Intelligent automation and analytics in private equity
April 2021 | TALKINGPOINT | PRIVATE EQUITY
Financier Worldwide Magazine
April 2021 Issue
FW discusses intelligent automation and analytics in private equity with David Alich and Clément Mengue at PwC Germany.
FW: How would you describe the private equity (PE) industry’s awareness of and appetite for intelligent process automation (IPA) and analytics technologies? To what extent have attitudes changed in recent years?
Alich: Historically, the private equity (PE) industry has been relying on institutional knowledge, intellectual property (IP) and intuition to spot opportunities and predict future trends. PE firms used to track and analyse investment targets and portfolio companies through Excel spreadsheets, static investment memos and customer relationship management (CRM) databases. Times are changing. More and more, PE houses have been looking at the potential of technology to automate workflow processes, improve fund accounting and reporting, streamline due diligence and analyse large datasets – both structured and unstructured. Early adopters in the PE space started using data and analytics to gain better insights into portfolio company performance and acquisition targets. They more and more deploy their own specialised teams for it. Furthermore, these innovators are now also blending internal and external data with data science capabilities to drive deal origination and post-acquisition value creation.
Mengue: Our regular exchanges with PE clients signal an accelerating shift from analogue operating models to embracing digital ways of working to collaborate and engage limited partners (LPs) and portfolio companies. According to our recent European surveys, about 90 percent of PEs firms expect artificial intelligence (AI) to have a transformative impact on the PE sector. Although actual investments into data science talent are limited to a handful of funds, 70 percent of the funds we surveyed indicated analytics and automation investments to be high on their agenda. Based on conversations in recent months, four out of five PE firms had a form of software tracking investment pipelines. Nearly 80 percent of analytics and AI use-cases in the investor space are expected to focus on the deal origination phase, as well as the deal evaluation phase, supporting investors in spotting market trends, and identifying and evaluating attractive targets. Some of the early adopters of advanced analytics are considering automating their backend processes in the coming 12 to 18 months.
FW: What benefits and opportunities can IPA and analytics provide to both general partners (GPs) and limited partners (LPs)? How are these technologies being deployed across the asset class?
Mengue: General partners (GPs) are adopting digital across the value chain, from monitoring portfolio companies to sourcing deals and assessing areas such as market dynamics, potential white space and buyer preferences. We also see increased appetite around AI and analytics to support asset screening, such as calculating openness to PE investment, assessing organisational capabilities, product portfolio and website traffic. Furthermore, analytics often support comparative analysis around employee attrition rate, employee satisfaction, and sales and marketing key performance indicators. Similarly, PE firms are increasingly building digital investor platforms as a gateway for all interactions with LPs, including reporting capabilities enabled by advanced analytics. Several of our clients have reaped benefits from analytics and intelligent automation and improved the investor experience. PE firms are typically on a time-crunch, and those that can increase productivity across the deal lifecycle will close deals faster and manage fund operations more efficiently. Overall, IPA and analytics, coupled with the right skillset, provide PE houses with an edge over their peers.
Alich: Analytics and data will drive almost every aspect of how PE firms work and create value with their portfolio companies. A clear analytics and data strategy are the precondition to implement and leverage opportunities – use cases that can be realised and ultimately create value. This applies to PE houses internally as well as to their portfolio companies. A strategy should be transparent, with all important information available when needed on a near-time basis. It should also provide deeper insights, overcoming information silos by deploying advanced analytics to go beyond the obvious, using external data sources and blending them with internal information. Additionally, a strategy needs to leverage intelligent and automated deal data analysis, with artificial intelligence deployed on structured and unstructured deal data, such as financial information, external data and reporting.
“Combined with intelligent algorithms, portfolio companies can gain end-to-end visibility throughout their supply chain and logistics networks.”
FW: To what extent has the coronavirus (COVID-19) pandemic shifted the way PE firms create value and generate returns from their portfolio companies? How can IPA and analytics help them adapt to market changes and drive growth?
Alich: The coronavirus (COVID-19) pandemic has worked as a digitalisation booster across all industries in terms of collaboration, work and exchange models – including virtual work, meetings, data rooms and site visits – and in regard to traditional versus digital business models, such as digitalised platform players versus small, local businesses. It has also accelerated deeply-rooted cultural change processes, such as the perception of digital communication means and data collection. Of course, this applies to all PE firms and portfolio companies, too. Value creation through further digitalisation of business models is necessary and demanded by the market. Not having it is no longer an option. Data and analytics could help answer questions to cope with the new situation beyond the pandemic. First, in terms of customer insights and marketing, how did customer behaviour and preferences change during and after the pandemic? Second, in terms of market and competitive intelligence and risk analytics, what are others doing? What risks and trends have evolved in our industry? How do we predict them? Third, in terms of supply chain analytics, what are the most vulnerable parts of our supply chain? What are the strongest? Finally, in terms of the macro environment, how is the pandemic developing? What economic indicators are important for our business and how do we forecast them?
Mengue: Unpredictable market dynamics require deeper insights into business operations that enable higher visibility and flexibility during changing circumstances. Analytics enable detailed scenario modelling to better manage working capital, inventory and capital expenditures. Combined with intelligent algorithms, portfolio companies can gain end-to-end visibility throughout their supply chain and logistics networks. Additional use cases focus on scanning vast sets of company ecosystem data, and monitoring customer preferences. Applied to specific applications, integration of analytics and automation can improve process efficiency and accuracy, reduce repetitive tasks and offer guided, personalised experiences to consumers – especially during periods of massive operational pressure and atypical working conditions in portfolio companies. Digital companies are driving the enterprise value higher than traditional companies mainly due to a data-driven strategy or focus. Successful portfolio companies can generate market share alpha by improving products using the data from customers. Data-driven portfolio companies reduce the risks when entering new markets, hence growth in new markets positively impacts earnings before interest, taxes, depreciation and amortisation (EBITDA).
FW: What considerations do PE firms need to make when evaluating the technology solutions available in the market, so they make the right choice to suit their needs?
Mengue: Some companies work with hundreds of ecosystem partners to stay at the forefront of technology enablement and insight generation. As for any software, PE firms must decide whether to make or buy, assessing multiple collaboration and deployment options. Often there are multiple avenues for building this type of solution, ranging from collaborating across portfolio companies, to joining forces with other PE firms to partnering with solution vendors and advisory partners. It is critical for PE firms and their portfolio companies to take certain steps. First, frame the business problem and issue to be solved, including identifying and tagging the right market intelligence. Second, understand what potential solutions are out there and align priorities. Third, translate ambiguous requests into a well-defined solution roadmap, determining what approach should be taken to harness company IP and enrich the data. Fourth, focus on specific applications by building analytics to glean insights to enhance investment opportunity search. Finally, consider future solution extensions of data-driven capabilities into the add-ons, to integrate them with the PE platform.
Alich: There are thousands of data and analytics solutions and providers on the market that promise to leverage data, thus their maturity and fit for purpose is very heterogenous and needs careful assessment. Analytics and data technology for PE firms and portfolio companies should be assessed and tailored to include focus use cases, industry specifics, the level of analytics and data maturity in a company, its ability to overcome information silos and integrate external data, and platform and ecosystem readiness. Furthermore, since pure tech will not solve analytics and data challenges, there should be consulting and advisory services coupled to it.
FW: What advice would you offer to PE firms on implementing and leveraging IPA and analytics to improve efficiency, drive innovation and yield maximum return on investment (ROI)?
Alich: Transitioning to an analytics and data-driven business is not easy. A business does not become a data-driven organisation overnight or simply because it implements some new technologies or hires, such as data scientists. This particularly applies to PE firms and their portfolio companies. There are five aspects to consider that help to focus efforts and to be successful when implementing analytics. First, defining the goal and being clear about how the analytics and data strategy supports the company’s strategy and digitalisation journey. Second, understanding what data, analytics assets and use cases already exist, identifying and classifying the existing data and analytics assets within the company. Third, assessing resources and capabilities to understand the company’s analytics and data resources and capabilities, compared to its strategic ambitions. Fourth, investing in people, culture, infrastructure and processes in a targeted way, focused on easy wins. Finally, implementing change and technology step by step by choosing use cases that are easy to implement and provide quick wins and a success story, increasing complexity and level of change stepwise.
Mengue: PE firms must focus on four key pillars to ensure maximum effectiveness: creating buy-in to expand the strategic use of analytics and IPA in the deal process and in portfolio companies, recruiting top data science talent and designing a suitable operating model, setting up a data lake and infrastructure to store and interpret data, and deciding how and when analytical insights will feed into decision-making processes to develop performance management objectives. Investing has become increasingly complex, and as such PE firms should consider using or implementing an ‘insights engine’, a new way of applying analytics and AI to cut through the clutter and expose value, which might otherwise remain hidden. Our experience shows that using such an engine can pay dividends by providing deeper insights at every stage – all the way from deal sourcing, through due diligence to post-deal and in fund operations.
“GPs and LPs that choose not to embrace automation and analytics will become second tier in the medium term and may completely disappear from the market in the long run.”
FW: What are the likely consequences for GPs and LPs that choose not to embrace automation and analytics?
Mengue: PE can be horridly conservative in adopting new trends and evolving capabilities. Many have only scratched the surface of what is possible. Automation and analytics technologies can be used to gather the lowest-hanging fruit before moving to the more specialised high technology. GPs and LPs that have not pursued automation and analytics will be behind in comparison to peers. Besides missing out on enhanced opportunity scouting and improved diligence process, there is also the operational risk of not leveraging automation and analytics. One concrete example resides in fund operations and reporting to LPs. Currently, much of this process is manual. However, much can be digitalised and streamlined into a highly effective investor experience and efficient process, including dynamic reporting.
Alich: The amount of available internal and external data will continue to expand. The same is true for available analytics technology. Consequently, the ability to get deeper insights, better steering and greater transparency, to then create new data fuelled platforms, services and products will rise steeply too, as will demand for it. GPs and LPs that choose not to embrace automation and analytics will become second tier in the medium term and may completely disappear from the market in the long run. Automation and analytics are already on their way to becoming a commodity beyond the PE sector.
FW: What are your predictions for digital transformation in the PE industry over the months and years ahead? Do you expect IPA and analytics to become a key component of this asset class?
Alich: I expect to see further heavy investment in data and analytics technology solutions by PE firms and their portfolio companies. Every fund will have its own analytics and data experts or data science teams who work on PE internal value creation projects to implement analytics solutions directly into portfolio companies. Leveraging internal and external data to enhance decision making can be a key driver of value creation in portfolio companies. Data monetisation through licensing data to third parties provides further scope for value creation, as does the creation of data and analytics fuelled platforms and ecosystems within PE portfolios or even among PE houses, such as use case libraries, and standardised and automated information exchange.
Mengue: Digital transformation is becoming a new value creation tool that enables PE or portfolio companies to capitalise on de-risked technologies, such as analytics, automation and AI. Even portfolio companies themselves can capitalise on digital transformation. Digital is usually synonymous with tech companies, but digital traditional companies can enjoy the same advantages, such as driving enterprise value higher with a focus on data-driven strategy. Overall, we will see continued focus on digital transformation toward data-driven business and operating models, as well as PE firms looking to capitalise on the benefits of advanced analytics within portfolio companies to address cash flow, liquidity and supply chain visibility. New digital value creation levers will include technology-enabled demand forecasting, inventory management, algorithmic pricing, sales analytics and assortment optimisation, and process automation, among others. Leading investors will use more data for semi-automated deal origination and fund operations. New data-driven capabilities of digital portfolio companies will enable innovative products and business models by applying utility, usability and predictability models to innovate at speed and scale.
Dr David Alich is a director in PwC Germany’s advanced analytics and technology unit in deals. He has more than 15 years of professional experience as strategy and project lead in delivering value through the deployment of data science, advanced analytics, data modelling and artificial intelligence across various industries, private equity firms and along the whole M&A cycle. He can be contacted on +49 (151) 462 68560 or by email: david.alich@pwc.com.
Dr Clément Mengue is a director in PwC Germany’s deals strategy practice. He leads commercial advisory and diligence services for private equity, venture capital and corporates around technology enabled growth, digital business opportunities and investment strategies leveraging on emerging, disruptive and exponential technologies and digital ecosystems. Mr Mengue supports his clients in resetting their technology enabled growth strategy from linear to exponential. He can be contacted on +49 (151) 629 78769 or by email: clement.mengue@pwc.com.
© Financier Worldwide