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Advanced Analytics in Portfolio Selection, Monitoring and Management
The use of Advanced Analytics represents a strategic competitive advantage especially in a dynamic and competitive market such as Private Equity and Venture Capital funds
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Intelligent Investment Portfolio Management
Private Equity fund managers face the constant challenge of managing their often diversified investment portfolios, drawing on invariably lean teams, whose ability to monitor a wide range of businesses is therefore naturally reduced. These professionals are responsible for controlling and monitoring the results of the activities of their various investees, whose businesses are often exposed to risks, both those inherent in their operations, and the risks related to the markets in which they operate (where, as a rule, originality and innovation predominate), which results in greater difficulty in anticipating deviations from the route, especially in periods of crisis of wide proportions, as is the case of the current pandemic of COVID-19.
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In this context, the introduction of Artificial Intelligence and Advanced Analytics becomes fundamental for the amplification of its capacity and agility in management, control and monitoring of the financial and operational performance of its investees.
Through the introduction and scalability of Advanced Analytics it is possible to obtain an effective automation of the follow-up of the results of its invested companies through automated dashboards that enable real time monitoring of the main performance indicators of operations, such as key indicators and adherence to short-term objectives and goals, forecasts and budgets, among many others, which considerably reduces the effort of data collection and compilation (the so-called data-crunching) by business analysts, thus freeing this specialized team of professionals for predominantly analytical activities that add greater value to the business of equity funds.
These professionals are responsible for controlling and monitoring the results of the activities of their investees, whose businesses are often exposed to different risks, both those inherent to their operations, and the risks related to the markets in which they operate (where, as a rule, originality and innovation predominate). This often results in greater difficulty in anticipating route deviations, especially in periods of large-scale crises, as is the case with the current COVID-19 pandemic.
In this context, the introduction of Artificial Intelligence and Advanced Analytics becomes fundamental for the amplification of its capacity and agility of management, control and monitoring of the financial and operational performance of its investees.
Through the introduction and scalability of Advanced Analytics, it is possible to obtain an effective automation of the monitoring of the results of its invested companies through automated dashboards that allow real time monitoring of the main performance indicators of operations, such as key indicators and adherence to short-term goals and targets, forecasts and budgets, among many others.
The use of Analytics considerably reduces the effort of data collection and compilation (so-called data-crunching) by business analysts, thus freeing this specialized team of professionals for predominantly analytical activities that add greater value to the equity funds business , in addition to substantially amplifying its management capacity.
Effective Monitoring of Big Data in the Definition of Strategies
Effective access to Big Data by Private Equity and Venture Capital funds in defining their investment strategies and in supporting the decision-making process is a key element for the expansion of their investment portfolio and monitoring of the businesses of its investees, especially in the markets where Startups operate, on whose monitoring and anticipation of the behavior of customers and competitors - as well as the trends and evolution of technological advances occurring in their respective segments - can translate into significant returns for their investments.
Just to get a sense of magnitude, in 2020, 168,546 scientific publications were recorded worldwide, according to Digital Science, the company that manages the Dimensions platform for research information.
In fact, the stratospheric expansion of global digitization has resulted in the public availability of equally astronomical volumes of strategic data, for which there is no possibility of manual monitoring or merely with the aid of traditional Business Intelligence tools.
Consequently, the adoption of Big Data search, detection and selection tools and robots (both structured and unstructured data, the latter estimated at more than 80% of the total publicly available data), becomes a matter of survival for the General Partners of Private Equity funds that wish to be ahead of their competitors, by obtaining in advance sensitive information that can guarantee higher returns on their assets, as well as a competitive advantage in the market.
Analytics Support in Due Diligence Processes
Any professionals who have already followed due diligence processes can attest to the chaotic environment in which so-called data-rooms and their respective data-files usually appear, usually composed of large volumes of documents and files, some not always made available through electronic (even though these are normally presented in an unstructured format), which invariably contributes to make it difficult and unnecessarily lengthen the stage of data evaluation and the processes of a negotiation, the consequent definition of its contractual bases and decision-making regarding potential capital investments, ultimately.
Private Equity fund managers who are at the forefront of their markets in terms of adding value to their businesses have successfully used the support of Artificial Intelligence tools to streamline due diligence processes, by through the use of optical character recognition, data mining and natural language processing devices, in order to increase their effectiveness and reduce lead times related to the process of condensing information, often anarchically dispersed across thousands of documents arranged in the data rooms of its potential investees.