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Article 5 min read

What are data silos? Why they’re a problem + how to fix your business silos

Data silos make life harder for support agents and customers alike. Learn how to free siloed data and improve CX.

By Patrick Grieve, Contributing Writer

Last updated February 23, 2023

Data silos

In today’s data-driven world, companies need to leverage their customer data to make informed decisions and improve their business. Yet some organizations still struggle with outdated or insufficient information. Other brands capture plenty of data but fail to connect it all because it lives in multiple sources and systems. Both situations can lead to the creation of data silos.

Data silos cause inefficiencies and complicate customer service interactions, leading to stressed-out support agents and unhappy clients. According to the Zendesk Customer Experience Trends Report 2023, only 22 percent of business leaders say their teams share data well. Sales, product, and marketing teams could also miss out on valuable customer insights. Businesses need to understand how information silos happen and how to eliminate them.

In this guide, learn what data silos are, how they’re problematic, why they occur, steps to fix them, and trends to watch out for in 2023.

What is a data silo?

A data silo is a set of information that can be accessed only by certain groups within an organization. Saying that information is “siloed” is another way of saying that it’s somewhere out of reach.

A data silo occurs when you have information that pertains to a customer or a business and it’s stored in various places. This results in data not being accessible for a lot of teams—or not accessible at all.

In a customer service context, that means support agents might not have all the information they need when interacting with a customer. This can hinder agents from providing a positive experience.

Why are data silos problematic?

Data silos are problematic because they reduce collaboration and transparency, create team barriers, decrease productivity, increase costs, foster poor customer experiences, and lead to an overall lack of adaptability. Learn about these data silo issues and more below.

Reasons data silos are detrimental

How do you identify a data silo?

Before you look to solve a data silo problem, you must first identify the cause. Below are some tell-tale signs that your business is dealing with a data silo:

  • Inconsistent data: Conflicting data is coming through from different departments.
  • Missing or hard-to-find data: Some teams can’t access or find important data.
  • Incomplete data: End users are discovering out-of-date or incomplete data.
  • Lack of data: Departments are complaining about not having enough data for certain initiatives.
  • IT budgets are rising: IT costs are quickly exceeding the budget.

Your IT, data science, or team that handles data should be able to provide some insight into how often these issues occur and what is likely to be the root cause. This could look like inconsistent data appearing and errors that go uncorrected.

Why do data silos occur?

Holding separate blocks

Unfortunately, siloed data can easily occur. Many organizations—especially large ones—naturally trend toward siloing. But why does this separation of data occur? Several factors lead to information silos, and they’re often intertwined:

Technology

Relevant data often live in different sources that don’t connect on the back end, which makes data sharing difficult. Organizations often rely on multiple business tools and databases, which may not fully integrate.

This lack of technological interconnectivity can lead to poor data management. For example, there could be different protocols or functionalities that result in systems being unable to talk to each other—out-of-date, custom-built systems are sometimes the cause of the disconnect.

Company structure

At the same time, many company structure issues can exacerbate the problem. Different departments within an organization can silo, and their data can silo with them.

For example, a company’s sales team may not collaborate with the support team. As a result, sales agents can’t look at customer service interactions to identify potential upsell opportunities or to determine if a client account has an open issue.

Company principles and culture

Company principles and culture may also cause data silos. Many teams may work independently from one another, participate in unhealthy competition, and foster a “data-ownership” vs. “data-sharing” mindset. This creates a culture of separation, leading to a data disconnect.

For example, the marketing department and sales department may both handle customer data at the same time, but because of the company culture, they’re encouraged to keep the data separate due to their different processes.

Ensuring that teams cross-collaborate is a top priority for business owners to help prevent siloed data. In our CX Trends Report, 82 percent stated they would be interested in combining service data with customer feedback data, and 78 percent sought to combine service data with sales data.

Business acquisitions and growth

Business acquisitions and overall company growth can cause data silos if internal processes can’t sync and scale. Growing your company, while beneficial and exciting, can cause some kinks in the short term.

For example, with an acquisition or merger, businesses typically add even more layers of management and departments that already have their separate stores of data and sharing processes.

7 steps to fix a data silo

How to fix a data silo

Knocking down data silos often requires new technology and initiatives. Businesses should decide what type of customer experience they want to provide, then empower their support agents to deliver that kind of care. Here are seven steps to fix a data silo:

1. Map out the ideal customer journey

From a CX perspective, breaking down silos starts with identifying objectives and mapping the customer journey. Begin by determining the type of experience you want to provide customers and the data required to create it.

Some businesses use customer journey mapping to chart every interaction a customer could have with their brand. Then, they analyze the information they need to optimize each stage of that journey.

Not every company will share the same goals, so it’s important to first establish your organization’s priorities.

2. Identify customer data gaps between teams

Your support agents are obviously going to play a huge role in crafting customer experiences, so determine what data they need to fulfill your CX objectives and fill any gaps between teams.

To start, take a holistic look at the tickets that agents deal with and determine the most common issues. Then, ask yourself:

  • What would help agents solve these issues more quickly?

  • What could help them reduce the handling time or be more efficient?

  • What tools are agents toggling between?

While the goal is to break down data silos, don’t overcorrect and overwhelm agents with too much information. Focus on finding what type of data is needed to help solve issues faster.

3. Invest in software solutions that allow data to be housed in one place

From a technical perspective, the best way to avoid information silos is to take your customer data from multiple systems and place them under a single source of truth. Instead of storing the data across different software, connect it all through an open, flexible platform like Zendesk. Zendesk allows you to:

Zendesk lets you connect and understand all your data—wherever it may live—and use it across your business, giving you a central place to create a single view of the customer.

Polaris Adventures saw great success in breaking down silos through its partnership with Zendesk. The software allowed all customer interactions to happen within a unified and easy-to-navigate platform. It enabled agents to access account information more quickly, collaborate with other agents, and improve average first-response time, which led to happier agents and customers.

Now, each agent can handle 30 to 40% more business, even as the customer base has grown.

That boost in efficiency stems from all interactions now happening in a unified workspace, where agents can better collaborate with their partners across the company.

4. Create a codified system for maintaining data organization

Additionally, it’s important to create a codified system for maintaining data organization. A codified system is a team-wide process and regulation for handling data. This helps keep all the information in one place and prevents it from getting lost.

For example, you can implement data governance and metadata management to assist with data organization.

5. Give agents the context they need

You understand the type of information your agents want access to, and you have that data stored in a single place that’s easily accessible—now what?

You need to provide your support team with that important info in a way that doesn’t overwhelm them. For example, Zendesk gives agents an “essentials card” that includes all the relevant details about the customer they’re engaging with. The card may contain basic information (like the customer’s name and preferred language) or more in-depth data (such as customer status or membership level).

6. Create a collaborative company culture

Typically, it’s a mix of technical deficiencies and a lack of organizational impetus that keeps companies from breaking down silos. Build a company culture where internal collaboration is encouraged and teams also have the tools they need to make it happen.

For instance, if your sales teams often host training sessions, you can loop in your marketing and customer service departments and encourage the sales team to share their data. This can help encourage different skills and perspectives, which helps promote a collaborative company culture.

In addition, ask for feedback from the various departments in your organization to see where cross-collaboration can be further improved.

7. Use artificial intelligence (AI)

As a solution to siloed data, many businesses are turning to the use of AI and chatbots. AI-powered customer service tools and applications such as chatbots make it easier for businesses to compile and view their data and streamline customer service. This includes:

  • Offering 24/7 support

  • Providing quicker resolutions and support

  • Reducing errors made by team members

  • Delivering personalized recommendations based on the data provided

  • Tracking and analyzing all data in one place

According to our CX Trends Report, 72 percent of business leaders say that expanding AI across the customer experience will be a main priority over the coming year. To get there, 67 percent expect to integrate AI and bot spending over the next year, with almost half committing to as much as a 25 percent increase in budget.

CX Trends stat

2023 data silo solution trends for businesses

Looking to keep data silo solutions top of mind this year? Here are some data solution trends to watch for in 2023.

  • Increased team collaboration: More than ever before, companies are taking steps toward creating a more collaborative culture to improve information sharing between departments.
  • AI: The use of AI and chatbots is an emerging trend for 2023 to help streamline support efforts.
  • Improved software solutions: Companies are turning to software solutions that can allow teams to easily access and view data in one place.
  • Codified processes: Companies are codifying processes and using data governance and metadata management to help with data organization.

Overcome data silos as a business

Whether your business is restructuring or overcoming market challenges, data silos can pose major problems for your overall growth. By following the tips above—and using sophisticated customer service software like Zendesk—you can ensure you streamline your data management and keep teams on the same page.

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