Table of Contents
- Data-Informed Decisions are Needed for Digital Transformation
- The Data Silos Problems and Other Blocks to Digital Transformation
- Following Is a List of Ways to Keep Data Silos at Bay
- Connected Data Optimizes Digital Transformation
At a time of seemingly ultrarapid digital disruptions, digital transformation in an enterprise needs a bold vision and an intent to embrace change. With the global digital transformation market projected to reach $2.8 trillion in 2025, leaders are expediting their transition to digital across their organizations. And as enterprises course-correct and adapt to specific strategies along this journey, they need a sound understanding of their data to drive informed decisions.
The needed understanding of data-informed decisions is because high-quality data is at the heart of all digitalization initiatives, from delivering invaluable insights to and uncovering latent operational efficiency strategies. And that’s the reason organizations’ must get careful about the creation of data silos.
Today 73.5% of most leading companies are data-driven in their decision-making. In almost every organization, data is collected from diverse sources to analyze and make business-critical decisions. And while these sources may number in the thousands and millions, having data silos building up across an organization is a natural outcome.
Despite modern-day databases and repositories being more robust, it is hard for them to completely ward off data silos, preventing them from realizing the true potential of their digital transformation initiatives.
As a matter of fact, 89% of IT leaders today view data silos as one of the leading obstacles to digital transformation. The formation of silos are often a result of a combination of factors, including mergers and acquisitions, disconnected teams, interdepartmental dynamics, lack of data control, etc.
To prevent the formation of data pockets across organizations, enterprises must cultivate a data-sharing culture rather than a data-owning one. Eliminating silos begins with a cultural shift, necessitating a change in perspective that starts at the top in an organizational hierarchy. Enterprises can adopt several strategies to eliminate such data silos and prevent them from perpetuating.
Various teams in a company hold data close to their chest, as data is knowledge, and knowledge is power. Various verticals typically work with exclusive jargon and processes pertaining to their own departmental goals. Each team sees itself as somewhat remote and distinct from the others, and segregated workspaces compound this spirit of disharmony.
All this leads to a sense of ownership and reluctance to share data with other teams among individual groups, which may harm the organization’s larger interests. Instead, organizations can nurture a culture of sharing and enabling a free flow of information. In doing so, they must also address the concerns of each group about data sharing and guarantee a mechanism to maintain data integrity.
Incentivizing and motivating individual teams to come together and nurture a culture of open data sharing and data unification is key to adopting enterprise-wide data connections. These initiatives resolve data silos, inspire a positive cultural change, turn the wheel of innovation, teamwork, and interdisciplinary efforts, and foster higher collaboration among the leadership.
Typically, various departments work in isolation, even while supporting one another to serve a common objective. Companies need to act as a single unit to optimize available datasets and improve team spirit, productivity, and output quality. While enterprise-wide sharing of information is key to augmenting productivity and generating novel opportunities, data silos pose a barrier to information accessibility, weakening the overall operational efficiency.
Operational inefficiencies can make discovering hidden opportunities difficult. Consequently, educating departments on how data silos endanger organizational success is critical to changing the overall data approach. It is essential to communicate to the teams about the benefits of collaboration and the adverse effects of silos. Promoting information sharing, transparency on task handling, and cross-functional cooperation breaks down silos.
Leaders must encourage team managers to prioritize addressing of silos and guide the whole organization to ensure a shift in perspective. The workforce needs to understand the basics of data silos and what can be done to fix them. They need to be aware of the data quality problems that stem from silos. To bridge the knowledge gap, enterprises must communicate the benefits of data sharing and data integrity, allowing the workforce to comprehend the shift better.
If the challenge of data silo continues to persist, they start developing organically, once again reflecting on the organizational work culture. The enterprise setup itself enables silos to build up over time. It happens when every department gathers and amasses its data sets, each with its own guidelines, measures, and targets.
Teams working in various departments cultivate their style of getting things done or processing data in ways most suitable to their requirement. These practices cause silos to accumulate gradually.
The culture of working separately in various groups compounds the problem of silos. Besides this, the technology and data management systems often differ from department to department, spanning over tools such as spreadsheets, accounting software, or CRM. Besides, most legacy systems cannot handle information sharing as each solution stores and analyze data in distinct ways, which naturally paves the way for silos to grow over time.
Data needs continued care and systematic solution to manage and prevent the effortless accumulation of silos. Additionally, the best-of-breed technology acquired by enterprises could generate unintentional data silos too. Businesses that need specialized technology must keep an eye on this aspect.
Companies across the globe are now centralizing data and sharing accurate versions of data to save time and cut costs. Enterprise-wide data glossary can be created to offer guidance across the board on data utility and storage. These data definitions equip interdisciplinary teams with pointers on how to comprehend data, create shared storage, and curb data silos.
They need to sustain and evaluate data standards across the internal and external ecosystems. It is crucial to note that putting all data into a single system will not deliver the required result by default. Hence, it is essential for companies to create cross-functional teams to push the agenda of data integration forward.
Every step should be towards integrating data for the entire enterprise, including the various departments, to avoid recreating a new set of silos. It is crucial to integrate data discipline across all the departments and impart mindfulness about the innately dynamic nature of data.
With the advent of cloud technology, centralizing data for analysis is becoming easier and faster. Cloud-based tools rationalize the data gathering process into a shared pool, due to which tasks that once took months and years to complete now take days and hours.
The roadmap for data silos elimination needs to include finding a way to centralize data. A central data repository optimized for efficient analysis is the key to finding solutions for data silos. The next thing is to integrate data correctly and effectively to prevent future data silos.
Organizations can incorporate data using several methods such as scripting using writing scripts including SQL, Python, or other languages to transfer data from siloed data sources and into a data warehouse. On-premises extract, transform, and load (ETL) tools can also automate moving data from various sources to the data granary.
Cloud-based ETL is a sophisticated cloud-enabled process that is faster and easier. The process uses the cloud provider’s infrastructure, working competently in any environment. ETL tools provide ways to collect data from different sources into a centralized location for analysis and eliminates silos.
They also solve data integrity problems by ensuring new data is available to everyone. Data centralization consolidates data access and controls it with a data governance framework.
Data silos adversely impact productivity, insights, and collaboration. But they can stop being a source of trouble when data is centralized and optimized for processing and analysis. When an organization understands the value of having a single golden repository of data, it changes the culture inherently.
Digital transformation could not truly take place in an organization without first solving the problem of data silos. It takes multiple levels of effort to resolve this problem, including a change in culture, an assessment of short-and long-term tasks, the creation of cross-disciplinary groups, an understanding of data, and a plan to get it all working seamlessly.
While this might seem like a daunting task, going beyond gathering and evaluating data to solve the issue of data silos is instrumental to the success of any digital transformation journey. It begins when organizations migrate to a more proactive approach to leverage the value of connected data.
Featured Image Credit: Provided by the Author; Shutterstock; Thank you!
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