At our recent webinar on Modernizing Due Diligence and Private Equity, Colin McIntyre Partner at PwC and Johnathan Tran, Managing Director at PwC Strategy&, discussed how due diligence processes have changed over the years and how leveraging technology and data can address some of the biggest challenges in due diligence process.
Below is the summary of the key highlights from the session. If you'd like to listen to the whole discussion, check out the webinar recording.
1. How has due diligence evolved and changed over the last years?
Not surprisingly, value has remained at the core of due diligence. What has changed significantly is how due diligence is conducted, who is involved, the data and the factors that contribute to the creation of value.
In the past, due diligence required physical data rooms, manual checks, and lengthy processes, which posed limitations for both buyers and sellers. However, advancements in technology, such as virtual data rooms and tools like Alteryx for data analysis, have brought a fundamental change. The pandemic has further accelerated the adoption of virtual methods and collaboration tools, leading to significant transformations in various ways.
One of the challenges brought by these changes is the overwhelming amount of data, which makes it difficult to find meaningful insights. However, with the advent of AI, more data can now be processed, allowing to prioritize a more insight-focused approach.
“Microsoft said it best, they like the word so much, they're using it, right? This idea of a copilot. And how do we now use technology to literally help the human make better decisions, not replace the human, but help the human. And so it takes everything we've done and puts it on steroids.” - Colin McIntyre
2. How do investors ensure they stay ahead and fully leverage data?
Due diligence has become multifaceted, encompassing not only market growth and revenue outlook, but also things like cost-saving opportunities and value creation post-acquisition. With the abundance of information available, identifying valuable insights from noise is crucial.
To stay ahead, it’s important to:
- - Start the process of due diligence early. With Expert networks like Arbolus and other outside indicators like web traffic, employee sentiment, or online product reviews etc. - there are many data points that you can begin to piece together months before the formal process even starts.
- - Identify three to five key themes or areas that are the most important about this asset and focus on analyzing those aspects in-depth, using both the data available and the limited time you may have with the management.
By adopting these practices, investors can ensure they make informed decisions and harness the power of data to their advantage while staying ahead of the competition.
“So because there's so much more information available on these target companies, both from Arbolus and expert networks, but also from these outside indicators I referenced at the beginning, right? So web traffic, app downloads, user engagement, employee sentiment, online product reviews, there are all these little data points that you can begin to piece together. We're seeing some clients start 6 months ahead of a process to get to an initial answer on how excited should we be about this company” - Johnathan Tran
3. With the overwhelming volume of information, is being thesis-driven even more important now?
Absolutely. Advancements in technology and access to vast amounts of data have leveled the playing field in the due diligence process. The increase in private equity and capital availability has intensified competition, so it's crucial to identify the key value drivers early on. This allows investors to make swift decisions, whether to pursue an opportunity aggressively or find unique opportunities to enhance returns.
The emphasis needs to be on focusing on a few critical factors and levers that have the most significant impact on the investment decision-making process.
4. What types of data, technologies and specific tools or applications are really supporting due diligence processes at the moment?
There are many different tools and applications that support due diligence processes and provide additional data points. Expert networks like Arbolus and third-party data sources can help gain initial insights and drive a more focused due diligence process. However, simply having more data is not always beneficial.
Nowadays, virtual machines, visualizations, and heavy analytics tools are needed to make data more usable and overlay different data sources to gain insights into growth or profitability drivers. Despite the advancements in technology, human expertise still remains crucial in the due diligence process.
5. When it comes to expert insights, does having more data drive investors to the right answer faster or confuse matters even more?
It is crucial to distinguish between potential signals and noise in the data to get closer to "the truth" and drive an investment thesis. Customer interviews, even if anecdotal, are more valuable when there is a sufficient sample size (N of 40 or N of 100). However, it is important to overlay those insights with known facts and other data points to develop a more confident perspective on the business.
Integrating the human element with data and technology is also essential. Gut instincts played a larger role in decision-making in the past due to limited access to data. The current opportunity lies in effectively harnessing data and identifying outliers to build conviction or exercise caution.
6. What are some of the emerging trends we can expect in the future?
Firstly, the continuous improvement in the quality of data as businesses develop larger data lakes and rely on structured data for their operations. Determining the most valuable and relevant inputs from multiple data points becomes crucial for specific situations and projects.
Another trend is the increasing demand for faster and more accurate data processing to stay ahead of competitors. With more bidders collecting alternative data sources, organizations will need to invest in data pipelines and optimize their outputs to reduce the time taken for analysis from weeks to days or even a few hours.
Additionally, generative AI is expected to grow and transform the way due diligence is conducted in M&A. While the current needs are still quite basic, such as summarizing data and packaging it in a digestible form, the potential of AI on businesses and M&A as a whole is enormous. As AI evolves, so will the needs and capabilities, opening up new possibilities for improved decision-making and uncovering hidden opportunities.
To listen to the whole discussion, and get more insights on modernizing due diligence processes make sure to watch the full webinar recording.