Quality control

by The Drawdown team 24 April 2024

Tech advances are opening up opportunities for private equity firms to leverage the power of data. Adopting new tools to enable access and provide insight and analytics can give a competitive advantage. However, ensuring the quality of underlying data is vital, say Lantern’s Charlie Markham (pictured) and Aztec Group’s Matt Horton and Geraldine O’Rourke

How sophisticated is the private equity industry today when it comes to harnessing the power of data?

Charlie Markham: We see real appetite and ambition for adopting modern technologies such as data lakes, real-time analytics and co-pilot. It is true that private equity has historically lagged when it comes to tech adoption, but there is a notable acceleration taking place.

In particular, we are seeing a focus on real-time data that is not only backward-looking, but that can be used to inform the future too. In that sense, private equity’s relationship with data is changing. This opens up many opportunities but as major financial decisions are increasingly being made based on insights gleaned from data, it is also putting significant pressure on the quality of the underlying data.

Geraldine O’Rourke: Private equity has always used data to support decision-making but tech advances mean that firms are now able to access and analyse more data and integrate more sophisticated data solutions that can deliver timely, quality data required to offer enhanced insight and, ultimately, competitive advantage. Data is now seen as a strategic asset.

Matt Horton: I agree. Data on its own is not enough. GPs need to be able to turn that data into useful insight. That requires robust, scalable and flexible solutions that can facilitate the collection, analysis and distribution of data throughout our organisation, client organisations and those of third parties such as law firms and placement agents.

What are the key challenges that GPs face in turning data into actionable insights?

O’Rourke: The biggest challenge is undoubtedly ensuring the quality of the data; that is paramount. In addition, GPs are dealing with vast amounts of fragmented data across different systems, some of which are not digitalised. Consolidating data from a range of sources and extracting key information, while ensuring data quality, is a key challenge.

We continue to develop our data strategy and tools, and are working closely with GPs to provide them with access to their data and the ability to integrate it into their own systems, as well as platforms such as Lantern. Enhancing data discoverability and accessibility to quality data in this way encourages innovation and collaboration around data and data products, which is key to turning data into actionable insights.

Horton: The traditional GP hierarchy has analysts at the bottom and the CFO and deal partners at the top. Platforms such as Lantern enable the right people to have access to insight whenever they need it. They are not beholden to an analyst being available or being able to get hold of a specific spreadsheet. It makes access to data far more democratic.

What are GPs’ options when it comes to addressing the data quality issue and what do you consider to be best practice?

Markham: We prioritise establishing a data governance framework, with clear policies around data collection, data validation and data usage. We address the question of data validation head on by validating raw data against trusted financial statements and quarterly reports. We have advanced systems and a talented team focused on reconciling that information and putting together a clear view of the client’s data. In addition, we have forged partnerships with high-quality service providers, such as Aztec, that are able to seamlessly provide us with quality information.

Finally, I would point to our underlying tech platform, which helps us validate data using a multi-layered model made up of an extensive suite of tests, humans-in-the-loop, supervised machine learning and other innovative technologies that we have been rolling out and look forward to continuing to roll out in the future.

O’Rourke: I would add that we believe that it is critical to create a culture within the organisation that values data accuracy and transparency, and then to foster that data-driven mindset and behaviours within the team, including ensuring that the right training is in place.

Markham: Absolutely. It comes back to the old adage of people, process and technology. Lantern is a tech delivery business but knowing that our partners on the fund administration side have top-quality people, processes and systems to ensure that the data coming through to us is spick and span, is paramount.

Private equity has historically lagged when it comes to tech adoption, but there is a notable acceleration taking place

Charlie Markham, Lantern

What are some of the common pitfalls that you observe in this process?

Markham: We typically work with CFOs and even they may initially show some reluctance when it comes to democratising data across the firm, until they can really trust the data. GPs spend an inordinate amount of time collecting, normalising and validating data. But they can move beyond that point. Through a combination of high-quality administrators such as Aztec and the technology that Lantern can offer, we can hopefully start to build that initial trust that can then enable them to do far more with the data that they hold within their firms.

Indeed, we have seen this happen first-hand with clients. Once they build faith in the data, then slowly that democratisation process unfurls and significant financial decisions can be made based on insights gleaned. In that context, we do not see ourselves as a system of record, but rather a system of trust, where we are able to support decision-making using forward-looking analytics and historic reporting.

How can a focus on data quality positively impact different stages of the private equity lifecycle?

Horton: The impact of quality data can be felt across the entire investment lifecycle and investment ecosystem, from deal origination to building credibility with investors. It is also important when it comes to valuations. While there have been significant improvements over time in this regard, a focus on quality data and even benchmarking will only make valuations more reliable going forward. Furthermore, with greater access to data, valuation no longer needs to be a quarterly exercise.

Data quality is equally important when it comes to portfolio management, meanwhile, where it can be used for effective monitoring and strategic decision-making. This ultimately enhances returns for investors at exit.

There is a lot of hype around artificial intelligence today. To what extent is data quality a prerequisite for leveraging the potential of AI?

Markham: We have all heard the maxim – garbage in, garbage out. If the quality of the data being used to train AI models is not good enough, then the system will make poor predictions and trust will be lost. That applies not only to the raw data going in but also to the way you interact with the model and provide feedback.

When it comes to the hype around AI, I also think it is important to ensure you are dealing with people who really understand private equity and the problems that need to be solved, and who then use that knowledge to identify the right tools to address those challenges. That will not always involve artificial intelligence.

Too often, AI is being viewed as this stellar technology that an organisation is determined to find a use for. We see that particularly around ChatGPT. We prefer to draw from market insights, conversations with customers and years of accrued experience within our team and that of our partners, to find the best possible solution. The solutions we bring to market are solving real-world problems for customers and giving them a competitive advantage as a result.

O’Rourke: For me, AI and automation are all about improving and enhancing our processes, empowering our people and supporting clients in smarter decision-making – and that means they must be grounded in high-quality data. Otherwise, any insight gleaned is going to be nonsense and any automation will not work. There is a vast opportunity ahead but any attempts to leverage that opportunity must have data quality at their heart.

How do you see GP demands evolving going forward and how are you responding?

O’Rourke: GPs will continue to seek to gain competitive advantage through data-led decision-making. So for us, using and continuously developing and enhancing tools that enable us to collaborate and work together with our clients as real partners is key. We are committed to evolving our services, our data programme and our client portal to meet those needs, so that both we and our partners can be more innovative and efficient, with data quality as the foundation.

Markham: From a Lantern perspective, we are focused first on data consolidation, combining an increasing amount of data from multiple administrators in a single source for our customers, so that we are not only able to provide the suite of products that they are expecting, but also, as Apple would say, “to surprise and delight”.

Whether it involves AI or other technologies, we are looking forward to providing GPs with innovations that they had not even realised they needed, but that ultimately prove to be game-changers within their firms.

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