Best practices in BI for PE-backed businesses

Business intelligence has become a more strategic priority in private equity-backed businesses. At Inflexion’s recent Data & AI Exchange, leaders from Medik8, Ocorian and JMAN Group discussed BI best practices, including data trust, dashboard simplicity, governance and AI readiness.

While some may baulk at the cost of putting money into robust data, it should be considered a worthy investment with a strong ROI, according to Inflexion’s Director for Data & AI Jan Beitner. 

And despite assumptions, the technology needn’t be the bulk of the work – it is more about people and governance.

Inflexion hosted a panel to discuss experiences in using BI dashboards to drive growth. 

What do you see in PE-backed businesses when it comes to BI?

Fraser Sym, Associate Partner, JMAN Group: Often, I’m having to assess quite quickly what the quality of the underlying data foundations is. Trust is a massive element. I see expensive, high-value leaders wasting time debating data rather than focusing on the actions that should come from it.

The first thing you need is consistency and reliability of data and KPIs to ensure the organisation looks at facts the same way. The second is consistency in how data is shared throughout the organisation. Those board-level KPIs need to cascade into a clear driver tree: dashboards that are regularly used by the people who can actually drive change, not just the data team. Without that, the numbers get reported but the business doesn't move.

The last thing is simplicity. Businesses often end up with hundreds of reports and dashboards. Usually just 10 to 12 core dashboards are needed to run a business effectively; it helps people focus on the things that really matter.

How do you get alignment around definitions and metrics?

Manou Campbell, Head of Data and Information Systems, Medik8: We have alignment across a lot of metrics, but some departments are definitely better than others at owning their numbers and being clear on accountability. Where we struggle more is when the same metric exists across regions or channels. Bringing stakeholders together to align definitions can be difficult.

One thing that helps is linking everything back to the company objectives. At the start of the year, when Medik8 sets its KPIs, I sit with the CFO and work through exactly how our department objectives align to the business priorities. That then filters through the teams.

You also need to think about whether the metrics themselves are meaningful. Engagement as a KPI for data teams is a good example. It’s easy to say people are using a dashboard, but what is that engagement actually driving in terms of output or decision-making?

How do you know when something isn’t right and needs fixing?

Fraser: There are usually some quick warning signs. One is seeing hundreds of reports. Another is when the BI team operates like a ticketing service, with business users constantly requesting data extracts. That demonstrates there isn’t a real partnership with the commercial side of the organisation.

The better approach is to ask: what problem are we actually trying to solve? If you understand the outcome the business is aiming for, you can often provide a much more effective solution than one-off data requests.

Another important exercise is defining the equity story early. At the start – or even midway through the hold period –  it’s useful to ask: what stories do we want to be able to tell at exit? Once you know that, you can identify the KPIs and operational metrics needed to support that story over time.

The technology itself is actually a relatively small part of the transformation. Most of the work is around people, alignment and governance.

Should BI teams report into the CFO or CIO?

Fraser: It changes as the business matures. Earlier in the PE journey, I think the best place is often through the CFO because they ultimately have to stand in front of the board and own the numbers.

There are also small behavioural mechanisms that help. For example, you can have reports marked as “signed off by finance”. If the report doesn’t have the badge, it shouldn’t be discussed.

Over time, data in more mature businesses may move into the COO or even Chief Data Officer organisation. But even then, the connection back to commercial ownership is critical.

Some larger businesses are now also treating data teams almost like a P&L. They want to understand both the cost of the data capability and the value it creates –  whether that’s efficiency gains, growth acceleration, de-risking or improving exit readiness.

What is AI changing for you?

Ali Greatbatch, Group Data & Analytics Director at Ocorian: AI is exciting, but baseline data quality still matters enormously. The top-level KPIs probably won’t change dramatically, but AI will allow us to interrogate them much more deeply and efficiently. We’ll be able to ask more granular questions around churn, process efficiency or operational performance much faster than before. But it only works if the data is robust and people understand how to challenge the outputs. We’re spending a lot of time training people on that.

Manou: I think self-service analytics will become much more normal again. A few years ago, many businesses pulled back from enabling self-serve BI because it felt too risky. Now, with better guardrails and AI tooling, it’s becoming much more manageable. People can ask why targets are being missed and generate detailed analysis within minutes. It’s completely changing how people interact with data.

Fraser: AI has elevated the data conversation massively in private equity. Six or seven years ago, data was often seen as a nice-to-have. Now it’s one of the first topics people discuss.

I also think businesses need to think about AI agents like employees. You wouldn’t expect a new hire to deliver huge value on day one. They need training, guidance and access to the right information.

The winners will be the businesses that are really clear on what they want AI to support and which business levers they are trying to improve.

What are your top tips for best practice in BI?

Ali: The quickest way to make this work is people. Getting the right people in place, trusting them, finding the right partners and building business buy-in has been the biggest success factor for us.

Manou: For me, storytelling is critical. The story leads and the data supports it. That’s what makes people engage with it.

Fraser: AI will move quickly, but businesses still need the right foundations. If you build on sand, it won’t last.

The discussion reinforced that successful BI functions are rarely defined by technology alone. Instead, the strongest businesses focus on trusted data, clear ownership, aligned KPIs and simple reporting structures.