In the past, when technology wasn’t yet developed enough to support broad and efficient sourcing, selectors naturally leaned on who they could trust. Working with managers they already knew or had partnered with before wasn’t just convenient, it was a practical way to manage knowledge and build confidence in performance.
When tools for global comparison are limited, trust and familiarity served as the foundation of manager selection. And rightly so.
However, this model is being challenged, driven by digital transformation in investment manager selection. Today, selectors are looking beyond their longstanding networks and uncovering new managers that align more with their objectives.
The traditional relationship-driven model, while valuable in fostering trust and continuity, can also introduce unintended blind spots. Relying too heavily on familiar networks or preferred lists can create structural constraints, narrowing the field of consideration. As a result, selectors may unintentionally overlook managers who are better positioned to meet the specific needs of their portfolios. These may include boutique firms with stronger ESG alignment, deeper expertise in emerging or niche asset classes, or differentiated risk-return profiles that better match their portfolio’s strategic objectives.
This is where the digital transformation in investment manager selection is proving to be a welcome necessity. New platforms and technologies enable selectors to scan the manager universe more broadly and objectively, supported by data-led insights that go deeper than reputation or proximity. With structured evaluation frameworks and advanced filtering capabilities, selectors can now assess managers based on consistent criteria, eliminating noise and focusing on substance.
By building on, rather than discarding, traditional relationships and coupling them with systematic evaluation processes, technology provides the missing layer of rigor and scale. It ensures that manager selection becomes not only more inclusive, but also more precise. Selectors are no longer constrained by who they know; they are empowered to discover who is truly the best fit, based on evidence, alignment, and measurable potential.
Digital tools aren’t just more efficient, they’re strategically essential.
In this new paradigm, asset manager selection is a data business. Success is cemented by what you can analyse and validate. Institutional investors are having higher demand to back their decisions with evidence such as performance metrics, consistency across market cycles, qualitative team assessments, ESG integration depth, and clarity in reporting practices. Data, within this context, does not replace human judgment; it sharpens it. It enables selectors to ask better questions, focus discussions, and build conviction not just in a firm’s track record, but in its ability to deliver on a specific mandate.
The historical reliance on long-standing relationships and preferred manager lists is certainly not disappearing. But it’s evolving. These relationships are now supported and strengthened by rigorous, data-led sourcing models that prioritise suitability and precision. With access to better tools and deeper datasets, selectors can expand their field of view while applying a more disciplined lens, ensuring that each manager relationship is built on alignment, not just familiarity.
Consequently, this shift reflects a broader understanding of why data matters in manager selection. It enables selectors to reflect on whom they have known to dive into real comparative analysis: risk-adjusted returns over time, consistency through market cycles, or team and process stability. Data makes these insights visible, comprehensible and attributable.
By using data to drive asset manager relationships, selectors are no longer limited to established lists or legacy networks. They’re empowered to evaluate a broader universe of managers with systematic discipline, ultimately prioritising alignment, and evidence. This isn’t just efficiency. It’s precision.
To be clear, this shift isn’t about replacing sales teams for their role remains essential. In the tech-enabled manager selection sphere, conversations start with, and are backed-up by, data.
Dialogue comes after data.
With the rise of enterprise applications in the investment management industry, asset manager selectors now should have the tools to screen, benchmark, and short list managers based on quantitative metrics and qualitative insights before any meeting is scheduled. This means performance, transparency, and alignment become the most important and supportive filters, along with personal introductions or peer recommendations.
This shift fundamentally improves the quality and efficiency of the selection process. Performance data, risk-adjusted returns, style drift, team stability, fee transparency, and so on, can all be analysed upfront, creating a clearer picture of each manager’s suitability. At the same time, technology can surface softer, qualitative signals that are crucial to understanding long-term fit, such as strategic focus, philosophy, and operational resilience, etc.
Consequently, these data points, now standing alongside traditional routes, provide a more robust and defensible foundation for engagement with asset managers. Better technology in manager selection allows investment manager selectors to enter conversations better informed, more focused, and with greater clarity on where it really matters.
This way, once asset managers receive meeting requests, it would save both the managers and the selectors time for casual introductions as they’ve already passed through a robust pre-qualification process. When selectors leverage data-driven technology and innovative tools to screen and evaluate managers upfront, only those who demonstrate a clear strategic fit, proven capabilities, and alignment with mandate requirements are invited to the table.
As a result, once the global relevant opportunity set is identified through a structured evaluation, sales teams can step in to contextualise those numbers, creating more focused and deepened strategic conversations with asset manager selectors.
In this way, technology doesn’t sideline sales, it actually increases their win rates.
This level of pre-vetting, hence, brings a significant advantage to asset managers: the probability of winning is substantially higher. Instead of spending time and resources on broad prospecting or unfocused meetings, managers are being considered in contexts where the buyer has already identified a potential match. The discussion is moving above “who are you” directly to “how exactly can you deliver on what we’re trying to solve for.”
Thus, technology removes noise from the process, ensures mutual relevance, and fosters higher-quality conversations from the very first interaction.
As discussed above, a data-first approach empowers investors to scan the global market with precision and build decision confidence. With the right tools for manager selectors to scan asset managers globally and analyse data deeply, selection teams can evaluate strategies side by side based on hard evidence.
Strategic partnerships now follow exceptional fit and proven value, not precede it.
By employing technology in the process, manager selectors can expand their lists, as well as create the conditions for more deliberate, merit-based decisions. When technology is embedded into the early stages of manager research and shortlisting, it levels the playing field. It creates an environment where excellence rises to the top, regardless of a firm’s size, history, or proximity to the selector.
An innovative infrastructure, purposefully built for the manager selection process, enables selectors to apply tailored filters across both quantitative and qualitative dimensions: from performance consistency, downside protection, and fee structures to ESG integration, team diversity, investment philosophy, and even cultural fit. These preferences can be calibrated to reflect the unique priorities of each mandate, making the discovery process broader, smarter, and more aligned with long-term objectives.
This level of precision and personalisation simply isn’t feasible through manual processes or relationship networks alone. It requires an infrastructure designed specifically for the complexity of decision-making. That’s why the demand for modern, transformative digital solutions for asset manager selection teams is rising sharply. These solutions don’t just speed up workflows; they enhance transparency, improve collaboration across teams, and unlock better alignment between manager selectors and managers from the very start.
As the future of asset manager selection is being reshaped around three core principles: transparency, merit, and strategic fit; the winners in this new era will be those who embrace data as the foundation and use relationships to enhance their manager selection strategy. It’s not about rejecting human connection; it’s about leveraging it, ensuring that every conversation is pre-qualified for mutual alignment in order to maximise the outcome for both manager selectors and asset managers.
Technology is changing how asset manager selectors select asset managers. Selection is no longer driven by relationships and familiarity alone, but supported by data. Asset manager research technology is shifting the focus toward breaking legacy monopolies, updating the role of sales, and setting new data-led standards. Relationships still matter, but today, they begin with insight, not instinct.
With contributions from: Abigail Dahlan is a Product Specialist responsible for enhancing the user experience of our manager selection and investment manager clients. Thao Do is a Marketing Specialist responsible for creating new thought leadership to help our users enhance their knowledge of our products.
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