For some time now there’s been a big push for teams to become data driven. Our data can guide us by telling us what’s actually working and what’s not. Not being data driven today seems like feeling around in the dark and hoping our ideas see the light. And a number of companies have seen the light by leveraging data to personalize marketing efforts, make faster data-driven business decisions and cut costs by making operations more efficient.

A study by Bain & Company found that data-driven companies are:

  • Twice as likely to be in the top quartile of financial performance within their industries.
  • Three times more likely to execute decisions as intended.
  • Five times more likely to make decisions faster.

chart showing top-performing companies embed data in decision making

Data Informed Means Balancing Data and Human Behavior 

This doesn’t mean everyone should strive to be data driven. Depending on your role you may need to be more data driven or more attuned to human behavior. Within your teams you need a combination of people with these different but complementary skill sets.

For example, we need our growth marketers to dive deep into our data and find patterns and inconsistencies which we can then use to improve our marketing efforts. Meanwhile, graphic designers need to be more attuned to your audience’s visual needs by understanding the psychology behind human perception. In between you find product design which requires you to both test, track and draw insights, but also use empathy to guide which insights will provide the best user experience.

Being data informed melds both sides. People who are data informed are able to take both quantitative and qualitative insights, observations and — dare I say it — gut feeling, and use all of these elements to make strategic decisions. Just like becoming data-driven takes time, becoming data informed takes time and also experience.

data driven vs data informed

The most successful companies use both data-driven and data informed decision-making. Relying too much on data without taking the human factor into account can be one of the most dangerous things for a company to do, this is why:

Related Article: How to Ditch the Guesswork and Become a Culture That's Driven by Data 

1. Misunderstanding Human Dynamics

Ethnographer Tricia Wang began working for Nokia in 2009 collecting research on how low-income people in China were using technology. As the dominant mobile company in emerging markets, Nokia wanted to use this information to inform its strategy.

Surprisingly, during her conversations with over 100 people she found what they actually wanted most were smartphones, even if it meant spending over half of their monthly income to get one. From a practical point of view this doesn’t make sense. Why buy an expensive smartphone when you can buy a much cheaper pay-as-you-go model? The truth is that smartphones promised more than just the ability to make calls. They promised entry into the growing high tech world.

But, after presenting her findings to the company, Nokia decided to go with their quantitative data. Nothing in the millions of data points they had collected indicated smartphones would be something people actually wanted.

What the company failed to see was that human dynamics are what drive trends. Focusing solely on data won’t allow you to see beyond your current and past market conditions.

Related Article: Why They Click: The Psychology of Your Audience

2. Design Flaws

Sometimes you’re too close to what you’re building. You’re excited about the possibilities but is it actually going to be functional in people’s daily lives?

Segways are a prime example of cutting-edge technology that failed to take into account practical design questions.

These smart scooters were predicted to reach $1 billion in sales faster than any other company in history. Well known figures like Steve Wosniak and journalist Piers Morgan were among the first to start riding them in public.

Inventor Dean Kamen believed that in the future everyone would be riding a segway. With more than $100 million put into research and development and widespread international hype, segways became too big to fail … until they did.

With a hefty price tag of $5000, segways cost as much as a used car. But, unlike cars, there were no designated lanes where they could be driven. Roads were out of the question and sidewalks were a grey area. You could ride them in an office building, but weighing 100 pounds, once you got to a set of stairs you were out of luck.

Segways are still around but mainly used by tour groups, building security and in large manufacturing warehouses. Perhaps if they had zeroed in on these target audiences more or had developed a more practical design that would fit naturally into the daily lives of a larger audience, things could have turned out differently.

Learning Opportunities

comparison of being data-informed vs. user experience

Related Article: Segway Inventor Dean Kamen: Science Isn't a Spectator Sport

3. Misalignment With Commercial Goals

Data can guide us down many different paths, but it's important to keep focus and not get swayed from your commercial goals. After all, businesses need to make money, or they will die.

There are times that your data may be telling you something that doesn’t actually align with what your users want and what your business needs.

Take Hotjar as an example. After investing over 3,500 developer hours and $200,000 on its mobile app, it made the decision to finally kill it in 2018. The research showed that launching a mobile app would be a great thing for the company. But everything else should have shown that focusing on improving its core products would deliver more value to its current customers, and ultimately more revenue for the company.

Just because the data says that “51% of B2B search queries are conducted on mobile phones” or “80% of B2B workers are using mobile phone at work” doesn't mean that it's the right call for your business. You have to first consider what makes most sense for your users and your product.

In Hotjar’s case, it turned out its users just wanted the ability to watch recordings on mobile. The team instead spent hours building an app which didn’t allow for this function.

The stand-alone data may tell you that you need an app — but if everything else, and your gut, tells you that you could offer more value to your customers in a different way, you should consider making a data-informed rather than data-driven decision.

At the end of the day we’re using data to create and design technology that will help our users in their everyday lives. It’s therefore essential that we consider the human aspect of each decision we make.

Finding a Balance Between Data Driven and Data Informed

Of course, there’s never a perfect solution. Again, the problem with making data informed decisions will always be the human factor. While your experience within an industry or role may help inform you in a way that you can’t get from data collection alone, your decision-making can also be biased by your past experiences.

There are times and situations in which being data driven or data informed will have its advantages. When you have a more established product and user base you have more insights you can use to optimize your product with data-driven decisions.

When you’re starting from scratch, especially with a disruptive product or new business model, you’ll have little historical data to draw from. Similarly, if you want to expand into new markets, relying on data coming from the audience you’ve already acquired could leave you shortsighted. This is where having data-informed leadership can really be a competitive advantage.

To find a balance between being data driven and data informed, follow these tips:

  • Aggregate and democratize your data — Whether you’re data driven or data informed, everyone should have access to your company’s data and keep up to date with it on a regular basis.
  • Collect qualitative data — Include user/focus groups and surveys as part of your research strategy.
  • Always be testing — Create a process for testing, especially when trying something new.

Last but certainly not least: Back yourself. You know your business better than anyone else. Data can guide your decision making at times but, ultimately, your experience and time spent getting to this point means there is an element of gut decision making that your business will require you to do. Back yourself to make the calls you need to, you have more information about what is right for your business than Google.

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