The data journey waits for no one
The question many are asking now is how can we bring that together; how do we leverage that data as an asset?
Compared to its hedge fund cousins, private equity has traditionally favoured pressing the flesh over tapping the keys.
However, as digital natives progress into senior positions, and as analytics tools become commonplace (and therefore affordable), data and the insights on offer are becoming integral tools.
Whether it be to identify and analyse deal opportunities, monitor and improve portfolio companies, or report performance to investors, the various ways in which data can be used, and its enrichment of all manner of tasks, means data has become an important asset.
There has been lots of talk in recent years about the wonders of AI and machine learning. AI is an inevitability for the asset class, as it is for all industries. But, in order to even begin imagining the possibilities, first get the basics right.
Effective use of data is all about good governance. Making sure quality information is captured and then inputted correctly before anything else. The old maxim, ‘garbage in equals garbage out’, only intensifies as more and more industries come to understand data as an asset.
Private equity has struggled in the past with data quality and consistency, perhaps because of its preference for contacts over calculations, which has hampered the creation of formal, standardised procedures.
The customer is always right
The onset of standardised reporting templates and portfolio monitoring software solutions marked the starting point of private equity’s data journey. Thanks to these developments, GPs are becoming more adept when it comes to collecting and inputting data.
LPs increasingly want information served to them digitally. Understandably so, with multiple investment types and numerous investment managers, in order to properly assess how each is performing, information needs to be aggregated before it can be interrogated.
GPs are at varying stages when it comes to how sophisticated they are when reporting. Some continue to use spreadsheets and PDF documents, others use portals and industry-specific software systems, while a few of the larger and more advanced houses have built their own data warehouses and systems, which enable almost instant reporting in any format.
However, there will come a time, soon, where those GPs relying on spreadsheets and PDFs will become obsolete; where investors will no longer commit to funds simply because the process of dealing with that manager over the life of the fund is too burdensome.
Not only is it vital that GPs develop effective data strategies in order to satisfy investor demands, a decent system can provide competitive advantages in other areas too.
For CFOs charged with gathering vital financial metrics from portfolio companies, a robust data platform can turbocharge reports delivered to the board and investment committee. In some cases, this kind of insight and analysis can be the difference between a failed investment and a home run.
This isn’t a ground-breaking revelation, and many CFOs have been busily adopting insight andanalytics tools. But what is worth noting at this point in private equity’s data journey is the way in which various data sources, databases and data systems interact with each other. Or to put it more accurately, how they fail to interact with each other.
“Private equity firms have a wide suite of software products available but there are still functional gaps, which are being filled by manually created spreadsheets and ad-hoc solutions,” notes Harpreet Lakhan, head of Holland Mountain’s data services business line. “The question many are asking now is how can we bring that together; how do we leverage that data as an asset? The tools are there to deliver the vision, the challenge is bringing it together.”
Indeed, clever coding and engineering types have been producing programmes for the private equity industry for more than 30 years now. And while several have attempted to deliver the holy grail of all singing all dancing front-to-back systems, let’s face it, it doesn’t exist. But what does exist are excellent systems for their specific functions.
Not the destination
Just as a private equity practitioner would assess and set about transforming or improving a portfolio company, the same approach must be adopted when it comes to digital development.
This is a journey, which requires a long-term view of the eventual destination, or vision, but which requires practical steps to get there. Says Lakhan, “Most private equity firms have the vision, but they need to take small steps. The best place to start is to think about what you can achieve in the next four to six weeks.”
Indeed, it would seem on the whole, the industry is aware of the competitive advantages to be had from advanced data interrogation and insight, but how to reach that digital utopia can seem overwhelming, especially when operational professionals are drowning in information requests, new compliance procedures, cyber security strategies, and all manner of tasks currently being piled up on their shoulders.
“Think about the execution as a journey,” advises Lakhan. “First have the vision, know where you want to be and then start to take incremental steps by presenting insightful data and analytics to different teams.”
Even the most arduous journeys become happy travels with the right crew. Again, much like portfolio company management, the key to success is having the right people on board.
Says Lakhan, “Recruit the right people. Bring in business people who know business analytics, not technical resources. We are starting to see more recruitment in the business intelligence, insights and analytics space for PE firms. These are roles that haven’t previously existed.”
The digital landscape is stretching out and transforming at such a pace it can often seem daunting or even impossible to navigate. And this isn’t likely to change either. Technology will continue to develop, and it will continue to grow in complexity. But for a typical mid-market private equity firm, no-one expects offices staffed by holograms and cyborgs. What is expected is effective governance of data, sensible adoption of well-suited products and tools, and robust integration of systems without manual inputs or processes.