DATA & AI DUE DILIGENCE
Understanding the value
of data & AI has never been
more important
~90% of the S&P 500 market value is composed of intangible assets (IP rights, reputation, and data). Juxtaposing this with the US$3.4T in global uncalled private capital, lead us to believe that understanding the economic value of data assets has never been more important.
And never more so than in due diligence.
DATA & AI
DUE DILIGENCE
DISCOVERING VALUE
How effective is a target company at leveraging data & analytics to power its business and operational models?
This question is the heartbeat of our data & AI due diligence. After all, you can't determine the economic value of data in isolation of the business.
Only by deeply assessing a company's data ecosystem, datasets, and algorithms can savvy investors determine value and uncover hidden potential to make better investment decisions.
VALIDATING WHAT'S REALLY THERE
Almost all of today's Information Memoranda claim 'proprietary, AI-backed decision making' and 'advanced automation'.
But the truth is that few traditional investors have the in-house skills to deeply assess data-intensive targets. Resulting in sub-optimal investment decisions and pricing.
I see a growing need for data due diligence. DataDiligence's findings enabled us to make a faster, more informed investment decision.
MANAGING PARTNER, PE FUND
IDENTIFYING BREAKOUT OPPORTUNITIES
For many businesses - especially PE-owned companies which have been heavily optimised using traditional operating methods - leveraging data and AI might very well be their 'last mile' in efficiency.
Or, data insights might be the next product or illusive revenue stream.
Identifying these opportunities pre-deal, means that investors can rapidly target value-creation strategies. And a data strategy can be crafted or refined in the first 100 days.
5 QUESTIONS ALL INVESTORS SHOULD BE ASKING THEMSELVES:
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How much does the target’s underlying data ecosystem play into value creation, today and in the future?
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Are we investing in data & AI due diligence proportionately to the perceived value?
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Do we have the experience —or know where to get it— to truly understand the AI & data nuances in this particular space and to develop unique insights?
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Is our data & AI diligence integrated with the broader commercial and financial due diligence effort, so the insights and recommended actions are consistent with where the value lies?
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Are these insights flowing directly into the value-creation plan to jump-start delivery on the investment thesis post-acquisition?
*Questions based on Bain's 2022 Private Equity Report
DATA & AI QUESTIONNAIRE & INFORMATION REQUEST
Our online due diligence questionnaire poses questions across the data ecosystem - strategy, analytics & data, people, and infrastructure.
Coupled with targeted information requests, we are able to build a strong understanding of the 'as is' data ecosystem.
DEEP-DIVE INTERVIEWS & DATA ASSESSMENT
Via select executive and investor interviews (frequently accompanied by the screen sharing of proprietary datasets/methodology) we validate the findings of our prior analysis.
And test our key scoping questions to determine the maturity and replicability of the target's data ecosystem.
COMPREHENSIVE
REPORT
Findings are presented in a comprehensive report, including:
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VALIDATION - what data assets are in place, plus those not yet leveraged (hence not in the ‘books’)
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VALUATION - do the data asset represent a premium or discounted valuation (data moat vs. data risks)
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VALUE CREATION - how ready is the business for advance analytics and AI, plus what is blocking the realisation of the value of data (focusing on decision making, optimisation & monetisation)