Data silos, also called information silos, have a very negative impact on business productivity and create significant risks of security breaches. However, these silos are now part of the daily life of many companies.
But then, how do you define what a data silo is? What impact do they actually have on businesses and how do they operate? But above all, how to abandon them without losing information?
Determine the provenance and extent of data silos
By definition, a “silo” is a structure used to house massive amounts of materials such as wheat or grain. Silos are usually juxtaposed and store goods separately. The material contained in the silo is abundant and circulates freely, but it is trapped. Similarly, a data silo is a collection of data within an organization that is isolated. Data silos “trap” information such as Word documents, media, metrics, feedback, financial reports, customer records, and contact information. Data silos make it difficult for employees to access, search, and analyze data across departments. The origins of data silos are complex. Several factors can be responsible for this, including corporate culture, infrastructure, and lack of technology adoption.
Corporate culture can be responsible for creating and maintaining information silos. If competitiveness trumps collaboration, departments are unlikely to agree to share their data.
Or, the root may be less malicious. In many cases, departments are not used to sharing information and until recently having a unified view of data was not a common goal. As a result, employee behavior did not reflect the need to communicate, share and analyze data across departments.
Company infrastructure can be another common cause of data silos. Before the advent of cloud technology, accessing information often required a chain of requests and attachments. Today, technology has made possible – and even standard – the automatic sharing of information. However, many organizations were not designed to foster an open and transparent flow of information between different departments and teams.
Similarly, the adoption (or lack of adoption) of a technology can reinforce data silos. Using technologies such as machine learning and natural language processing (NLP), companies can search, access, filter and transform data into actionable insights.
But many organizations have fallen behind when it comes to new technologies. Although it has been proven to improve operational efficiency, three out of ten companies do not have a digital transformation strategy. In many cases, organizations have not adopted technologies to help them search and filter data.
Finally, limited software integration can produce data silos. Teams often use different software to meet different needs, storing data in tools inaccessible to other groups (imagine a finance team trying to access data generated by a marketing tool).
Why do data silos impact productivity?
Take a look at your organization. Is your information siled?
If so, your employees’ productivity suffers.
As mentioned above, data silos prevent the flow of information. This can have long-term negative consequences for the business: reduced productivity, wasted time and resources, and even limited growth and revenue.
First, data silos slow down the rate of productivity.
Collecting data manually can be tedious and time-consuming for employees, who must make requests to other employees via email or Slack to access what they need. This can cause significant delays and interrupt the workflow of both parties. According to a report from Panopto, employees waste 5.3 hours a week waiting for data from co-workers – or recreating information that already exists.
Second, data silos cause organizations to consume storage space unnecessarily. Information silos often contain repetitive data or outdated and irrelevant data. Personal information created by former employees and outdated surveys are two examples of irrelevant data.
Without a way to organize, filter, and search data, organizations continue to accumulate this type of data at the expense of storage space.
Data silos can be costly. Lost productivity is estimated to cost US businesses $1.8 trillion each year (Hubspot), and data silos are responsible for some of this lost productivity.
When employees spend part of the day retrieving (or recreating) information, they aren’t making the best use of their time or energy. Their work also suffers from a lack of insight. When employees don’t have access to data, they are unable to perform as well. For example, a marketing department employee who does not have easy access to MRR data cannot make sound and informed decisions about marketing spend.
Storage space can also be an additional cost for organizations that pay for on-premises servers to host information or for subscription fees for cloud technology they may not need.
Limit the creation of data silos and dismantle existing silos
Before removing information silos in your organization, you need to identify them.
There are several signs that point to the existence of data silos in the organization. Some of these symptoms are cultural, others are more structural.
If your teams aren’t collaborating or setting common goals, data silos may be to blame. When teams don’t have access to the same information, they can’t get a full and accurate picture of what’s going on. This can make collaboration and goal setting difficult. It can also fuel an unhealthy culture of handover within an organization. When a team is underperforming, the lack of transparency can make it easier to blame the inefficiency on another team.
If you find that several of your teams are launching similar projects or using similar software systems, this may be evidence of a lack of integration. The ability to share data keeps teams on the same page and staying as efficient as possible when making improvements, solving problems, or adopting new systems.
Breaking down data silos in organizations is not a simple task. You’ll need a multi-pronged approach that takes into account company culture, infrastructure, and most importantly, technology.
To change the corporate culture around data flow, you need to advocate against data silos. The best way to do it? Present the benefits of an approach to data that is collaborative, transparent and efficient.
When employees can get a clear and comprehensive view of available data, they are able to make more informed decisions. Part of this is the ability to glean insights from structured (such as customer metrics) and unstructured (such as media and text) data. They are also able to work faster and more efficiently, reduce errors, and achieve their goals without complicating their lives unnecessarily.
To make the enterprise infrastructure more integrated, data should be brought together in a data warehouse or data lake, using an intelligent enterprise search engine. Bringing data together in one center makes it easy to search, filter and evaluate. Creating a data lake also increases data transparency.
Ultimately, businesses and organizations need data management not only to break down silos, but also to create a data search and analytics strategy.