Data silos were the top concern amongst businesses in 2024, according to fresh research by data education firm Dataversity.
The annual study found that 68% of those in data-centric positions named silos as the number one challenge facing their organisation. This figure was up 7% against the previous year and outranked other high-priority concerns such data quality and a lack of data governance within firms.
Dataversity suggested increasing regulatory pressures and the race to adopt AI technology was likely why the issue was front-of-mind amongst data professionals. But what are data silos and why are they such a concern for businesses?
What are data silos and why do they occur?
Data silos are stores of data that operate in isolation from one another. When this occurs within a business, vital information becomes trapped – much like grain in a farm’s silo.
Often, these silos resemble a company’s organisational structure, with each silos separated by different departments, teams or business units. This happens because different teams may collect, manage and store their data in different ways, resulting in systems that either aren’t compatible with one another or are simply inaccessible to anyone outside that team.
This disconnect then makes finding and sharing data harder within a firm. This is particularly true in larger organisations where departments tend to operate more independently from one another or have their own priorities and budgets. Business growth, acquisitions and mergers can further entrench silos, especially if there isn’t an effort to align and properly scale internal data processes.
What challenges do data silos cause?
Silos prevent organisations from getting a full view of their data. These gaps in visibility can then impact decision-making, reduce efficiency amongst staff and lead to costly errors. This is because silos make it harder to maintain data quality.
Teams operating in silos will often struggle with duplicate, inconsistent or missing data and, as a result, the insights that can be gained from this data will be limited. This is because inconsistencies and gaps then create issues with data accuracy and integrity within businesses.
According to research and consulting firm Gartner, poor data quality costs organization an average of $12.9 million (around £9.9 million) every single year. MIT Sloan Management Review, meanwhile, put the price of bad data at around 20% of a company’s revenue. And that’s just the immediate financial impact. Poor-quality data can also damage customer relationships and can put a company’s reputation at risk – this is particularly true in financial services where even the smallest of errors can have huge impacts.
How to break down data silos
By removing silos, firms can get a full and accurate view of their data. This, in turn, helps an organisation uncover better insights from their data and make more informed decisions. But, before you can begin transforming your firm’s data ecosystem, you must first get a better understanding of how your data ecosystem is currently working.
The first step towards this is to perform a data audit across all teams, departments and business units. You can do this by tracking and documenting your data sources to gain a clear understanding of your data management structure. From there, check if your data adheres to regulations and internal guidelines, and assess whether it’s complete and consistent.
Once you understand where your company is at, the next step is to consider where you would like your firm to go. By developing a clear strategy around your data and aligning this with your wider business objectives, you can ensure that your firm gets the most out of its efforts and puts in the appropriate amount of time and resources.
Next, it’s time to assess the gap between where your company currently is with its data management capabilities and where it would like to be.
Consider whether more robust internal processes and stricter data governance policies are needed to help ensure your data remains accurate, consistent and trustworthy. Think about the technology your firm is using and consider whether it is aiding in improving accessibility and consistency within your business. Look at all the ways your firm might work to bridge that gap.
How do you stop silos returning?
Fixing data silos within an organisation is not an easy task, but stopping them cropping back up can be even harder. This is because to stop data silos occurring once and for all, there needs to be a meaningful shift in a company’s attitude towards data.
A business may invest in the right technology and set up flawless data governance policies but, without a strong data culture, silos are likely to return over time.
A true data culture is one where all employees – from executives to frontline workers – view data as a valuable asset and understand how to interpret, analyse, and leverage it effectively. It is one that promotes transparency by making data accessible and encourages collaboration across departments to uncover insights and overcome challenges. By maintaining a robust data culture, organisations can better drive innovation, boost efficiency and make more informed decisions, providing long-term benefits that help them stay competitive and agile in an ever-changing world.
