Private capital firms cannot let off-the-shelf software solutions control data strategy, writes Ingolv Urnes of psKINETIC. Ingolv spent a decade with Goldman Sachs in London, Frankfurt and New York, before founding psKINETIC.
Successful private capital firms will not simply use standard off-the-shelf software providing little competitive advantage. They are moving to develop proprietary solutions to manage and control a distributed data ecosystem and they continue to digitize processes at pace to collect better data.
Deals (not data) were the focus of entrepreneurial investors in the early days of private equity and other alt asset classes. As firms grew, they tended to implement the same off-the-shelf software as their competitors. Eventually the off-the-shelf providers moved to the cloud to offer software-as-a-service (SaaS) platforms.
The result? Private capital firms ended up with a number of distinct siloed applications: one for CRM/early-stage deal tracking, one for fund admin and another off-the-shelf for portfolio monitoring. At the same time, we see the SaaS platforms attempting to control ever more of their clients’ processes and…their data; each provider trying to lock in its clients (investors will recognise this as a good business model – for the software owners).
Investment professionals and operational teams are realising that – despite vendor promises of APIs and easy integration – much valuable data is hard to extract. Despite talk of open systems, the platform providers are unlikely to willingly give up their increasingly powerful position (BlackRock did not acquire eFront to build a free-for-all environment).
The future goal is to intelligently glue your systems together in a fully controlled distributed data model. Based on our experience, one challenge is the actual capability of your existing solutions and what contractual entitlement you have (or costs you will incur for APIs) as regards to data. Another important step along this roadmap is to collect and improve data relating to your current manual processes; data flying around in excel and email (issues with analytics and governance/integrity) is low hanging fruit.
There is plenty of exciting data sciences work and value to be added from the stuff right under your nose. Look to combine data sets to extract value. For example, consider combining portfolio monitoring with analysis of management incentive packages across portfolio companies; or quarterly valuation with simulating carry scenarios.
Moving towards a distributed data model is primarily a strategy and mindset challenge. MS Azure, Google and AWS all now offer the cloud-tools required to implement – in an iterative way – a future proof data strategy for firms to take control of their data. On the analytics and reporting side, PowerBI appears to be one of the key contenders.
Over time we predict that successful private capital firms will take the steering wheel back from off-the-shelf platforms. They will build their own fully controlled, powerful ecosystem of internal/external and structured/unstructured data to drive future returns.