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If you ever feel like your teams speak different languages when it comes to data, it is a classic symptom of data silos. The information gets stuck in one department, system or tool, making it difficult for anyone to see the full picture. Siloed data can affect different departments, from the sales team to HR and development.
In this article, we’ll break down why data silos happen, the problems they create and how you can finally tear down the walls to unlock smarter, faster and more connected decision-making.
Companies handle a large volume of data from different sources. If data is not properly managed, it can become isolated within separate systems, creating barriers between teams. These barriers are known as data silos.
When data silos exist, teams cannot easily share important information, which can harm data quality and integrity. Often, data is divided across different systems; structured data may be stored in data warehouses, either on-premises or in the cloud, while unstructured or semi-structured data may be stored in separate data lakes or specialised storage solutions.
This fragmentation makes it harder to get a complete, unified view of the organisation’s data. All these factors make data management complex and prevent organisations from fully leveraging the value of information.
With data silos, teams are unable to work with updated information, which often results in inconsistent and inaccurate data. On top of that, they waste time reconciling discrepancies, which slows down workflow. Other concerns that may arise are:
An isolated data system stores redundant or missing information, leading to inaccurate data reporting. Also, silos lead to inconsistent data analysis, which affects data quality and integrity.
Imagine a situation where a company’s treasury system records payments differently from the ERP integration systems. The finance team may report inaccurate cash flow. These gaps provide inaccurate reports and make it harder to plan and manage capital effectively.
When dealing with siloed data, the chances of having duplicate information are very high. This means the team must take extra steps to deal with it. This whole process of retrieving the lost data and using it again is time-consuming and costly. Instead of using the resources more efficiently, employees are left fixing data problems.
Imagine each department uses its own financial analysis and reporting software. The finance team must spend additional time and make efforts to collect data from multiple systems and fix errors. This duplication not only slows down reporting but also wastes resources that could be used for more important tasks.
With siloed data, each team operates and communicates with its own system. Without shared access, it’s impossible to align goals and respond to market demands or new opportunities. The lack of visibility slows down communication, making it difficult for teams to be informed and connected. By integrating systems, departments will be aligned and financial reporting will be more precise.
The most common reasons silos happen are:
In many companies, teams often work in isolation, creating their own separate systems. This lack of coordination can lead to inefficiencies, as data is not shared between departments. It can result in limited access to information, duplicate data and increased costs.
Additionally, each department may rely on different tools to get work done. Without proper data integration, teams struggle to access the information they need, creating barriers to analysis and slowing down decision-making.
When teams don’t have the right skills or resources, integrating data becomes a challenge. Also, they often create quick, independent solutions just to meet immediate needs. Over time, these disconnected systems become harder to integrate, making it difficult to share information or maintain consistent data quality across the business.
Financial regulations don’t always specify how the data should be stored, so many companies adjust them to comply, accidentally causing data silos. For instance, storing budget and forecast data separately by department or region can break information, making it harder for finance teams to get a complete, consistent view for planning and reporting.
As a company grows, each department often works on its own strategy to meet the goals. Without a centralised data strategy, these independent strategies will store the information separately, causing silos. For example, when a company expands, finance teams work with their own tools. Without creating a unified solution, data ends up fragmented, making it difficult for more accurate forecasting.
Companies can identify data silos in the everyday work environment. There can be concerns such as:
Limited access to platforms.
Spending too much time and effort compiling reports.
Missing or lack of data.
Reports with discrepancies or gaps.
To easily catch these problems, organisations should start examining how data flows across different departments. Also, they should look at how each team handles data, which tools they use and if they struggle to share information.
In finance, data silos often appear when accounts payable, accounts receivable and payroll maintain separate systems that aren’t connected. For instance, if AP data sits in one platform while AR and payroll are tracked elsewhere, it becomes difficult for the finance team to get an accurate picture of cash flow or create unified financial reports. Delays, inconsistencies and duplication are clear signs that silos affect financial planning and reporting.
When a company spots data silos, it can take the next step – finding the best way to break them down. Here are practical tips to do that:
Transforming data operations with modern technology can prevent the creation of new silos by improving integration across systems, streamlining data flow and providing real-time insights.
For example, finance teams often manage data from multiple sources – tools, ERP systems and forecasting software. By moving this information into a cloud data warehouse and data lakehouses, organisations can unify their financial data. This will not only eliminate silos but also allow teams to access accurate finance information for reporting.
Strong data policies define how your data is collected, stored and used across departments. Being compliant with data standards ensures consistency and accountability, which is the foundation for better collaboration. This can help to break down silos and maintain data security and integrity.
In financial planning and reporting, for example, standardised data policies can ensure that budgeting and forecasting follow the same flow across departments. It easily and accurately collects reports for further analysis.
Organisations must provide regular training to educate teams on data accuracy. Implementing clear data protocols will help teams adapt to a culture that encourages collaboration and data sharing.
For example, retail companies often bring together marketing, sales and inventory teams under one data platform. By integrating sales trends, stock levels and customer behaviour, they create a single source of truth that helps optimise promotions, manage supplies effectively and improve overall profit.
Promoting a unified solution across departments simplifies compliance and boosts collaboration and productivity between teams. All data must be shared through a centralised system to ensure consistency, accuracy and accessibility. When data flows seamlessly across platforms, teams can operate as one.
Extract, Transform and Load (ETL) tools help teams to share data. They can improve data by moving it from certain silos into a more centralised location, such as a data warehouse. On-premises ETL tools are hosted from the organisation’s site, while cloud-based ETL tools are offered by the vendor.
Data warehouses are built for quick access and analysis, not for handling daily transactions. This provides a full and clear view of the data.
Once the silos are eliminated, it can positively affect the whole organisation and processes. Breaking down data silos ensures:
Implementing a single source of truth ensures data integrity by allowing teams to have real-time insights into the finances. Instead of working on separate datasets, everyone, including stakeholders, can access the data while reducing errors, avoiding duplicate work and focusing on delivering more accurate reporting.
When all the data is in one place, teams don’t waste time collecting information across multiple platforms. Collaboration becomes easier because everyone is working from the same dataset. This way, decisions can be made faster and projects will run smoothly.
Centralising the data makes it easier to protect sensitive information. IT teams can implement consistent policies and protocols to avoid unusual activity that may increase the risk of breaches. This will ensure compliance with data standards and regulations and build trust with stakeholders.
When teams have access to complete and consistent data, they can better understand customer behaviour. They can respond faster to their demands and deliver solutions more accurately. These improvements increase satisfaction and loyalty in the long run.
Having data silos is a significant challenge for every organisation. It not only affects the work, but also the trust. Getting rid of them requires taking the right steps to improve decision-making and productivity. The most effective approach is to combine data into a single, unified source so everyone has access to the same information. By breaking down these silos, organisations can leverage the full potential of their valuable data.
Request a free demo with Mercur to learn how our platform can help you eliminate data silos and unify your financial data process.

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