It’s nothing new to say that data and the way it’s growing is becoming one of the major assets all across industries nowadays, from healthcare, to finance, going through insurance, sports, media, marketing, logistics, and almost every way you want to look.

Several techniques or disciplines as data science, machine learning, artificial intelligence are commonly heard on the news, social media, or forums we can attend, but to get to that maturity and awareness isn’t built overnight.

What does it mean to be data driven?

It’s normal to hear that companies base their decisions on data, but also a lot of hype is built around these terms. To be data-driven it’s not only to analyze results report after each half or quarter, it also involves developing a culture, giving new skills to employees, empowering them with roles and responsibilities and being able to find in the market the missing talent, investing in technology and infrastructure but the most important part is to build processes that support a data-driven workflow. All of these parts framed by a data roadmap will take the company through all the stages and to the next level.

If we had to define data-driven, it would probably be: having data as a key strategic pillar in our business. This includes using data all across the company, measuring our performance, and having a culture that values data central to the operations.

Are we there yet?

It’s hard to predict how long it will take to get somewhere when it’s unclear where we are standing. There’s probably a quote about this somewhere!

We can identify 5 stages companies go through before becoming data-driven:

• Data unaware: even though there may be systems and infrastructure, no data is being collected nor stored. The company hasn’t built consciousness about the importance of storing data and the potential it has.
• Data collectors: systems, processes and infrastructure are only collecting data. There’s a high chance people don’t know what data is being stored, there’s no integration and our data will be a little bit messy.
  There may be areas working with data but in an inefficient way.
• Data aware: data is recognized as an important asset, and the company is taking its first steps towards building our first solid repository that works as a stepping stone in order to consume our data efficiently.
• Data guided: This is a big step! The company now has accurate information about what happened yesterday. The repository is now solid, and the processes that integrate our data are working, we have developed a reporting solution and data is being considered by key users for decision-making purposes.
• Data proficiency: Wow! Companies can now generate and consume data insights on a daily basis, in order to start thinking about what will happen tomorrow. In order to reach this stage, data abilities and skills are strengthened.

It sounds simple, right? Well… it’s not! It takes hard work and determination.

A basic roadmap…

Where are we today?

Performing a data maturity assessment is the big first step that every company should take in order to build the roadmap towards being data-driven. Asking the right questions and gathering appropriate information for each area of our company is a key component to get a full picture of our level of maturity, data-wise. Companies should evaluate the way their systems are currently performing, and the aspects that should be transformed in order to reach the goal of being data-driven.

Knowing our business needs

There are no one-size-fits-all approaches. Each company presents a different scenario, and every business area will have different needs. It’s important to get to know in detail how they work, and what they’re willing to do, in order to identify data and technology use cases.

Let’s get into technology

You’ve probably noticed that I’ve barely talked about the need for technology so far, and that’s because processes and culture are key elements in this transformation, but technology plays a really important role as well: it’s the enabler for all this to happen.

Designing our data architecture
We have to translate all our use cases into solutions and that’s why we need to design our data platform to be as reliable, seamless, and scalable as possible.

This doesn’t only involve the way our data is stored but also how it’s collected and ingested into the storage, and then, how it’s consumed from it.

In future posts, I’ll try to share and explain some alternatives as well as their advantages and disadvantages.

Consuming our data
You may have heard of data visualization, data science, machine learning, and maybe artificial intelligence: all of those disciplines or practices use data as one of their main fuels, and they can be really useful when it comes to understanding our business or optimizing different processes of it. We will get here, but we still have a way to go.

Build your culture

Building the right culture is much more important than having the right tools (don’t misunderstand me, it’s actually really important to have the right tools, design, and implementation). The development of a data-driven culture inside the company will be one of the most important but hard steps on your path.

Let’s recap

Being data driven involves much more than technology investment and development. It involves building a culture, developing skills and having a roadmap where we have a clear view of where the company is and where it is going.

In the near future I’ll be sharing some more thoughts regarding data architectures, the different technologies and techniques you can employ to gather, store and consume all the data generated at your business and with it, enhance it, and take it to the next level.