Not all teams and people operate the same when it comes to a data-led organization. It would make sense that at different organizational levels, various skills are needed to make a data-driven culture happen. The question is if your team has the skills and motivations at the various levels that are needed to make this happen.
Let's talk for a moment about motivation. The idea of a data-driven culture is that at every level in the organization there is an understanding of why data is important. This means that even at the lowest level, front-line workers, understand how data is being collected, what it is being used for, and how that data contributes to helping the organization operate at a higher level. If this base level isn’t achieved, then it is hard for the organization to produce good data that will help leaders make the decisions they need for the business. For some people, this may even mean giving them training and access to data manipulation tools like Excel, PowerBI, Tableau, etc.
To earn this level of understanding in the organization one must have a vision for how the data will help and educate the team members on how important their collection is. It also helps if having this type of data can make their job easier. If you can achieve those two results, then it will make it easier for you to have the data needed to improve.
For middle-level management, it is equally important for them to understand how data is going to be used. Oftentimes, they will utilize this type of data to allocate resources, educate teams and predict business to upper-level management. You want your middle-level managers to be very data fluent so that they can utilize as much of the data as possible to be predictive.
To earn this level of understanding at the management level you will need to have education around data fluency and being predictive. Executives need to ask the right types of questions and ask how data contributed to decisions in order to allow data fluency at this level to happen. If executives back off from those asks, there will be a greater tendency to operate from gut vs. data.
I shared a little bit about the actions that executives need to take to help set the downline expectations of data, but executives also need to utilize the data they are receiving to make decisions. Some of the types of data sets that executives in a data-driven culture would want to look for are:
These are just some of the samples of how executives might use very different datasets.
As you can see, a data-driven culture is different at various levels in the organization. Having a plan for how you roll this out and train the different teams will be important.
Data and analytics leaders are critical to the performance of any company. These roles are not just crucial at specific points in time; they are essential to the long-term success of any business. These roles are expected to play a growing role in the future of almost all companies. Promoting data fluency and engaging more individuals in the data discourse is crucial to the job. The importance of data and analytics leaders is increasing because of new challenges. They help drive performance by ensuring data is relevant and accessible and analyzing it to uncover insights that can be used to improve business processes across departments and geographies. This article will discuss the importance of data and analytics leaders in today’s digital world.
Chief Data Officers (CDOs) are the new hot job title in data science. As companies scramble to hire CDOs, they see this role as essential to their future. After all, a chief data officer is the highest-ranking data scientist within an organization. They are typically responsible for developing and implementing strategies for managing, analyzing, and monetizing data from multiple sources. To help you understand the challenges CDOs face as this newer role is added to many companies, we’ve compiled this list of common mistakes that CDOs are making right now, along with advice on how to avoid them so that you can hit the ground running as soon as possible.