But change is hard: Especially in data

Despite the industry’s desire to drive significant change in asset allocations – addressing the core issues of low automation and high spreadsheet usage – the scale of the transformation challenge in this space is significant. Of all functions where we are trying to drive change across investment operations, change in asset allocation management is by far the most complex. Failure rates (i.e. projects failing to be approved or being cut short prematurely) are higher on asset allocation projects than on any other area - with 13% of respondents failing to launch or run projects in this space.

That one-in-every-eight transformation projects fails in the asset allocation space helps to explain the continuing inertia in this area. With limited chances of success (even amongst those to try to drive change), challenges in the ‘post-spreadsheet bounce back’ phenomenon (described above) and no compelling external events (outside of Australia), it is no surprise that many asset owners leave the spreadsheets where they are.

Whilst data transformation relies most of all on people, people (or their absence) are unfortunately the central issue in driving change. Over 41% of projects fail to launch because the human resources are not available to define and execute on change projects. A further 15% of projects are cut short because of a lack of support from subject-matter-experts – meaning that over half of the industry is seeing their transformation work frustrated by a lack of human capital.

This is no surprise. Experts are required to make sense of what data is and where it goes – but those same experts are may often be fully committed to other regulatory projects, for example. If these specialists are not sufficiently available then projects can begin to drag or over-run, creating compounding effects of cost escalations, risks of changes in priorities, etc.

Equally the challenge can also be having the wrong people. Until very recently, the core profile for investment operations was stability and continuity – which have been at the centre of both hiring and performance management processes. As we now ask the stable and conservative experts of our firms to be change-agents and to help achieve enterprise transformation, there is a core question of how many people are ready and incentivised to make the shift.

It is no surprise then that several asset owners (of all size profiles) cite a critical concentration of expertise on a tiny number of (2 to 4) individuals as one of their key business risks today.

If shortages in human expertise (particularly around data) are the central reason for projects failing to launch, dependencies on legacy technology platforms are the single largest factor causing projects to be slowed or cut short.

With 21% of respondents citing the inability to change legacy systems as their #1 reason for projects failing to complete, legacy platforms clearly hold many unpleasant surprises in store for those trying to drive change. Whether this is driven by unjustified optimism at the start of projects (i.e. “how hard can it be to change that system?”) or by a true lack of system flexibility is unclear – but more work is clearly needed in understanding and scoping system dependencies before projects eventually begin.