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Why a Private Equity Backed Company Should Leverage Data Analytics Tools — And How

 

Why a Private Equity Backed Company Should Leverage Data Analytics Tools — And How

Equity holders are always looking for information about their investments or the companies they’ve invested in. With the fast-paced, digitally driven world we live in now, it seems like the demand for data is greater and more pressing than ever. Because private equity (PE) funds look to their portfolio for information about their performance, the faster an organization can set up data analytics tools and systems to provide data proactively, the more time it can save and the better decisions it can make — and of course, the happier and better the relationship between the organization and PE fund leadership!

At the same time, many PE funds are holding companies of portfolio firms in different industries, so it makes sense that a specific fund would desire the same type of reporting and visibility into each entity it holds. A best practice is for a PE fund to implement one analytics and business intelligence system across its portfolio, thereby allowing it to get similar views into different businesses and make more robust, strategic decisions.

But the overarching question here is: How do PE funds and PE backed companies implement a data analytics system?

What Does a Business Intelligence and Data Analytics Implementation Involve?

The first step toward implementing a business intelligence system or tool is to get buy-in. If the executive team doesn’t understand the value of a data analytics tool or even the value of metrics and reporting, you’re dead in the water.

At Wipfli, we provide our PE-backed clients with an investment summary, which is a one- or two-page document that identifies and elaborates on the business justification for the importance of the data initiative. This document can be shared among C-suite executives to communicate the overall business justification, the return on investment (ROI) and value the company receives from the project and the overall impact of a data analytics implementation on the company as a whole. When you tell this story, it arms you with the key messages and information you need to have conversations and get buy-in from the right stakeholders to move the project forward.

You also should include department heads in the buy-in process and ask what their challenges are. For instance, if the CEO and CFO simply assume that the Vice President of Sales needs to see one specific metric over another, the value of your data decreases, as does your ROI. Include department leaders in conversations from day one and try to align the value or impact that data analytics systems can have on them specifically.

Once you get buy-in, planning is the most important step. Take the time upfront to map out a holistic plan. It may seem premature, but if you believe you may use multiple systems in the future, then you should map out a longer-term plan that allows you to transition more effectively. Think about where you want to be from an analytics and technology perspective in five years, and then work backward and prioritize. 

Then make sure to identify your key requirements. Document what data elements or KPIs you need to provide the PE, as well as those that can help you better operate the business. Starting with clear requirements will help you analyze solutions available in the market as well as the service provider to help you get it implemented. You can also perform a fit-gap analysis that tells you what your current state is, where you want to be and where the gaps in your analytics and reporting are. This analysis is extremely helpful in choosing a business partner to assist with the implementation.

Of course, then there’s the implementation. This is where change management is vital. A data analytics system is a total transformation effort; throwing a new system into the mix without communicating to employees why you’re introducing it and what its benefits are — or training them on how to use it — will cause your implementation to fail. It’s important to have end users working alongside the technology implementation team or partner to gain the necessary ownership and empowerment to drive adoption once the implementation is finished.

Who Should Oversee the Company’s Business Intelligence System?

Analytics and business intelligence in general do not fall within the realm of IT. As a forward-looking executive with decision-making power, the CFO should head the implementation process, with input from the CEO and CIO/CTO as well as department heads who represent all areas of the business. Your cross-functional team can make sure all interests and needs are accounted for.

Ideally, a Vice President of Business Intelligence will head analytics efforts once the system is established. Having that VP roll up to the COO or another operations executive ensures the data gathered is not just forwarded on to the PE fund but also used by the company itself to make better business decisions.

What Are Some Best Practices for Gathering Data?

Right off the bat, you’ll need to allocate more time than you think to data aggregation and cleaning. The truth is, nearly everyone thinks their data is clean, but it never is. A lot of times, there hasn’t been a systematic change for years, and you’re trying to export data that doesn’t fit into the new system. Don’t underestimate data transformation.

When you’re looking at analytics, especially for PE-backed companies, determining important metrics for the fund also means understanding leading and lagging indicators. 

In the manufacture of a product, for instance, your leading indicator could be uptime on a machine or the scrap percent of material handling, basically things that are more tactical and day-to-day functions. A lagging indicator would be total revenue and sales, essentially the bigger picture or “end product” view.

When you’re establishing your metrics, it’s important to break down your data into different categories so you can map it appropriately and use it more easily and effectively. You should also plan how to reconcile information when there are differences in the data coming in from departments such as sales, operations, finance and customer support. In addition, look at how you can streamline inefficient business processes or correct systems that are hindering this process or its results.

If you have questions about how to prepare your organization to implement and utilize a business intelligence system or data analytics tools, contact Wipfli. We’re happy to talk through the challenges companies face, ideal solutions and best practices.

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Rowley_Matt
Matt Rowley
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