Understanding the difference between data-driven and data-informed

Data is key to growing your business, regardless of your industry or specific growth goals.

It can help you understand what your customers want, what products and services resonate with them, and where you have expansion opportunities. A business that understands and acknowledges the power of data is better positioned to increase market share and attract new customers.

However, there are different approaches to using data. While some organizations opt to follow a data-driven business model, others prefer to remain data-informed. Both approaches involve using data to make decisions, but there are fundamental differences between the two.

Whether you’re working for a startup or joining an established organization, understanding what it means to be data-informed or data-driven can help you factor metrics and numbers into your company’s business plan.

“Data-driven” means relying on data to guide the direction of your organization. A data-driven business makes crucial decisions based on data.

Most organizations acknowledge the impact data can have on their bottom line—but data-driven companies take this a step further, letting metrics lead their decision-making process. In these businesses, data guides the entire organization, from the sales and marketing departments to IT and beyond.

The data-driven approach is based on the idea that numbers don’t lie. Data and analytics either support following established patterns or back even controversial business decisions to break new ground, all based on what the metrics say.

Benefits of the data-driven approach

When your business adopts a data-driven approach, you can expect the following significant benefits:

• Evidence-based decisions: being data-driven means you always have metrics and numbers to pull from and reference. Evidence-based decisions can help foster long-term success and enhance revenue growth.

• Ability to act proactively: rather than reacting to a change in the industry after it happens, you can follow the data and identify something that could be problematic in the future.

• Eliminates emotionality: being data-driven means emotions have no real role in decision-making. Following the data instead of someone’s gut instincts means stakeholders are put on a level playing field.

Drawbacks of the data-driven approach

The data-driven approach also has some drawbacks, including the following:

• No interrogation: in a data-driven approach, the data is trusted blindly without any real question as to why something is the way it is.

• Data quality: low-quality or insufficient data can lead to poor business decisions.

• The bigger picture is ignored: the bigger picture isn’t always considered when an organization adopts this approach. There’s no place for subtleties, which is particularly difficult if there’s no large data pool to draw from.

Becoming a data-driven business can be tricky. It requires some knowledge of how to handle large and often complex data streams. However, when you are aware of the drawbacks and challenges, it can provide a path to deep organizational growth and increased profit.

When a business is data-informed, it uses data as a factor in making decisions rather than using it as the entire basis for strategies.

A business that takes a data-informed approach uses other tools and resources, including user research, employee experience, third-party insights, and other types of feedback. In other words, data isn’t the be-all-and-end-all, and it isn’t the only valuable source of information.

Benefits of the data-informed approach

Consider the following advantages of using a data-informed approach:

• Draws from multiple sources: one of the most obvious benefits of following a data-informed approach is that it uses multiple sources to make decisions—not just metrics. A business might develop a more comprehensive strategy when it embraces subjective sources and other avenues of research.

• Embraces creative thinking: being data-informed works well for complex projects that require several inputs, as it can facilitate a creative approach to problems, goals, and projects.

• Helps identify trends: you might have an easier time identifying market trends when you don’t hyper-focus on data alone. This approach allows you to embrace more growth opportunities and keep tabs on your competition.

Drawbacks of the data-informed approach

Here are some drawbacks of the data-informed approach to be aware of:

• The potential to disregard data: numbers are hugely valuable even in a data-informed approach. A lax attitude to tracking, recording, and monitoring the data you need to signal whether your strategies are working could create challenges. This is especially true in startups or smaller companies that haven’t yet established reliable data tracking methods.

• Emotional influences: a data-informed approach can lead to conflicting information and emotional decisions from stakeholders. Without hard data to guide important strategy decisions, stakeholders might be pulled in different directions, causing friction within the business. This can have an impact on nearly every facet of the organization, especially if employees feel a sense of conflict.

New and emerging businesses might initially embrace a multi-faceted data-informed strategy, but it’s important not to lose sight of the metrics that form the basis for revenue growth and customer acquisition.

A data-driven approach relies on data to guide decision-making, while a data-informed approach treats data as just one source of information that factors into decision-making. That’s the primary difference between the two.

One approach isn’t necessarily better than the other. Many businesses use a combination of both to craft effective business strategies.

While it can be difficult to choose the right data approach for your business, the amount of data you have to work with should influence your decision.

If you have a large volume of data and enough employees to manage it, you could consider a data-driven approach. Alternatively, the multi-faceted data-informed approach could work well for your needs if you have only small amounts of data. It may also be suitable for startups that are just beginning to adopt formal business strategies or companies that regularly deal with complex situations.

Many businesses choose to adopt a blend of these approaches because both have advantages and disadvantages. Regardless of their industry, most businesses will need to learn when to use each approach according to the specific situation.

Consider what goals you are trying to achieve and the type of data you have at your disposal. Don’t feel obligated to commit to one approach. There’s no reason why you should choose one strategy and use it exclusively, especially as your business grows and evolves.

Acknowledging the value of data is only the first step. Figuring out how to use the data at your disposal and harnessing it in new and exciting ways is key to discovering new possibilities.

Whether you opt for a data-driven, data-informed, or hybrid approach, maintain an innovative mindset, and you’ll be empowered to succeed.

A data-driven approach is when you allow the available data to inform your business decisions rather than any subjective opinion or third-party research.

Data-informed is an approach that embraces other sources of information for making business decisions, including user research and customer feedback.

Data-centric is the final stage of data evolution when data is being used at every level of the business. All approaches are valuable and worth considering.

A concept-driven strategy is a set of strategic concepts or organizing principles that stakeholders agree will work best for an organization. Data-driven, on the other hand, is an approach that relies on data to guide decision-making.

These principles are not mutually exclusive. Concept-driven and data-driven strategies can often coexist within the same company to serve overarching goals.

Being data-driven is when you allow the data to influence your business decisions rather than opinions or outside influences. Data-inspired decision-making is a more exploratory approach. It has no specific outcome expectations but can provide observed trends that you can use as a basis for innovation and further exploration.