Data silos: Understanding what they are and how to fix them

Data is one of your organization’s most valuable assets. But this value depends entirely on how reliable, accessible, and connected it is. If you can’t achieve a unified view of all of your information, you’ll never be able to make business decisions that consider the big picture. 

Here’s the problem: Businesses have more teams and depend on more platforms than ever before. This can lead to an issue where data becomes isolated from other systems, trapped in data silos that only one team or department can access. 

This guide will explain what data silos are, why they’re a problem, and, most importantly, how you can break them down to improve collaboration and make smart decisions. 

What is a data silo? 

A data silo is an isolated repository of data, usually held by one department or team, that’s disconnected or ‘walled off’ from the rest of an organization. 

Just like grain silos on a farm are sealed off from the outside environment, data silos keep critical business data trapped in separate systems. For instance, silos often develop when data is controlled by a single department, maintained on a standalone solution like a CRM, or stored in a format that isn’t accessible to other teams.

When data is siloed, it impedes an organization’s ability to manage and share information as well as ensure its quality. Plus, if valuable info is scattered in different places, a company’s leadership may struggle to see the whole picture, and that can negatively impact their decision-making. 

The key characteristics of data silos 

There are four key elements that define a data silo: 

• ‍Isolation: Siloed data usually lives on separate systems (like spreadsheets, CRM solutions, and point-of-sale systems) that are disconnected from the rest of the business. 
• Incompatibility: These systems and solutions typically don’t play nicely together, making it hard for businesses to unify their data and collaborate across departments. 
• Limited access: To make matters worse, many siloed systems are only accessible by one team or individual, restricting visibility for others. 
• Inconsistencies: Data silos also regularly lead to inconsistencies and to duplicated data that may vary wildly in quality between systems and departments. 

The ability to make data-driven decisions today depends on data sharing and unity across departments, which can provide a full view of all the information you possess. Silos won’t just slow you down; they’ll actively make it harder to stay agile, stay compliant, and make decisions that drive growth for your organization. 

Data silos vs data warehouses

Think of data silos and data warehouses as the opposite ends of the data management spectrum. 

Data warehouses are centralized systems that unify data from multiple sources. It’s like putting all of your information in one big storage room that each team can access and utilize when they need it (as long as they have the right access permissions). On the flipside, data silos are isolated data repositories sealed off from the rest of an organization.

Ultimately, data silos and data warehouses are both completely different and completely interlinked. Silos create barriers to effective business communication and decision-making; warehouses break down those barriers and work to eliminate information isolation. 

How do data silos form? 

Data silos form when information becomes trapped in business units, effectively walling the information off from the rest of the organization. Here are some of the different factors that can create this problem:

• ‍Your organization’s structure: Different teams use different processes, rely on different systems, and have different goals. This can lead departments to work in isolation rather than collaboratively, creating fragmented silos of information. 

• Your company culture: If your departments and teams work separately and view data as a team asset instead of an enterprise resource, it can compound the above problem and lead to missed opportunities for cross-collaboration. 

• The technology you use: A sales team will likely rely on a CRM, while a finance team will use accounting software. These tools seldom integrate, which can make it easy for valuable information to remain locked away within platforms. 

• Mergers and acquisitions: When companies merge, they often bring separate systems, ideas, data structures, and processes along with them. That can increase the potential for critical information to end up in silos if a concrete data management plan isn’t in place. 

• Available resources: A limited budget for software can lead teams to adopt one-off solutions like personal spreadsheets over organization-wide platforms, further fragmenting data.

• Regulatory requirements: Security and privacy legislation can lead teams to isolate data to maintain compliance. While these controls are absolutely essential, they can increase the potential for data silos, especially if regulations differ between departments. 

The problem with data silos

Data silos are a detriment to everything from day-to-day workflows to long-term enterprise planning. To see how that can play out in the real world, let’s compare two organizations: one that doesn’t have data silos and one that does.

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How to spot a data silo 

Siloed data is incredibly common. It’s also hard to avoid, especially if you haven’t gone through the process of identifying data silos and breaking down the barriers yet. 

The first step to fixing the issue is knowing how to identify it. Here are some questions to ask yourself to decide whether data silos are posing a problem for your business. 

Do your technologies speak the same language?

Do you have a CRM, an email tool, and a billing platform? Are these disparate systems storing different versions of customer data? This often leads to each team running from a different playbook, creating unintended silos.

Are your teams on the same page? 

Do you find that your teams are constantly requesting information that already exists elsewhere? If the sales team is regularly asking the marketing team for their data and vice versa, there’s a good chance that insights aren’t easily accessible between departments either.

Are you compiling your reports by hand?

If you need to dig through databases and duplicate data to find the right information for your reports, this is a sign that your data isn’t unified. Aside from costing you time, this can also make your insights less accurate.

Are conflicting metrics impacting decision-making? 

If you were to ask each of your teams a question like, “How many leads did our last campaign generate?” and each department gives a different answer, it’s a telltale sign that disconnected systems are creating data silos. 

Do you have the full picture of your customer journey? 

One of the many benefits of unified data is that you can see your entire customer journey at a glance. If your customer information is fragmented in silos, no one can see the full picture. This can lead to missed opportunities for personalization. 

Is decision-making being hindered by missing data? 

If you find that you’re regularly waiting for teams to verify reports that don’t line up or you’re pulling up numbers from the depths of your point-of-sale solution, data silos are the likely culprit. 

So, what’s the solution? 

Data silos occur for countless reasons, especially if you have a broad organizational structure. But the good news is they don’t have to be permanent fixtures. 

Knowing how to identify the problem is the best place to start. If you’ve discovered an issue through your answers to the questions above, you’re already on the right path to fixing the problem. The next step is to put a strategy in place to break down the barriers. In the process, you’ll improve collaboration across your entire business and unlock the full value of your data. 

How to break down data silos

Here’s the step-by-step process we recommend to eliminate data silos within your business.‍

1. Assess your data

You can’t break down silos if you don’t know where those silos exist. The first step is to identify the systems and repositories that store data within your organization, such as:

• Customer relationship management (CRM) systems
• Project management tools
• Marketing automation utilities
• Accounting software
• Enterprise resource planning (ERP) platforms
• Data warehouses and lakes
• Email platforms
• Databases and spreadsheets

Once you’ve pinpointed all of the areas holding critical data, look at data flow to determine how all of your information moves between your systems. 

This will let you spot bottlenecks, such as your sales team needing to manually email CRM data to your finance team each week. You can also find areas where systems work in total isolation. 

This process will help you work out your priorities when it comes to the next step. ‍

2. Centralize your data

With a grasp of the problem, you can begin centralizing your data into a single source of truth. 

One effective way to achieve this is to unify your data into a ‘central hub’ like a data warehouse or data lake. Tools like ETL (extract, transform, load) pipelines can help you pull data from different systems, standardize it, and then load it into your centralized repository. APIs can also connect your platforms with minimal manual effort. 

Another solution is to opt for a cloud-based data governance platform that can unify your data across all systems to give you granular visibility over all of the information you possess. RecordPoint, for instance, can identify, aggregate, and classify your structured and unstructured data from almost any source by connecting to over 1,000 systems and applications, bringing it all together in a centralized platform, without you having to move a thing from its original location. 

3. Implement a data governance strategy

Making sure your data is centralized is a start, but it won’t fully fix the problem if your data isn’t managed well. It’s important to create a robust data governance framework that will determine how your data is managed, categorized, stored, shared, and secured. Here are some points to consider: 

• Assign data stewards: Appoint a dedicated committee of stewards who will oversee data quality, enforce policies, and make sure you’re compliant with legislation. Secure organization-wide buy-in by assigning representatives across every department.  

• Data governance policies: Create clear policies surrounding data ownership, access rights, quality standards, security, and sharing. These policies should be consistent and easy to understand to reduce confusion and keep data standardized. 

• Train your teams: Educate your team on your policies with ongoing training sessions and workshops. Aside from informing everyone on best practices, this can also help improve data literacy and strengthen a sharing culture over time. 

Remember to treat your data governance strategy as a living framework. Regularly audit your own data best practices and evolve your approach as you scale. 

4. Choose the right tech stack

Legacy applications and systems are so often the enemy of total data unity because they rarely play nicely with other solutions. Modernizing your tech stack will help you find solutions that integrate with your centralized data platform. 

For instance, transitioning away from an on-premises system to a cloud-based CRM can allow for easier data syncing and sharing across your entire organization. You should also look for tools with native integrations and APIs so that data can flow freely to your centralized repository. 

5. Build a culture of collaboration

Breaking down silos is as much about people as it is about tech. Develop a culture of open data sharing across departments, encouraging teams to consider data as a shared asset rather than the property of a single department. 

It’s important to be consistent and secure buy-in from everyone, from leadership teams to frontline employees, by clearly communicating the benefits of data sharing. This will help your workers understand the need for the shift. You can also align your KPIs around broader business outcomes rather than tying them to specific performance metrics to encourage company-wide collaboration. 

Lastly, remember that a culture shift doesn’t happen overnight, so be consistent and reinforce your message through regular communication. 

Benefits of breaking down data silos

Let’s round things off with some of the benefits you’ll achieve when you implement our guide and work toward breaking down your data silos:

• Efficiency: When your data is unified, your teams don’t have to spend so much time hunting around for the right piece of information, so they can invest their time working on core tasks.
• Agility: Having granular data visibility makes it easier to pivot when new information comes in, improving your agility in response to trends. 
• Quality: A standardized, centralized database reduces inconsistent data and makes your insights more trustworthy and reliable. 
• Decision-making: When you have the full picture of all of your data, confident decision-making becomes easier and faster. 
• Collaboration: Data that flows freely is data that your teams can easily share with one another, and that encourages communication and collaboration. 
• Scalability: Connected data is the foundation of everything from automation to AI, giving you the tools to get the most out of new technology and scale efficiently. 

How RecordPoint can help

Doing away with data silos is one of the smartest moves you can make for your business, but that doesn’t mean it’s easy. 

Part of the problem is that many organizations struggle to gain full visibility over where all of their information lies, so they subsequently find it difficult to unify it in one place. Fortunately, that’s one of the many ways RecordPoint can help. 

RecordPoint will unify all of your data in one place, classifying it automatically, no matter where it resides, giving you complete visibility over all of the information you possess.

From there, our solution will give you every tool you need to govern your data throughout its lifecycle and maintain compliance while opening the door to the many benefits total data visibility delivers. Explore the platform today to see how we can break down barriers in your organization. 

FAQs

Can data silos ever be a good thing? 

In general, no. Silos can sometimes be useful to help a department move faster, rather than waiting on shared processes. However, when all of your data is unified, standardized, and easily accessible, you see long-term benefits rather than short-term ones. The costs of data silos typically outweigh any benefits of speeding up certain processes within your organization. 

What’s the difference between a data warehouse and a data lake? 

The main difference is that a data lake stores both structured and unstructured data, whereas a data warehouse only stores highly structured data. Both approaches have merits when you’re breaking down silos. A data lake is good for storing your data ready for future processing and analysis, but a data warehouse is the best choice for making structured data accessible for business intelligence. 

What can leaders do to help break down silos? 

Leadership sets the tone for company culture. They have a responsibility to encourage buy-in from the rest of the organization, support collaboration, clearly explain the benefits of data sharing, and make sure data governance is a top priority.