Is data in the driving seat for enterprise valuations?

At the acquisition stage, what should you be looking for in terms of data and its value?

Go back to basics – look at the amount of data available, the architecture and infrastructure of where the data is collated and how it’s stored, how the tech stack is built, the structural approach and data strategy, and the period it’s been captured for.

When you have billions of data points, it’s easy to get lost. Consider the overarching operational decisions that will optimise value and how the data aligns with them. For example, if a key focus is marketing, does the data give you a clear customer picture?  Think about the insights you can monetise to help drive growth and, therefore, value. In a study by Bain & Company, only 4% of companies said they have the right resources to draw meaningful insights from their data.

At the acquisition stage, a lot of the exploration and due diligence process is about identifying opportunities. Look at the data itself and understand what’s actually visible – the quality, the way it’s collated, the way it’s stored – but also look at the talent behind it – the people who run and govern the data, how it’s reported, how the value is extracted from it.

As you move to the development stage, how do you start to unlock your data to help drive strategy?

As you begin to develop a strategy for a new business acquisition, the reality of making big changes and switching direction can be daunting, so utilising data to make small adjustments to begin with may make more sense. Looking at developing a data lake? Start with a data puddle that solves some small problems first. As you develop and understand the data better, you can connect the puddles to become ponds and then the ponds will connect to eventually become a lake.

If you acquire a company that doesn’t have a data culture, people change is the hardest element. Pick specific examples of where you can use data, show your people how to use it, and embed utilising data throughout your strategy and the day-to-day of your employees. Once you have people who know how to use the data, you’re most of the way there.

If a company is built from day one as data-centric, the CEO will likely have enough knowledge to drive the data strategy. Frequently in legacy companies, a CDO hire is made to facilitate data transformation, and there’s less buy-in from the board and cultural momentum because it’s not an embedded business element. The share of leading global firms with a CDO rose to 27% in 2022, up from 21% the previous year. The role is particularly prevalent in Europe, with over 40% of top European firms looking to a CDO for data leadership. Boards need to be aligned with data transformation; they don’t all need to be experts, but there should be a decent level of understanding. If not, bring in advisors and consultants to support the message. Data requires a high level of governance – it’s a huge business benefit/risk area and needs to have that oversight and insight from the board.

Establish some overall principles for your data. Whilst it’s important to get input from across the business, the data strategy should be created by the leadership team and communicated down. Having a holistic vision and standardising it across your systems will help to align your workforce, but don’t be too rigid on this; mapping out how to achieve your vision from start to finish leaves little room for flexibility and it’s unlikely that your plan will follow an exact path.

Data plays a vital part in optimisation – what do you need to consider at this stage?

Organisational design is at the heart of optimisation, and data is a core element of this. Consider where data sits within the business – is it within IT, with the CDO, or with the strategy team? Find correlations between different areas of the business and establish how data links them to identify the best team structure. There’s a common debate around whether a centralised data team is more or less effective than a dispersed team, but effectiveness is dependant on how the business uses its data. A central team gives more focus; a dispersed team embeds data (and buy-in) throughout the organisation.

Compliance is one of the board’s main responsibilities, so regulation and risk aversion can become the focus rather than how to harness the data for growth. Have an advisory team or committee formulate the commercial thinking to shine a light on profitability or value; when the board has compliance at the forefront, working out how to monetise data doesn’t work without that advisory help. Corporate boards may tend to over-index on risk, but this is where challenge and flexibility come into play. In a Private Equity environment, value must be created quickly. Risk is therefore reduced because the focus is on speed and there is less buy-in required from the board.

As generative AI becomes a more popular and familiar tool, the potential to use it to enable business growth is a huge draw. Fundamental process and infrastructure elements need to be stable before bringing in the next shiny thing – and data plays an important role. Generative AI utilises data points to develop and become potentially autonomous, a conceptually exciting possibility. However, there are considerations in terms of ethics, data security, and governance that must be addressed first. The best way to avoid risk is to not do anything, but there needs to be a balance or there’s no growth.

When it comes to liquidity, how do you communicate the value of your data?

The ability to demonstrate the security of your data is an important factor. Trust and brand reliability are key elements at the liquidity stage, and managing customer data plays a role in that. Security must be an embedded behaviour that every person in the company embraces. It becomes an essential and non-negotiable building block of modern corporate culture. The value of a company’s data is directly linked to its quality and integrity, therefore its architecture and security become fundamental value drivers.

Buyers and investors will look at how your company data can be considered as a stand-alone asset – yes it’s intrinsically linked to the business, but does it have a singular value? Identifying how other businesses can use your data is the key. Without understanding what can be done with the information, you can’t attach a value to it. For example, if you’re able to demonstrate impressive ROI on a commercial project, using data insights alongside the narrative to illustrate how it was done, that data is clearly much more valuable than a basic dashboard. Data on its own is not where the value lies; the critical judgement and application of the data is.

Insights were provided during a La Fosse Private Equity panel event by:

• Richard Wazacz – CEO of Travelex, former CEO and Co-founder of Octopus Choice and Octopus Cash
• Carla Stent – Board Chair and iNED including Telecom Plus plc, Evelyn Partners, Marex plc, Post Office, and former COO and CFO of Barclays GRCB, and Virgin Group
• Lorenzo Bianchi – CDTO of Sector Alarm Group, former Digital Transformation Operating Partner at KKR, and former Google senior leader
• Eser Tireli – VP of AI and Data Solutions at Bain & Company
• Elizabetta Camilleri – Chair of PE-backed Access Partnership and Togetherall, NED at BOV and Boring Money, Board Advisor to multinationals and startups
• Facilitated by Jonathan McKay – Chairman at La Fosse, Forward Partners UK, Move.ai, and Driftrock
• Hosted by Jack Denison – Global Head of Executive Search and Interim Management at La Fosse