isn’t seen as a resource at their disposal — it’s considered the most important asset they have. These companies tend to outperform competitors without data scientists because they mine for insights strategically and proactively.
Further still, an emerging breed of data-centric companies integrates data as the strategic centerpiece of all departments and levels. For these companies, data is the business model. They strive to operate as the data hub for an industry; they gather metrics from every step in the value chain and compile and partition vast data pools to extract value in myriad ways.
Data-centric companies ease access to industrywide information, thus streamlining how decision makers leverage their insights. In that way, a successful data-centric startup is likely to serve the needs of much larger, established companies in the industry.
Observing Data Centricity in Action
In practice, some industries would thrive with one data-centric enterprise that acts as a central repository for industry players across the value chain. As a result, these companies enjoy a durable competitive advantage. Here are two examples:
FreightWaves
Imagine a data exchange similar to a Bloomberg Terminal — but for freight information instead of stocks. That’s what FreightWaves offers in the form of a hub that collects and displays real-time data threads from throughout the shipping chain. Users from blue-chip companies such as UPS and Google can log into this platform to make data-driven decisions about pricing, placement, routing, or hedging.
Understanding the complex forces that affect shipping (such as weather, economic changes, technological advancements, and regulatory updates) is now mission-critical for all competitive companies in the market — even those without dedicated data science departments. In that way, FreightWaves serves the needs of much larger companies that need freight insights but wouldn’t otherwise have access to the right data.
LO3 Energy
With electric vehicles, smart homes, and distributed renewable energy sources all taken online rapidly over the past few years, major forces are widening the data void in the energy economy. LO3 Energy offers a platform that aggregates electricity usage data on the local level, creating a simulated microgrid backed up with blockchain technology. This data-centric platform makes it easy for industry players to leverage advanced enterprise analytics, balance loads more closely, and create tighter incremental finance hedges.
From an investor’s perspective, data-centric companies look highly attractive. They enjoy durable competitive advantage — even during uncertain times like these — and they’re transformational for entire industries. If you’re eager to get involved with data-centric companies while they’re still in the startup stage, Ascend Venture Capital can help. Download our white paper, sign up for our newsletter, or schedule an appointment to talk with our GP and data-centric expert, Dan Conner.