What does ‘data-driven’ really mean?
Data-driven is a common business term, but few companies know what it means or how to achieve it. Learn more from Nephos CEO, Michael Queenan.
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“Data-driven” is a commonly-used term these days. Everyone is saying it, but do they really know what it means or how to develop data-driven operations in their businesses? There are many steps to becoming data-driven, whereby decisions are made based on data, not intuition; the early building blocks of data discovery and strategy are essential to becoming a truly data-driven enterprise.
Once you’ve developed an initial understanding of your data and what you can do as a data-driven business, your organization’s workflows, processes and goals can be optimized for better results and greater business value. In this guide, learn what it means to be data-driven, and check out some tips for creating and sustaining an effective data-driven business strategy.
Just because you have data analytics tools and use data to make decisions doesn’t necessarily mean you are a data-driven organization. Truly data-driven companies handle their data just as you should handle employees: by creating a safe and secure environment where they can thrive.
The first step toward becoming data-driven and creating an ideal data environment is understanding exactly what data you have, where it lives, how it is used and how accurate it is. Once you have identified these critical factors, you can begin your data journey and set your specific goals, whether it’s improving the customer experience or introducing new services.
Any business-to-business or business-to-consumer company can make better use of its data. However, the value will vary from sector to sector. Retail, for example, can extract lots of behavioral data about purchases and make relevant recommendations. For a law firm or advertising agency, it might take a little more effort to identify and optimize valuable data assets.
At a basic level, data-driven businesses fall into two categories: those that use data to boost sales and improve customer service and those that use data to enhance operations and processes.
Determining how your organization should use data to impact business objectives is an important first step toward aligning your data strategy with real business value. Depending on your line of business and the market you’re targeting, either a sales, an operational or a combined focus might be most effective.
To achieve sales efficiency, a game developer might measure how long people are playing the game, the length of time between games or popular character choices. By utilizing these datasets to understand user habits and behaviors, developers can shape the design of the game, from in-game rewards to color schemes.
From this new knowledge, the developer can move forward to capitalize on and monetize these insights. In B2C scenarios like this one, consumers are frequently asked to provide feedback on their experiences, which creates additional data points that can drive development decisions.
On the other hand, we have engineering companies that primarily use data-driven strategies to enhance their current operations, processes and procedures. From monitoring robot performance to evaluating plant efficiency, these companies often use data generated by the Internet of Things to give them an increasingly granular view of data.
For the many companies trapped in a traditional frame of operations, they need to adapt to the changing expectations of the modern market and put data front and center.
