4 Most Common Ways Data Silos Affect a Company

Data silos impact integrity, collaboration and analysis.
 

We’ve talked about analysis paralysis, the most common reason data can impede decision-making. Now, we’ll steer the conversation beyond data capture and the right cadence for decision-making checkpoints. We’ll examine organizational structure and the impact of silos on data and analysis.
 

Business silos inhibit a complete view
 

Departmental silos within an organization are seen as a growing pain for most companies and is considered one of the largest detractors of innovation across the board. Unfortunately, silos in most organizations are there for a purpose, with a  goal of focusing specialized talent towards very specific goals. 

The problem with these silos is that they generally create isolated islands of teams rather than an organization of people working together towards a common goal. When it comes to data, the challenges are no different. Business silos within an organization generally create data silos, making it almost impossible to connect all of the data streams into a single view. It also hinders the ability of decision-makers to have a clear view of all of the important business data needed to make the appropriate overarching decisions based on its analysis. 
 

The four most common ways data silos affect a company
 

Limited view and analysis

Business and data silos generally require each department or group to aggregate and analyze their data separately from the others within the company. Because of this, decisions are made within groups rather than at a corporate level with the big picture in focus. 
 

Lack of integrity

Data aggregated by departments are generally stored separately, using different technologies, tools and providers. The challenge here is that data between departments will be inconsistent and very difficult to integrate. In addition, the data can become less accurate and, in some cases, could be out of sync when different teams collect similar data.
 

Duplicated resources

As data is being stored separately, the analysis of it is normally done separately as well. This leads to increased cost in hosting, analytics packages and labour because each department will need separate budgets to manage their own practices.
 

Lack of collaboration

Separation of data continues to drive a siloed corporate culture where each department will compete to ensure they have the funding to pay for the resources they’re creating.
 

The key to breaking down data silos is to create an organizational culture where business silos don’t exist. Unfortunately, it’s not always as easy to do as we’d like it to be. Another way to eliminate data silos is to create a unified data strategy where data and its analysis is centralized by a neutral group and then distributed to the teams who need to understand it and make decisions based on it. 

Another cultural aspect that can impede data-driven decision making is fear of failure and we address it in the next blog of this series. Make sure you check in with us again.