Big Data Should Be Big Agility!

Every decade there is a new paradigm we all should follow. Most of us are still in the midst of an Agile transformation, while the push to become data-driven is already knocking on our doors. No worries, they are not that different as you might think. 


“Go Data or go home” seems to be the phrase of this era. If you cannot write down the words “Big Data” in your annual report, then you are doomed to be crippled by the competition within a blink of an eye, or so they say. And while we are told that data is the new panacea, the majority of the organizations are still struggling to yield significant value from it.

As a consultant (specialized in Big Data and Data Science) I see clients that jump on the data-train in fear of missing out. Most of these companies are eager to develop a stunning, next-level, industry disrupting data-driven product 2.0, but end up empty handed. We cannot all be the next Facebook, Google, Amazon or Uber. So, why should we even try?


The Real Value of Data Is… Data.

Don’t get me wrong. I think there is much to gain when you think of data as a valuable asset and start to innovate with this, creating new business models. However, you can do more with data than creating awesome data products. Or maybe I should say “you can do less” with data! People tend to forget that besides data products, platforms and ecosystems, data is still just data. Data, that even without all the innovational coinage gives good old-fashioned information.


Now We’re Talking Agile!

So how does this information add value to your business? By assisting in your Agile way of working! Wait, wait, why are we suddenly talking about Agile? Yeah, you might think, that as a consultant I like to jump from one buzz word to the next, hiding myself behind business lingo. However, as an advocate of the Agile way of working, I think that there is much to gain when using simple data analytics.


Change to Be a Changer

While some of you might think that Agile is only about moving post-its on a Scrum board, it actually is all about adaptability and flexibility of your organization, products and services. A truly Agile organization is able to change smoothly and swiftly to meet the demand of their customers and the society in a digital world that is changing as fast as ever.


It’s All About Feedback

The only way you can achieve this is by getting loads of feedback that is fast and accurate. Of course, you could ask for this feedback, but when humans are involved it is usually neither fast nor accurate. When you can use system generated data as feedback to improve your products you can learn, pivot and develop the right things at a much higher velocity. Evidently, feedback is not the only aspect of great agility, as you still need a climate that can cope with this change. Nevertheless, it’s definitely an essential and often overlooked component.


Rapid Feedback Supports Rapid Change

So how does this work? The first step is to look at the data that you already have. Most organizations generate and store large amounts of data, which nobody really uses. The second step is to really build in the data feedback loop into your products and services, meaning that you really design everything to provide useful data with the purpose of generating real-time feedback.

Two examples:

  • Website improvements: A lot of businesses register the amount of time visitors spent on their website. They usually assume that longer is better. However, it is often the other way around. I wouldn’t say it’s a positive thing, if visitors need a lot of time to find the thing they were looking for! So, use this feedback to optimize your website! For example, try to move around the sign-in button or alter its appearance and monitor the effect it has on the time it takes people to sign in. Sign-in buttons, the location of relevant pages, menu bar hierarchy; it can all be optimized by analyzing time spent on pages. If you then want to bring it to the next level, try to add additional data such as search bar entries and there are even trackers that monitor the movement of the visitor’s mouse, so you know what they focus on.
  • Urban planning: Some governments take years to plan infrastructural changes, due to the complexity of it. However, there are cases where they skipped the major part of the planning and just followed their instincts. By placing sensors in the streets, they could easily see what the effect was of certain traffic interventions, such as changing streets to pedestrian-zone only. Does it cause serious traffic jams? Then they could just reverse it within a day, or they can make some additional alterations in the infrastructure as the sensor data shows exactly where the problems occur. When sensors are in place, the data has an endless potential to improve the city (depending on the type of sensors of course). Think of deciding the best place to create parking places, or where traffic lights should stay longer on green or not, or which public trash cans have to be emptied and when. If the data is (near) real-time, then swift changes can be made with ease.

Be bold, be agile.

 DataDevelopment