How to Fix Data Silos & Unlock Your Data’s Full Value

When you’re trying to build a growth strategy for your business, you need reliable and consistent answers to routine questions. But sometimes, finding that information feels like a trip to the DMV: the answer you get depends on the person you talk to.

So why is it that this type of situation occurs across most companies? The most common reason is the result of data silos.

Data silos present a major problem for modern businesses. When different departments within an organization each have a unique process for collecting data, building a cohesive strategy for growth becomes nearly impossible.

Fortunately, there are ways to identify and fix data silos before they waste any more of your company’s resources.

In this article, we’re going to take a deep dive into:

• What data silos are

• What causes data silos

• Common warning signs of data silos in your organization

• How to fix data silos

Let’s start by becoming crystal clear on what data silos are and why they’re such a problem.

What are data silos?

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Data silos occur when one department either collects or has access to data that isn’t available to other departments.

Data silos are a nearly ubiquitous problem in mid-sized to large organizations. Dun & Bradstreet/Forrester Consulting released a report that found the biggest obstacle for organizations reaching their marketing and sales initiatives comes down to “managing data and sharing insights that drive actions across organizational silos.”

It’s easy to see how these information silos can form. For example, imagine your marketing team keeps a contact list with an email service provider (ESP), like Mailchimp. And your sales team uses a customer relationship management system (CRM), like Salesforce, to track and follow up with warm leads.

Over time, the two lists will grow increasingly different. Some leads will unsubscribe from the weekly marketing newsletters but remain in the sales department’s CRM. Other customers will likely churn out of the CRM and get annoyed when they see a new marketing email from your company appear in their inbox. In the end, everything could have been avoided if those lists had been working together rather than being treated as unique data sets.

What is the data silo problem?

Here are just a few of the problems that data silos can lead to:

• Employees are unable to access the data they need. Employees wasting time chasing down information—or worse, not even knowing it exists—will hurt efficiency across the board.

• Departments have fundamental misunderstandings that stunt growth. When data is incomplete or inconsistent across teams, you’ll have internal strategies that aren’t supporting one another.

• Money gets wasted. When departments don’t share data, they can waste money looking for answers the company has. Or worse, they can end up working at cross-purposes, at a major cost to time and money.

• Privacy and compliance concerns. Maintaining compliance with data privacy regulations requires companies to have a clear picture of what data they have and how it’s collected. But data silos increase the likelihood that sensitive data is being mishandled.

What are the causes of data silos?

The first step to finding and fixing data silos in your businesses is understanding what causes them. Here are the main reasons why data silos occur:

Lack of centralized IT infrastructure

Data silos can occur when each department in your organization uses different software to collect or store their own data rather than having a centralized system (such as a data lake or a data warehouse). This problem often arises when companies adopt new technologies.

In many cases, each department will form a unique committee when thinking about getting a new tool or software. These committees are full of stakeholders who tend to focus on how a new tool functions, but they forget about how well it integrates with the global company’s tools and apps.

Companies need to consider how well a new tool integrates into their overall tech stack to provide a unified view. Source.

Over time, each department develops its own fragmented data.

Siloed organizational structure

Your business might not be set up to encourage cross-department communication—or at least not as well as it could be. This is especially true as many companies have adopted a fully remote working environment.

It’s easy to see how a company of 10 employees would have an easier time sharing data than a company with 500 employees. The larger your organization becomes, the more difficult it can be to have a coherent and efficient system for internal communication.

In other cases, you might find departments intentionally hoarding relevant data to boost their own performance. This is known as “silo mentality” and might be a signal that it’s time for a culture shift in your organization.

In a moment, we’re going to talk about how to fix data silos once you find them in your organization. Before that, though, let’s look at a few of the most common warning signs that these silos exist in the first place.

Common warning signs of data silos in your organization

Finding data silos doesn’t have to be difficult. You just need to know what you’re looking for. Here are the top three warning signs for spotting a data silo in your organization:

• Team members repeat the same question, indicating they don’t have access to the data they need.

• Departments blame other teams when problems arise, indicating they may be working from different data sets, leading them to different conclusions and strategies.

• You do not see any ROI from your data collection tools, indicating you haven’t implemented a truly data-based strategy yet.

How to fix data silos

In order to fix data silos, you’ll need to invest in data governance. This traditionally boils down to three steps.

Centralize your data with a CDP

The first thing you should do is invest in a proper customer data platform (CDP) to make data integration (and data sharing) easy. A reliable CDP will help you with “data orchestration,” the process through which you take siloed data from multiple locations and combine them. Then you—or your CDP—will organize that information, remove duplicate data, and make everything available for data analysis tools.

The right CDP helps you create a more granular customer view. Source.

For example, Landbot turned to Segment in March 2021 to build a more reliable and efficient tech stack. As a result, they saved over 2,000+ hours per year of engineering time and increased accessibility to customer data by 80%. With a more organized system in place, their marketing team was able to integrate 12 new tools in just six months.

Not only do these tools give you global insight into your marketing/sales initiatives, but they also allow you to create a singular customer view.

Standardize data collection across all departments

Next, you need to standardize the way you collect data across all of your departments. This goes beyond figuring out what individual metrics are collected and taking a closer look at how that data is recorded.

Without standardized data policies, something as simple as collecting dates or times can quickly get complicated. One department might record the date as “June 1, 2022,” while another writes it as “06/01/22.” Or if parts of your team enter the time using AM or PM (2:00 PM, for example), and others use the traditional 24-hour clock (14:00).

When that data flows to your centralized repository, it will be understood as distinct sets of information in the tools that process it. That means you won’t be able to keep a coherent system for data collection, and the same metric will continue to be viewed through two distinct lenses.

In the end, this leads to even more inefficiencies that negatively impact your bottom line.

Incorporate more internal communication in your data governance policy

Again, in some cases, your data silo might be the result of your company culture. And a culture shift might be exactly what you need to break down data silos. Departments should be encouraged to learn from one another’s data on an ongoing basis, instead of teams like product and marketing only meeting when it’s time for a launch.

This kind of collaboration might have been easy when your business consisted of seven employees in a co-working space. But since you’ve grown, you’ll need a clear data governance policy in place to guide your organization’s internal communication.

This includes mapping out your data collection ecosystem, having each department identify relevant data they need, and creating a small reference guide to what, why, and how specific metrics get tracked.