Data is often considered the oil of the 21st century. To move forward in a world increasingly being influenced by digital transformation, businesses need to generate as many actionable insights as possible from the business data. This can help the management to make data-driven decisions across their entire operational landscape.
Even before the COVID 19 pandemic, a McKinsey organized survey of enterprise leaders found that budgets on data-related initiatives from businesses are likely to increase 50% year on year. While today, we have technology ranging from simple data analytics to high-end artificial intelligence-driven data processing to uncover actionable insights, there is still a big challenge to overcome for enterprises before unlocking the benefits of data in their ecosystem – data silos.
Today even though, we have technology ranging from simple data analytics to high-end artificial intelligence-driven data processing to uncover actionable insights, there is still a big challenge to overcome for enterprises before unlocking the benefits of data in their ecosystem – data silos.
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In simple terms, a data silo is a collection of data or information collated by one group of people, processes, and systems in a functional unit. This data is inaccessible to other groups or group entities owing to differences in data governance, modeling, and security policies followed.
Data silos occur in every enterprise. As the size of the business increases, the data silos expand in volume considerably.
So why do data silos occur?
Every individual department within an enterprise may follow age-old practices of collecting, processing, and storing their functional data. They may use different applications, databases, and processes to handle various activities and daily work routines.
Each of these data stores or information silos may get populated with a large volume of data over time. When the number of departments increases the number of data silos and the diversity of data within each silo also increases exponentially. Ultimately, the business would experience barriers to their digital ambitions as different departmental systems may find it nearly impossible to exchange data. Even if they somehow manage to interoperate, data quality may be compromised.
Only when data from different departments are easily understood and seamlessly exchanged within the enterprise, can it be called healthy data. To ensure success, decision-makers need a 360-degree view of the data to analyze and infer insights from them. This is where enterprises need to learn the art of reaping actionable insights from data silos.
Here are some strategic inputs on how to enable your enterprise to solve the challenge of data silos and uncover actionable insights or intelligence from them:
Nearly 80% of the job for data scientists in an organization are related to data preparation i.e. collecting the data from disparate enterprise systems and repurposing them into desired formats for analytical processing and modeling. This humongous effort is because different departments or teams within the organization do not have a singular objective on data management. For leaders, this is the right time to set up a unified data management framework for the entire enterprise.
By forming a core group of experts from every department, businesses must create a uniform policy for data generation, the schema of models to be followed for processing the data, and a common protocol for storing information. The importance of doing so must be made aware to all employees with the core group members becoming the advocates of promoting unifying objectives within their respective teams.
As soon as a cultural shift from teams towards unifying their data objectives is achieved, the focus from leaders must be on ensuring that different functions or departmental business systems are able to leverage a centralized data pool. This will serve as a single point of truth from which collaboration, innovation, the agile transformation of processes and people can all be centered on. It eliminates multiple answers for the same question from a functional perspective. This bolsters the ability of the organization to achieve synchronization in their storytelling efforts and boost marketing efficiency.
Software applications deployed across multiple departments may have been implemented over the years when data governance standards were rarely a requirement. Communication gaps between different business systems are a major source of the formation of data silos within an enterprise. In fact, studies show that nearly 84% of employees feel that a business is missing out on leveraging value from their data due to being stuck with legacy solutions.
Enterprises must re-visit their application development strategies to ensure a fair representation for data management and silo elimination objectives in future apps. They should also make investments in transitioning and re-engineering existing legacy applications to ensure their data models are in sync with expected data quality metrics.
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Once a unified data collection and storage framework is in place across the enterprise, the next step is to ensure seamless integration of different business systems. This will ensure the availability of data across systems for cross-functional analytics as well as decision-making. However, to achieve this seamless transition, there is a need for the organization to become preachers of agile digital systems.
The IT department needs to transition from a “Deny All First” principle for information access to a “Facilitate Everything” mode of operations. By setting appropriate controls on how information governance needs to be made in every department, the role of the IT department must be to create a framework with guidelines for different teams to freely manage data workflows within the enterprise. This will eliminate bureaucratic and political delays that are often found in large corporations which are in desperate need of data-driven insights.
Corporate data has endless value but if only an enterprise knows how to use it. While modern technology can help in utilizing data for better business, it is imperative for enterprises to first ensure that they make quality data available for the same. As we move further in the digital economy, more unique data sources will emerge in the markets like the Internet of Things. Creating a strategic data management and information exchange framework at the earliest will help enterprises to compete and succeed against competitors faster.
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