The impact of data silos and how to eliminate them: Inisghts from Factor Blue


As companies increasingly rely on technology to automate their processes and streamline their operations, they must be aware of potential threats that may hinder their growth. Among these are data silos, a leading cause of inefficiency and operational bottlenecks. Factor Blue, a technical e-commerce agency based in The Netherlands, helps clients untangle spaghetti-like IT landscapes with multiple systems that don’t communicate well with each other due to data silos. We recently sat down with Jesper van den Bogaard, CEO of Factor Blue, to discuss what data silos are, how to prevent them from forming, and the role of data integration in eradicating them. Here’s what he had to say.
How do you explain data silos to your clients?
“In a nutshell, data silos are isolated data sets stored in separate systems or departments which prevent efficient sharing of information and integration across an organization. I often describe data silos as islands surrounded by water, each holding valuable resources but cut off from one another and the mainland, making collaboration and access difficult. In turn, integrations act as bridges, connecting these islands to the mainland and each other, enabling the flow of information.”
Based on your experience, what is the leading cause of data silos? How are they usually formed?
“Data silos usually pop up when departments operate independently and use their own specialized systems that lack integration with the rest of the organization. This can happen when there’s no unified strategy for how data should flow across the organization or when teams rely on outdated legacy systems. It’s also common when companies grow quickly or go through mergers and acquisitions, and the different systems just don’t mesh. Without a conscious effort to unify systems and encourage teams to share and collaborate, data remains trapped in isolated systems and forming silos that make it harder for everyone to work efficiently and make good decisions.
I also think it’s important to note that the underlying problem is that organizations aren’t aware of the huge impact data silos can have within their organization, so they do not invest enough time and resources in tackling or preventing this issue. Data silos are not simply a technical problem; they are also an organizational one.”
Are data silos only an internal problem, or can they also appear when dealing with external suppliers?
“In e-commerce, external suppliers often contribute to the formation of data silos by using their own separate systems like CRMs, ERPs, or inventory management tools that don’t integrate easily with the organization’s internal systems. These external systems can limit the flow of information by only allowing certain data to be shared within specific processes or workflows rather than providing a holistic view of the entire operation. For example, a supplier’s ERP system may only share order details with the e-commerce platform but not with the marketing or customer service teams, leaving them in the dark and limiting their ability to access up-to-date information. As a result, each department works with partial or outdated data, creating silos that make it harder for teams to collaborate and make informed decisions based on the full picture.”
Are clients aware of their underlying data challenges when reaching out to Factor Blue, or do they often discover new issues during your discussions with them?
“Most of the time, they’re already aware of their data challenges when they reach out to us. They don’t come to Factor Blue unless they seek a solution. However, part of our role is to help raise awareness about the bigger picture. Sometimes, clients will say, "Wait, is this a data silo? Is this what’s causing our issues?"
During meetings, they’ll often describe situations like, “We need to process manufacturing, but the invoice is here, the order data is there, and we’re manually passing information around, with data scattered across different systems.” What they are describing are data silos since the data is fragmented and isolated in various places.
Even though they might not immediately recognize the term "data silo," they can usually pinpoint a connectivity issue. They know something isn't working smoothly, and they’re often frustrated by the lack of integration between systems. The real challenge is that many clients don’t fully realize the risks of having data spread out like this. It can lead to inconsistencies, conflicting information, and ultimately, poor decision-making that can affect the entire business.”
Are data silos more problematic in bigger or smaller companies?
“Data silos can be problematic in both bigger and smaller companies, but they tend to be more challenging in larger organizations since the large number of departments, systems, and data sources increases the risk of fragmentation and makes it harder to integrate everything. This is especially true with fast-growing companies. I have encountered several companies that experienced accelerated growth between 2020 and 2023. As they scaled up, they had to introduce various systems for different departments to keep up with the increased orders, customer data, and growing marketing efforts. For example, marketing teams used one system, while finance adopted another. This approach led to a fragmented setup: systems were loosely connected, but there was no unified view of the entire operation. Instead, the focus was on what each system could do, rather than on how they could work together to provide a cohesive picture.”
How can companies tackle data silos? Is it a once-off thing or an ongoing effort?
“Tackling data silos and preventing their formation starts with people, not technology, and it is an ongoing effort. I think many companies see getting rid of data silos as a one-off project they can check off their to-do list. They identify a silo and think, "Okay, we’ll fix this," and once the project is complete, they assume the problem is solved. But in reality, it's an ongoing process of adaptation and improvement. It's not just about connecting systems to eliminate the silo; it's about continuously adjusting how the organization handles data.
A big part of this is ensuring the right practices are in place so people aren't tempted to bypass the system when they find it inconvenient. Even when there's a clear process for handling data, if employees don’t buy into it, they might create workarounds that end up becoming data silos again. I had a client who experienced this firsthand: they bypassed the system, which led to a significant data issue. So, it’s not just about fixing data silos and implementing technology; it’s about creating a culture and efficient processes that prevent new ones from forming over time.”
If you could give companies one key piece of advice for tackling data silos, what would be the first step they should take?
If I could give companies one piece of advice, it would be to invest in a solid data integration strategy right from the start. Make sure your systems and processes are set up to connect and communicate across departments. This means implementing technologies like APIs, a central data hub, or a middleware solution like an iPaaS to connect systems effectively. However, as I mentioned earlier, building a culture of collaboration and transparency within the organization is just as important.
Additionally, think about who’s in charge of data within your company. Is there a dedicated person or team? If not, consider creating a role like a Head of Data, especially if your organization grows. Having someone responsible for overseeing data can help ensure the strategy is consistent and the company doesn’t fall into the trap of isolated systems again.”
Why is it essential for organizations to break down data silos, and what broader impact can they have on operations, decision-making, and compliance?
“It’s crucial to know where your data is, what you can do with it, and why specific information matters to your organization. Ultimately, it’s about using your data to make strategic decisions and extract valuable insights. Unfortunately, many organizations aren’t fully tapping into this potential. Often, departments are isolated, each focused on their own "island." However, building strong connections between these islands, as we discussed earlier, leads to better collaboration, clearer information, and a more efficient way of working. This helps reduce data silos and ensures smoother operations.
Another key point is that data silos can also cause serious issues with compliance and governance. When your data is scattered and isolated, it becomes much harder to meet legal requirements, especially since these regulations evolve quickly. This makes your organization less flexible and adds extra operational costs as more time is spent verifying and managing the data.”
How can organizations ensure the successful use of data, and what role do adaptability, organizational culture, and AI play in managing data effectively?
“To ensure data is used successfully, organizations need to set things up in a way that encourages everyone to handle it correctly. It’s not just about the tools you use, like data management systems, but also about creating a culture where data is valued, and people work together to keep it accurate and transparent. Adaptability is really important here—not just in the tech but in the way the whole company approaches data. As things change, the way teams handle data should evolve, too.
AI can definitely help with this. It’s not just a buzzword; it can really make a difference in how data is managed by automating many tasks, offering valuable insights, and helping people make better decisions faster. By embracing AI, organizations can improve how they handle data, reduce mistakes, and get even more out of the information they have, ultimately leading to better outcomes.”

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