General partners have always been fond of number-crunching the data of their portfolio companies. But the crunching, these days, allows them to masticate the numbers into infinitesimally finer pieces than before – and then to reassemble them in all manner of ingenious ways.
In response, some have entered the world of big data – using IT to gather, analyse and act on huge sets of information. Apostles say that private equity investors can use big data to make a real difference to the operational performance of their investments.
“There are two different types of private equity company these days,” says Roberto Pagani of A.T. Kearney, the management consultancy based in Chicago.
As the head of the industrial sector at A.T. Kearney’s London office, he works with many general partners in making their portfolio companies more profitable. “There are those that are primarily hands-off: their focus is to buy good businesses and then let management do their own thing,” he says. “There are still a few around. But the model of trying to improve the operational performance of all of the underlying assets has become increasingly prevalent.”
Pagani says big data and other analytics techniques have so far been used in sectors like utilities, telecoms and retail, “but eventually pretty much every industry will in some way or other be improved through them. In a few years I wouldn’t be surprised if every private equity fund has a team of two to four in-house analytics experts”, assisted by two or three people at each portfolio company and up to 10 consultants who can be called on at busy times.
Daniel DenBoer, principal in the KPMG Strategy Group, based in Phoenix, Arizona, has an intriguing example from a private equity client that bought 50 percent of a petroleum-based products company.
Management demanded that the prices paid by customers should be driven by the market, but KPMG discovered, after using big data techniques, that customers with similar attributes were not paying the same prices for the same products and service levels. This was largely because the salesforce was proving reluctant to pass on price rises in the broader market to favoured customers.
“After training the salesforce in new pricing templates, we were very successful in delivering necessary price improvements to eliminate break-even or loss-making business,” says DenBoer.
Pagani argues that when compared with the combined total of the large amount of staff at every portfolio company, the number of personnel required for big data techniques is small beer: creating such systems is “not very labour-intensive”. Already, “many of the larger funds we’re talking to are definitely doing something in this area”, though when it comes to mid-market general partners, he estimates that such practices are probably still “quite rare”.
A.T. Kearney recently completed a project for an internet-based broker operating in a particular mass-market industry, where it used big data to analyse millions of transactions and calculate demand patterns. It showed how this information can be used both to optimise pricing by customer segment and to improve the supply of services.
However, other IT experts are sceptical that complex analytics are what most general partners should be focusing on. Some think for many GPs a more pressing issue is to concentrate simply on getting basic IT systems and processes right.
“One of the big data issues is that about 80 percent of all the data in portfolio companies’ systems is in disparate systems, or not organised at all,” says Sean Epstein, head of private equity, EMEA, at SAP, the software company. “It’s not that they have more data than Nasa. It’s more that they don’t organise data in the right way.”
Epstein cites a recent meeting he attended where a data management firm shared with general partners the results of a data audit at a GP client’s portfolio company. The audit found three dead people on the payroll. “Clearly there was something broken in the process linking the payroll company, payroll processors inside the company, HR and the finance department,” says Epstein.
He believes, however, that resolving such issues is not a huge task: it might require 30 days of analytic work followed by 60 days of data clean-up.
Another field where operational performance can be improved is in the collection and organisation of data in order to work out how a company is faring – but in this case, it is the performance of the general partner itself that can be ameliorated, rather than that of the portfolio companies.
This is largely about saving staff time.
“Day to day, about 50 percent of asso-ciates and analysts’ time is spent capturing the financials of the portfolio companies in which the general partner invests,” says Michael Sala, managing director and global head of client development of the private capital markets division of Ipreo, a global provider of financial services technology, based in New York. “Really, analysts are just glorified data processors, but this is not what they should be doing.”
Despite this enormous investment in staff time in collecting and organising data, the end result is still often far from satisfactory. Epstein of SAP outlines a scenario: “Imagine that you asked the members of general partner investment committees today if they could immediately dig into their iPads and get the most critical Key Performance Indicators for each of their portfolio companies without calling one of their analysts or principals – people who in turn would need to call the portfolio management team, who would have to pass the query on down the organisation. Most would say they couldn’t.”
However, Sala claims that if they use iLevel, an Ipreo investment reporting system, they can cut the proportion of each day spent by analysts and associates on data gathering down from 50 to 15 or 20 percent. Sala says these people would no longer have to spend large amounts of time retyping data and performing other menial IT tasks.
How could more automatised investment reporting be used to improve the operational performance of private equity funds? General partners could cut costs by firing large numbers of staff, but most observers see this as unlikely. The analysts and associates could, instead, devote their days to working in ways better suited to their skill levels.
“There are higher-value activities for them to do,” says Epstein of SAP. “They could spend time having constructive, qualitative discussions with the management of portfolio companies.”
For such people collecting data is, ultimately, “not an effective use of time”, concludes Giles Travers, director, alternative investment funds, at SEI Investment Manager Services in London. “Technology can take low-value work away from high-value people.”