Discover how DHL Group increased connectivity across the enterprise and automated multiple processes end-to-end
A data silo is a repository of raw data that is only accessible to one area or team of a business and isolated from the rest of the organization. Information within a data silo is often held in a system that is incompatible with other data sets. This restricted access makes it hard for other areas of the business to access and make use of the data.
Data silos often occur in large organizations where departments have their own budgets and priorities, so carry out their own digital transformation projects and operate separately. They can also inadvertently appear within the organization when legacy technology is not upgraded or properly integrated with the rest of the technology stack, leading to trapped data that’s left behind.
Data silos can cause a multitude of problems for organizations. All of the problems listed below can ultimately lead to increased costs, missed opportunities, and poor customer experiences caused by inconsistent data and poor collaboration across the business.
Lack of visibility: Employees don’t have a full view of information across the organization if they are working with siloed data. With no centralized view, departments, teams, and stakeholders will all see different information. This leads to siloed working as well as siloed data. Your organization should have a consolidated view of data to enable a holistic view of your business operations.
Inaccurate reporting and analysis: Data silos lead to data being duplicated, outdated, and incorrect. Data is meant to inform decisions, but inconsistent data sets can lead to conflicting or incomplete data, which hinders management and analysis; and in turn prevents the organization from progressing. Additionally, if teams are only analyzing data from their own silo, this can skew reports. If data is not integrated, it can be hard to cross-check information from different sources.
Barriers to communication and collaboration: In organizations with data that’s not integrated or compatible across different systems, information sharing becomes hard, so teams will continue with their siloed approach to working. When departments and business units only have access to their own data, they won’t be able to work towards larger business goals. They will stay focused on their own data with a reluctance to share information, further exacerbating the issue.
Inefficient ways of working: Teams who are solely focused on their own data sets may miss opportunities, such as carrying out work when other teams may have already completed the same or similar tasks, or being unable to identify key data patterns, simply because they don’t have a holistic view of the organization’s data. If information is shared between incompatible systems, there is also a risk of error or duplication when data is rekeyed, which can affect data quality.
Data security risks and compliance issues: While incompatible systems can pose an issue, data silos can also form when teams or individuals store and share data in Excel spreadsheets and over email, which can present a multitude of risks. When every team has their own way of managing and storing data, it can be hard to enforce data security and compliance and ensure proper protection for sensitive data.
Barrier to agility: It’s difficult to be a responsive business and respond to changing market conditions or customer demands when you have an incomplete view of organizational data. Data silos make it hard for your organization to move at pace as time is wasted on data gathering in order to look at the big picture. You need to adapt your business as a whole to evolve and grow, which isn’t possible when departments aren’t all working with the same data.
Use an orchestration layer: You don’t have to scrap all your enterprise architecture to make your data silos compatible. You just need to integrate them. You can use a single platform to act as an orchestration layer to unite people, processes, systems, bots and data across your organization and provide a digital 360-degree view of all elements within the business.
Enterprise data management: Creating a data governance program can not only help to identify data silos and help eliminate them, but also prevent new ones from being created in the future. Having an enterprise-wide data strategy will keep your teams aligned and ensure that all data is shared securely and safely across the organization. Mapping out business processes and data workflows can help to ensure data is properly managed and shared. This will discourage from individuals hoarding or mismanaging data, such as those pesky Excel spreadsheets.
Create a culture of data sharing: To eliminate data silos, and a siloed way of working, you need to instil a culture of data unity throughout the organization. This should be led from the top down, with your C-suite setting an example and filtering down the use of collaborative platforms and ways of working throughout management and across business units and teams. Emphasise the benefits of a united way of working, and you’ll soon get everyone on board, and all reap the rewards from collaborating and sharing data.
So, data silos can present big problems for enterprises. Once we tackle the problems caused by data silos, we also need to think about how to promote collaborative ways of working within the organization. For a business to be efficient, not only does the data need to be integrated, but multiple business areas and users need to effectively interact with and process data.
Using a unifying platform that acts as an orchestration layer, you can effectively manage the people in your organization, as well as the systems.
Delivery: You can gather, filter, group and prioritize pending tasks for your team in a Smart Inbox, based on data from business processes. This ensures that cases are solved in order of priority and data to resolve the case is effectively and securely shared between teams.
Routing: In larger enterprises, where data and organizational silos often pose a problem, you can route work based on unique user characteristics to ensure efficient working. For example, An orchestration layer allows you to route tasks based on geography, language, time zone, and skills. The platform will intelligently route work by calculating the task and due dates and assign work appropriately.
Allocation methods: Much like a CoE approach, you can allocate tasks to users. Your platform can automatically evaluate the allocation rules defined for each task and select an employee that meets the criteria to complete the work. It might be that you require the first person available, or the person with the most appropriate expertise to solve a particular issue. Once work is allocated automatically, you free up resources from manual assignment as well as ensuring the right employees are working on the right cases based on their skills.
Work patterns: Obviously, when sharing data across the enterprise, you need to set governance rules and guidelines to ensure that only the appropriate users have access to sensitive data. Different personas can be assigned different permissions and data views through the platform, and be allocated separate duties to mitigate unauthorized actions.
Accountability: Ensure proper data governance and accountability across your organization using your platform to set Service Level Agreements, escalation processes, and audits. This helps to set a high standard for customer service and ensure ongoing customer satisfaction.
Create a unified way of working and deliver end-to-end visibility across your organization with an orchestration platform. Bizagi's capabilities enable you to connect the people, processes, systems, bots, and data that support your day-to-day business operations. This can help you orchestrate operations to boost visibility, enhance security and preserve IT infrastructure and resources.
Find out how we can help you to eliminate data silos in our platform overview.
