What’s making companies stumble so badly?

Reasons point back to a basic failure to understand what transformation is and, therefore, how to take advantage of its possibilities. Both McKinsey and HBR cite the need for companies to bring a big picture view of their organization to the table, and to factor in well-thought-out vision and mission perspectives over a checklist approach that simply improves short-term business-as-usual results.

BCG underscores the importance of a long-term strategic orientation: “Beyond mindset, culture, and metrics, a long-term orientation also means investing in the exploration of new ideas that could be the basis of future advantage,”and also suggests factoring in the sad reality that “when it comes to transformations, no one is special.”⁵

The odds of achieving all aspects of an ambitious change are low, and have been persistently low over time, despite lessons learned. That’s why approaching a transformation with an entrepreneurial outlook, in which you are open to new ideas that are anchored to your fundamental long-term vision, will allow you to think strategically and not tactically, and result in greater success.

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Apply lessons learned to technological transformation

A technological transformation may be transformative in itself or it may be part of a larger business transformation. In either case, lessons learned from business transformations also apply:

Lead with a comprehensive future-focused mission
Consider the process a series of mini-transformations that may even continue beyond the program, rather than a single flip of the switch
Be open to new ideas throughout
Learn from the mistakes of your competitors
Position for tomorrow’s opportunities, not just today’s crises

For some financial companies, technological transformation is no longer optional because operational issues are swamping resources. Others have realized their solution to poor performance and/or cost overruns lies in a data and systems overhaul. Many firms still have datasets locked up in legacy platforms or other function-specific silos. On the flip side, many aspire for AI to be a game-changer for their organizations.

Wavestone’s latest Data and AI Leadership Executive Survey, primarily CDOs and CDAOs, found that investments in data and analytics were a top priority for 87.9% of firms, while 62.3% also cited investments in GenAI as a top priority.⁷

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Modern data architecture is foundational

Whatever their particular goals, firms should stay focused on achieving a target state of unified data architecture, instead of chasing the technology of the day or the latest trend. Not only do siloed structures fiercely limit scalability, but they also trap enterprise value. A centralized data and tooling system addresses, among other downsides, the high cost of ownership, poor governance, and unreliable data quality issues of disparate or redundant stacks. The right architecture allows you to run your business in a more optimized, streamlined way.

As studies have shown, the key to many business or technology transformation projects is organized, clean data. From more efficient, effective reporting to integrating middle- and back-office functions to generating trustworthy modelling, achieving the results expected from an investment in transformation begins with data quality.

For example, data quality is central to AI. Predictive models that rely on low-quality data will result in equally poor-quality predictions and recommendations. Companies reliant on modeling to make strategic decisions on products and services are taking a risk to leapfrog to AI without addressing their significant data issues. Even the more fundamental task of digitizing what was previously manual data entry requires understanding where that data comes from, how it’s used, how it’s verified, and who needs access to it for analysis and reporting, among other uses.

Put another way, a single unified platform with robust specialized capabilities allows financial companies to move their data strategy forward, building in resiliency and allowing for ongoing transformation.

Sources:

1. Five Truths and a Lie About Corporate Transformation, Boston Consulting Group. April 12, 2024.

2. Business Transformations that Work, Bain and Company

3. Losing from day one: Why even successful transformations fall short, McKinsey & Company, December 7, 2021

4. Transformations that Work, Harvard Business Review, May-June 2024

5. Five Truths and a Lie About Corporate Transformation, Boston Consulting Group, April 12, 2024

6. 2024 Data and AI Leadership Executive Survey, Wavestone, January 9, 2024