Most M&A deals fail to create value because of poor strategic planning and/or inadequate due diligence. While AI can help identify hidden strategic opportunities and see through complexity which might disguise company performance, it lacks transparency and is prone to omissions and "hallucinations", especially in specialised or domain-specific information. Given what's at stake, any reliance on AI constitutes an unacceptable risk. Knowledge graphs strike a balance between n-dimensional (inferred), data-driven insights and full transparency. They can help to uncover complex patterns, relationships and anomalies between entities (across very large datasets), and to present them clearly and concisely in a visual format.
Elixir helps corporate developers and their advisors to design, build and exploit knowledge graphs which help identify suitable targets (and reduce wasted time), enhance M&A tactics, drive efficient deal processes and unlock substantial transaction value.
Knowledge graphs enable sophisticated landscaping exercises and hi-fidelity contextualisation of markets, customer profiles, relationships and preferences, and the benchmarking of performance.
The interconnected structure of knowledge graphs helps identify synergistic relationships and dependencies (e.g. common suppliers, customers, investors and referral networks) which can be used to uncover hidden opportunities and the best means of approach.
Details of key relationships, clinical and financial risk clusters, performance and risk concentrations help identify potential economies of scope/scale; risks/conflicts of interest and avoid expensive potential post-merger integration issues which support more efficient and effective negotiations and deal processes.