Size doesn’t matter, but variety does. You would think that a data-driven organization has a lot of data, petabytes of data, exabytes of data. In some cases, this is true. But in general, size matters only to a point. For example, I encountered a large technology firm with petabytes of data but only three business analysts. What really matters is the variety of the data. Are people asking questions in different business functions? Are they measuring cost and quality of service, instrumenting marketing campaigns, or observing employee retention by team? Just getting a report at month end on profits? You’re probably not data driven.
As I have articulated previously, data-driven organizations are a culture, it is not about toolsets or data scientists. It doesn't matter how much data you have, it matters that you have enough data to make an informed business decision.
Everyone has access to some data. Almost no one has access to all of it. There are very few cultures where everyone can see nearly everything. Data breach threats and privacy requirements are top of mind for most data teams. And while these regulations certainly stunt the ability of the company to make data available, most data-driven companies reach a stage where they have developed clear business processes to address these issues.
It comes down to what data is important for each business unit. Most business units don't need credit card information or PII information about individual customers. Understanding what data will drive better business decisions in each unit and focusing on getting those units the needed data in a consumable format is the key.
Data is all over the place. One would think that the data is well organized and well maintained — as in a library, where every book is stored in one place. In fact, most data-driven cultures are exactly the opposite. Data is everywhere — on laptops, desktops, servers.
This can be dangerous. Remember there is nothing worse than fighting about the validity of data. If operating units all have their own sets of data, then it becomes a competition of who's data is right instead of what decision we should make based on the information at hand.
Companies prize insights over technology standards. Generally, the principal concern of people in data-driven businesses is the ability to get the insight quickly. This is a corollary of point #3. Generally, the need to answer a question trumps the discussion of how to best answer it. Expediency wins, and the person answering the question gets to use the tool of their choice. One top 10 bank reported using more than 100 business intelligence technologies.
I really like this, as long as you don't fall into the trap I discussed above. To get people to adjust to a technology instead of providing insight is lost time. Getting a huge organization on 1 platform is problematic at best, a disaster at worst. If analysts can work in tools they have mastered, it will allow them to get insights faster. Faster insight is a major competitive advantage.
Data flows up, down, and even side to side. In data-driven companies, data isn’t just a tool to inform decision makers. Data empowers more junior employees to make decisions, and leaders often use data to communicate the rationale behind their decisions and to motivate action. In one data-driven company, I observed a CEO present a 50-slide deck to his full team, and almost all of those slides were filled with charts and numbers. Most fundamentally, data empowers people to make decisions without having to consult managers three levels up — whether it’s showing churn rates to explain additional spend on customer services vs. marketing or showing revenues relative to competitors to explain increased spend on sales.
The old thinking was to create a business intelligence team that would provide the data for the organization. Each operating unit should be in charge of their own data analytics. There should be a centralized business intelligence team to provide a checks and balances, but operating units are best to answer their own questions, they know their business best. Democratizing data throughout the organization is key to having a data-driven organization.