Data Due Diligence

Our data due diligence allows organizations to gain a comprehensive overview of the target company's documentation and data across different areas of the business

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Monetization Through Data Due Diligence

Data is a leading concern when organizations plan to acquire or merge with other companies. It is normally during the investigation phase prior to a transaction, that we perform in-depth assessments of the target company's (critical) documentation and data across different areas of the business. We also assess the company's readiness to monetize data through strategic collection, utilization and company-wide connection of data. We consider the feasibility to extract, transform and load data from different technologies to create one consolidated overview for senior managers, C-level executives and the private equity investor.

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With an OMMAX Data Due Diligence You Will Receive

  • Evaluation of the technology architecture and the product development roadmap in the context of the company's business and growth strategy 

  • Evaluation of the technology architecture, its dependencies and scalability 

  • Analysis of the company’s application programming interfaces for data exchange 

  • Evaluation of the software portfolio including code, processes, best practices, and documentation reviews  

  • Evaluation of the company's data and machine learning pipelines, and model management to compare it against given benchmarks 

  • Analysis of the company's data utilization status quo and potential to achieve growth objectives through data-driven upselling, cross-selling or optimization of the customer experience 

  • Evaluation of the company's opportunities to sell/broker data in established ecosystems 

  • Assessment of foreseeable external shifts in the data area (technically / legal) which could disrupt the company's current business 

  • Assessment of the maturity of the company's data and analytical models in order to develop data-driven improvements or new business opportunities 

  • Assessment of the complexity/diversity and quality of the company's data 

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