The world’s data has doubled in the past two years – so how can investment professionals utilise the data boom to their advantage?
La Fosse’s annual panel event for 80 Private Equity professionals focused on how to leverage data as an asset from due diligence through to post acquisition.
The panel included:
Data’s value has exploded, but those with the power to leverage it are – still – relatively scarce. Whilst organisations may be sitting on pockets of useful data, there are often few individuals at board level in a portfolio company with the expertise to drive a data-led strategy, with those with the technical know-how are generally lower down in the organisation. A lack of understanding perpetuates a risk-averse approach, with fears of board scepticism, GDPR and Information Security risks holding organisations back.
In this landscape, there is potential for Private Equity to create a huge amount of value: as Martin pointed out: ‘everyone keeps saying that data is the oil of the new economy. But you need to find someone who knows how to drill for it before it becomes valuable.’
What’s more, PE’s breadth of perspective means they’re uniquely positioned to identify opportunities for value creation, particularly at the intersection of industries. Its striking that some of the best stories of value creation through data see it being used far beyond a business’s initial proposition – Lisa cited Unity, initially a tool for building graphics for gaming which now lends its expertise to the automotive and architecture industries, or payment company Square’s move into lending. This has incredibly valuable application where PE is concerned, as Carla observed: ‘you have the opportunity to look across so many businesses, and so many sectors, and find pockets of unused data.’
Discussing the use of data to get an early understanding of potential target assets from the outside-in, Matthew said ‘It works well if you are a specialist investor who has a good understanding of your market, and if the market itself is relatively transparent – for example real-estate, where you can easily access real-time transactional data from Zoopla or RightMove. It tends to work less well in smaller investments, opaque markets and with less specialised investors.’
A cross-industry perspective also puts PE is in a strong position to learn lessons from other assets when drawing up a viable strategy. At this point, it’s key to keep an open mind and a crucial adaptability – as Martin adds ‘you’ll discount loads of ideas until you get to one which is worth the bet.’
It’s worth remembering that just because the asset’s board might be risk-averse when it comes to data-use, doesn’t mean that there isn’t the appetite in the business. Often data strategy is something which management teams have always wanted to try out but never felt able – meaning that there is huge potential for getting them involved and excited at an early stage. The first question it could be worth asking the management team is ‘what have you always wanted to do, but never had the chance?’
Matthew cautioned that ‘amongst the worst things an investor can do is to ask for data from the management team, and then disappear for 3-weeks whilst they analyse it’, explaining that ‘realising the full value of a firm’s data assets – and what the data really means – will often require investors, management teams, and often advisers to work closely together’.
External expertise vs in-house capability.
Getting the right skillsets into the company is crucial. However, it’s also complicated. Striking an accord between external expertise and internal capability is a balancing act, particularly when operating to a strict value-creation timeline.
Lisa emphasised the importance of having a CTO with a software and enterprise information management background, and engaging in strong collaboration with the CTOs of portfolio companies. ‘Data needs to come from the existing systems – often it is kept well, but not used as smartly as it could be.’
She highlighted the potential risk of not having data teams in close collaboration with tech. ‘Costly decisions could end up being made, such as implementing a CRM system over disparate systems when a cloud based solution could be more efficient. You can build up internal capability but to accelerate progress you need to supplement the internal team with a combination of external experts – whether niche data companies or specialist interim consultants.’
For the more transformational questions, Matthew suggested that the value of external experts lies in their ability to bring a different perspective to the industry. Martin added that advisors that are adept at operating with complex businesses often give a voice at board-level to data specialists from lower rungs in the organisation.
However, as Lisa pointed out, the emphasis should be on building up internal competency, therefore bringing on external data partners should be treated as an investment in internal capability, not a “black-box” solution. External partners should be incentivised to add measurable value, transfer skills and knowledge, and also leave.
Furthermore, it’s important to be incredibly involved to understand how much value you are really sitting on. ‘Marie Kondo your data to work out whether you have a fantastic asset, or just junk.’ Advised Ryan. ‘Don’t give data scientists false confidence about the quality of the data you have.’
As the conversation about data is increasingly moving onto AI and the automation of business decisions, it’s now fundamentally changing the way that people work. Employees are expected to surrender their decision-making faculty to a machine, but still held responsible for its decisions – an uncomfortable proposition.
Such a substantial adjustment means that care should be exercised to avoid what Carla described as ’tissue rejection’ of data teams and strategy. There are a number of ways which these complications can be tackled, in chief by working closely with the management team at every stage, upskilling and placing a heavy emphasis on communication – for example, by sending existing teams on data and analytics bootcamps.
There’s no silver bullet for the question of where data should “sit” in an organisation – depending on the asset and the skillset of the leadership, a team might flourish under a CTO or CCO. What’s certain, is that getting the right leader is crucial. Lisa suggested that businesses need to ‘avoid individuals who are going to use the data to their own advantage rather than the organisation’s advantage first and foremost. You have to find someone highly collaborative to work with the business at every step.’
The leader will also need to ensure the team’s goals are aligned to commercial outcomes for the business. Shipping in a team of highly expert data scientists and letting them create solutions in silo doesn’t work – partly because they will feel so separate from the business that they’ll be trying to build solutions in a vacuum disconnected from broader strategy, and, as Ryan raised, they’re unlikely to become hugely popular in the existing businesses. It’s crucial to not only be incredibly transparent about the logic that is forming decisions, but also put collaboration and organisational uptake at the core of the strategy.
“Fantastic event on data analysis and how to derive commercial returns.”
“Real insights to take away and help my companies do business better.”
“As a PE investor – an interesting insight into data’s significance.”
“As regular PE fund investors ourselves, it was interesting to hear how PE advisers look at the increasing value of data for many corporates. It has also prompted me to look at the efficiency and relevance of our own Group data usage over the next few months!”
Jack DenisonDirector - Global Head of Executive Search and Interim Management