Go to app
GuidesCustomer research

What are data silos, and why are they a problem?

Last updated

23 May 2023

Author

Dovetail Editorial Team

Reviewed by

Hugh Good

Working in a large organization with over 100+ employees? Discover how Dovetail can scale your ability to keep the customer at the center of every decision. Contact sales.

Scattered, muddled, divergent…disappointing. Do these terms describe your organization's data? If it's sitting in silos, the answer is probably "Yes," at least to some extent.

Intentional or not, having data silos is a costly problem in this day and age. When decision-makers can't tap into crucial customer insights because they're hidden deep within silos, they miss out on opportunities to strategize, improve, optimize, and ultimately compete.

But what exactly are data silos? Why are they a problem, and how can you dismantle them? Read on to get comprehensive answers to these and more silos-related questions.

What are data silos?

Data silos are collections of data that only one group or department within an organization can access. This data remains isolated from everyone else in the organization, sometimes for months or even years.

In fact, many organizations today have embraced data silos as a "natural" part of their operations. That explains it's easy to find a sales team with sole access to the sales prospect database. Not even marketing or accounts receiving are privy to that database, yet they would benefit if allowed unobstructed access.

How do you identify a data silo?

Before knocking down data silos, you must first determine the cause. Below are some tell-tale signs that your company is dealing with a data silo problem:

  • You can't get a big-picture view of your business

  • Some teams can't access or find important data

  • End-users are coming across incomplete or out-of-date data

  • Departments are transmitting conflicting data

  • Some teams are squabbling and hoarding data

  • Errors in data are going uncorrected

  • Some teams are complaining about not having sufficient data for certain initiatives

Some of these signs might look rather familiar; others might be completely new to you. Either way, be sure to get a full report from your IT or data science team to learn how often these issues occur. 

How do data silos occur?

In some situations, a data silo may be entirely intentional. Some forms of data may only be reserved for a few individuals or teams due to the sensitivity of the data or how it's meant to be used. 

Often, data silos crop up naturally as organizations grow, and factors such as technology, company culture, and organizational processes inhibit information flow. Furthermore, management may—intentionally or not—foster a competitive environment among departments, which can result in duplicative efforts and insulation of data and information sharing.

There are three common causes of data and information silos within an organization:

Too much software

CRM, email, finance, support software, and email are all designed to help you market, sell, support, and operate better. However, many of these tools don't directly integrate with one another. And when they fail to "talk to each other," silos inevitably crop up.

Rapid growth

While growing fast is undoubtedly good for any organization, infrastructure and processes may sometimes fail to scale with the necessary speed. 

On top of that, individual departments may implement processes and applications in an ad hoc fashion. This yields data assets usable only by the teams that produced them, as well as a backlog of cleanup and integration work for data managers and IT.

Company culture

Remember at school when you'd put your arm around your work so no one could have a peek? Some companies inadvertently encourage this behavior at work. Their culture allows teams to operate as distinct entities with unique processes and lingo.

The downside of such a system is that teams may start viewing each other as competitors, causing them to keep their data out of everyone else's reach. When each department hoards data and refuses to share it outside of its own ecosystem (or indeed, where it's technically difficult for them to do so), it can quickly lead to silos. 

Why are data silos problematic?

We've established the causes, so now let's dive into why data silos can ultimately harm your business.

Data silos limit the view of data

Data silos make it impossible to gain a 360-degree view of your organization. Without a complete understanding of business processes and performance, employees have limited insights and can't identify opportunities to improve the business.

Data silos threaten data integrity

When you have information stored in several locations, you won't know the 'correct' version. Even worse, you may not know who made changes or whether they had the authority to do so.

Data silos waste resources

If multiple departments all collect and store the same data, you're spending more money on storage than necessary. Also, duplicate data sabotage productivity since employees spend time managing and curating duplicate sets of information than they otherwise would do to get work done.

Data silos discourage collaborative work

When data is siloed, it becomes difficult or impossible to share. As a result, the collaboration between departments and teams may suffer as individuals have less in common to unite them as they are working from disparate data.

Data silos discourage data democratization

When data remains trapped within departments, it prevents other groups or departments from evaluating or asking questions about the data. This hinders discoveries and preparing data ready for enterprise decision-making.

Solutions for getting rid of data silos

You already know how detrimental data silos are. But the question now is, how do you break down silos? 

Here are practical ways to remedy the problem and strengthen your organization's data management policy.

Improve company culture

More often than not, deep-seated cultural practices encourage silos to grow. So if you want to break down data silos, start by improving company culture.

Have a one-on-one with your people. Speak to both the "keepers" of the siloed data and to the "out-groups" who commonly request access. Then use that information to probe any cultural barriers that may be present.

If you find any, and there are no compliance or security risks to doing so, remove them immediately. The goal is to heal old wounds and ensure no animosity and mistrust between teams or departments. 

Once that's done, focus on launching new initiatives that encourage employees to collaborate in cross-functional teams. This may be a long-term initiative rather than a short-term fix, but it could pay off as your organization expands.

Create a plan of action

Working out a clean plan of action before taking your first steps will undoubtedly help everyone involved. This plan is likely to look very different between organizations. Remember to plan out everything from sourcing the solution to implementation to training and completion.

While at it, clearly communicate the problems with silos, as well as the benefits of data sharing and data integrity, so that employees understand the shift.

With clear communication, a clean plan, and a clear goal, you'll help to keep everyone happy and eager for change.

Use integration software

For some organizations, bringing data under one roof is practically not feasible. That's why such companies choose to keep their data in different pieces of software. 

If your business uses multiple pieces of software to keep data, correctly integrating that software can help you avoid data silos. The good news is that you don't have to develop your own integrations internally. An integration platform can do all the heavy lifting for you and help you link your tools and teams.

Search for applications with native integrations

If you find it hard to unify data with integration software, you'd be glad to know that it's not the only way. Opt for systems that offer native integrations instead.

Most modern systems will permit native data integration. For example, financial systems will integrate with other e-commerce and billing applications and CRM systems with marketing and sales tools.

While many applications do have native integration, every single tool can't have this ability. Do your due diligence when investing in new technology. Is the application capable of integrating with your existing systems? Talk to your vendors. If it's not available, then why? Having data locked down for no reason is undesirable for any company.

Centralize your data

To prevent data silos, find a way to centralize your company data. Consolidated and standardized data in a central repository will help your employees retrieve data without any hiccups or setbacks.

One of the best methods of dealing with data silos is to centralize the data on a cloud-based data warehouse or data lake. This relatively new form of data management has multiple benefits, including better data security, better workflows, a better path to scalability, increased chances of finding valuable insights, and faster comprehension of new data.

Take time to sort through outdated data

Setting aside time in your employees' schedules to appraise collected data may seem like a waste. However, eliminating outdated or duplicate data will give your company some much-needed wriggle room.

First, the process frees up storage space. Second, it makes integrating all your systems even more effortless. From an employee's point of view, streamlining your data allows them to access the latest and most accurate information without complications.

During the actual exercise, you can choose to include employees and make it a bonding or a team-building activity between departments.

Alternatively, you can bring in a team of business data owners. They will work through all data to ensure it is relevant and justified. They will need to ask important questions like:

  • Why is it being gathered or stored?

  • Where is it being stored?

  • Is the old data required for legal reasons? If so, can we archive it?

  • Do we need to build a business case to remove data?

The takeaway

By knocking down data silos, information will flow freely within your organization, and employees will be productive.

But it starts with identifying whether silos exist in your company. We gave different signs to look out for; if you missed it, please recheck the article.

If you do pinpoint silos in your company, use the strategies in this article to combat them.

Remember, data silos aren't going away overnight. It takes time and effort across all structures within an organization. But it's totally worth it. With the right tools, plan, and mindset, you can tear down silos.

FAQs

What is an example of a data silo in a company?

A classic example of a data silo is when two departments store the same data (e.g., prospect name and phone number). This causes confusion about accuracy and integrity.

Another example is when a company's sales department runs a database that the accounting department doesn't know about, causing the two departments to operate independently and not share data about sales and customers when they really should be collaborating.

What is a data lake vs. silos?

A data lake is a centralized repository that stores all of a company's information and data on a single interface without interfering with its initial format.

Data lakes primarily remove data silos and prevent new ones from developing by facilitating the centralization of information.

What is the opposite of a data silo?

The opposite of a data silo is data integration, which combines data from multiple sources to provide a unified view of the data. When done right, integration promotes data consistency, accuracy, and integrity while encouraging employees to work as a team.

Should you be using a customer insights hub?

Do you want to discover previous customer research faster?

Do you share your customer research findings with others?

Do you analyze customer research data?

Start for free today, add your research, and get to key insights faster

Get Dovetail free

Editor’s picks

What is customer experience marketing?

Last updated: 30 April 2024

Sales analysis templates

Last updated: 13 May 2024

How to analyze your NPS results

Last updated: 4 July 2024

CSAT analysis template

Last updated: 13 May 2024

Related topics

Product developmentMarket researchPatient experienceCustomer researchResearch methodsEmployee experienceSurveysUser experience (UX)

A whole new way to understand your customer is here

Get Dovetail free

Product

PlatformProjectsChannelsAsk DovetailRecruitIntegrationsEnterpriseMagicAnalysisInsightsPricingRoadmap

Company

About us
Careers11
Legal
© Dovetail Research Pty. Ltd.
TermsPrivacy Policy

Product

PlatformProjectsChannelsAsk DovetailRecruitIntegrationsEnterpriseMagicAnalysisInsightsPricingRoadmap

Company

About us
Careers11
Legal
© Dovetail Research Pty. Ltd.
TermsPrivacy Policy

Log in or sign up

Get started for free


or


By clicking “Continue with Google / Email” you agree to our User Terms of Service and Privacy Policy