How data analytics helps private equity accelerate value creation

October 6, 2020

Private equity firms are making investment decisions based on balance sheets and profit and loss (P&L) statements with Excel® being the go-to tool of choice for data collection and analysis. Most firms lack access to the real-time reporting required to make informed decisions post-acquisition. Portfolio companies are often running their business on a mix of enterprise resource planning (ERP) systems, homegrown legacy applications, and fragmented financial and operational data—making data reliability suspect at best.

Leadership teams, in collaboration with their private equity owners, are focused on making operational improvements designed to drive towards a successful liquidity event. The lack of clear visibility into performance too often has deal teams flying blind in their ability to make informed, data-driven decisions to optimize people, processes, and technology.

This lack of a firm grip on the company’s financial and operating metrics causes managers to become constrained. Similar constraints placed on deal teams further exacerbates the problem and can cause both to become frustrated and reactionary when it comes to making critical decisions.

Data analytics tools are transforming how decisions are being made throughout the investment lifecycle. Leading private equity firms are already embracing this and implementing data-driven approaches to analyze portfolio performance. Portfolio executives need the ability to access near real-time data across their portfolio for data-driven—versus gut instinct-driven—decision-making.

“At a time when PE firms face soaring asset prices and heavy competition for deals, advanced analytics can help them derive the kinds of proprietary insights that give them an essential edge against rivals. These emerging technologies can offer fund managers rapid access to deep information about a target company and its competitive position, significantly improving the firm’s ability to assess opportunities and threats. That improves the firm’s confidence in bidding aggressively for companies it believes in—or walking away from a target with underlying issues.”
Source: Bain & Company[i]

Data-driven dashboards allow PE firms to more effectively manage operating performance across their portfolio. They enable access to reliable operational and financial data that provides a true picture of the potential value of a company, as it’s being built during the holding period and at exit. Another important benefit is the value this drives from a broader stakeholder perspective. From investors, to limited partners, to portfolio company leadership and PE firm partners, access to the same data drives more consistent decision-making based on reliable data.

In organizations bogged down by siloed systems and manual, error-prone spreadsheet-based reporting and analysis, transparency through reliable data creates more ownership and accountability with individuals to ensure teams are consistently focused on the right priorities. Data driven transparency drives progress from the bottom up and the top down. It changes the culture of a company from an operating performance measurement and management perspective. A thoughtful data analytics strategy makes it very difficult for people who are used to hiding behind manually manipulated data.

A major goal of private equity is to zero-in on the key performance metrics that most impact a company’s value and potential, empowering portfolio companies and their PE firm owners to address issues quickly and proactively.

Excel is NOT the answer

Businesses create a lot of data they can’t manage properly. The lack of actionable data leaves deal and management teams operating at a suboptimal level of ‘controlled chaos and confusion.’ Portfolio executives are too often beholden to Excel and its limitations in their efforts to understand the data and make informed decisions on how to shape a strategy and manage performance to meet stated end-goals.

Private equity firms are increasingly becoming aware of these limitations and their consequences and more firms are turning to alternatives such as data visualization systems, analytics, and data warehouses. The result comes in the form of newfound clarity and team alignment around data-driven decision making, removing frustration, and transforming performance problems into growth strategies.

Embracing industry-leading business intelligence tools, private equity and portfolio company leadership can graduate from Excel-based analysis to real-time analytics-based dashboards that will result in better decision-making tied to growth and investment return value.2

Four steps private equity firms can take to implement a data driven strategy and plan

Step 1: Define the business case, core objectives, and supporting framework

Identify the business objectives and support framework where you feel analytics will help drive the most impactful insight. This is critical in establishing a clear direction in efforts to operationalize data. Don’t try to boil the ocean, less is more in the beginning.

  • Identify the leading indicators and related KPIs that are most impactful to measuring operational performance improvements and managing value outcomes
  • Focus on the highest value initiatives
  • Identify the risks in meeting stated goals related to these initiatives and a plan to manage to these risks
  • Set realistic and achievable expectations, remain aligned and consistent to these expectations. A ‘moving goal post’ will derail efforts to succeed.
  • Strike a balance between level of effort (light lift is optimal) and value impact.
  • Again, avoid boiling the ocean. Avoid perfectionism. Version one is better than version none. Do over engineer efforts to improve data quality, modify a transactional system or spend months standing up a data warehouse before you’re extracting value from your data.
  • Move with speed. Ensure the plan you have developed will drive material results quickly.
  • Choose a leader in a senior position who has a proven track record of building alignment and consensus at the firm.
  • Choose a stakeholder who has a technical background who understands underlying data sources and how to extract and deliver data.
  • Target a single data source or a report for one key stakeholder in the firm. Provide that individual one data point to focus on in helping them get more comfortable with the data in fostering a deeper understanding of the value and benefits it provides.
  • Leverage lessons learned by analyzing manageable amounts of data to the analysis of other sources of data. This will improve your ability to analyze initial data insights and sheds light on future plans to drive further adoption across the firm. This is key in helping to understand what works and what does not work early in the process.

From here, identify stakeholders who own and are responsible for target KPIs for each functional area of the business (sales, finance, HR, supply chain, warehouse/inventory management, etc). Align around clear success criteria and related measurement and management approach.

Step 2: Focus and prioritize opportunities that will give the biggest bang for the buck

A rapid return on investment can be realized with the proper focus and prioritization.

Examples of functional areas that are often targets early in the implementation of a data-driven strategy and plan:

  • Sales: Increased visibility into the sales pipeline will enable more informed decision making by sales leadership to effectively coach, manage, and drive results.
  • Finance: Accounts receivable—a clearer understanding of why customers are delaying payment can allow the organization to get actionable around plans that will improve receivables.
  • Product marketing: A better understanding of trends that impact the sales of products will inform better decision making and planning with product marketing (and sales)

Step 3: Identify and enlist the support of analytics champions to acceleration adoption

Early adoption and traction within the firm will be based on your ability put the right stakeholders in place and empower them to succeed. This is critical in seeding adoption and driving sustainable growth via usage of analytics across the firm to drive decision making.

Careful thought needs to be given in identifying these players who must understand the connection between data and the story it tells related to operating performance of the company. All grounded in a solid understanding of the strategic plan to drive growth.

Identify two to three key players who can drive early adoption.

Carefully selecting and empowering these champions to build buy in across the firm is the most critical element of succeeding.

Step 4: Take a “sprint”-based approach to systematically understanding and rolling out your data strategy and plan

Leverage this proven implementation approach by working in shorter timeframes to accomplish smaller deliverables at a faster pace. Quick wins in the form of meaningful data driven insights that help drive better decision making is a systematic approach that is a winning formula.

Make analytics your competitive advantage

For those private equity firms that fail at leveraging data analytics to more effectively measure and manage value creation, it will be 100% about culture versus having access to data. Whether firms generate the data themselves or acquire it from external sources, the amount of data available to private equity firms is vast. Firms that choose not to use data to create and manage value run the risk of becoming obsolescent, or at the very least, lose competitive advantage. By building these capabilities both at the fund and portfolio company level, firms can elevate their game in driving a new level of performance management and related value creation. As a result, firms can be both more accurate and more aggressive in valuations when buying companies while also increasing their exit valuation potential.

[i] Bain & Company, Advanced Analytics: A Powerful Edge, but It’s Not for Amateurs, Feb 25, 2019.

2 Jon Thompson, “What Is Business Intelligence for Private Equity?” Sep 19, 2019.

Filed Under
  • Data and Analytics
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