Data analytics has become one of the driving forces behind successful and creative businesses. However, whether or not businesses are taking full advantage of its capabilities-- or even understand how to properly use them-- is still a widespread issue in most industries. Some companies have created a data-driven culture and run with it-- leading to new ways to solve problems and create better ways to produce their product, or market their service. But there are also other companies that either are not properly using data, waiting for the data to show them what to do, or have no idea where to start with data.

In this article, we’re going to draw on data analytics experts who have offered their takes on what makes a data culture work-- and what doesn’t. It is interesting to note the similarities and themes than seem to repeat in all kinds of industries. We’ve put together seven key areas that these data experts agree are fundamental to fostering a successful use of data. These themes are the first step to creating a personalized data culture.

1. Data Culture is Decision Culture

Data is a part of business culture-- and it is necessary to stay at the forefront of the competition. It is the best way to analyze your customer base-- and it is one of the most helpful methods of solving complex problems. However, collecting data just to have data is no way to move a business forward. Most data analysts agree that you need to focus on what your problem is-- and start from there. Companies get into trouble when they try to work something out based on the data they’ve collected-- which isn’t helpful at all.

The end goal of collecting data is to make better, more informed decisions. Take a process that you are currently using, and see if the results you get are optimal. If they’re not, identify where the gaps are-- is it knowledge, or lack of understanding, or is there a problem that was previously unknown or left unsolved. These are all questions companies should be asking themselves. If you want to start with the basics, examine what you think your industry will need in the next couple of years-- then develop a plan that lays out how you’ll achieve those goals, and let the data drive the decisions.

2. Data Culture and Executive Commitment

With any important initiative, there must be high level executive support. The CEO should be engaged and a part of the creation of any data management plan. If they simply don’t know what the company needs to do with data analysis-- teach them. Education is essential to a thriving data culture. Engagement and communication are other important keys to keeping everyone in the loop, and aware of progress made towards the goals.

CEOs are aware that digitization is the future-- and having data is the key to solving problems, adapting systems, creating innovative products, and optimizing services. With executive level as well as board involvement, this creates a community of people who are all working towards the same goal. When there is access to the data-- as well as a transparent means of communicating about it-- this can lead to better interactions amongst levels of management as well as an increase in progress towards solutions.

3. Data for Everyone

CEO and board engagement is crucial-- but a top down dictation never works well. Employees have to be excited about the data-- and what problems they can solve with it. Data isn’t going to just offer amazing insights on its own-- rather people should be using it to create better services or better products. This means everyone who is working to achieve either of those goals should have access to the data they need. When people can access the data they need easily-- your company is starting to build a data culture. 

This doesn’t happen overnight, but eventually it will become another part of their daily routine. By allowing access to many types of employees-- not just data analysts--  to the collected data, there are a greater number of creative solutions that can be extracted for a variety of issues.

4. Data Culture and Risk

Data collection and management must be carefully balanced with a risk management program. Every company has specific parameters set up to ensure the safety of their data-- as well as for those people who use it. There should always be controls to how the data is viewed, managed, and used-- this will help productivity and safety work seamlessly.

Rules and regulations are key to ensuring that the use of the data to encourage innovation and growth is fostered in a safe environment. Knowing how to use the data-- in relation to having a solid risk awareness-- is crucial to keeping a company thriving and creating. Learning how to mix the two processes in an efficient and effective manner will help instill a respectful appreciation of both.

5. Catalysts

When creating a data culture, it is imperative to have someone who can bridge the gap between the two worlds of data science and on the ground employees. This is the person who can take it upon themselves to make sure that whatever problem you are trying to solve-- they are actively involved on both sides. Creating a point person who can act as a liason may not be a technical person at all-- they could be extremely well at communicating within their department-- or perhaps they find the idea of solving problems exciting.

This is an ideal person who takes the project and makes it theirs-- they want to see the issue solved and are willing to work on either end to that degree. Top down approaches can only go so far-- you need to have someone on the front lines integrating these ideas and practices as well.

6. Sharing Data?

Companies want to have total control of their data, but do not want to incur the possible liabilities and risks that are associated with storing sensitive information. Data needs to be safeguarded and effectively protected from outside risks. This is why having a third party system to store and secure data is critical to an effective data management strategy. Another key component in addition to storing and protecting data is having access to it. If it is not readily accessible by an organization, then it is not contributing to future decisions and business objectives. 

Companies treat their data as a necessity-- one that they would rather not share with the rest of their industry, which is why security is key. This is indicative of how data analytics are now seen as a proprietary source of information-- one that can offer a company a competitive advantage over its competition. By allowing third party data storage companies to manage their information, organizations can feel more in control of their data and allow it to be used to their best advantage. The emergence of this data culture has given companies the confidence to share their data and know that it is secure.

7. Relationship Between Talent and Culture

Data driven companies are realizing that just because you have a PhD in computer science-- does not necessarily mean you are the right fit for their data culture. There are plenty of people who may not even be digital natives-- but have the right set of skill set needed to analyze problems and use the data to come up with some amazing solutions. Functional skill sets can transfer across industries-- and just because someone did not have experience in the specific industry-- they should not be ruled out.

Companies are looking for people who may even come from a non-traditional area of expertise-- their ideas and viewpoints can shed new lights on the situation and offer additional insights. This is a great way to come up with creative solutions to problems that people operating with the same mind set might not have considered. 

Another great way to get additional knowledge is to take current employees and transform them into a more data-focused position. They will still have all the knowledge of having been on the ground in their department-- but now you are utilizing their specific perspective to assist with data analysis and problem solving.

Data should be at the center of a business’ overall strategy-- it should be used to solve problems and create better services and products. The shift to a data culture is necessary-- but it cannot be done with a top down approach. The employees need to be engaged and excited about using the data-- and understanding how it is beneficial to the growth and profitability of the company.