Marketing is increasingly a data-driven discipline. The rise of targeted, personalized marketing and new tools like conversational artificial intelligence has accelerated the need for more and more data. 

Fortunately, marketers typically have access to vast amounts of corporate data to help them build effective campaigns. But, often, the data is less helpful than it could be because it is broken up into data silos.

What is a Data Silo?

A data silo is a data collection accessible to one group within an organization but not readily available to other parts of the organization. More simply, having data silos typically means that your departments or functions – human resources, sales, customer service, etc. – each maintain separate databases. And most marketers are all too familiar with the challenges of drawing their data from all these competing sources.

The presence of data silos complicates efforts to make sense of data collections. Different data silos have different database structures and different types of data, ranging from simple spreadsheets to highly unstructured data. Aggregating and analyzing this disparate data can be challenging.

From a high-level perspective, data silos make sense. Every department needs specific data to do its job well but may not need information other departments value. Why, for instance, would human resources need to access customer records? And why would logistics professionals need information on personnel reviews?

But when you look at data silos more closely, it is clear that they are more harmful than helpful.

Why Data Silos Exist

Every organization may have different reasons for siloing data. But there are several common causes for data silos across businesses in all industries.

Company Structure and Management 

Corporate organizational structure is a primary source of data siloing. Just as different departments have different goals, workflows, and compliance obligations, they also have other data sources and repositories. And, because there is often little or no interaction between various company functions, they don't see the need or benefit in sharing data.

Department and Function-specific Applications

An extension of the structural reason for data silos is the use of department and function-specific applications. For many years, it was the norm to have siloed applications focusing on specific tasks, and those applications often had their own data storage.

Every function at a company likely uses the same word processor or the same email platform. And there might even be shared storage for those applications, although siloing of data even for shared applications has not been uncommon (e.g., the "accounting drive" or the "sales drive").

But most departments also have separate applications as well. Whether CRM applications in sales, ERP applications for supply chain operations, or time-tracking applications for human resources, individual departments use specific tools that simplify their workflows. But these tools often contribute to data silos.

Incomplete Integration of Acquired Assets

Businesses don't rely solely on organic growth; acquisitions and mergers have always been common. There have been more than half a million M&A deals worldwide in the past decade, totaling trillions of dollars. 

With acquisitions, however, comes the challenge of integrating the acquired business's data sources or merging them into the purchaser's systems. These efforts are never simple, and they often leave dangling or orphaned data sources, as well as data associated with legacy applications. 

Even organic growth can lead to siloed data, however. If there is not an overarching, company-wide plan to scale systems to accommodate growth, individual departmental scaling efforts may only serve to worsen data siloing. 

Why are Data Silos a Problem?

Data silos can be very efficient for individual functions. But as a whole, data silos create more problems for an organization than they solve, particularly for organizations that want to make the most of their data.

Data Silos are Inefficient

Data silos often contain repetitive information, which makes them highly inefficient. Getting the information into the data silos requires duplicative data entry efforts, increasing costs for the business and diverting employee time. Getting rid of data silos increases productivity, a prime goal for any organization.

Moreover, even though the mantra "disk space is cheap" abounds, the fact is that unnecessary data duplication creates added storage costs. These costs can take the form of additional on-premise hardware that IT departments must manage and maintain or add resources at cloud storage providers. 

Data Silos Lead to Data Inconsistencies

Duplicative data entry also potentially creates data inconsistencies. When data silos contain similar information but silo owners update their data separately, conflicts can arise, putting the data's integrity in question.

Consider a simple example - contacts. Having conflicting contact information is far from unusual when different departments have shared contacts but maintain separate contact databases. And this can become an issue for companies if those departments inadvertently make repeated efforts to communicate with a customer on similar topics, irritating the customer and making life harder for the company's reputation management team.

Data Silos Hinder Analytics 

One significant benefit of big data is that it can support high-end business analytics. Business analytics is not limited to long-term strategic planning or financial projections but instead is useful for every function, especially marketing.

Marketing needs big data to understand the business's ideal target customers fully, create effective targeted marketing campaigns for them, and provide the best possible customer journeys. But data silos feed only incomplete information into analytical workflows, limiting their effectiveness. 

With data in silos, organizations can never get a full picture of their health and competitive position. And they are likely to blame ineffectiveness on business analytics tools rather than the underlying data quality.

Data Silos Deter Collaboration

If a department uses only siloed data, it has no reason to interact with other parts of the company that may also have helpful information. But keeping company functions completely siloed misses out on opportunities for collaboration and synergy. And it further handicaps the organization by limiting the benefits of the creative brainstorming that often comes when different functions with different mindsets come together to address common issues.  

Data Silos Increase Compliance Concerns

Data siloing also makes corporate compliance programs that much more difficult. Indeed, data silos have negative procedural and substantive ramifications.

To begin with, having numerous standalone data sources increases the risk that the company will simply lose track of data collection. Worse yet, data sitting around in software that the company is not actively updating or in legacy systems is a prime target for cyber attackers, as these types of repositories are notoriously insecure.

Disparate data silos also make it harder to comply with applicable laws and regulations, for example, privacy laws. With data spread across the organization in multiple locations and formats, compliance personnel and tools must strain to ensure they have covered all their bases.

How Can You Eliminate Data Silos?

Faced with data silos that limit their effectiveness, what can marketing departments do to improve data quality? There are several ways that marketers can help break down silos, from fostering cultural change to helping identify the right tools. 

Create a Sharing Culture 

Overcoming cultural barriers is one of the first steps toward achieving data integration and sharing. Marketers cannot simply say they need data sharing to do their jobs better. Instead, marketing professionals must actively sell integration, showing the C-suite and other departments exactly how data sharing will benefit everyone in the long run.

Cultural change must have management's buy-in, and preferably they will be vocal cheerleaders. But marketers can give the C-suite the incentive to effect change.

Create Corporate Data Governance Policies

Companies must do more than build the proper culture. They must also enshrine those values in governance documents so that all employees, current, and future, know how to handle data appropriately. 

Effective data governance programs include conducting data inventories, building data workflows and architecting data storage. Done correctly, they can help organizations break down existing silos and avoid creating new ones.

Begin Unifying Data Collections

While it sounds simple, integrating data can be anything but. And here, marketers must rely on the company's technical professionals. Selecting the right platform, most likely cloud-based, for unifying all company data can be a daunting task. Performing the actual integration can be even more challenging. 

Organizations can look to cloud-based data warehouses and data lakes for consolidating existing data of all kinds, structured or unstructured. And tools like ETL (extract, transform, and load) allow organizations to aggregate and normalize data in a single usable location.

The faster a company gets the process underway, the faster it will be able to reap the benefits of data integration.

Conclusion

Big data gets bigger exponentially every day. So companies need to give their marketing departments the best tools for accessing, analyzing, and using all the high-quality data they can get their hands on. And getting rid of data silos is one of the best steps organizations can take to do so.