How Chronograph and QuantSpark unlock data-driven value creation strategies for Private Equity firms

The decade-plus tailwind from accommodative monetary policy following the Global Financial Crisis has been replaced by an investment backdrop of rising interest rates, inflation, and slower growth, creating strong headwinds for value creation in private equity and venture portfolios. In this shifting landscape, firms are evaluating existing playbooks and looking for new approaches to deliver expected returns, employing a more hands-on approach with portfolio companies.

As private equity firms prioritise operational efficiency and combat obstacles to margin compression, sustainable growth, and cash flow management, leveraging data as a strategic asset in the post-investment process becomes paramount. Ultimately, firms rewiring their value creation approach to place data analytics at the core will be best positioned to discover hidden opportunities for portfolio company growth.

However, for most private equity firms, aggregating operational data and deriving portfolio-level insights remains time-consuming due to outdated data collection and aggregation methods. Together, QuantSpark, a leading data analytics and AI consulting firm, and Chronograph, a next-generation portfolio monitoring solution, partner to provide shared clients with advanced technology infrastructure for implementing data-driven value creation strategies.

How Chronograph expands data access and enables seamless data sharing

Many private equity firms grapple with data fragmentation issues. With information scattered across multiple systems, it makes it challenging to assess KPI health for funds and portfolio companies, and these silos and coordination gaps can ultimately divert attention from top priorities within the value creation plan. However, for many, accessing and leveraging portfolio company data as a strategic asset remains challenging due to legacy systems that lack automation, flexibility, and seamless downstream interoperability.

Chronograph’s Flexible Data Model Enhances Operational Data Accessibility

Now more than ever, investors need access to high-quality operational data within a single source of truth to achieve their value creation plan targets, which requires efficiently tracking progress through granular KPIs harmonised across their portfolios in a consolidated platform.

With no limits on the types of metrics that firms can create and maintain, Chronograph’s flexible data model allows firms to collect all reported operational, financial, and non-financial qualitative data reported by portfolio companies and pull these insights into downstream analysis — while still retaining the ability to produce uniform core KPIs and consistent reporting across their portfolio. With enhanced data accessibility and a single source of truth for portfolio company data, GPs can amplify the breadth of data they tap to monitor and propel their value-creation strategies.

Further, GPs can implement automated internal workflows to approve datasets before pushing them to a data warehouse or BI application, creating greater trust in the insights gleaned from downstream analysis.

Downstream Data Sharing Via Chronograph’s Snowbank Solution

In addition to portfolio company data, private equity firms manage vast amounts of complex data, often housed in a variety of disparate systems and third-party databases. By consolidating this data alongside their Chronograph data within a well-structured data warehouse, firms can further unlock powerful analysis to illuminate powerful value creation opportunities and insights.

Chronograph’s data warehouse solution (“Snowbank”) automatically replicates Chronograph data into the Snowflake Data Cloud, significantly simplifying data transformations at scale. With turnkey installation and no limitations on extraction or access to data housed in Chronograph, investors can materially reduce their time-to-production for dashboards, visualizations, and other BI tools built on top of their Chronograph data, seamlessly powering downstream analytics.

Additionally, as private equity firms look to explore AI opportunities to accelerate time to insight, automate tasks, and streamline workstreams, standardised data at scale becomes essential. With portfolio monitoring data digitally organised and structured in Snowbank, firms are better positioned to incorporate portfolio monitoring data into AI and ML applications.

From data to action: QuantSpark's transformational approach

Once a private equity firm has ported its portfolio monitoring data into Snowflake, it can further unlock value by enriching it with its own proprietary and third-party data datasets and building powerful dashboards and visualizations that surface impactful insights.

QuantSpark combines strategy, data science, and data products to improve business decision-making at the strategic and operational levels. Further, QuantSpark provides private equity firms with the framework needed to seamlessly integrate their Chronograph data alongside market data, internal Excel files, and other disparate data sets, creating a single source of truth and paving the way for powerful analytics. Some benefits clients receive from QuantSpark collaborations include:

• Centralised Data:  QuantSpark builds a centralised data warehouse, and automated pipelines to ingest data from Chronograph and other data sources, providing a single source of truth for comprehensive reporting and analysis.

• Enhanced Data Accuracy: Automated data ingestion and refresh processes minimise human errors, ensuring data accuracy and integrity.

• Comprehensive View of Investment Performance: Integrated data sources provide a holistic view of investment performance, enabling you to identify trends and opportunities.

QuantSpark’s approach

QuantSpark begins every collaboration with in-depth workshops designed to uncover each firm's unique data process requirements. Subsequently, cloud infrastructure is customised to align with these requirements and organizational objectives, with all data flows undergoing meticulous completeness, accuracy, and reconciliation testing prior to deployment to ensure optimal data quality.

Next, QuantSpark works to incorporate the client’s proprietary data to provide enriched datasets. For example, many clients have valuable data tied up in unwieldy Excel models; QuantSpark safely and securely extracts this data to the data warehouse.

With all data consolidated, QuantSpark prepares the data for consumption, joining Chronograph data with the client’s proprietary datasets, such as forecasted company performance metrics into interactive dashboards to unlock real-time strategic insights.