In the agriculture world, silos have been around for thousands of years. A farm might have multiple silos, each independent of the others and containing its own type of grain or other material.
In the corporate IT world, data silos operate in similar ways. They house independent data by separate business units or departments. But whereas agricultural silos are essential for protecting the grain, data silos can be harmful because they limit access to important users and can result in bad decision making based on outdated or incorrect data.
How Are Data Silos Formed?
Data silos occur within a department or business unit that collects and stores data specific to its business processes. They are often formed by siloed technology, which is a system specific to the department or unit. The intentions behind the creation of a silo might be good, such as a department adding a system to solve a problem or implementing new technology to handle growth. Silos can also occur when a large company acquires an operation with systems that don’t communicate with others in the greater organization.
Problems with Data Silos
While silos often occur naturally, they can still be detrimental to a business if allowed to remain. The main challenges of data silos are:
- Different departments reporting inconsistent data
- Business intelligence and data science teams being unable to access or find relevant data
- Executives complaining about lack of data, when really the data is in an inaccessible silo
- End users discovering data sets are incomplete or out of date
- Unexpected IT costs to maintain and manage legacy systems housing data silos
When one department wants to use siloed data from another unit and exports or duplicates it, the data instantly becomes dated and is no longer being updated in real time by the siloed technology. To obtain updated data, an end user must return to the original data source. If the new user changes or adds to the data, then the original user no longer has a complete data set either. This can result in errors and inaccuracies, and bad decisions.
Consider the example of an aerospace organization with a parts subsidiary that uses its own technology to track inventory. Another unit within the aerospace organization needs 100 titanium bolts and accesses the parts subsidiary’s inventory data noting the bolts are available. The unit doesn’t place an order for the bolts right away but relies on the data it has downloaded. Then five days later the unit once again accesses the parts subsidiary’s data silo, finding that the bolts are no longer available.
Management relied on outdated data. If the different divisions of the aerospace organization were using a single data thread, each department would have had real-time access to the data and updates.
Once created or inherited, data silos and their related technologies can be difficult to eradicate. Internal politics often plays a role as department heads or unit leaders are reticent to give up their legacy systems. Each department operates separately with its own goals, priorities, and IT budget.
Setting an overall data management strategy can help with aligning data with business operations on an enterprise level. Affecting cultural change is another solution. As businesses strive for digital business transformation, consistent and consolidated data management will become a necessity for data access to take place across the enterprise in real time.
Dassian Can Help with Data Silos
Our suite of solutions is designed to create a single digital thread across your enterprise, allowing real-time access to data you can rely on for decision making. Contact us today.