Leveraging 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 basis for better resilience in any company is often based on the availability of operational data. Having access to the data you need to solve problems or opportunities is a must if you expect your operations managers and management teams to run their business better than the competition.
You need and want your portfolio companies to be operationally robust – to be ready and able to respond to changes and challenges in their business. Having seen dramatic market changes in recent years, we should all 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 operations managers should consider as you strive to make yourself more operationally robust:
- Computer engineering takes time and effort. You can do a quick and dirty version of computer engineering (aka loading it into a spreadsheet), but that won’t be sufficient to achieve what you really need in your businesses.
- Building a data-driven culture takes time. It is not enough to have the data ready; you need to change the way your companies use the data in their tactical and strategic decision making. It takes some planning and some patience to achieve.
- It takes time to add value to the data. When you have readily available data, you as an organization should strive to add to 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 when you have it in a centrally accessible location.
- Come after that. You need and want better analyzes in every company you own or manage. This is a journey, not a single project. Getting started now is critical to building agility and resilience over time on that journey.
Computer engineering can be labor intensive
Portfolio companies tend to have multiple application source systems that generate and store data. These multiple systems store the data in their proprietary databases, in a format best suited to transactional systems, and probably redundantly store common reference data such as customer number and customer name, address and so on. To get all that data, standardize it, scrub it and model it the way you need to manage your business takes months. You will likely need to hire consultants to build data pipelines, create a data warehouse to store the data, and then build the reports and dashboards for data analysis.
Professional and managed service 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 the right, clean data. Dashboards and reports are built quickly when the data is available.
A data-driven culture must be nurtured and built
Giving your managers access to data and reports is only half the battle. Most managers are used to making decisions without the complete picture and without a complete set of data. Resilience comes from having the data and using it wisely. If you build it, not everyone will use it.
Successful analytics projects include organizational change management elements to drive better data behavior. Training, better analytics tools, collaboration and usage measurement are just some of the best practices you can bring to your analytics projects to drive better use of the data and analytics tools that will lead to more robustness 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 efficiency of your decision-making process. Most departments and functions have access to their own data – finance has access to GL and financial data, marketing has access to market data and so on. Building a single data model that includes all the data from all the silos increases the level of collaboration that allows your managers from all functions to simultaneously see and react to business performance.
Let’s be honest, most businesses are still managed through elaborate functional spreadsheets that serve as the best source of data for quick analysis. Spreadsheets are great for individual analysis and reporting, and for quick ad-hoc analysis. They are not a viable tool for large scale collaboration and will never enable the data value enhancement that comes from a “single source of truth”.
Your operations leaders need to build resilience as they scale their companies
Change is constant, mthe sheets evolve, and today’s problems and opportunities are not tomorrow’s problems and opportunities. Modern data and analytics solutions can radically improve your operational resilience and deliver higher value. These solutions can be technically and organizationally complex and will take time to implement and achieve results. Start building resilience in your portfolio companies by mapping out a data strategy and creating the data foundation that your companies need.
