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Breaking down silos: Combine legacy and modern data sets for successful data transformation

Last updated on October 24th, 2022 at 11:28 pm

By Steven Karan, Vice President of Insights & Data, Capgemini Canada

Data is the key to unlocking business insights, and organizations looking to remain competitive in the market must master the art of data strategy. Despite this need, most modern enterprises struggle with where to start – and how to make data transformation a financially prudent process. 

For data experts, the challenge facing organizations is very clear: siloed data. By breaking down silos to combine legacy and modern data sets, leaders can unlock a more consolidated view and realize the value of the data being collected, rather than missing out on crucial insights tucked away in various corners of their business. 

The option to undergo a data transformation is widely available, but only recently have organizations begun to truly realize the negative ramifications of maintaining a decentralized data collection process. 

Witnessing the benefits of consolidation – much like missing a party you weren’t invited to – creates a “FOMO” effect. Leaders who don’t take the leap to proactively break down silos will soon realize that the fear of missing out on a competitive edge is far greater than the challenge of combining legacy and modern data sets. 

Understanding the need for consolidation 

As enterprises have begun to move from on-prem to the cloud, the inefficiencies of legacy systems have become increasingly clear. Bringing together modern data unlocks value insights that were previously inaccessible. By moving to a new data platform paradigm – such as a data lakehouse – the entire enterprise migrates, resulting in a culture shift from command and control to a more customer-centric model.  

Consider highly valuable customer data in a legacy system collected by the finance department that isn’t being leveraged for marketing because the two business units leverage separate data warehouses or are otherwise disparate. Breaking down the silo between departments forces the leaders across the organization to connect, driving better customer outcomes and delivering better insights holistically. 

Beyond efficiency, modern solutions have significant cost benefits. Legacy on-prem solutions are more expensive to upkeep, whereas cloud solutions drive down the overall cost of data by eliminating the overhead associated with on-prem solutions. 

Furthermore, siloed data presents risks to data integrity. Maintaining a handful of separate data pockets – each owned and operated by different teams – presents cybersecurity risks that can be costly for an organization to manage and also risks the trust of customers. 

Pillars of a successful transformation

There are several key components and digital capabilities that make this process successful, including: 

  • Strong executive sponsorship promotes robust change management to ensure common goals and communicate benefits clearly. 
  • An empowered, de-centralized governance approach prevents internal issues and data breaches, improving overall security.
  • A change management plan outlines goals and ensures that leadership can pick the right ecosystem of solutions. 
  • A well-architected, vendor-agnostic solution combines the data sets and accelerates how quickly legacy data can move into the cloud. 
  • Understanding the requirements, types of data (structured/unstructured), and company goals reveals the right solution with the right extract, transform, and load (ETL) tools. 
  • A strong data ecosystem of partners outlines what will be managed internally and what will be leveraged externally
  • A talent strategy that leverages the correct composition of skills to guarantee a successful transformation journey

For example, organizations utilizing B2C as their main source of revenue can benefit significantly from developing a platform that provides a 360-degree view of their customer. This type of system provides information on how to better serve customers with the right promotions, customer experience (CX) initiatives, and beyond. In one recent case study, a consumer-packaged goods company migrated their data tech stack to a data platform of record with a holistic customer view and saw immediate results – lowering the cost of data operations by 33% simply by moving from legacy to the cloud. 

Benefits of a scaled approach

The way organizations approach data transformation is typically impacted by culture differences – with some regions willing to take bigger bets while others are committed to a more risk averse approach. However, the recent shifts in global business have begun to tilt the needle, with more companies seeking a scaled approach to data transformation. 

With a scaled approach, leaders may not see the immediate growth and results, but are able to slowly weed out unnecessary elements and build out their modern platform over time. With this method, the OpEx cost is lowered while the CapEx cost increases, all while the organization becomes familiarized with what a consolidated platform actually looks like in real-time. 

This snowball effect demonstrates credibility and allows the enterprise to gain alignment internally and with stakeholders, unlocking savings and value as they progress through the process. 

As cloud continues to increase in prevalence, many companies will begin looking to sunset legacy tools and make way for new systems. The key to successfully undergoing this process is to ensure the existence of guiding principles and outline a well-constructed data strategy from day one. 

To maximize return on investment (ROI) and avoid carrying old technical debt into a new structure, establishing a centralized data storage system – and waving goodbye to silos – will set any organization up for success.

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