Data Warehousing and ETL: The Key to Insights for Private Equity

This is the third blog post in a four-part series on how Private Equity firms can better use data and technology to their competitive advantage.

Whether it’s SEC auditors or investors requesting information, time is of the essence when it comes to the reporting done by Private Equity firms. In today’s digital environment, being able to quickly access relevant information is crucial to providing the appropriate response—and closing a deal—before the competition.

In our previous posts, we covered streamlining your data and choosing an analytics solution, plus the importance of a data management strategy for private equity firms. Here, we’ll explain how firms like yours can gain greater business intelligence and insight into corporate performance by combining two powerful technologies: data warehousing and ETL.

What is Data Warehousing?

Put simply, a data warehouse database is a central repository for storing a large amount of historical data. Unlike typical databases, however, a data warehouse is designed to give you a long-range view of data over time.

Even better, a data warehouse stores the data in a series of snapshots where each record represents data at a specific time. You can also search, gather, and present data from multiple sources in an aggregated report-based summary format for more efficient reporting and analysis. With data driving more and more business decisions, information like this is valuable currency for firms overseeing portfolios and originating deals.

What is ETL?

Often used to build data warehouses, ETL stands for Extract, Transform, and Load. ETL is a type of data integration used to blend data from multiple sources. The process is simple. Data is extracted from a source system, transformed into a format that can be analyzed, and loaded into a data warehouse for storage.

Because the data is extracted and set into usable formats, the risk of human error from inputting data manually is greatly reduced. Business users can also access the data for analysis through simple queries, visualization, charting, tables, and other forms. The result? Analysts find the relevant information they need faster and can put the time they save towards tasks like preparing the initial operational assumptions for investment or building a forecast for the potential of the business.

A Solution Designed for Private Equity

Data warehousing and ETL work together to store all of your data in a central place. This kind of technology also eliminates version control issues, freeing the team to focus on the analysis instead of worrying about the precision of data and reporting.

Analytics Solutions like Altvia Answers use this efficient combination to empower business users to get the information they need themselves, so they don’t have to rely on clunky programs or waiting to get data from other teams.

An end-to-end business intelligence solution, Altvia Answers connects to, transforms, normalizes, and displays all of your data across systems. It’s a holistic solution that brings all of your data together into a single source of truth, removes error-prone processes, and answers your questions.

A traditional crm was built for general ‘customer’ scenarios

Software platforms have made the world a better place by making work a better place. Indeed the world is better off when people enjoy their jobs even marginally more, and workplace applications on big CRM platforms like Salesforce.com have done that and much more.

But the potential that platforms like these offer presents diminishing returns: once the platform provider has engineered too many industry specific components into its platform, its usefulness for other industries begins to be threatened, and with that so do the usefulness of the component tools built into the platform.

So it is with the CRM category that Salesforce.com has defined: it is generic enough to work for many industries, and yet still offers the potential for others to round off the edges and nail more vertically-oriented and extremely tailored software solutions.

Private capital markets are actually a great demonstration of this dynamic. Where generic CRM platforms simplify — appropriately so — to assume there’s a business, a customer, a sale, and service of that customer, there are a few industry-specific pieces that are missing.

Take for example, that investors become customers by investing through legal entities the GP raises. It’s a subtle but important nuance that just doesn’t make sense at a platform-as-a-service level (because it’s overly complicated for a simple one-time sale that many industries require), but which can easily be added without 10 years or software engineering. Once provided, the rest of the platform’s components become tremendously powerful again and you’re set to take over the world.

As a traditional CRM in our pillars methodology, these nuances must be present to properly account for investors in these legal entities, potential target companies and which are owned by these entities, the context of all interactions with these parties (as well as the appropriate overlap, ie co-investments), and how you’re arriving at finding these opportunities on both sides of the equation, such that you’re able to piece together what’s effective and what’s not. Not just because we say so, but because these are the very relationships and data that are key to the motivation behind a CRM in any industry.

It’s critical, too, that the valuable publicly-available information that helps to enrich CRM systems and save users painful steps of entering it themselves is fully-integrated at the platform level.

Again, look no further than the 3,000+ pre-built integrations that Salesforce.com — the creator of the CRM platform concept — has at a platform level to do so, and which only exists by way of holding just short of overly-specifying certain industry workflows that would present challenges to properly integrate.

Stakeholder reporting and communication (investor relations) draws on a range of datasets

The traditional “customer service” model of CRM systems once again makes overly-simplified assumptions about the customer relationship when applied to private capital markets.

In fifteen years I personally have yet to hear the terms “warranty” or “service call” in this market because it’s just not the same. But make no mistake, as uncomfortable as it may be to say aloud, customer service is more important now than ever and it’s constantly happening; the industry is, after all, considered to be a financial “service”.

As it turns out, that service is primarily information-based — it’s driven by data and takes the form of reports and analysis that drive decisions, and then end up again in investor-facing reports and analysis.

The foundational elements of a private capital markets CRM must be built such that they accommodate this data (like we discussed above), but so too that it can accommodate additional supporting data that investors (customers!) need in the context of service.

Oftentimes this supporting data — financial metrics and time-based values, for example — is believed not to meet the traditional definition of CRM and the natural thought is “well, better do this in Excel!”.

While I happen to believe Excel is still the greatest software application ever built, its introduction to this value chain we’ve discussed herein actually creates the problem many firms suffer from: key data needed to provide customer service (again: effectively the entirety of a firm’s reports and analysis) is now in disparate systems and detached.

Both of those dynamics are important and distinct: not only is this supplemental data disparate, but when brought together there is no logical association that can be made between the two data sets.

Allow me, then, to make the point very simply: not only can this financial and time-based value data (you may be thinking about is as “portfolio monitoring” or “accounting”) be a part of a CRM, it is arguably the most important part of a CRM because it’s at the core of what providing service to the customer entails — information that comes out of data!

Firms need a digital method to engage stakeholders (ie investor portals)

Investor portals are not new; in fact, for many of us — including myself — they conjure up horrifying nightmares in which we’re aimlessly guessing at folders to find the newest document we need.

So in lies the opportunity: not only have the portals we’ve come to hate not simplified the process of acquiring information, they’ve failed to create an entirely new experience that is “customer service” driven.

To be fair, this is not a B2C market where you’d be long out of business for not having focused on customer service and thus the customer’s technology-driven experience. But don’t expect to be around too much longer if you aren’t thinking about this shift.

Today’s institutional investors increasingly expect this same consumer-like experience, and a massive opportunity is being missed by not providing it. It’s not about providing them the experience they desire; it’s more about the ability to measure engagement that is had in return.

Put simply: what’s keeping the market from providing this experience is the availability of the information that’s required to create the service that provides the experience.

If you’ve hung in this long, you know that by focusing on your CRM, you have the data that’s required to manage the customer relationship and the technology-driven experience through which that information is shared to create a differentiated and opportunistic customer experience.

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