Today’s businesses rely on data to formulate their growth strategies—data-driven and data-informed approaches are two unique ways you can leverage data to gain a competitive edge.
Although the differences are subtle, each approach takes a different direction and changes how your company works with its available data.
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Taking a data-driven approach is usually the more objective strategy, but it might cause you to miss the bigger picture.
On the other hand, going the data-informed route can introduce too much data flexibility for some businesses.
So, how do you know which one is right for your company?
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The Data-Driven Approach Defined
Taking a data-driven approach means relying on data to make all of your decisions all of the time—every aspect of your business strategy depends on interpreting the data you have available.
It’s an excellent approach that allows you to harness data to gain unique insights into your customers. However, it has one massive flaw: it doesn’t account for personal experience. A data-driven approach focuses less on the big picture and is all about the facts—the hard data gets the final say.
Let’s look at an example where we have two different versions of an ad. We like the first ad and believe it will perform better with our target customers but decided to test each one. After evaluating their performance, the second ad comes up with a lower customer acquisition cost. So, even though we’re pretty sure the first ad is better, taking a data-driven approach means using the second one because that’s what the data says is better.
One of the most significant benefits of a data-driven approach is that it takes the decision-making out of your hands and prevents personal bias. It tells you exactly what to do without your feelings or gut instincts getting involved.
This aspect eliminates some nuances of the decision-making process. It has the additional benefit of making it easier to push back against your stakeholders that may have different agendas—cold hard facts and figures make defending your business’s position to its stakeholders easy.
A data-driven approach can also help you identify trends that could signify future problems. Instead of reacting to market changes, you can be proactive and identify potentially troubling situations using data.
However, solely using data to make decisions can easily make you miss the bigger picture. Additionally, it’s easy to rely on the wrong data that may not be statistically significant with a data-driven approach, preventing you from making truly informed decisions.
To truly be data-driven, a business needs to collect large data sets over time to gain an accurate look into the market conditions. Maintaining a purely data-driven approach is extremely challenging. Even though 74% of businesses wish to be data-driven, only 29% of them can successfully transform their data into an actionable plan.
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The Data-Informed Approach Defined
Taking a data-informed approach involves using other inputs alongside your data, like user research and personal experience. So, data makes up one part of your decision-making process instead of the entire thing.
Let’s look at an example similar to the one we discussed above to test out two different ads. And let’s say we want to use click-through rate to evaluate their performance.
The first impressions are that the first ad returns a higher CTR than the second ad. So if we were to take a data-driven approach, we’d immediately pick the first ad because the data says it’s better.
However, if we take a data-informed approach, we want to see the bigger picture. After further testing, we find that, while the first ad has a higher click-through rate, it also has a significantly higher cost per click.
Then, our personal experiences tell us that both ads have better CTRs than average. If we run the second ad, we’ll run with a more effective budget without compromising performance.
That’s the difference between data-driven and data-informed.
The most significant benefit of a data-informed approach is that it lets us see the whole picture and gives us quality rather than just quantity. You can combine other inputs with your data to better understand what’s happening, uncover unique solutions, and make more informed business decisions.
Rather than focusing solely on data, this approach allows you to come at business problems with somewhat unorthodox solutions that wouldn’t come to light with a data-driven strategy. We can blend data with things like our business experience to come up with different ways to view issues and keep up with changes early on in different trends.
For example, if industry changes or competitors cause your customers to change their preferences, you can catch it earlier with a data-informed approach, whereas a data-driven approach might not notice the change before it’s too late.
The biggest issue with a data-informed approach is that your decisions can be easily swayed by outsiders, like when we talked about how data-driven methodologies can help you push back against stakeholders. It can be challenging to convince them why you’re operating a certain way when you use other inputs to make business decisions.
A data-informed approach is also prone to personal bias, even if your company’s decision-makers try their best to keep bias out of the process. It also presents many more options, unlike data-driven strategies that simply focus on the objectively best way forward, which can lead to choice paralysis.
Data-Driven vs. Data-Informed: Which Is Best for Your Business?
Both approaches have pros and cons, and you don’t have to choose just one. Many businesses take different approaches based on what they’re trying to solve.
A data-driven strategy is typically best for making either/or decisions, like our example of testing two different ads. On the other hand, a data-informed strategy is typically best for complex projects that might benefit from multiple inputs, especially processes that rely on creativity.
Ideally, you should find a balance between data-driven and data-informed strategies and use the appropriate approach for your current projects. Data-driven approaches are ideal for making decisions with quantitative inputs, while data-informed approaches are ideal for making decisions with qualitative inputs.
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