Digital innovation is reshaping the way most industries and businesses are functioning today. ML, virtual reality, sensor technology, internet of things, and other disruptive technologies are transforming every industry.
Data is the new fuel that is accelerating the adaption of these technologies in every industry. It is estimated that by 2030, data collection and analysis will become the basis of all future service offerings and business models in every sector.
Investment industry including Private Equity (PE) and Venture Capital (VC) firms are no different when it comes to data. There is a huge influx of data including historical, operational and market data that is now available. With the correct data strategy this data can be converted into insights to assist both in getting the most ROI from current portfolio of companies and future acquisitions. To achieve data-driven decision-making capabilities investment firms should adapt a phased approach in the following key areas.
- Due diligence process should incorporate insights derived from consolidated internal and market data for more informed investment decisions.
- A repeatable methodology should be deployed for collection of data from profile companies to drive insights for operational efficiency.
- Performance of portfolio companies should be measured throughout their lifecycle by drawing insights on the consolidated financial and operational data.
- To increase market evolution of portfolio of companies, processes should be implemented to collect and analyze market segment data.
- To maximize the potential of sale, evaluation process data needs to be collected in way that can drive meaningful insights.
- ML/AL models should be built on the top of the available data to provide more accurate predictions on areas relevant to the investment firm.
Every investment firm that has inspirations to become a data-driven organization needs to integrate and understand the diverse data generated by their portfolio companies. A data strategy needs to be developed for collection, consolidation, and analysis of data to enable deep, automated insights into portfolio of companies to apply the right approach to grow these companies, increase market valuation and operational efficiency, and make more informed investment decisions.