Quality Control: How to check for errors in your investment performance

Sean P. Gilligan, CFA, CPA, CIPM
Managing Partner
May 5, 2021
15 min
Quality Control: How to check for errors in your investment performance

Recent investment performance calculation mistakes at Pennsylvania Public School Employees’ Retirement System (“PSERS”) have highlighted the importance of quality control reviews and raises questions about where risk exists, how these risks can be mitigated, and what role independent verifications should play in the quality control process.

What happened at PSERS?1

An error in the return calculation for Pennsylvania’s $64 billion state public school employee retirement plan has had serious implications for its beneficiaries and those involved in the calculation mistake.

In 2010, the plan, which was already underfunded, entered into a risk-sharing agreement where employees hired after 2011 would pay more into the plan if the return (average time-weighted return) over a specific time period fell below the actuarial value of asset (AVA) return of 6.36%.

In December 2020, the board announced that the plan had achieved a return of 6.38%, a mere 2 basis points above the minimum threshold. But in March the board changed its tune, announcing that the calculation was incorrect and the 100,000 or so employees hired since 2011 (and their employers) should have actually paid more into the plan.

What’s worse is PSERS also announced that the FBI is investigating the organization, although details of the probe have not yet been released.

According to PSERS, a consultant, that had calculated the return, came forward and admitted to the calculation error. But the board also said that it is looking into potential cover up by its staff. From what we know, at least 3 independent consultants were involved in providing data used for the calculations, calculating the returns, and verifying the returns. So, with all these experts involved, how could this happen and what can your firm do to avoid a similar situation?

Key issues to address in an investment performance quality control process

Firms should develop sound quality control processes to help identify errors before results are published. Often these processes either do not exist or are insufficient to identify issues. Following a robust quality control process that considers the key risks involved and then finds ways to mitigate these risks greatly increases the accuracy of presented investment performance.

Although we do not yet know the cause of the errors found in the PSERS case, we can highlight a few primary reasons errors occur in investment performance reporting. Primarily, errors found in published performance results are caused by:

  • Key Issue # 1 – Issues in the underlying data (e.g., incorrect or missing prices, unreconciled data, missing transactions, misclassified expenses, or failing to accrue fixed income)
  • Key Issue #2 – Mistakes in calculations (e.g., manual calculations that fail to match the intended methodology)
  • Key Issue #3 – Errors in reporting (e.g., publishing numbers that do not match the calculated results)

A robust quality control process should specifically address all three of these areas.

Considerations when designing a robust quality control process

Key Issue #1 – Issues in the underlying data

As they say, garbage in, garbage out. It is important to ask and address questions confirming the validity of data before it is used to calculate performance. Specifically, consider how the data used in the calculations is gathered, prepared, and reconciled before completing the calculations. Is there any formal signoff from the operations team confirming that the data is ready for use? Has a review of the data been conducted by an operations manager prior to this confirmation being made?

While deadlines to get performance published can be tight, taking the time to ensure that the underlying data is final and ready to use before performance is calculated can prevent headaches later on.

The following is a list of issues to look for when testing data validity:

  • Outlier performance – Portfolios performing differently than their peers may indicate a data issue or that the portfolio is mislabeled (i.e., tagged to a different strategy than it is invested in).
  • Differences between ending and beginning market values – Generally, we expect a portfolio’s market value at the end of one month and the beginning of the next month to be equal (unless using a system where external cashflows are recorded between months and differences like this are expected). Flagging differences can help identify data issues.
  • Offsetting decrease/increase in market value – Market values that suddenly increase or decrease and then return to the original value may have an incorrect price or transaction that should be researched.
  • Gaps in performance – A portfolio whose performance suddenly stops and then restarts may have missing data.
  • 0% returns – The portfolio may have liquidated and may no longer be under the firm’s discretionary management.
  • Very low market values – The portfolio may have closed and is only holding a small residual balance, which should be excluded from the firm’s discretionary management.
  • Net-of-fee returns higher than gross-of-fee returns – Seeing net returns that are higher than gross returns could indicate a data issue unless there are fee reversals you are aware of (e.g., performance fee accruals where previously accrued fees are adjusted back down).
  • Gross-of-fee returns and net of-fee returns are equal – If gross-of-fee and net-of-fee returns are always equal for a fee-paying portfolio, it is likely that the management fees are paid from an outside source (paid by check or out of a different portfolio). The returns labelled as net-of-fee in a case like this should be treated as gross-of-fee returns.

Key Issue #2 – Mistakes in calculations

Mistakes happen, but there are ways to reduce their frequency and impact. First, you’ll want to consider how manual your performance calculations are as well as the experience of the person completing the calculations.

Let’s face it, Excel is probably the most widely used tool in performance measurement, especially for smaller firms. While many firms likely find Excel to be a user-friendly tool for calculating performance statistics, it has its limitations. Studies have shown that up to 90% of spreadsheets contain errors and spreadsheets with lots of formulas are even more likely to contain mistakes. Whether it’s not properly dragging down a formula or referencing the wrong cell, fundamentally, the biggest problem is that users do not check their work or have carefully outlined procedures for confirming accuracy.

Although this may seem obvious, having a second set of eyes on a spreadsheet can save you from the embarrassing headache of having to explain errors in performance calculations. It is even better if this review is a multi-layered process. Having someone review details as well as someone to do a high-level “gut-check” to make sure the calculations and results make sense can reduce this risk. Depending on the size of your firm, this may be easier to accomplish with a third-party consultant, where you serve as a final layer of review.

Having this final “gut-check” can help prevent avoidable errors prior to publication. We find that this final “gut-check” is best performed by someone who knows the strategy intimately rather than a performance or compliance analyst, as these individuals may be too focused on the calculation details to take a step back and consider whether the returns make sense for the strategy and are in line with expectations.

If you use software to calculate performance, you can significantly reduce the risk of manual error, but due diligence should still be performed from time to time to manually prove out the accuracy of the calculations completed in the program. This does not need to be done every time but should be conducted when introducing a new software system and any time changes are made to the program.

Key Issue #3 – Errors in reporting

It may seem silly, but many performance reporting errors come from transposing strategy and benchmark returns in presentations or placing the return of one strategy in the factsheet of another. Therefore, it is important to consider how the final performance figures make it from the system or spreadsheet into the performance presentations. Are they typed? Copy and pasted? Or are the performance reports generated directly out of a system? It’s not enough to complete the calculations correctly, the final reports must also be accurate, so adding a step to review this is crucial.

A similar review process to the one described above can really make a difference, but ultimately, understanding the vulnerabilities of your performance reporting will help you design quality control procedures that address any exposure.

Calculations completed by external performance consultants

Whether performance is calculated internally or by a third-party performance consultant, the same key issues should be considered when designing the quality control process. Due diligence should be done on the performance consulting firm to evaluate the level of experience the firm has with calculating investment performance and what kind of quality control process they follow prior to providing results to your firm. This information will help you determine what reliance you can place on their procedures and what your firm should still check internally.

For example, outsourcing performance calculations to an individual or single-person firm likely necessitates a more in-depth review since this individual would not have the ability to have a second set of eyes on the results prior to providing them to your firm. However, even larger performance consulting firms with robust quality control processes may not have intimate knowledge of your strategies, meaning that, at a minimum, a final “gut-check” should be done by your firm prior to publication.

Reliance on independent performance verification firms to find errors

Many firms that hire performance verification firms rely on their verifier to be their quality control check; however, this may not be a good practice for a variety of reasons. If this is a common practice at your firm, you may want to check the scope of your engagement before relying too heavily on your verifier to find errors.

Verification is common for firms that claim compliance with the Global Investment Performance Standards (GIPS®). But even firms that claim compliance with the GIPS standards and receive a firm-wide verification are required to disclose that, “…Verification does not provide assurance on the accuracy of any specific performance report.

This is because verifiers are primarily focused on the existence and implementation of policies and procedures. While their review may help identify errors that exist in the sample selected for testing, it specifically does not certify the accuracy of presented results. While the verification process is valuable and often does turn up errors that need to be corrected, regardless of the scope of your engagement, a robust internal quality control process is likely still warranted.

Firms that are not GIPS compliant may engage verification firms for various types of attestation or review engagements like strategy exams or other non-GIPS performance reviews. In these situations, the scope of the engagement may be customized to meet the needs (and budget) of the firm seeking verification. A clear understanding of exactly what is in-scope and specifically what the verifier is opining on when issuing their report is key.

Situations where the engagement entails a detailed attestation tracing input data back to independent sources, confirming that calculations are carried out consistently, and verifying that published results match the calculations, allow for heavy reliance on the verifier as part of your quality control process.

Alternatively, when the scope merely consists of a high-level review confirming the appropriateness of the calculation methodology, a much more robust internal quality control process should be applied.

Knowing the scope of the engagement your firm has established with the verification firm is an important element in determining how much reliance can put on their review and findings, which can then be incorporated into the design of your own internal quality control procedures.

Key take-aways

Mistakes happen in investment performance reporting, but a robust quality control process can greatly mitigate this risk. Understanding the risks that exist, designing processes to test these risk areas, and understanding the role and engagement scope of all consultants involved are essential items in designing a quality control procedure that work for your firm – and hopefully one that will help you avoid situations like what happened with PSERS.

If you are not sure where to begin, we have tools and services available to help. Longs Peak uses proprietary software to calculate and analyze performance. Our software helps flag possible data issues and outlier performers and also produces performance reports directly from our performance system.

In addition, our performance consultants are available to work with your team to help identify potential vulnerabilities in your performance reporting process and can help you develop better quality control procedures, where needed.

Questions?

If you would like to learn more about our quality control process or any of the services we offer (like data and outlier testing) to help improve the accuracy and reliability of investment performance, contact us or email Sean Gilligan directly at sean@longspeakadvisory.com.

1 For more information on PSERS, please see this article from the Philadelphia Inquirer.

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Most managers assume that losing an allocation comes down to returns. Underperform the benchmark, underperform peers, and the mandate goes elsewhere. That happens, but it's not usually the reason a manager gets cut from a search after the numbers already looked competitive.

More often, it's something in how the performance was presented that made an allocator hesitate. A number that didn't match across two documents. A risk statistic nobody could explain. A question in due diligence that the manager couldn't answer cleanly. None of these are calculation errors. They're trust problems, and trust is what allocators are ultimately seeking when they write a check.

Here are the performance problems we see that cost managers allocations most often, and none of them start with the returns themselves.

The Numbers Don't Match Across Documents

An allocator pulls up your factsheet, your pitchbook, and your GIPS® Composite Report, and the composite's five-year return isn't quite the same in all three. Maybe it's a rounding difference, or the factsheet reflects a different "as of" date. The allocator doesn't know that, and they aren't going to assume the best. Inconsistency reads as carelessness, and carelessness in performance reporting raises an obvious question: what else isn't being checked?

This is why we push firms to treat marketing and GIPS compliance as one coordinated process rather than two departments working from different source files. Every document that leaves the building should trace back to the same underlying data.

This matters even more now that due diligence itself is being automated. Operational due diligence teams and consultants are increasingly running AI tools that cross-check pitchbooks, factsheets, DDQs, and regulatory filings against each other, flagging contradictions that used to slip through manual review. A rounding difference or a stale figure that a person might have missed a few years ago is exactly the kind of inconsistency these tools are built to catch instantly. Clean, consistent marketing materials aren't just good practice anymore — they're what it takes to pass a review that may happen before a person ever looks at your numbers.

Performance That Looks Selected, Not Reported

Showing your best-performing account, your best-performing period, or a composite with an unusually small number of accounts invites the question every allocator is trained to ask: what am I not being shown? Due diligence teams know that everyone can't be top quartile. The SEC Marketing Rule's anti-cherry-picking provisions exist because this pattern is common enough that regulators built rules around it, and sophisticated allocators are watching for it. If your performance can be read as overly flattering rather than representative, assume a diligence team will read it that way.

Wanting to lead with your best numbers is an understandable impulse. But diligence teams are trained specifically to spot it, and selective disclosure, even when every number in it is accurate, tends to read as a bigger warning sign than an honest, complete track record would. The stronger story is discipline: the periods where you held to your stated mandate and didn't deviate even while returns lagged. That's a harder story to tell than "we outperformed," but it's the one that actually holds up, because it shows you didn't drift toward whatever was working elsewhere just to keep pace. Chasing returns outside your stated process isn't skill, it's strategy drift, and allocators are trained to spot that just as readily as cherry-picked out performance.

Our advice: resist the instinct to lead with your best examples, and show the scenarios that build trust instead. We recommend showing the ones that demonstrate you stuck to your stated mandate, policies, and procedures, especially when the outcome wasn't your best quarter. Discipline under pressure is a more durable credential than a strong one-off time period, and it's the kind of evidence that holds up long after that number is forgotten.

Statistics You Show But Can't Explain

A page full of risk statistics doesn't build confidence on its own. It invites a follow-up question, and if the manager can't explain what a downside capture ratio of 85% says about the decisions actually made in the portfolio, the statistic becomes a liability instead of an asset. Allocators aren't just checking whether the numbers are favorable. They're checking whether the manager understands their own portfolio well enough to explain it. Statistics presented without interpretation signal that the second answer is “no.”

Likewise, a page of portfolio characteristics that have nothing to do with how the strategy is actually run are not doing you any favors. If you're not making decisions at the sector level, a sector breakdown doesn't tell an allocator anything about your process. If you don't manage individual position sizing, a top-ten holdings list is not adding value.

Your factsheet should be a roadmap for the conversation you want to have, not a checklist of everything other managers include. Every number on it should be something you can explain: how it got there, what decision it reflects, and what it says about how you manage money. A statistic that's only there because everyone else shows it likely isn't helping you if it doesn’t demonstrate active decision making. It's inviting a question you may not have a good answer to.

It's the same logic as a good resume. One padded with every certification, hobby, and unrelated past role doesn't read as impressive, it reads as overwhelming and maybe irrelevant, and it makes the reader work harder to find what actually matters to the job at hand. A factsheet works the same way. The strongest ones include only what's relevant to the case being made and make it easy to connect every line back to it.

No One Can Explain Why a Decision Was Made

This is the one that costs managers the most, and it's rarely about the numbers at all. An allocator asks why a composite was redefined, why a benchmark changed, or why a particular account was excluded, and the answer is a shrug or "that's how we've always done it." Undocumented decisions create the impression that performance is being managed reactively rather than governed intentionally. Firms that can point to a clear, contemporaneous record of why a judgment call was made close that conversation quickly. Firms that can't do this will leave the allocator wondering what other judgment calls haven't been documented either.

The Common Thread

None of these problems are really about whether the strategy performed well. It comes down to whether the story behind the numbers holds up consistently under scrutiny. Allocators aren't just buying returns. They're also buying confidence that what they're being shown today will still be true, and still explainable, a year from now.

The fix isn't more disclosure for its own sake. It's making sure everything across your performance reporting tells the same, well-documented story before an allocator ever has the chance to ask why it doesn't.

GIPS® is a registered trademark owned by CFA Institute. CFA Institute does not endorse or promote this organization, nor does it warrant the accuracy or quality of the content contained herein.

There is a common assumption among boutique investment managers that the Global Investment Performance Standards (GIPS®) are built for the largest firms in the industry — that compliance is something you pursue once you've reached a certain scale, a certain client type, or a certain level of institutional credibility.

That assumption is understandable. And it is costing firms real opportunities.

The GIPS standards have no AUM threshold to get started. There is no minimum number of clients or composites required before a firm can claim compliance. And increasingly, the institutional marketplace is not waiting for firms to reach some undefined moment of readiness before asking for it. If you are newer to the GIPS standards and want a foundation for what they are and why firms pursue them, start with our post What Are the GIPS Standards?

 

The Market Has Already Decided

The gatekeepers of institutional capital such as consultants, outsourced CIO platforms, model delivery networks, and institutional allocators, have been quietly raising the bar on performance reporting standards for years. GIPS compliance has shifted from a differentiator to a baseline expectation in many of these channels.

According to eVestment, two out of three manager searches conducted by investors and consultants on their platform exclude firms that are not GIPS compliant. That means boutique managers without a compliance claim are not being passed over, they are simply not being seen. As we explored in From Compliance to Growth, GIPS compliance has effectively become the price of admission for firms seeking to expand into institutional channels.

The question is not whether your firm will eventually need it. For most managers with institutional ambitions, the answer to that question is already yes. The real question is when you choose to pursue it, and whether you make that choice on your own terms or in response to a mandate you cannot afford to lose.

 

What Compliance Actually Builds Inside Your Firm

The benefits most managers focus on are external. Things like the credibility signal, the access to channels, the due diligence box that gets checked. Those benefits are real. But some of the most meaningful returns from GIPS compliance are internal.

Implementing the GIPS standards requires firms to formalize processes that often exist informally. Composite definitions. Discretion criteria. Benchmark selection rationale. Fee policies. Error correction procedures. For many boutique managers, the implementation process is the first time these decisions have been documented and applied consistently across the firm.

That discipline matters beyond GIPS compliance itself. A firm with clean, documented performance infrastructure is better positioned for regulatory examinations, investor due diligence, and operational due diligence reviews. It demonstrates to sophisticated allocators that the firm is run with the same rigor they apply to their own oversight responsibilities. And for firms that are not primarily focused on institutional distribution, this operational foundation has standalone value, the kind of infrastructure that supports sound governance regardless of who is asking. For more on what a well-governed GIPS compliance program looks like once it is in place, see What Good GIPS Compliance Governance Looks Like in Practice.

 

The Single Best Argument for Starting Now

Here is the point that does not get made often enough: the smaller your firm and the shorter your track record, the easier it is to become compliant. That ratio flips quickly as you grow.

Retroactively constructing composites across a large number of separate accounts is genuinely difficult work, particularly when no framework existed at the time to assign accounts to composites at inception, or to move accounts between composites as investment objectives changed, client restrictions were added or removed, or mandates evolved. Working through that history portfolio by portfolio, period by period, requires both detailed documentation and sound judgment. It is one of the most time-consuming phases of any GIPS compliance implementation, and the complexity compounds with every account and every year of history added.

A firm with 30 separate accounts and a two-year track record faces a very different implementation project than the same firm a few years later with 500 accounts and a five-year track record. The strategy, the clients, and the investment process may be nearly identical, but the administrative burden of reconstructing historical composite membership correctly is not.

The firms that find implementation most manageable are the ones that started before the project grew into something unwieldy. The firms that find it most painful are the ones that waited until an institutional prospect made it urgent.

What if you are not ready to commit to full compliance yet?

That is a legitimate position. But there is a practical middle path worth considering: even if a firm does not want to claim compliance with the GIPS standards today, building out the composite structure and creating policies and procedures for managing those composites now is a worthwhile investment. That framework does not require a formal compliance claim to be useful. Additionally, it can be carried directly into a full GIPS compliance program when the time is right, dramatically reducing the effort required at that stage.

 

The Real Costs

Becoming GIPS compliant requires real work, and it is worth being direct about what that entails. At a high level, implementation comes down to four phases: defining the firm, building a GIPS standards policies and procedures manual, constructing composites and calculating performance, and creating GIPS Reports with ongoing monitoring controls. We walk through each phase in detail in A Practical Framework for Implementing the GIPS Standards.

In terms of ongoing commitment, firms should expect monthly composite management, annual GIPS Report updates, periodic policies and procedures reviews, and distribution tracking. For a lean team, owning all of this internally is often not realistic. The good news is that outsourcing to a GIPS compliance consultant is a well-established path for boutique managers and one that many firms in our client base have taken successfully. The total cost of compliance for a focused, well-organized firm is frequently lower than managers expect, particularly when implementation is approached while the firm's history and account universe are still manageable.

 

Is This the Right Time for Your Firm?

Not every firm is at the same point in this decision. Managers with the strongest case for pursuing GIPS compliance now include:

  • Firms actively pursuing institutional mandates or seeking coverage from investment consultants
  • Managers on model delivery platforms or building toward that distribution channel
  • Firms planning meaningful growth over the next two to three years
  • Any manager whose clients or prospects have already raised the question
  • Firms that simply want to build a best-in-class performance reporting foundation, regardless of where their distribution strategy stands today

The case is lower urgency for firms focused exclusively on high-net-worth or retail clients with no near-term institutional ambitions; however, there is still value in building a sound performance reporting structure, and the sooner it is established, the easier the work will be.

On Verification: You Can Wait

Verification is independent, voluntary, and valuable. It is also not required to claim compliance with the GIPS standards, and for cost-conscious boutiques, it is a reasonable place to exercise flexibility.

A firm can become GIPS compliant today and gain all the operational benefits and the ability to make the compliance claim and defer pursuing verification until there is specific demand for it. When an institutional prospect or consultant asks whether the firm is verified, that is the right moment to add it. The compliance foundation built now makes that future engagement faster and less disruptive. For a detailed walkthrough of what the verification process involves, see our series How to Survive a GIPS Verification.

Verification is worth having. It just does not need to happen on day one.

 

The Longer You Wait, The Heavier the Lift

GIPS compliance is not an initiative that gets easier with time. Every year a firm grows its account base, extends its track record, and adds complexity to its operations without a compliance framework in place is another year of history that will eventually need to be organized, documented, and reconstructed.

The managers who find implementation most straight forward are not the ones with the most resources. They are the ones who started early enough that the project was still proportionate to the size of the task.

If your firm is headed toward institutional distribution (most boutique managers we work with are), the best time to build this infrastructure is before you need it. The second best time is now.

 

Longs Peak Advisory Services specializes in GIPS compliance and investment performance consulting for investment managers and asset owners. We have helped over 250 firms implement and maintain compliance with the GIPS standards. If you are evaluating whether now is the right time for your firm, we would be glad to talk through it. Reach out athello@longspeakadvisory.com.

 

GIPS® is a registered trademark owned by CFA Institute. CFA Institute does not endorse or promote this organization, nor does it warrant the accuracy or quality of the content contained herein.

Every Spring, the performance measurement community gathers for PMAR: The Performance Measurement, Attribution & Risk Conference, hosted by TSG. This year marked the twenty-fourth annual, and I left thinking about it differently than I have in years past.

Most years, the themes evolve gradually. This year, I felt like the ground was moving.

The theme nobody put on the agenda but ran underneath nearly every session was the pace of change. Specifically, what artificial intelligence is about to do to our work. And while I came away energized, I also came away with a healthy dose of " we (as in everyone) are not ready for how fast this is coming."

Here's what stayed with me.

AI Was the Undercurrent of the Whole Event

The session titled "AI, Anxiety, and Opportunity: What Performance Professionals Need to Know" was, predictably, one of the most sought-after sessions of the conference. The panel, which included practitioners from across the industry, did a nice job naming both sides of the coin: the anxiety of not knowing what your job looks like in five years, and the opportunity sitting right in front of us if we lean in.

Here's my honest read of the room, though. The mood was optimistic. Maybe a little too optimistic. There was a comfortable assumption that AI will mostly handle the tedious parts and leave the interesting work to us. Or that AI won’t take your job, someone that knows AI will. I'm not sure it'll be that tidy.

From what we're already seeing in our own work and across the firms we serve, the capabilities are advancing faster than most people can comprehend. The days where “our industry is just slower to adapt” are gone. Just last week, anthropic released Fable 5 and before it was shut down (temporarily?), we played around with it a little and its capabilities are dumbfounding. I don't think it will be long before these conferences look drastically different. Different sessions, different vendors, maybe a different sense of what the job even is. That's not a doom prediction. It's just a reason to pay closer attention than feels comfortable.

Separating Skill From Luck Just Got Harder and More Important

One of my favorite sessions was Michael Ervolini's "You Can't Find Skill in Returns: Distinguishing Performance From the Decisions That Generate Them." It's a deceptively simple premise: returns tell you what happened, not whether the manager was actually good. A great number can come from a great decision, or from luck. A bad number can hide genuine skill.

What I appreciate about PMAR is that the community keeps bringing fresh perspectives to this old, hard problem: how do we actually evaluate skill versus luck? It's a question that never fully resolves, and every year someone pushes the thinking forward.

It struck me that this question gets more important in an AI world, not less. As machines take over more of the calculation and even some of the decision-making, our value shifts toward judgment – knowing which decisions deserved credit, which results were noise, and what a number actually means in context. That's the kind of discernment a model can assist with but can't own. For more from Mr. Ervolini, here's a link to his latest book Skill vs. Luck.

The GIPS Challenges That Keep Coming Back

I'm biased here, but the "Common GIPS Challenges and How to Avoid Them" session was a highlight for us, in part because our own Matthew Deatherage, CFA, CIPM, was on the panel alongside peers from TSG, MassPRIM, and Strategic Investment Group.

What I always find striking about this topic is how consistent the challenges are. Firms pursuing compliance with the Global Investment Performance Standards (GIPS®)* tend to stumble on the same handful of issues year after year, and almost all of them are avoidable with the right foundation in place. That's a big part of why we do what we do at Longs Peak: helping firms get ahead of those pitfalls instead of discovering them during verification or, worse, during a regulatory exam.

Matt is a familiar face on these panels, and it's great to have our perspective in the mix. But the takeaway that stuck with me tied right back to the AI thread running through the whole conference.

Across several different panels, presenters talked about feeding the GIPS standards into their own AI models to churn out GIPS reports. And here's the thing, anyone can do that. You can drop the standards into a model in minutes. What a model can't do is provide critical judgment about how a principles-based framework should be applied to your specific facts and circumstances and whether those GIPS reports and statistics were calculated correctly. The GIPS standards aren't a checklist; they're a set of principles that require interpretation, and interpretation is exactly where experience earns its keep.

I'm not saying don't use AI to help build a framework. Use it. But like any model, if you don't really know what you're asking it to do, the output won't save you. Simply asking a model to "make my firm GIPS compliant" isn't going to make it so. At least not yet!

And there's one problem every performance professional already knows AI hasn't solved: data. As they say, garbage in, garbage out. Meaningful performance lives and dies on clean, well-organized data, and no software tool or AI model fixes messy inputs alone. At Longs Peak, we have spent the last 10 years working with clients to improve data quality through data integrity testing. For us, these AI models have only expanded what’s possible. We know one thing for sure: setting these tools up with the proper context (i.e., knowing what to look for) and then evaluating that context on an ongoing basis may turn out to be the most crucial piece of it all.

CFA Institute Is Listening on the CIPM

A session I didn't expect to find as interesting as I did was "CIPM Through the Practitioner Lens," facilitated by Rob Langrick of CFA Institute. Rather than simply presenting at the room, CFA Institute came to listen and gather candid feedback on the CIPM designation: where it's delivering value, where it's falling short, and how it should evolve to stay relevant to the work we actually do day to day.

The audience didn't hold back, and there were some genuinely thoughtful suggestions including how the code of ethics will evolve in this new AI era, some recommendations on reformatting the exam to break it into smaller chunks (going into greater detail on each) as well as adding a CIPM group within the CFA societies to encourage further connection. It was refreshing to see CFA Institute putting real energy behind a credential that so many of us have invested in and want to see grow in value. Given the pace of change in our field, willingness to adapt feels necessary. For anyone interested in contributing ideas to the CIPM, you can use this link to provide feedback.

A Quick Word on the Trivia

I'd be remiss not to mention that Performance Trivia got a much-needed upgrade this year. In past years, only a handful of contestants got to play while the rest of us watched (though in fairness, not all of us were clamoring for the spotlight). The new format this time allowed everyone to participate (without taking center stage), and it was a lot more fun for it. A small change, but it captured something I value about this community: it's competitive, but it's also genuinely collegial and prides itself on memorizing quirky names and vintage formulas.

Before PMAR Even Started: Women in Performance Measurement

For me, the week actually started the day before the conference, at the Women in Performance Measurement (WiPM) gathering. An event created just for the women in our industry. It's one of my favorite parts of this trip every year, and not only because the conversation is good. There's something energizing about being in a room full of women who do this work, comparing notes and reconnecting.

Fittingly, AI came up here too, though in a much more hands-on way than it would on the main stage. Practitioners shared real use cases, both personal and professional: the small ways AI is already saving them time day to day, and the bigger experiments they're running at their firms. It was practical, curious, and refreshingly free of hype.

We were also lucky to have a guest speaker, Lidia Arshavsky, who spoke on executive presence. She broke down how executive presence actually gets evaluated inside organizations (the signals people pick up on, often without realizing it) and offered practical recommendations for strengthening your own. It was the kind of talk that's useful no matter where you are in your career.

It was a great way to kick off PMAR, and an even better way to reconnect with women I only get to see a few times a year. Sometimes the most valuable part of a conference happens in these opportunities to network and reconnect within our niche performance community. A big thank you to TSG who donated the space for this event to take place and have done so for many years.

What AI Can't Take From Us

The conference's forward-looking sessions, including "Innovative Ways to Present Performance: Dashboards & Analytics," got me thinking. The tools are evolving so quickly and so much of the analysis, presentation, and reporting can now be automated. I am left wondering how long the traditional use of software in our space will last in its current form.

When the capabilities advancing fastest don’t always come from the established vendors, who benefits? My hope is that everyone does. That these tools level a playing field that used to tilt heavily toward the largest institutions, give smaller firms the ability to deliver high-caliber analytics previously out of reach, and push the whole field toward better solutions. That makes for a more competitive space and ultimately a clearer picture for investors to evaluate their options.

That's the optimistic case, and I believe it. But it only holds if we stay clear-eyed about where our own value comes from and that's the note I want to leave you on. The pace of change is a reason to focus, not to panic. The things that make us valuable are the things AI can't take: consciousness, judgment, and the human-in-the-loop accountability that clients ultimately trust. Machines will calculate faster and present prettier. They won't sit across the table from a client and take responsibility for what a number actually means.

So, by all means, get curious about the tools (Claude seemed to be most people’s favorite – mine as well). Experiment. Don't be the individual or firm that gets left behind. But anchor yourself in the part of this work that's irreplaceably human, because that's the part that was always the point.

See you at PMAR 2027. I suspect it'll look a little different.

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