Data management and analysis are a big part of modern business. You hear about the importance of data analysis all the time, and many platforms are giving professionals the power to create queries and generate reports without help from IT or data scientists. It's the very definition of self-service analytics.
But exactly how are you supposed to use data to make a business decision? In this blog, we'll talk about a couple of common approaches.
Data-Driven Decision-Making
Here's the strategy you hear about most often. With this approach, the data is the deciding factor of all major decisions. It eliminates any biases and relies solely on hard evidence.
Organizations use data-driven decision-making all the time. Think about A/B testing ads or using demographic data to develop marketing plans.
While impactful in many cases, this approach does have some drawbacks. The biggest is that it ignores the bigger picture and removes some of the human element from the equation. Also, it requires a trove of data to be effective. If you're using only a tiny sample, reports might not accurately represent market conditions.
Data-Informed Decision-Making
With a data-informed strategy, you're still using reports to guide you in the right direction. But instead of relying on it entirely, you're keeping the human element in the mix. For example, you might use the data to identify trends and gauge where the market is going. You may even compare the data to what your competition is doing, taking both factors into account before deciding.
The definition of self-service analytics is allowing business professionals to utilize data and generate reports without in-depth knowledge of data science. Data-informed decision-making is perfect for self-service analytics because it doesn't require a ton of data expertise to use.
The only downside of a data-informed strategy is that biases and stakeholder influence could sway the organization's decision-making. The data isn't the deciding factor like before, so there's plenty of wiggle room for things to go south.
Making the Most Out of Data
Ultimately, there are pros and cons to both of these strategies. However, data-informed is often the go-to. Data should always be the backbone of significant business moves, but having the flexibility to consider other factors can make all the difference.
Read a similar article about data driven email marketing here at this page.
