What do I do?
I always hear the same question, "What's the best tech stack for my growing fund?"
- Do I get a front-to-back suite?
- Do I combine multiple best-of-breed solutions?
- Do I outsource it all?
- Do I get some combination of the above?
It's not a simple question considering the diversity of options and in many cases all the intermingling and overlapping value propositions - all confused by buzzy marketing messages that aren't that clear in what they actually do. This complexity is leading many firms to outsource their operations, which is a really good option if you don't have the talent or resources to handle in house. However, make sure that decision doesn't come from a place of wanting to ignore tech. It's important to be careful around the creation and evolution of data silos. Data silos are much easier to recognize when you're controlling all aspects of data creation and management. However when a large percentage of this is outsourced, it's easy to lose touch with how efficient the entire operational process is (or isn't!). This begins to snowball at a macro level, and you end up with numerous layers of duplication, inter-period data gaps, and unnecessary reconciliation efforts creating cost and slowing down deliverables. We're obviously struggling at an industry level with The Great Resignation, in large part because technology isn't being fully leveraged.
It's important we also don't make this a conversation only about "efficiency". It's about retention of talent, it's about creating opportunity for analytics that didn't exist before, it's about maximizing firm-wide ROI, it's about creating capacity for scale that may not seem attainable right now.
Why is this happening?
I'll tell you a secret. The technology you bought to help you, is actually making things worse. The tech providers with the largest market share in private capital have been around since the 90's and early 2000's - well before cloud computing was a thing. They weren't built to take advantage of collaborative frameworks with multi-party access and data sharing models. They were built for singular firms to solve their own problems, within their own operational "box" of data and processes. Modern companies are working much closer with each other and expectations for multi-party workflows, real-time data sharing and data fidelity have increased. The older technology companies simply can't update their offering to keep up. You're likely hearing promises of what's "coming" but quarter after quarter you don't see any changes. The longer you stay with a bad solution the more at risk you become - losing clients, losing employees, losing opportunities.
What should I expect?
Raise your expectations for data and technology. Whether you're outsourcing today, considering it in the future or managing in-house you have teams of personnel that can all benefit from a single-source of data. If you're producing portfolio reports that pull in data points like invested capital, shares owned, valuations, IRR, realized proceeds, and more - those are data points that should be coming straight from your fund accounting solution. If you're managing multiple CRMs independent from service providers - those systems should be transparently synchronized to ensure everyone is acting on the latest information, reducing potential frustration points from your investors who expect consistency. Demand that the technology creating, processing and hosting your data is collaborative. If it isn't today - it's not likely going to be soon. Fund Accounting solutions hold a trove of rich data that other downstream users should be able to enrich and leverage for their own initiatives - whether you license the solution directly, or not!
How can Entrilia help?
We launched Entrilia to address the lack of digital collaboration in this industry. We've built a multi-tenant deployment architecture that combines a fully cloud-native, modern SaaS experience with the configurable personalization each firm requires. Our Fund Accounting and Operations solution is automating the creation of accounting data in a multi-dimensional, multi-ledger structure that allows further enrichment on top to power the most sophisticated business intelligence of today and tomorrow.
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