How PE firms can turn data into a competitive advantage
Data science has been used for decades to improve business performance. Now, new innovations like machine learning, cloud computing, and open sourced software (e.g., R, Python) are making it easier for PE firms to identify insights and opportunities well beyond the norm—and to do it at deal speed.
In our new report, The Information Edge, we show how data science is transforming the deal business, illustrate how PE firms are using data science to create value at the pre-deal, post-deal, and pre-sale stages, and suggest ways PE firms can integrate data science within their deal process so that they can win in an increasingly competitive market.
Why is data science critical for PE firms?
Data science is a multidisciplinary approach that brings together different talents and ways of thinking with innovative technologies to collect, combine, and assess significant amounts of data in order to provide more robust business insights for strategic decision making.
PE firms today have the chance to leverage data science in ways never before possible. Data scientists with relevant skill sets, the increasing availability of external third-party data sources to fuel predictive analytics, new automation tools that can be leveraged in real time, and AI and machine learning solutions that can support better decisions are only making it easier for PE firms to embrace data science. When used effectively, data science can help PE firms assess potential deals, predict ROI based on shifting market levers, and adjust their change management activities. In today’s market, data science is the tool that can set PE funds apart from their competition.
Recognizing value at different deal stages
The value data science offers to PE firms is significant; it can give PE firms the information needed to win deals and help drive the results they envision after the deal is done.
Embracing data science: Should PE firms build or buy?
There is no right answer to the “build or buy” decision—PE firms need to assess their deal volume, sector focus, existing talent, and other relevant factors to determine whether it makes sense to build an internal data science capability or to search for a comprehensive data science partner who can help them turn data into a true advantage.
To develop in-house capabilities, PE firms need to focus on ensuring they have the right people who can institutionalize a data science way of thinking. They also need to develop processes to help enable data science and implement the technologies and tools they need to support data science capabilities over the long term—such as AI, RPA, or machine learning. They also need to identify and gain access to relevant external data sources they can use to help fuel complex data analytics.
To identify the right data science partner, PE firms need to take the time required to identify a partner who can provide comprehensive data science support across their PE lifecycle. They can do this by asking key questions like:
Find out more
PE firms that leverage data science fully can gain a significant competitive advantage. To explore some real-life examples and find out more, read The Information Edge.