Making Your Business Data-Driven the Right Way

AI & Machine LearningAnalytics & VisualizationData AnalyticsData ScienceData Transformation

Data is scaling so rapidly that the workload it produces can’t even be compared to what data teams were dealing with in the past 3 or 4 years. If there was a time when the lifecycle of software consisted of its development, shipping, and then automatic use of it, now the process has become more sophisticated.

Things changed as the amount of accumulated data changed. It first began with single monthly reports to portray the data flow, and suddenly teams of data scientists and engineers were needed to monitor and track data.

Egor Gryaznov, co-founder and CTO of Bigeye, emphasized that the pace at which companies release updates has moved from yearly or twice a year to monthly, and at times even more frequently.

“[Years ago] a data warehouse was a piece of software you installed on your server. That was a node, and you created more nodes that you had to manually manage. Because there was so much complexity in this, the software had to move slower.”

Infrastructure changes make it possible for information to be processed faster than ever. Egor continues to explain that “because the infrastructure can move faster, everything else can move faster.” Our challenge is to turn this data into business benefits.


What Does It Mean to Have a Data-Driven Business?

survey conducted by EY concludes that nearly 81% of businesses consider data to play an important role in decision-making. Moreover, around 31% of the businesses surveyed in this report had changed their infrastructure and operations to achieve this.

But what steps should you take to implement a data-driven infrastructure and what traits characterize a data-driven business?

Data minimizes the risks of failing by taking decisions that aren’t based solely on gut feelings but on the numbers and actions of their customers. Analytics stay at the core of working with data. Here are some other features of data-driven businesses:

  • Facts and trends are the bedrock of the executive strategy.
  • Data-democratization is established throughout the whole organization.
  • Business leaders don’t take decisions without evaluating the available data.
  • All employees have achieved some kind of data literacy.
  • Organizations function on a testing mindset. No product is released without proving assumptions and hypotheses with market data.
  • Continuous development is the heart of the business for both staff and software.

Is Data Overload a Problem?

An issue that is resurfacing when it comes to data relates to the capability of companies to collect data. The fact that companies can now easily collect data has overloaded them with an enormous amount of data sets that are constantly updating.

Curation and cleansing of data have become challenging and require proper attention. Businesses need to come to grips with the fact that not all of the collected data is useful. Data observability has become mandatory for organizations to filter their data and focus on what helps them make informed decisions.

We can identify cases when data teams spend time and computing power to produce reports not because they’re required but simply because they can produce them. Are those reports on short timelines really needed? “You have all this data updating 24 times a day for a nightly report that’s never looked at again,” Egor said.

Common obstacles to buildings data-driven business. Source

What Should Be Measured?

Relying on the truth when it comes to data is important. Data is continuously expanding and evolving but asking a few fundamental questions can help you differentiate between the data that is worth measuring versus the data that is less important.

  • What data is this?
  • What does it look like?
  • What are its use cases?
  • What people are aware of it?
  • What state is it currently in?

Change is essential for useful implementations. Companies should be willing to change their practices and the data collection they prioritize. These data collection decisions are strongly related to the outcome of business intelligence teams and lastly to the business decisions. Tracking down the issues properly will help you make the right decisions.


Using macro measures is useful when you are looking to measure change but it’s not an efficient way to identify the underlying issues you should tackle. Instead, focus on smaller processes or individual projects. However, all these would be useless if you aren’t exchanging your findings and results with business leaders for them to be coherently on track with the trends and changes.

Blue Orange Digital specializes in building data-based affordable solutions for businesses of different sizes. We’ve effectively helped organizations to adopt a data-driven approach (including a Fortune 500 bank), and we can help yours too. Schedule a free 15-minutes consultation for us to discuss further here.