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Making a business case for data management

10 November 2021 Greg Farrington

Identifying a data management solution that will address the needs of the business is only part of the challenge for data and technology leaders. An equally important aspect of the job is ensuring internal buy-in from both the exec who will sign the check and future users of the solution.

These observations are underlined by the findings of new research about data management conducted by the organizers of the FIMA conferences. When asked about the biggest challenges for driving investment in data management technology, 45% of respondents said obtaining buy-in from key stakeholders was one of their biggest hurdles, while roughly 40% said they face a major issue convincing teams that the new solution will help them or the organization as a whole.

So how do you overcome these challenges and win support for the data management solution that you know will help your organization? In my experience, data and technology leaders must be able to answer the following questions clearly and fully:

  • How will the new solution create value?
  • How will it make teams' workflows simpler and more efficient?
  • What is the cost of not having a single trusted version of your critical business data?

The first step in answering these questions is to identify the pain points in your current data management processes. Data management is a broad term that touches numerous areas of a business. As such, it is critical to identify exactly where the data management process is falling short today and where improvements should be a priority.

Understanding this fully can help both when choosing the data management solution that best fits your needs and when identifying opportunities for efficiencies, cost savings and workflow optimization that will help make the case to internal stakeholders.

My team and I work closely with clients and prospective clients to help them build business cases for new data management programs. When doing so, we focus on the following categories of tangible, quantifiable benefits:

  • Automating Manual Processes: It is important to look across the incumbent operational set-up and consider (A) how many people are involved in supporting the data management process today and (B) how many could be redeployed to higher-value projects if an optimal data management platform was used to take ownership of those operations. With regulatory scrutiny and competitive pressure increasing, the inefficiency and operational risk associated with spreadsheets and other manual processes are no longer sustainable.
  • Eliminating Duplicative Efforts: Too often, various business lines in an organization collect and process exactly the same data in different silos. It is not uncommon to find that a firm is replicating the same work two or three times or paying for the same data feed several times. The right data management solution and right implementation strategy (read my colleague Natalia's recent blog for more on implementations) can create meaningful savings by centralizing data from across the enterprise, and validating and mastering it once before distributing it to downstream systems and users. For some of our clients, the primary driver for undertaking a data management project is the cost reduction they will achieve by eliminating duplicative requests for high-cost data.
  • Time to Market: Firms are under intense pressure to deliver change quickly, but this can be challenging when using inflexible, legacy systems. As businesses grow, it is critical that they have operational and technology infrastructure that will scale with them. The same applies to internal processes. For instance, many firms still have key person risk, in which a single individual manages a crucial business process or operation. Data and technology leaders can mitigate this risk by identifying these vulnerable areas and migrating them to an automated platform.
  • Confident Decision-Making: Industry participants increasingly view their data as a strategic asset. The ability to consume multiple sources of data, often in near real-time, in multiple formats has become a basic requirement for many. By implementing suitable data quality, governance and transparency rules, users at these firms can be truly confident in the data they use to inform their decision-making. Data lineage is also becoming a critical factor for demonstrating regulatory governance.

Identifying and quantifying the above opportunities to increase efficiency, reduce costs and optimize performance will meaningfully strengthen the business case for investing in a new data management solution. The role-out of a new enterprise-wide initiative (such as ESG) or preparations for major regulatory change also present good opportunities to review the internal data and technology landscape.

Drawing on experience

Most financial firms conduct a strategic evaluation of their data management processes only once every decade or two; it is just not part of their day-to-day focus. In contrast, it is something that my colleagues and I contribute to regularly to support our clients and prospective clients. As a result, we have a huge pool of experience and expertise to draw on, as well as insights into best practices. We can also offer use cases and references that can provide stakeholders with a clearer picture of the value our EDM Solution Suite offers and how it can work for their organization.

By focussing on quantifiable benefits and drawing on the experience of your data management provider, you can put together a compelling business case that will win support for your chosen solution.

For more on this topic and insights into the latest data management technology trends, download the full white paper here.

IHS Markit provides industry-leading data, software and technology platforms and managed services to tackle some of the most difficult challenges in financial markets. We help our customers better understand complicated markets, reduce risk, operate more efficiently and comply with financial regulation.


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