The process of collecting, analyzing, and managing data is vital to the success of any modern business. Those who use Data Intelligence—the easy access of high-quality data across an organization—to connect and power their business don’t just elevate themselves in an era of digital transformation, but also create a notable, competitive edge over organizations that do not.
This Data Intelligence task, however, is easier said than done. The challenges facing businesses are as diverse as they are numerous, especially when it comes to harnessing a culture of data within an enterprise on its first attempt at Data Intelligence.
To overcome these hurdles, businesses must first understand what obstacles they face and harness the full power of their existing data–this is usually the biggest challenge standing in the way of extracting real value from data. Once a clear understanding of these obstacles is achieved, new processes can be instituted to streamline Data Intelligence and benefit the business in many valuable ways. This includes unifying and ensuring the trustworthiness of both existing and incoming data.
Neither identifying the barriers nor overcoming them has to be a difficult process, especially with professional guidance and a focused commitment to refining the processes. Many organizations are already leveraging their data successfully and reaping tremendous rewards as a result.
The importance of Data Intelligence
While there is no question that data is integral to organizational success in a modern, data-driven world, the exact importance of Data Intelligence remains a murky concept for some. Everyone knows it is important, but not everyone knows why–especially not to the degree necessary to implement effective processes that connect and power business.
The operational and financial impact of leveraging data to your advantage—rather than allowing it to overwhelm your organization—are profound. Best-in-Class organizations, defined as being the top 20% of companies surveyed by Aberdeen, exhibit higher levels of customer satisfaction, operating profit, workforce productivity, and more than other companies. These clear indicators of success share a strong correlation with superior approaches to Data Intelligence, giving organizations that prioritize effective data use and implement streamlined processes the upper hand.
The continuous flow of high-quality data that these Best-in-Class organizations stress enables them to make better decisions and find and maintain success.By dedicating their resources and time to not only resolving data management issues, but ensuring they have the structure in place to eliminate them going forward, these organizations exceed their operational and financial goals.
Better still, this outcome is within the reach of any business with a focused approach to Data Intelligence .
Data struggles
Achieving the level of success enjoyed by Best-in-Class organizations does not occur by chance. There are many data-related barriers to circumnavigate and overcome on a consistent basis, and the majority of these struggles are shared by organizations across industries. The tide of data is constantly rising, and the continual accumulation of data creates its own challenges. In fact, about 20% of companies identify this as a leading challenge they face—data simply grows too quickly to be properly analyzed and managed.
The never-ending increase is not the only data maintenance issue organizations face. Data silos compound the problem by isolating data in locations and manners that make them inaccessible and information poor. Nearly 26% of organizations find their data to be too difficult to access—a problem that bleeds into other data management dilemmas. A whopping 41% of organizations report poor-quality data as a point of concern, noting that this subpar data informs decisions and leads to negative outcomes. The lack of trust in data that this particular problem generates is a significant side effect of this obvious problem, acting as an excellent example of how data management issues can snowball.
With data struggles so common among organizations, two prominent questions arise—what is the solution and what are the successful organizations doing differently?
Prioritizing Data Intelligence
One of the best ways to modify your approach to Data Intelligence is to evaluate what successful businesses are doing differently and model your processes after them. While every business is different, this method of imitation and adaptation will give you a strong starting point for determining where your approach has fallen short and how it can be improved. After all, those businesses are successful for a reason.
As you look to the standard-bearers of Data Intelligence, identifying what they have in common will give you an even clearer picture of what works. Luckily, much of the research has been done for you, giving you the shortcut to the success your organization needs.
Based on the survey data from Aberdeen, Data Intelligence prioritization accompanied by automation technologies is the primary determining factor that elevates Best-in-Class organizations. Tools that facilitate data automation and unification are invaluable, especially when integrated into each step of your data processing. From acquisition and preparation to cataloging and governance, ensuring that data is accessible and accurate helps reinstate trust in the quality of data. In turn, this enables informed decisions to be made decisively and quickly, benefitting your business in profound ways.
It is important to realize that, even if you put your organization on the right Data Intelligence course, transformation does not happen overnight. Instead, you must embrace a long-term strategy for revolutionizing your approach to Data Intelligence. This means addressing one issue at a time in a continual approach to development and innovation.
Where to start
Data governance
With so many aspects of Data Intelligence pulling your organization in different directions, it can be difficult to determine what to focus on to begin your digital transformation. Again, examining what the Best-in-Class companies are prioritizing can be a useful exercise in planning your own route. A significantly greater portion of Best-in-Class companies focus on improving their data governance, indicating that this particular area of Data Intelligence is vital to success. In fact, 50% of the Best-in-Class organizations prioritize data governance compared to only 35% of All Others. This gap in perceived importance and focus is telling.
These organizations start with data governance because it is essential in the process of unifying data as it is collected, stored, managed, and used. This prevents data from being unstructured and allows the organization to continuously improve other aspects of its Data Intelligence approach. It is the key not only to keeping pace with the massive influx of data, but also to ensuring that data is organized, accessible, and usable.
Data quality
Proper data governance facilitates another priority of Best-in-Class organizations—data quality. Poor-quality data muddies information and makes decision-making difficult. It can lead to misconstrued and downright wrong impressions of perceptions of the enterprise. This is a massive problem.
By stressing the quality of data and the availability of that trustworthy data to everyone across the organization, you can create an environment that fosters confident, informed decision-making. About 54% of Best-in-Class companies report that data quality is a focal point, while only 36% of All Others echo this sentiment.
A shocking percentage of organizations face data access and data quality issues, setting them up to fail before they even start. With the stream of data only increasing, having these weaknesses in your Data Intelligence approach is bound to lead to shortcomings and prevent your company from running efficiently.
This is why data unification and quality control are so essential in the age of modern business. They influence everything from trust in data to confident decision-making, thereby disrupting business operations and wreaking havoc on success. In other words, these issues must be resolved by implementing processes that facilitate effective Data Intelligence.
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Organizations that are streamlined in their Data Intelligence approach tend to focus on automation, data governance, and data quality. As a result, they enjoy tremendous benefits and success. For those striving to join the elite businesses in leveraging Data Intelligence to their benefit, there is much to be learned through observation and using the right tools.
