Most companies we know today born in a time where information was scarce which explains perfectly why they haven’t developed a Data Driven component into their cultural DNA. To have a good feeling on what I mean when I say lack of information let’s take a look at some figures.
- 90% of the data on the internet has been created since 2016 (IBM Marketing Cloud Study)
- Around 200 million wearable devices where sold in 2019, increasing around 600% in just 3 years.
- The internet users came from 16 million in 1995 to 4.5 billion in 2019. There are 83% more internet users during just the last five years.
- Every minute on Twitter 473,000 tweets are sent.
- Every minute on Facebook: 510,000 comments are posted, 293,000 statuses are updated, and 136,000 photos are uploaded.
- More than 100 million text messages are sent every minute via SMS or text app.
Today’s top companies born in really different worlds even those that came only 4 years later! Take a look:
- When Amazon was founded (July 5th 1994) it was less than 15 million internet users worldwide.
- When Google was founded (September 4th 1998) it was 147 million internet users worldwide.
- When Facebook was founded (February 2004) it was 757 million internet users worldwide.
- When Instagram was founded (October 6th 2010) it was 1,7 billion internet users worldwide.
- When TikTok was founded in 2017 it was around 4 billion internet users worldwide.
So the situation all these companies had to face was really different and for sure the context was a key variable responsible of the development of their current culture. For companies like Amazon or Google, was definitely more difficult to develop a Data Driven culture than for the ones arriving later. The quantity and quality of data they had at the beginning was not much. In contrast of what we could think Google and Amazon are some of the most Data Driven companies today.
So even when newer companies tend to develop a more data oriented culture it doesn’t depend just on that. Apparently there are other variables involved that drives a company to include a Data Driven component into their cultures.
One of those other variables is competitiveness. You can make money without data, but you can’t be competitive without it. So if you are playing in a highly competitive industry you have no chance but to develop a Data Driven culture or wait until it’s too late.
It’s way easier to lean to do new technical thing, like Machine Learning than to change make cultural transformation. Changing a company culture takes time and require people to stop doing something in the way they always did it and start doing it in a different way, every day, every month until the new things become the norm. Let’s take a look at the Top 11 the practices that are common on Data Driven companies.
Common practices in Data Driven companies
- The C Level includes a data professional.
- Proficiency level in data and analytics is required for all management positions.
- Employees don’t depend on a BI or Data & Analytics department to find the data they need. Most employees have access to self service data tools.
- High failure tolerance. Using data to test new things is normal and there’s no downside for employees if they fail in the process.
- There’re no data silos. Most of the employees, no matter in which department or area, are accountable for the generation of their data and they know how important is to share it.
- Data is accesible for everybody.
- Data and Analytics professionals are involved in projects from the beginning.
- Everybody has access to data trainings.
- Meetings are data centric.
- People feel confortable saying “I don’t know”.
- They compete against themselves. Internal benchmarking vs external benchmarking.
On the contrary you can identify if your company, or a company you are visiting, is not Data Driven if they face some of the following situations.
The six top situations you can normally face in a company not governed by data.
- During a meeting people use past experiences as substitute of data and sometimes as an irrefutable truth.
- Meetings discussions are normally focused on people and their experience rather than in data.
- Inferences are a common currency and they are presented as fixed statements normally uncountable or hyperbolic like “People like this”, “Everybody knows that”.
- Ideas become “projects” in a blink but they never get implemented. Those ideas are normally proposed by the “epiphany” of a Hippo (Highest paid person opinion).
- People are normally very failure sensitive and if they fail they try to hide it or find an external responsible.
- People leave meetings without really knowing what’s expected from them.
Have you faced other type of situation in either a Data Driven or not Data Driven company? Please post them in the comments section.