What Are Data Silos? How Do They Weigh Down Your Business?

Did you know nine in 10 IT leaders point to data silos as their biggest obstacle to digital transformation? In our data-driven business environment, there’s an app for nearly everything. 

A CIO can gain insight into cross-departmental data and govern when and how it gets surfaced. A customer service rep can pull up customer interactions across any channel. A developer can see which APIs are already built in the ecosystem before diving into a new integration project. From business analysts to data scientists to marketers, lines of business use technology and accessible, shared information to make informed decisions, improve workflow, and create memorable customer experiences.

What are data silos? 

A data silo is a collection of information isolated from — and not accessible to — other parts of the organization. Data silos create issues such as inconsistent information across the organization, an inability to grow or scale processes, and redundancies between departments. They create myriad problems for organizations, and nearly every industry feels the pain of siloed data. Organizations cannot digitally transform without a shared, accurate, and informed data snapshot of customers, inventory, and more. 

Data silos generally manifest in an organization as a result of three common issues:

1. Disconnected technology. Lines of business have changed how data exists in an organization. Once upon a time, central IT was a powerful gatekeeper to systems, and CIOs had tight control over the enterprise tech purse strings. Now it’s more common for non-IT business units to buy their own technology. This has left IT with a mess of disconnected systems and applications in the enterprise and a backlog of integration requests.
2. Company culture. Knowledge is power. When groups receive incentives to “get ahead,” they tend to guard valuable information, which breeds a culture of distrust and competition. This sense of possessiveness can cause redundancies across the organization. Often, it acts against the interests of the business as a whole. 
3. Organizational structure. Siloed initiatives = siloed data. Forrester and Salesforce found customer data comes from too many sources for business leaders to easily make sense of it. These silos negatively impact the quality of customer and prospect experiences.

Everyone benefits from the real-time, on-demand information new technology provides. But it comes at a cost to IT. The speed of change has broken the traditional IT operating model. The average enterprise runs on nearly 900 applications, and only one-third integrate with one another. As a result, enterprises have made integrating data sources their top priority.

An effective data strategy allows organizations to unlock data from any system and put it to use. This requires an understanding of what a data silo is and how it evolved in your organization in the first place.

How do companies and organizations manage data silos?

The federal government is a high profile example of the pain from data silos. For example, the U.S. Government Accountability Office (GAO) estimates the federal government can save tens of billions of taxpayer dollars if Congress and the executive branch reduce fragmentation, overlap, and duplication across agencies.

Unfortunately, few organizations have the luxury of building their infrastructure from scratch. As a result, companies often take three common approaches to tackle data silos:

1. Swivel chair interfaces. Have you ever had to type the same information into many different systems just to update one data point? If so, you’ve been victim to “swivel chair” interfaces. A swivel chair interface is a common workaround that involves manually entering data into one system and then entering the same data into another system.
2. Data lakes or data warehouses. Gartner defines a data lake as “a concept consisting of a collection of storage instances of various data assets. These assets are stored in a near-exact, or even exact, copy of the source format and are in addition to the originating data stores.” In contrast, data warehouses are repositories for structured, filtered data processed for a specific purpose. Both merge and store data from across the organization in a single place. But they can create significant challenges as the data grows stale and requires time-consuming maintenance to update, access, and secure. Additionally, in these models data ownership is often unclear, often causing access violations.
3. APIs. APIs (application programming interfaces) allow systems and applications to speak to one another in a common language. This creates a “system of systems” within the enterprise that enables disparate systems to share data in real time.

How APIs break down data silos

An API is only as valuable as its adoption, which companies like eBay, Coca Cola, and Amazon realized early on. These companies used APIs to break down data silos and speed up their company’s digital transformation by driving a company-wide API strategy. 

According to our annual connectivity benchmark report, 89% of companies have adopted some form of API strategy. But levels of adoption vary from most primitive (project-by-project) to mature (company-wide). Organizations with top-down, company-wide API strategies see 36% more developer productivity and 67% more project completion compared to organizations that take a bottom-up approach.

The takeaway: An API strategy speeds digital transformation

Research shows a company-wide API strategy enables technical and business groups to work together to break down data silos. CIOs and IT can take a proactive role in shaping their business transformation strategy. Companies see real, tangible business results including faster delivery time for teams, visibility for CIOs and business leaders, and control over how people access and share information.