Data Integration Digital Transformation
Digital Transformation Technology

Data Integration – The First Step Towards Digital Transformation

What began as a buzzword two decades ago, digital transformation is a mainstream phenomenon in the business world with almost every organization making calculated moves to transform part or all of their business with technology solutions for better results. 

In fact, by 2023 it is expected that digitally transformed organizations across the world will contribute a wealth of about USD 53.3 Trillion or in other words more than half of the world’s nominal GDP figures. 

As massive as the impact may seem, several businesses fail to follow a disciplined approach to transform their organization with digital technology available in the market. 

Jumping too fast into digital without the basics – the most widespread mistake in digital transformation

One of the biggest mistakes that most organizations make with their digital transformation is ignoring the importance of data integration and proceeding with investing in powerful digital platforms across their business units. 

While digital platforms can make jobs easier for people in different departments, operating them in silos will hurt the organization as a whole. When leaders realized the importance of data-driven processes, they were quick to add new data generation and collection mechanisms. Today’s businesses have no scarcity for data or information, but the key challenge is leveraging benefits from this abundance of data by plugging them into meaningful business use cases. 

Read: A Digital Transformation Framework for Small Businesses

Data Integration as the first step of a successful digital transformation

The first step of every digital transformation initiative within an organization should be data integration. There should be a mechanism that captures or collects data from across sources like data warehouses, data lakes, cloud application data stores, in-house local servers, and streaming data from field devices or operational environment data sensors. For the entire business to realize benefits from data, there is a need to filter out unproductive data and supply only high-quality information to various business systems in formats they require for processing.

Decluttering the complexity of digital experiences through data integration – An example

Let’s examine how data integration can act as a catalyst for a unified digital experience in an organization. 

For simplicity, let us cover remuneration as a use case within an organization. From the time a candidate is hired, he or she gets inducted into the organization, multiple teams would be involved in calculating the final wage paid to the person at the end of the month or on the time period specified in their employment contract. 

For processing the payment, payroll administrators would require information such as 

  • The candidate info and their subscribed benefits like insurance, medical claims, etc., from the HR department
  • Their billable or clocked work hours from their respective department or project’s work management group
  • Their leave information from the leave management system 
  • Any added benefits or deductions as applicable for the past month to accommodate the special needs of either the company or the employee, the details of which may be stored siloed in multiple intradepartmental systems.  

For automating the entire experience, systems handling operations at different departments must supply data on demand to the payroll management system, all calculations need to be autonomously managed, and a trigger for paying the correct settlement to the employee’s bank account needs to be made to the finance department for releasing the payment. 

Data from different departments may be stored away in different formats like spreadsheets, forms, or in the form of textual elements in databases. For the unification of different data streams, organizations need to put in place an integration mechanism like a data integration hub. Such a data integration hub can collect all information and insights from various data streams, extract quality information from the streams, and supply them on demand to different systems autonomously after converting them into formats they require. 

The integrated data architecture eliminates time spent in validating the source of every data required for a transaction (in this example, the salary settlement). With an integrated view, the leadership team can get a bird’s eye view of the entire process and filter out patterns from different departments that cause unexpected changes in the functioning of the whole process. For example, it becomes easy to gauge insights such as what digital systems or capabilities are needed by the HR to quickly facilitate timely delivery of information to other dependent systems. 

The right data (and not abundant data) makes a difference

Having a large pool of data may be convincing for leaders that their digital strategy is well put in place. However, without proper integration of the data with multiple systems and a unified architecture in place for seamless data quality assurance and interoperability, this siloed data is not any worthier in a business sense than the old mechanism where data generated was scarce. Every department within the organization from finance to HR, marketing, sales, operations, IT, legal, etc. have their own fortifying data protection and management policies which have been drafted from years of governance. The problem arises when inputs from one or more departments are needed for creating a unified experience for their customers Even if one departmental system creates a problem with their data, the entire transaction of the business with a customer may come to a grinding halt. The example highlighted here portrays how data integration simplifies digital transformation and sets the backdrop for a scalable experience for all stakeholders. Growing enterprises with digital ambitions definitely need to pay attention to this.

Would it be useful if you had access to data integration and analytics solution allows for the customizations as per the specific business needs? Would you like it if you can kick-off your data initiatives in less than 6 months?

Let’s connect if this is something that interests you.

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