Harnessing private equity data for portfolio resilience
Scaling a private equity firm’s portfolio companies creates value, and increasing their native agility multiplies the value created. The foundation of better resilience in any company is often based on the ready availability of operational data. Having access to the data you need to address problems or opportunities is a must if you expect your operating executives and management teams to more adroitly run their businesses than their competitors.
You need and want your portfolio companies to be operationally resilient – to be ready and able to respond to changes and challenges in their operations. Having seen dramatic market changes in recent years, we all should be prepared for continued dynamic economic and competitive pressures to challenge even the best of our portfolio companies. Resilient companies will respond better to such challenges and will outperform their peers. Here are four areas you and your operating executives should consider as you strive to make yourself more operationally resilient:
- Data engineering takes time and effort. You can do a quick and dirty version of data engineering (also known as loading it into a spreadsheet), but that won’t be sufficient to achieve what you really need in your companies.
- Building a data-driven culture takes time. Having the data ready is not enough; you need to change the way your companies use the data in their tactical and strategic decision-making. That takes some planning and some patience to achieve.
- Adding value to the data takes time. Once you have easily accessible data, as an organisation you should strive to add or enrich the data. Scoring customers or products, cleaning or scrubbing your source data, and adding external data are examples of ways you can enrich your data once you have it in a centrally accessible place.
- Get after it. You need and want better analytics in every company you own or manage. This is a journey, not a single project. Getting started now is paramount to building agility and resiliency over time on that journey.
Data engineering can be laborious
Portfolio companies tend to have multiple application source systems that generate and store data. Those multiple systems store the data in their proprietary databases, in a format that best suits transactional systems, and likely redundantly store common reference data like customer number and customer name, address, and so on. To get all that data, standardise it, scrub it, and model it in the way that you need to manage your business takes months. You likely must hire consultants to build the data pipelines, create a data warehouse to store the data, and then build the reports and dashboards for data analysis.
Professional and managed services firms with experience working on enterprise analytics projects will note that data engineering consumes the majority of the time and effort put into their projects. Ask any financial analyst or business intelligence developer – most of their time is spent getting their hands on the right, clean data. Dashboards and reports are quickly built once the data is available.
A data-driven culture needs to be nurtured and built
Giving your executives access to data and reports is only half the battle. Most executives are used to making decisions without the complete picture and without a full set of data. Resiliency comes from having the data and from using it wisely. If you build it, not all will come to use it.
Successful analytics projects incorporate organisational change management elements to drive better data behaviours. Training, better analytics tools, collaboration, and measuring adoption are just some of the best practices that you can bring to your analytics projects to drive better use of the data and analysis tools that will lead to more resilience in your portfolio companies.
Data collaboration increases the value of your data
We consistently find that cross-functional sharing of data and analytics increases the value and effectiveness of your decision-making. Most departments and functions have access to their own data – finance has access to the GL and financial data, marketing has access to marketing data, and so on. Building a single data model that incorporates all of the data, from all of the silos, increases the level of collaboration that lets your executives from all functions simultaneously see and react to the performance of the business.
Let’s be honest, most enterprises are still managed through elaborate functional spreadsheets that serve as the best data source for quick analysis. Spreadsheets are fine for individual analysis and reporting, and for quick ad-hoc analytics. They are not a viable tool for extensive collaboration and won’t ever enable the data value enhancement that comes from a “single source of truth”.
Your operating executives need to build resilience as they scale their companies
Change is constant, markets evolve, and today’s problems and opportunities are not tomorrow’s problems and opportunities. Modern data and analytics solutions can radically improve their operational resilience and drive higher value. These solutions can be technically and organisationally complex and will take time to implement and achieve results. Start building resiliency in your portfolio companies by mapping out a data strategy and creating the data foundation that your companies need.
About the author
Paul Corning is Strategy Executive, Data Insights at 2nd Watch.
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