FSI Tech Spend Analysis 2014: Introducing T-Alpha
You cannot control what you do not measure.
Forgive us for dragging out this bromide, but it still is – and always will be – absolutely true. At a time when the capital markets industry – and the broader financial services industry, as well – is undergoing an unprecedented transition, it has never been more important to measure, and then measure more. And, in an age of increasingly advanced analytical tools and methods, it’s easy to see that measuring stuff – lots of different stuff; more so than ever before – is becoming infused into and spilling off of the backs of more tasks and workflows.
In parallel, the post-GFC regulatory juggernaut appears to be leaving no stone unturned when it comes to market, credit, liquidity, operational and a host of other risks. If you are not already measuring any conceivable risk from omni-directional perspectives and increasingly real-time temporal waves, the regulators are on their way to force your firm to do it.
The results so far are actually pretty impressive: Tiptoe through any Tier 1 bank’s 10-K filing (or 20-F filing, in the case of foreign banks) and you will find literally hundreds of new pages with metrics about balance sheet compositions and stress tests that did not exist in these filings just a few short years ago.
Yet, there do remain serious gaps – still – which is where this particular story begins: Enter TCO, or total cost of ownership. At the other end of the spectrum from the (mostly mandated) progress on risk analytics there is a paltry amount of transparency on technology spending. Augmenting this dichotomy, initial TABB Group outreach confirms that the understanding and quantification of TCO is only an emerging topic among capital markets participants, at best.
Chances are that developing metrics that allow firms to achieve a much more accurate understanding of their technology spending is going to remain voluntary. But though voluntary, the urgency with which most capital markets firms need to achieve better understanding of their technology TCO has risen to the equivalent of a five-alarm fire. Having specific metrics on TCO for existing solutions, and moreover, for comparison to new solutions is imperative for navigating the road ahead, particularly when it comes to preserving and growing profitability and for having strong decision support for how to harness the plethora of innovations that threaten to disrupt this industry for those who ignore them.
TABB Group’s version of TCO – which is notable for going beyond the obvious triumvirate of hardware, software and data costs to include the relevant human capital and managed services costs – is not yet part of the vernacular. Strange, this – since we calculate herein that IT human capital costs are averaging more than three times the combined hardware, software and data costs. This lack of awareness is what we hope to begin to change, right here, right now.
In this inaugural TABB Group Technology Spending Analysis – the first of its kind – we start by showcasing a comprehensive framework for the components of TCO. From there, we leverage a sample of observable financial data from ten Tier 1 market participants – eight global banks and two large asset managers – plus estimates on staff category segmentations and technology usage patterns to develop a sequence of six benchmarks that highlight the TCO per employee in front-office roles and five other categories. We also showcase strategies for managing TCO levels, with specific emphasis on the role of services in alleviating excess costs for functions that do not contribute to competitive advantages and that are simultaneously likely to benefit from management by outside specialists.
Finally, we take this analysis a critical – and as far as we can tell, unprecedented – step further: We introduce the concept of “technology alpha,” or “T-Alpha.” Comparative per-employee TCO metrics are incredibly important, but to what end? Like an orphaned bookend, the story on technology spending is not complete without a story on its impacts. (Who cares if we spend a ton if we make a ton, too?) It turns out that revenue per employee (RPE) is that other bookend. When comparing TCO per employee and RPE – and adjusting for scale of the company, as well – our T-Alpha factor rises to the surface. Moreover, even within a small sample of ten Tier 1 players, additional concepts such as the “technology beta frontier” and the drag of “technology debt” begin to come to light, as well.
The next age of global markets will be marked by increasing efficiency and – surprise, surprise – unthinkably awesome innovations. Firms that don’t reconfigure their technical footprint to deliver far better performance at substantially lower costs will find it difficult to stay in the game. How your firm migrates from yesterday’s tools to tomorrow’s tools depends, in large part, on its ability to perform detailed TCO – and, ultimately, T-Alpha – measurements. And, though we are only at the beginning of the exercise, with admittedly ambitious plans to extend our modeling far beyond this initial sample, we expect at the very least that these initial benchmarks and new concepts will fuel the debate.
In this 38-page, 43-exhibit TABB Group Study, FSI Tech Spend Analysis 2014: Introducing T-Alpha, we start by showcasing a comprehensive framework for the components of TCO. From there, we leverage a sample of observable financial data from ten Tier 1 market participants plus estimates on staff category segmentations and technology usage patterns to develop a sequence of six benchmarks that highlight the TCO per employee in front-office roles and five other categories. We also showcase strategies for managing TCO levels, with specific emphasis on the role of services in alleviating excess costs for functions that do not contribute to competitive advantages and that are simultaneously likely to benefit from management by outside specialists. Finally, we introduce additional concepts and begin to quantify new metrics known as “T-Alpha,” the “technology beta frontier” and the drag of “technology debt”.