How Data Silos Impact Business Decision-Making

Data silos, which are effectively isolated data repositories within an organization, are one of the most common data management problems. They create barriers to information sharing and information use in general, hindering business performance by adding friction to collaboration, decision-making, and business operations. This sand in the gears of business processes is so common that it can become invisible, but it comes with real costs. 

Inaccessible data means that analytics are based on an incomplete data story, that AI training models are missing relevant information, and that personalization is limited or incorrect because it doesn’t include important aspects of customer profiles. Data that exists but is inaccessible to the people who need it doesn’t add value to a business.

how to fix data silos

What Causes Data Silos?

The ultimate root cause for most data silos is usually either the lack of a unified information strategy or one that is poorly implemented due to ineffective governance or other organizational factors. In either case, lack of organizational alignment is a key contributing factor. This generally results in a fragmented and inconsistent data and information environment, which creates an inefficient and frustrating experience for users.

Some specific technical and organizational issues come up again and again as causes of data silos and other common data and information management ailments.

  • The core of most data and information management dysfunction is a general lack of alignment between business units and business functions. In the absence of unified practices, both governance data and information management practices across the organization will inevitably diverge, resulting in data silos.
  • A technology-first approach that pays insufficient attention to user needs will also inevitably lead to technology solutions that are inappropriate for business needs. For example, think of the continuing prevalence of manual point-to-point, spreadsheet-based processes (despite the availability of multiple data management tools within an organization). 
  • Technical and data debt, a buildup of unresolved issues in technology or data systems over time, can create similar challenges. For example, this often occurs when new business units, products, or processes from mergers and acquisitions are not fully integrated. 
  • A lack of unified business language will inevitably lead to miscommunication and data silos. Without shared terminology and definitions for business processes and entities, information sharing and data integration across an organization become impossible.

Despite their bad reputation, there are situations where data silos are acceptable or even required. When managing regulated data and when security is a primary concern, isolation of data sets may be the best approach. Governance policies should account for this to ensure that sensitive data isn’t accidentally shared, combined with other data for analytics or AI training, or used in other ways that violate compliance.

The Effect of Data Silos

The most noticeable effect of data silos is a fragmented data experience. This occurs when users struggle to access and work with data because it’s disconnected across systems and tools. As a result, businesses face a number of negative impacts on their operations.  

  • Data silos encourage bad habits. When users encounter a data experience that doesn’t meet their needs, they develop workarounds to help them do their job. This can result in ad hoc or ungoverned data sharing, inappropriate copying of data sets, use of inappropriate or unauthorized tools, and the creation of new silos. All of these are important contributors to poor data quality and increased compliance risk.
  • Without a unified view of organizational information, decision-making is hindered and opportunities might be missed. Fragmented data leads to discrepancies in reporting and analysis, eroding trust in the accuracy and reliability of organizational data. When data is siloed, it hampers integration, collaboration, and the ability to generate meaningful insights.
  • When data users struggle to find and access needed data, and when the data they find requires extensive cleaning and harmonization to be usable, it leads to duplicated efforts and wasted time. This ultimately increases costs and has an overall negative impact on operational efficiency.

Looking for the effects of fragmented data also helps to diagnose and catalog specific data silos where they exist within an organization. 

  • Data audits can help catalog data and identify data sets that are redundant or duplicated, out of date, or stored inappropriately, for example, spreadsheets on SharePoint sites.
  • Tools and platforms are also frequently siloed. This can lead to multiple copies of the same data set and must be accounted for in governance processes. Understand what data resides within a system and if it is siloed.
  • Interviews and other user research to understand the reality of how users discover, access, and share data within the organization. Be especially alert for ad hoc data sharing, which is often based on informal employee networks and knowledge held by specific people. Also be alert for “dark data,” which is stored and managed outside of formal governance processes.
  • Identify the specific information needs of data users. Work with them to understand gaps in their data experience. What data do they need but is difficult to find? What are the differences between different business units?

What to Do About Data Silos 

Data silos are typically a symptom of more general issues with organizational alignment. A holistic approach that considers the broad business context of why and what data the organization collects and uses, how it is collected and managed, the needs and workflows of data users, and the technology environment is most likely to be fruitful. 

Fortunately, improved organizational alignment has benefits that go well beyond just breaking down data silos.     

  • The challenge is not just breaking down data silos, but improving organizational alignment. Start with a general agreement on the value of data as a business asset and commitment by all data stakeholders to doing their part in data governance and management. 
  • A shared set of taxonomies providing standardized business terminology and definitions across the organization, and mapping to specialized terminology and jargon where necessary, is a critical information asset.
  • Technology alone is not the answer. No technology investment will overcome the lack of a unified strategy for it will support business needs.  
  • Employees need more than just data, and unified information will account for this. Consider unstructured data and content in all its forms; strive to understand organizational needs for knowledge, not just data.

Want to eliminate data silos and align your business strategy? Factor can help. Contact us today to request a consultation.

John Tulinsky
Information Architect |  + posts