Setting Up Mid-Cap PE Funds and Portfolio Companies for Data Analytics Success

Most senior leaders recognize the value of building additional data-driven insights into strategy and operations. Value has two dimensions: The first is running the business better, making strategic, tactical and operating decisions, using the full range of information and insights available. The second is creating value from the data itself: integrating value into existing products and services or creating new products.

While there is often agreement on the potential value to be created via data analytics, there is typically concern about potential obstacles, which range from a lack of shared vision around what is important and worth pursuing, to siloed, messy data and processes, and limitations of legacy systems and technology.

Unfortunately, many companies get trapped in an idealized vision of an all-encompassing technology solution that promises to eliminate obstacles and create significant business value, but to do so only after a prolonged period of investment and disruption. It is an enticing vision that becomes a convenient excuse. How often do mid-market CEOs hear, “Yes, we’ll be able to look at that once we have the new system implemented, in eight months?”

The alternative is a value-based approach to data analytics: An evolutionary process that identifies a road map to an ideal end state but takes incremental steps to control risk and bring valuable insights forward. The approach allows for course correction as business reality changes, forces delivery of value in usable time frames and focuses on delivering value to discover limitations in systems, data and process. All of this is pursued in parallel with a larger technology transformation to increase the likelihood of success, or as an alternative path to the massive investment of time and resources of such a transformation.

Related content: Data Analytics and Due Diligence: Key Ways to Drive Value

Based on Stax’s experience working with mid-market private equity sponsors and management teams across industries and situations, here are common steps to success:

Clarify the business value first, rather than evaluating technology or systems. Outline a vision of the end point, remain flexible and approach the initiative in increments. Next, define outcomes for each increment along three dimensions: valuable insights for the business; enhanced understanding of process, data and systems; and capabilities built for the organization. Finally, encourage a test and learn, rapid-failure and learning culture.

Don’t accept existing systems as an excuse. In the worst case, data can be extracted and processed outside existing systems. Often, existing silos can be linked in the middle via light technology and process.

Compared to a systems transformation, for most midmarket companies the value-based incremental approach is more consistent with driving positive returns within PE time frames, while reducing risk and complexity.