Case Study

Inawisdom Platform supports Operational Innovation at Hg


Hg is a private equity firm and sector expert investor, committed to helping build ambitious businesses across the technology and services space, primarily in Europe. Hg has over £9 billion funds under management, invested across over 30 portfolio companies.

Hg’s focus is building better businesses and accelerating topline growth. The in-house Operations Innovation (OI) team partners with the Portfolio management teams to support the delivery of these ambitions, often drawing in its trusted third parties from its network to provide further bandwidth or specialist expertise.

Hg specializes in B2B technology/services sectors that are often naturally ‘data rich’ and have the potential to deliver tangible bottom-line impact through data insight. However at the start of Hg’s investment in a company, this data is often disparate, disconnected and spread across a variety of internal and external systems. Even when data can be accessed, the volumes and complexity are often deemed overwhelming.

However Hg’s OI team has a strategy and the capability to help management teams unlock the value of this data. In-house Data Scientists and Data Engineers, CIO ‘systems’ expertise and a strong bench of specialist partners mean Hg can help portfolio companies rapidly enable and leverage ‘Data Driven Business’ decisions.

Business Challenge

Hg requires the ability to rapidly generate a robust, reliable and responsive ‘Cloud data analytics platform’ from which it can undertake data science activities to provide their specific portfolio companies with a variety of capabilities, from standardised MI/Metrics and KPIs, through to more advanced predictive modelling.

Hg partners with Inawisdom, recognising the requirement for an architecture that can be deployed for Hg, then consistently scaled by deploying dedicated platforms for their portfolio companies, leveraging a consistent approach.

Inawisdom’s advantage is to have deep skills in both AWS and Machine Learning, understanding the data science activities that Hg and portfolio companies might want to undertake both in development and in production settings. Using their Rapid Analytics and Machine-Learning Platform (RAMP), Inawisdom leveraged automated AWS CloudFormation templates for the rapid deployment of tailored, but consistent, data platforms for Hg and their portfolio companies. This includes data ingestion and cataloging (via a data lake), data science (using the Deep Learning AMI) and visualization technologies. The provisioning of the RAMP platform is rapid and fully automated.

As well as partnering with Inawisdom, this forward-thinking approach led Hg to strategically partner with AWS as the recommended cloud provider for their portfolio of companies. As experts in data analytics, artificial intelligence, and Machine Learning, Inawisdom deployed advanced analytics infrastructures using AWS. More importantly, the Inawisdom RAMP platform enabled the delivery of business insights and embedded predictive models for a number of Hg portfolio companies. As well as deploying for Hg itself, Inawidsom’s deployment of AWS services has also extended across a number of Hg portfolio companies.

Business Outcomes

Hg’s Data Science team now use a cost effective and secure on-demand data platform to deliver and run machine learning models. These models are deployed for a number of Hg portfolio companies, leading to optimized sales conversion rates and better understanding of sales pipelines, as well as other benefits. Tangible value has been generated from the resulting ‘data driven’ business decisions. Typically, the very first ‘outputs’ from these engagements create an immediate return on investment.

Furthermore, the flexibility of the AWS platform has also been beneficial, enabling the addition of new platform components as projects change over time, such as the need for more processing power or memory. The flexibility in the operating landscape and the ability to scale (up or down) on demand has enabled the Data Science team members to focus on creating value from the data, rather than worrying about whether they have sufficient processing power, storage etc. All the deployments conform to Hg’s agreed product vendor preferences in order to leverage economies of scale in both licensing and skills.

The RAMP-based AWS data platform uses automated scheduling to minimize run costs. On-demand AWS services are used to minimize not only EC2 costs but also third-party license costs, allowing some services to be running less than 1 percent of the time while still delivering the business outcome.