CTOs: Dealing with (unfair?) pressure
CTOs and COOs in private capital are coming under unfair pressure as complexity is growing faster than AUM. Since everything is digital, ‘everything’ lands in the CTO or COO’s lap. Alex Tyler and Ingolv Urnes of psKINETIC look at the challenges and successful coping strategies.
“We want to double AUM (…never mind exponential complexity)”
AUM growth is great, but since a large proportion comes with geographical expansion and new investment strategies (e.g. from private equity to direct lending, or getting into CLO) this growth leads to accelerating operating and tech complexity. In parallel the compliance burden has been accelerating, a trend which may become even stronger with the most recent invasion of Ukraine and appropriate ratcheting up of sanctions against Russia and Putin’s inner circle.
Top firms are often led by buccaneering deal makers. Closing the fund (double the size of the last fund) and finding great investment opportunities are top of mind. Firms historically just
held it together with Excel sheets, email, a few ‘bastardized’ off-the-shelf software
solutions and smart / hard-working staff. Historically, the (boring) practicalities such as fund setup and LP onboarding ‘just happened’.
A well-oiled machine or ill-defined processes & late nights?
The traditional view is to think about AUM growth leading to an inflection point where firms suddenly require disproportionally more expensive staff to manage internal processes; some ‘experts’ suggest this may be around $25bn in AUM.
However, our research and experience suggest that this inflection point is primarily driven by complexity - not AUM. For a straightforward PE fund making a few large investments per year with a relatively simple LP-strategy, this step-change may well be at $30bn or even $40bn AUM. But few operate ‘simple’ strategies anymore; the proliferation of funds, investment strategies, geographies, and capital raising strategies, means that firms can meet this inflection point as early at $10bn AUM.
Further complexity is increasingly being added by private capital firms aggressively pursuing AUM and diversification through the acquisition of asset managers operating in niches.
The biggest challenges come from scale and a high degree of interdependencies between the core processes of fundraising, investing, monitoring and disposal. A typical challenge is created by investor relations wanting to meet LPs mandate demands (maybe via SMA) and reporting demands; unless this is clear to the whole organisation, fund allocation becomes tricky and subsequent reporting near impossible.
Everything is digital, so ‘everything’ is now the CTO’s problem?
Private capital firms have grown rapidly, and many have invested heavily into technology,
function by function. When return on this tech spending does not materialise, a seasoned CTO – often from outside the sector – is hired.
Since everything is digital, ‘everything’ has a tendency of landing in the lap of the CTO, from Bloomberg feeds to corrupt Excel models. The pressure on incoming CTOs continues to build: complexity is increasing and software implementations have often reinforced silos. People are focussed on efficient working in their own department and a competitive culture makes it harder to focus on the end-to-end process and improve effectiveness across the value chain.
Less software engineering, more process engineering
The temptation of configuring a new feature or building a small application to solve a
problem is great (and something software engineers love doing). The downside is that unless the end-to-end process is understood, many of these software solutions are basically ‘hardening’ the silos and reducing agility. Just consider the process of negotiating and onboarding an LP and the subsequent impact on processes around mandate compliance or
quarterly LP reporting.
Fundamentally, firms need to upgrade the prioritisation of process engineering and answer questions like “what data is expected”, “who owns the data”, “what other systems”? Root cause analysis of pain points and collection of process data become key.
CTO Survival Tips
Make it your mission: Work with the CEO, you can help them ‘double AUM with constant head count’.
- Can’t scale without data: Dealmakers love data; you need to make sure they understand that one cannot have good data without a corresponding good, well-defined process.
- ‘Just show me the data’: The top team will get it as they want to scale; but expect pushback from middle managers and department leads - they either ‘just want to get on with their job’ or ‘just know’ they are doing a good job. Ask them for the data and the accompanying
- Appoint process owners: Functions or departments (= silos) used to be a way of grouping work to allow efficiency through specialisation (e.g. legal or IR). If you want good data, you want data on the full value chain or end-to-end process. It is no good knowing that an LP can be KYC-onboarded in one week, but it takes four weeks to agree the investment mandate.
- Appoint data stewards: Data is only useful if it is understood and trusted. The business must assign clear responsibility for who owns what data set (IT can provide master data
management tools, but ownership must sit with the business). This is an important pillar of a data-led culture.
- Use the tools of process engineering: IT should support the business with the tools required and source or build capability in business analysis, including overall process architecture (L-0 to L-3) and end-to-end process and data mapping for key pain points/broken processes.
- Tangible results in 90 days: Nothing gives the team around the CTO more credibility than successful implementations that add value quickly. Projects should be dimensioned to deliver value in 90 days or less – rapid, small project success is better than dreaming of the big, perfect solution.
Finally, which is the quickest way to lose the job? Failure to get the business (not IT) to own the processes and be data stewards. You should provide the tooling and the support, not run the support desk for poorly defined processes or lack of data stewardship.