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.

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1. Focusing Too Much on Big Data and Not Enough on Small Data

One of the biggest data challenges for CDOs today is that they often focus too much on big data and not enough on small data. This is a mistake because it means that CDOs are ignoring the most valuable insights found in the world of marketing, analytics, and customer service. Big data has its place, but it’s not always the best way to solve problems. It can often slow down an organization’s ability to make decisions because of the difficulty of data and preparing it effectively is more. The infrastructure required for extensive data is significantly different. At the same time, small data helps us understand customers better by looking at what they say, what they do, and how they interact with products or services. Key Learning: try to find small wins as you come on board with smaller projects that are impactful to the organization. 

2. Not Having a Solid Plan for Determining Success

The chief data officer (CDO) is a newly created position within many large companies. It is difficult to determine where the goal will be when stepping into a role, as most of these roles have never existed. The CDO’s primary responsibility is to ensure that an organization utilizes its data. The CDO needs to ensure that data is available to stakeholders to make critical business decisions. To do this, many CDOs are making mistakes by having no defined plan for determining success. This lack of planning can lead to organizations missing out on opportunities such as new products, services, or markets they might otherwise have been able to capitalize on. Key Learning: Make sure you have a plan in place and it is run past many executives for their input and alignment. 

3. Analyzing The Wrong Data

Another mistake that chief data officers make is not having checks and balances to ensure that the right data is being analyzed. This can lead to wrong data being used for decisions in the business. It's not just about looking at the numbers but also understanding what they mean and how they were collected. Data is not neutral. You have to know who managed it and the business reasons for why the data exists. If you don't understand why there's a good chance you'll make decisions based on faulty assumptions or not apply data correctly to decision-making. Being generally more data-confirming than data-driven. Key Learning: Identify key stakeholders across the organization who will help you understand the business side of how data is being used and collected. 

4. Ignoring the Importance of Data Governance

The mistakes that CDOs are making now are often due to not having a strong data governance program. The number one reason why CDOs fail is that they don’t have a strong data governance program in place. Governance is critical for ensuring that data is consistent, validated, and reliable. This is particularly important in the case of CDOs, as they are likely to have a high volume of data coming in. Key Learning: Preplan how you are doing to handle data governance not only with your team but across the organization. 

5. Assuming That All Data is Good Data

Just because you have data doesn’t mean that all of it is good data. Before you can start utilizing data, you must make sure that you clearly understand how that data is being collected,, why you need it, and what you will do with it afterward. Collecting and analyzing data can be tricky, depending on the type of organization you work for. The first step in building a data strategy is to know what you currently have. To do this, you need to understand the quality of your data, its governance, and how it's used across your organization. Key Learning: Make a repository or catalog of data and determine, based on how it is collected, the quality of that data. 

6. Focusing Too Much on Onboarding Data to the Team

The onboarding process for new data sources can be critical for CDOs, which is why it’s essential to get it right. CDOs rely on data from third-party sources, so the onboarding process is essential to ensuring the data is clean and consistent. However, CDOs sometimes make the mistake of focusing too much on data onboarding. This can cause the team to lose sight of the end goal. The onboarding process is critical, but it’s important to remember that the ultimate goal is to use the data. It’s not to get the data into the CDO process; it’s to ensure it is clean, validated, and ready to be used. Key Learning: Look for some smaller wins while collecting data with a more significant strategy. This way you can immediately win.

7. Not Making Data Communication Effective   

Not everyone in an organization needs to understand data, processing, or analysis. However, everyone must know the data's hidden meanings to plan their work accordingly. The common mistake is that CDOs are not making data communication effective between themselves and all of the leaders across the organization. CDOs should effectively communicate data insights to each key position holder to plan their activities accordingly. Also, they must understand data fluency across the organization. They must present the results of data analysis in such a way that even employees who do not understand data understand the outcome. Key Learning: Make sure you have communications for different levels in the organization and help improve data fluency across the entire organization. 

8. Not Recognizing the Importance of Data Culture

The data culture is an essential part of the success of any organization. It can be defined as the set of values and practices organizations use to manage, protect and leverage their data. Data culture is a critical element for an organization, especially when it comes to the protection of customer information. As a result, if there isn’t a culture around data, then it is hard to support business units and leaders with data. Key Learning: Ensure that there is a culture around how data is being used in your organization and work to improve the overall data culture. 

9. Not Keeping Up With Technological Advances

Another mistake Chief Data Officers are making today is not keeping up with technological advances. Some technologies have been around for years, but new ones come out every day — and these new technologies are quickly becoming a part of everyday life. They may be doing it to save money, but it's also a missed opportunity to use new tools to help them make better decisions. Key Learning: Be aware of what is happening in the industry in terms of tools that can be utilized and always be evaluating the best methods, without creating too much disruption to your team. 

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As you can see, there is a lot of pressure on CDOs entering today’s market. At Team Mindshift, we help support CDOs as they transform their organizations with coaching and learning programs that can be deployed to improve data fluency and culture. If you are a CDO, we would love to talk to you about what you are facing in your organization and how we can support you. We are also hosting a Monthly CDO roundtable, to help form a peer group that supports you on your journey.

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