What does it mean to become a data-centric organization?
By Eric Schmidt
Data alone doesn't change the world. People do.
Moving to a data-driven organization can be scary. Especially when you have been a successful business or entrepreneur that has relied on gut or feel for so long, it can can be incredibly scary or overwhelming to rely on data. So many questions about the data – do you trust it? Is it accurate? Etc…
If you have survived this long (and been successful) you might be tempted to think you can keep doing what you have been doing. Unfortunately, that thinking won’t get you very far these days.
The world of business is being transformed before our very eyes. Consumers' and business' expectations are changing weekly, maybe even daily. Innovation is happening at a breakneck pace. Technology is driving new models and new roles within organizations. It's an exciting time and yet, all this change can easily leave a company paralyzed trying to find that magic formula to growth.
We are not saying that becoming a data-centric organization is the magic formula to growth – but it plays a huge part. In future blog posts we will explore the other components of that formula – especially the people/culture/philosophy part (which we believe might be the most important component).
You can hope the whole data thing blows over and goes away (we don’t recommend that). As scary as “data-driven product development” or “data-driven marketing” sounds, with the right tools, basic foundational knowledge and some courage you can collect and analyze data quickly to make the best decisions for your business. You are not collecting data in order to judge, but rather in order to study it to determine how you can improve. It’s not about success or failure – but rather making better informed decisions.
One of the important things to keep in mind, is that gut or feel still plays a key role (in our minds) in becoming a data-centric organization. In our case, developing initial hypotheses is a critical starting point – waiting to accumulate data or analyzing existing may not always be the most practical starting point. Another important aspect to becoming a data-centric organization is to remember that data-centric doesn’t necessarily mean deep data capabilities – analytics, predictive modeling, AI, BI and other sophisticated methods and expensive tools. All of that is important but can be overwhelming and reminds me of this quote:
“Big Data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.”- Dan Ariely, Author of Predictably Irrational
Hopefully this example helped provide some context as to how you can slowly move towards becoming a more data-centric organization without feeling like you have to have incredible data scientists, sophisticated processes and platforms. Eventually the goal is to get to more and more maturity and sophistication, but that will be a natural evolution as you get more and more comfortable with the data and the decision making abilities it enables. One of the biggest issues we see and will explore in a subsequent blog post is best described by the following illustration. This (in our experience) especially holds true in the SMB market space. So stay tuned as we will share our experiences with the ‘Data Wheel of Death’.