There is a lot of discussion in the business world these days about data maturity.
Companies that don’t utilize data lean heavily on intuition and industry experience when making business decisions.
In contrast, a data-driven company will use market insights, trends, and patterns found through analyzing data in their decision-making process.
As a result, they often experience several benefits, including:
- Increased efficiency
- Better products and services
- Faster speed to market
- Improved identification of opportunities and risks
[How does your organization stack up? >> Take the Data Maturity Assessment]
However, there are still a lot of questions around data maturity, including:
- Why is data maturity necessary?
- How can you achieve it?
- What are common pitfalls?
Unfortunately, there is a lot of misinformation out there about data maturity. This article will focus on the five common misconceptions about data maturity.
1. Achieving data maturity is a linear process.
The biggest misconception about data maturity is that it’s a linear process that starts with collecting data and ends with using it to make decisions.
In reality, achieving data maturity is more like a journey than a destination. There will be ups and downs along the way, and you may find yourself revisiting earlier steps as you learn and grow.
Achieving data maturity is an ongoing process, not a one-time event. As your organization grows and evolves, so will your data needs. It’s crucial to continuously monitor your data to ensure that it remains accurate and actionable, and make adjustments to your governance processes as necessary. Otherwise, you’ll quickly find yourself back at square one.
2. Only large companies or IT departments can achieve data maturity.
It’s also a common misconception that only large companies can achieve data maturity. This simply isn’t true.
There is an ability and a need for all companies to improve their data maturity.
According to a recent KPMG survey, “only 29 percent of [companies] have adopted a comprehensive data strategy at scale, even though more than 70 percent of [companies] believe it is likely that effective and widespread data usage will radically change the business model.”
Data maturity is something that any organization can strive for, regardless of size or industry.
While IT departments play a critical role in achieving data maturity, they cannot do it alone. Business leaders must be involved in setting the goals for data maturity and ensuring that everyone in the organization understands the importance of adhering to strict data governance standards.
Only by working together can organizations hope to achieve true data maturity and move up in the continuum.
3. Data maturity is expensive and time-consuming to achieve.
This one depends on how you look at it.
Yes, achieving data maturity requires investments of both time and money upfront. However, these investments will pay off in the long run by helping you avoid costly mistakes and missed opportunities. In other words, achieving data maturity may require some short-term pain but it will result in long-term gains for your organization.
4. You need perfect data to achieve data maturity.
This misconception probably arises from the fact that quality data is important for achieving data maturity. However, perfection is not required.
In fact, striving for perfection can actually impede your progress towards data maturity. The key is to focus on continuous improvement rather than perfection.
Data maturity and data quality are two completely different concepts.
Data quality refers to the accuracy, completeness, timeliness, and consistency of your data. Data maturity, on the other hand, refers to how well-organized and structured your data is. A dataset can be of high quality but low maturity (i.e., poorly organized and structured) or vice versa (i.e., well-organized and structured but with low quality data).
5. Once you achieve data maturity, you’re done forever.
Finally, some people mistakenly believe that once you reach a certain level of data maturity, you’re done forever and don’t need to do any more work in this area. This couldn’t be further from the truth!
Data maturity is an ongoing journey, not a destination. As your business changes and grows, so will your needs in data management and decision-making.
Piling up more and more data isn’t the answer either. While it’s true that more data can help you make better decisions, it’s not the only factor that contributes to data maturity. Oftentimes, access to more data can also bring more access to other issues.
Additionally, other factors such as the quality of your data and how well it’s organized are also important for data-mature organizations.
Data maturity is an important concept for businesses to understand and strive for—but there are many misconceptions about what it really entails.
In this article, we’ve debunked some of the most common myths about data maturity. If you want to know more about improving data-related decisions for your business, check out our course and begin to translate data insights into business strategy.
Leverage Data for Business Decisions
Data Science for Business Leaders is designed for business leaders to partner with data professionals, learn what problems to solve with data, and how to leverage the findings to make better decisions.
- Focus on data projects that drive business impact
- Gain better outcomes through stronger partnerships
- Identify the fastest path to actionable insights
- Champion data-driven decision making