Buy vs Build – Leverage a Specialist Data Validation Service Provider for Systems Upgrades/Migrations

Introduction

When it comes to systems upgrades or migrations, data validation plays a crucial role in ensuring a smooth transition and maintaining data integrity. Organizations are faced with the decision to buy vs build. In this blog post, we will make the case for engaging an expert data validation service provider, highlighting the numerous benefits it offers over in-house development.

Access to Expertise and Specialized Knowledge

Engaging a data validation service provider brings immediate access to a team of experts who’s specialty this is. These professionals have extensive experience in handling all types of data validation challenges. They are well-versed in complex performance and risk analytical data needs, compliance requirements, industry best practice, emerging trends et al. By leveraging their expertise, organizations can ensure comprehensive and accurate validation of their data during systems upgrades or migrations.

Speed and Efficiency

Systems upgrades and migrations usually come with tight timelines and deadlines. Engaging a data validation service provider allows organizations to leverage their established methodologies, tools and frameworks, resulting in faster and more efficient data validation processes. Specialist service providers have already built and refined their data validation solutions, enabling them to swiftly deploy and execute the necessary data validation tasks. This helps organizations meet critical project timelines and minimize costly disruptions and delays.

Cost Savings and Scalability

Most things are possible if you throw enough money, people and time into the effort but who wants to develop their own in-house data analytics validation solution? This development would require significant investment in terms of resources, time and ongoing maintenance at the expense of a strategic investment for the firm. Engaging a data validation service provider eliminates the need for these upfront costs and allows organizations to leverage the specialist provider’s infrastructure and resources. Data validation service providers typically offer flexible pricing models, allowing organizations to scale their data validation efforts based on their specific needs. This ensures cost and time savings and the ability to adapt as project requirements evolve (which they invariably do!).

Reduced Internal Burden and Resource Allocation

Building an in-house data validation solution requires organizations to allocate critical resources, including skilled developers, data experts and IT personnel. Engaging a data validation service provider relieves the burden on internal teams, enabling them to focus on their core competencies and strategic initiatives. This allows organizations to leverage external specialist resources without the need for extensive recruitment or training efforts, ensuring an optimal allocation of resources internally.

Access to Advanced Tools and Technologies

Data validation service providers invest in advanced tools and technologies to enhance their data validation capabilities. By engaging a specialist provider, organizations gain access to these tools without the need for additional investment. Providers leverage cutting-edge technologies such as automated data validation engines, machine learning algorithms, and data quality frameworks to ensure accurate and efficient data validation. This helps organizations leverage the latest advancements in data validation without having the build and ongoing maintenance.

Lack of Priority and Budget

Unlike specialist data validation service providers whose focus this is, in-house data validation solution initiatives often struggle to receive the necessary priority, budget allocation and senior management attention. They may be considered less urgent or strategically unimportant compared to other initiatives, resulting in limited resources and reduced funding. Consequently, the internal build is likely to be compromised, leading to an incomplete or inadequate outcome which is not fit for purpose. Also, whatever investment was made would have been wasted.

Perceived as Core vs Peripheral

In-house data validation solutions are sometimes seen as peripheral to core business functions. They may not receive the same level of attention or support as other critical initiatives, resulting in limited stakeholder engagement and less organizational commitment. This can hinder the development and maintenance of a robust and comprehensive data validation solution. For specialist data validation service providers the solution is primary & core to the business.

Vulnerability to Cost Cutting

When organizations face cost-cutting measures, ‘under-the-hood’ initiatives are often the first target. The lack of visibility and understanding of the data validation solution’s critical importance may lead decision-makers to consider it as a non-essential expense. As a result, there may be insufficient investment and inadequate resourcing/time for a working solution let alone ongoing maintenance and enhancements.

Technical Credit & Reusability vs Technical Debt and Throw-Away Efforts

In the absence of dedicated budget and long-term planning, in-house data validation solutions are sometimes built as throwaway developments in an ad-hoc manner. This approach results in accumulating technical debt – making future enhancements and scalability developments necessary and more challenging. The lack of a comprehensive and cohesive strategy leads to repeated efforts and rework, increasing development time and costs, and still with no robust scalable solution in place to show for it.

Resource and Skill Constraints

Building an in-house data validation solution requires skilled resources with expertise in data management, validation techniques, and technology infrastructure. However, organizations may face challenges in attracting and retaining such talent due to competition in the job market or limited internal resources. This resource constraint can impact the development and ongoing maintenance of the solution. Also, these hires – if you can get them, command high compensation given their close working experience with data analytics such as portfolio modeling, performance attribution, risk analytics, compliance monitoring etc.

Maintenance and Support

Once the solution is built, ongoing maintenance, updates, and technical support become the responsibility of the organization. This can place a burden on internal IT teams, diverting resources from other critical tasks and initiatives.

Conclusion

Essentially, every firm needs a specialist data validation solution, even if they don’t know it, but it’s only a specialist service provider who’s willing and able to make that strategic investment in people, technology and time that results in a robust, scalable solution that works for now and for tomorrow. How many migrations, upgrades, conversions and outsourcing arrangements are disrupted and delayed, with fractious finger-pointing over data quality, for the want of a data validation solution that’s fit for purpose?