What are Data Silos & How to Prevent Them When Data Sharing
Because of how complex product management can be, it’s not hard to see why effective data sharing can be difficult to achieve throughout an entire organization.
These obstacles result in data silos that lead to different departments having conflicting data and struggle to access data quickly.
In this guide, we’ll go over what data silos are, how they occur, why they’re problematic, and the steps you can take to break down data silos!
What are data silos?
Data silos are a repository of data held by one business unit and only accessible to that department.
This makes the group of data difficult or impossible to access by other groups throughout the rest of the organization.
How do data silos occur?
Even organizations with existing systems for managing data could fall victim to data silos if individuals or departments go rogue.
In the majority of cases, data silos result from how organizations manage business processes, approach data storage, and run their IT operations.
Other factors that could lead to the occurrence of data silos include:
- Company culture. Corporations with highly-competitive working environments could lead to departments intentionally hindering the access of other teams to their pools of information. This is often done with the goal of controlling the flow of information and monopolizing data assets.
- Organization structure. If your organization is structured in such a way that various subsidiaries, sister companies, and business entities are run separately then multiple data silos could manifest as a result.
- IT deployments. Modern businesses can now choose from countless data platforms like NoSQL databases, cloud object storage, big data storage, and special-purpose databases depending on their specific needs. Due to the wide variety of software solutions, some data could fall through the cracks.
- Mergers and acquisitions. Whenever an organization merges with another company or acquires a separate business, there’s a high likelihood that information can get lost while moving data or become isolated during the data transfer process.
Why are data silos problematic?
You might be wondering what the big deal is and whether or not a data silo can really be problematic for your organization. Well, there are actually a few major reasons why all your data should be readily accessible to multiple departments.
In his 2007 HBR Silo Busting article, Harvard Business School Professor of Business Administration Ranjay Gulati wrote that: “In a survey of senior executives I conducted a few years ago, more than two-thirds of the respondents cited this shift as a strategic priority in the next decade. But their knowledge and expertise are housed within organizational silos, and they have trouble harnessing their resources across those internal boundaries”
Here are four problems that could arise as a result of data silos:
Creates inconsistent data
Storing data separately can lead to a number of issues. First of all, it creates more data warehouses that need to be updated on a regular basis.
Failure to update every data warehouse in a timely matter will lead to certain departments working with outdated information (even if other units within the organization already have newer data).
This outdated data could lead to specific teams producing subpar outputs due because they were operating on old data.
Without teams being able to view existing data, there’s also a high likelihood of duplicate data being stored.
Disrupts company collaboration
Data silos limit collaboration across departments because each team only has access to its own data and thus relies on that alone to make decisions.
This leads to a divided organization with every team working independently rather than collaborating with each other on cross-functional projects.
The long-term ramifications of these data silos could include an inability for teams to share the same vision.
Siloed data can lead to missed insights, lost opportunities, and miscommunication
Most business operations involve multiple customer touch points throughout an array of different channels (and within separate stages of the buyer journey).
In practice, this means that employees from different teams such as marketing, sales, support, and billing will all interact with the same customer.
If these teams don’t share data with one another but instead keep their data separate, it’s far too easy to lose track of a customer’s journey, problems, and job-to-be-done (JTBD).
This results in customers needing to repeat the same story multiple times whenever they speak with a different department.
This is perhaps the most costly drawback of information silos as it can impact customer lifetime value (LTV).
Data security and regulatory compliance issues
Last but not least, data silos can make it difficult to maintain high levels of security and remain compliant with various regulatory guidelines. You might think that compartmentalization makes a company’s data safer, but the opposite is usually true.
If you have employees storing documents, spreadsheets, and other internal data on individual devices rather than shared storage, it gives cybercriminals more targets to aim for.
Because data silos make it difficult to track who has access to what, this also makes it hard to comply with data privacy laws.
Trying to protect data stored in silos is like securing a building that has a hundred different entrances.
How do you identify data silos?
Before your company can be rid of data silos, you first need to learn how to identify them in the first place. There are a few things you can look at to determine if silos exist within your organization and where they reside:
- Inconsistent data. If different departments are reporting data that are inconsistent with one another then this is a clear indication that the only data available to each team is the information they’ve stored themselves.
- Access issues. If your business intelligence or data science teams are struggling to find and access relevant data for their research, then it’s highly likely that isolated data sits in silos beyond their reach.
- Executive complaints. If you have executives complaining about poor quality data or a lack of information on specific business operations this is a potential sign of data silo issues that keep them from finding what they’re looking for.
- End-user complaints. Similarly, any complaints from end-users citing incomplete resources or out-of-data data could be indicative of data silos.
- IT costs. If you come across an unexpected spike of unbudgeted IT costs then this could be a manifestation of data silos increasing the friction associated with processing data and thus slowing down your technicians.
If you notice one or more of these symptoms then you’re likely dealing with data silos.
How to break down data silos?
When it comes to figuring out how to solve your data silo problem, better data governance is usually the only way forward.
There are multiple levers you could pull on to improve your data governance and we’re going to look at five strategies in the sections below!
Restructure the data management system to promote common data standards and policies
Once you’ve identified the systems or processes that are leading to the creation of data silos, it’s time for a restructuring effort to restore the free flow of information across departmental lines.
Afterward, you’ll need to standardize data policies across the organization to ensure that silos don’t crop back up in the future.
Implement data integration to avoid creating a data silo
Data integration is one of the best methods to ensure that data silos don’t become a recurring problem within your organization.
When building out your tool stack, it’s important to look for solutions that have two-way integrations with other software that your company uses.
Userpilot is a prime example as we have dedicated integrations for HubSpot, Intercom, Google Analytics, and various analytics platforms to ensure that all our customers are able to easily share data across the solutions they use:
Centralize data across multiple tools with a data warehouse
After auditing how your storage space is currently structured and asking employees about their daily changes regarding data access, it’s time to decide which systems to discard or merge to promote a more streamlined flow for your data lake.
The ideal solution is to migrate all internal information to a unified central system with custom permissions and bulk export capabilities. Of course, proper security controls will need to be in place to ensure that bad actors don’t abuse their access to the central database.
Don’t collect the same data from users to prevent customer data silos
When more than one department extracts data from the same users, there’s a high potential for overlap and duplicate data. In some cases, the teams may not even realize that they’ve been collecting the same data from the same customers until the data silos start causing issues.
Having a single dashboard for all survey responses, customer feedback, and user data can prevent such issues. Here’s a look at Userpilot’s central dashboard that combines all data points from onboarding survey responses to net promoter scores:
Create a more collaborative company culture
You’ll never be able to cultivate a work environment where all the data is available to the departments that need the information unless you instill a culture of collaboration.
You should encourage cross-department data integration from the earliest stages of your company so it sticks around as your business grows.
One tactic would be to have an inclusion team dedicated to bridging the gap between executives and interns or encouraging open lines of communication across multiple departments. This is especially important for companies with team members in different countries and time zones.
Conclusion
As you can see, data silos can make it difficult for a company’s sales team or marketing team to extract data from separate databases. This, in turn, hinders business growth and negates the operational efficiencies of digital data management.
Ensuring that other departments are able to readily access company data relevant to their scope of work is crucial to collaboration. After all, data sharing is paramount to streamlining other systems that rely on the same information.