2023 M&A Analytical Trends – Buying and Selling Data Science

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Our M&A Transaction Services Practice assists Private Equity clients in partnership as a professional services consultancy for their PortCos providing strategies they may need for them (IT, Cyber, Data, Distribution, and others); including pre-close tech and product/commercial diligence, post-close value creation execution, and sell-side go-to-market strategies: Furthermore, we specialize in advising the C-suites on their Data Strategy (business intelligence tools, data science, data warehousing, etc.).

We hear these terms interchanged or, moreover confused to describe the hot new software company’s offering in many Technical Due Diligences.

Since 2020, we have seen a change in trends for what the funds are interested in and what they want to know when it comes to seeing behind the data architectural curtain: Our clients rely on us to know what’s worth the ROI and what is worth divestiture: We’re here to help.

Digitalization in M&A

It’s a harsh truth, but M&A has been slow in digitalization adoption allowing for data and analytics capabilities to assist them in navigating the marketplace: Professional consultancies who specialize in the area with the right resources (like Liberty) have built and increased M&A analytics platforms in partnership with PE firms to drive deals: Rules-based systems, Machine Learning algorithms, and Data Analytics now exist to automate and interpret much of the M&A process(es): Virtual data rooms operate as a trusted area for confidential information and intellectual property (IP).

In due diligence, automation can assist in saving so much time in the process of transactions between entities. Overall, the insights from Data Analytics allow us to be better equipped in negotiations as well as assist in post-deal integration value creation upon integration: A study by Business Sale Report found that “given the scale at which this looks set to happen, (with forecasts that due diligence will take, on average, under a month by 2025) this alone will clearly be enough to make AI and machine learning revolutionary forces in M&A.”

No matter the case, investments in Data Science and Machine Learning tech are on the rise: This means that the PE firms are also getting more tech savvy and becoming more thoughtful in their partnerships for whom they choose to conduct evaluations on those offerings.

Gartner writes, “The traditional pitch experience will significantly shift by 2025 and tech CEOs will need to face investors with AI-enabled models and simulations as traditional pitch decks and financials will be insufficient.” With the growing amount of data out there, the commoditization of data is in the limelight: Companies are using data for all types of offerings from new market disruptors to answering new needs in the industry: That’s where we come in.

The PortCos and Their Offerings

When conducting Technical Due Diligence here at Liberty, we bring in our subject matter experts: Our staff of seasoned professionals have experiences across a swath of industries: This becomes especially critical when evaluating a PortCo product offering and the way they manage their business. We compile Business Technology overviews, and we analyze everything from the Investment to the Software, Application(s), Infrastructure, and Security to the Organization and SDLC processes: We want to ensure we know them in and out: We’ve seen the good, where the PortCo manages is open with us about their methods and processes: We’ve seen the bad, where a PortCo has too high a headcount managing what five data engineers can produce: We’ve seen the ugly, where the PortCo selling an “AI” is a conglomeration of regular expressions and API calls; that’s not how the industry defines “artificial intelligence.”

What Is Moving in the Marketplace

Now to the good stuff, what is selling?

  • Data as a Service (DaaS): With the commoditization of data comes analytics that are sold and/or licensed as a product offering. PortCos with aggregated data and IP market these analytical tools no different than Software as a Service (SaaS) experience.
  • Data Clean Rooms: This one isn’t particularly new to the PE firms we work with, but it will continue to evolve. The PortCo IP and other sensitive data protection requirements will provide a need for more protection as cybersecurity threats continue to evolve as well.
  • Data Fabric or Data Mesh: Coined in 2019 by Zhamak Dehghani, CEO and Founder of Nextdata, this is a framework for treating data like your asset and exploring the democratization of access to it. The idea of a mesh or fabric is one where multiple business lines come together to share each other’s data. This includes four pillars 1) Self-serving Infrastructure as a platform, 2) DaaS and/or Data as a Product, 3) Federated computational governance, and 4) Decentralized data ownership and architecture – all domain-oriented
  • Augmented Analytics: When you think about all the data that is out there, think about what is possible now. Today, we can create ad hoc queries on simple business questions like “what should my marketing budget be?” and get an AI-driven return from competitive market data. This concept reduces the need for Extract, Transfer, and Load (ETL) or Data Engineering pipelines thus also reducing the need for greater headcount and Operational Expenses.
  • Synthetic Data Generation: With Data science-oriented tech unicorns on the rise, we are seeing the art of the possible becoming more translatable to the average social media scroller. OpenAI is currently leading the charge with what they have built in DALL-E, GPT-3, and ChatGPT: When building Machine Learning models, they need to be trained on data to produce the ideal outputs for validity: AI tools that are able to create their own synthetic data to better train themselves will continue to build new questions into that conversation of validity.
  • Environmental, Social, and Governance (ESG) Data: Stakeholders globally are now demanding a reduction in carbon emissions. We’re seeing the integration of net-zero and carbon-negative initiatives in every business: We’ve even evaluated some software that tracks it: Databricks writes that, “In 2006, when the United Nations launched an initiative aimed at promoting responsible investing, 64 companies committed to factor in [ESG] issues when they made investment decisions…few would have predicted that a little more than a dozen years later, the Principles for Responsible Investment would count more than 3,000 organizations and $80 trillion committed to ESG investing.”

Summary

At Liberty Advisor Group, we know Technical Due Diligence: With the constantly evolving and growing data landscape, the focus of M&A within tech will continue to become cumbersome: The expertise to interpret analytics and data-oriented product offerings is more paramount than ever before: Understanding Data Science, Machine Learning, and AI solutions and why they are beneficial is something we at Liberty Advisor Group produce analysis on daily within our M&A Transaction Services Practice: We are here to help.

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