In today's digital age, organizations of all sizes are overwhelmed with data. Despite this, many companies are still unfamiliar with how to effectively and correctly leverage data to maintain a competitive edge. A recent 2023 survey by Oracle and author Seth Stevens-Davidowitz of Decision Making Dilemmas found that 78% of business leaders are exposed to more data than ever before. I could tell that they were dissatisfied. Even worse, 86% of decision makers say that large amounts of data are making decisions in their personal and professional lives more complex.
To address these issues, organizations must take steps to alleviate ongoing concerns about data management. However, mastering this specialty requires understanding the larger data environment. By taking a closer look at specific data management challenges and developing a proactive strategy, organizations can begin conquering the huge data frontier that will undoubtedly transform modern business.
General Manager of Data & Analytics at Insight Software.
Challenges of effective data management
It's no secret that businesses struggle with data management. This is especially true when data is fragmented by department, making it difficult for users to share and collaborate. Siled data poses significant collaboration challenges, including delayed reporting, limited data visibility, and poor data quality. If an organization cannot collaborate effectively, teams will struggle to respond quickly to leadership needs and custom data queries needed to advance the business in changing conditions. This is evidenced by a recent study that found that more than two-thirds of IT and finance professionals spend an entire day each week on business reports. Inefficient and disjointed reporting from siled data continues, further reinforcing the lack of an open data culture that many companies promote but struggle to operate with.
Too often, organizations continue with old patterns and build data programs that look for business problems instead of asking important questions about what data they need to run their business. As a result, it is difficult for organizations to make informed decisions when they cannot see their data or understand how it is being used in the business environment and the appropriate context. For example, in the Capital One survey “Discovering Data Management Trends”, 76% of business leaders reported that they will find it difficult to understand data in 2022. This finding highlights how many organizations do not have a solid foundation of data infrastructure. .
It's also common for organizations to become complacent with their data management strategies without considering how they need to evolve to accommodate end users with current domain expertise. Additionally, when organizations migrate or change their data management processes, this transition becomes more difficult for those making the changes. Rather, given advances in cloud computing services, data governance, and data fabric products, there are ways to think of production environments less as integration projects and more as delivering the right data tools to end users. The key is how organizations can embrace a democratized open fabric while adopting the right data management strategies to support faster innovation and adoption.
turn obstacles into opportunities
Data issues are not the be-all and end-all for organizations. The reality is that companies can take strategic steps to address ongoing data concerns. In fact, the best way for CFOs and other business leaders to address data management concerns and avoid embarking on long-term transformation projects is to empower non-technical employees to rapidly generate their own analytics. Special focus is on increasing immediate effects. Doing so begins building a context around a self-service data culture and domain-specific data environment, a valuable step in your data-driven journey. It's clear that intuitive, self-service data analysis and reporting capabilities are not just a nice-to-have, they're essential.
Achieving business agility requires IT and other technical staff to spend their time solving complex technology challenges rather than creating and troubleshooting a growing backlog of reporting requests from operations teams. . The first step is to remove one of the manual processes and report builders and enable a subset of current users (spreadsheets, BI tools, and other future deemed analysis programs). For example, this allows operations teams to spend less time collecting and processing data and more time analyzing it. Additionally, following this process reduces dependence on key individuals as the right software increases the rigor of the process and makes it easier to hire new, less experienced staff.
By taking a step back and understanding where companies are today and what problems they need to solve based on their data, organizations can make the most of valuable data insights. Determine exactly what tools and resources you need. The next step is for organizations to harness the power of context, automation, and intelligence.
The power of context, automation, and intelligence when developing strategic strategies
At the end of the day, the key to implementing an effective data strategy starts with context: how to best leverage specific data to run your business. Identifying ways to bring disparate teams together for rapid success to focus on cross-functional data collaboration and sharing will build confidence and her FOMO. From this point on, leaders can employ a variety of automation techniques to quickly eliminate data gaps, handoffs, and manual processes that simply waste time and introduce bias.
Benefits of successful automation and data management include improved data quality, increased efficiency, fewer errors, increased compliance, improved decision-making, and lower costs. Moreover, sound practices enable the foundation for innovations such as leveraging his AI and machine learning when needed. Whether your organization needs to go to market faster, streamline operational procedures, or create a clear view of your enterprise data, automation, and data management solutions, your team needs the most You will be able to better handle one of your critical underserved assets: the data and employee domain. Knowledge helps organizations become more agile and predictable, ultimately reducing unnecessary operational overhead.
Today, businesses are drowning in data, but the majority don't fully understand the huge benefits that data can bring if leveraged correctly. More importantly, effective data management is not only core to operations; Organizations can often see a return on investment if they take data seriously. However, significant obstacles still need to be overcome before companies can begin to reap meaningful benefits from their investments in big data and intelligence. By addressing the specific challenges of implementing effective data management and taking proactive steps to address them, organizations can ensure a solid foundation for large-scale data initiatives and stay ahead of the competition. You can differentiate yourself from other companies.
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