Business use-case identification
Strategic alignment and roadmap identification
Data infrastructure roadmap development
Success with AI & Data Science solutions requires not just data scientists but also entire cross-functional, agile teams that include data engineers, data architects, data-visualization experts, and—perhaps most important—translators. We provide tailored ethnographic evaluation to explore the client’s nuanced strategy, challenges, and opportunities and their relevance to available AI & Data Science solutions. In light of these evaluations, we understand that client’s overall strategy also needs to be revised from time to time to reflect the AI & Data Science solutions technological growth curves.
- What we do:
- Business use-case identification;
- Sector-specific research;
- Data acquisition roadmap development;
- Vendor landscape assessment;
- Cost and time implications;
- Data infrastructure roadmap development;
- Strategic alignment and roadmap identification;
- Scenario modeling & illustrated implications of decision alternatives;
- Alternatives to AI and/or Data Science;
- Non-Profit Business Intelligence.
The biggest challenges are people and processes. In many cases, the change-management challenges of incorporating AI & Data Science solutions into employee processes and decision making far outweigh technical AI implementation challenges. As leaders determine the tasks that machines should handle, versus those that humans perform, both new and traditional, it remains critical to implement programs that allow for constant reskilling of the workforce. While Strategy will result in a number of initiatives, we consider implementation to involve multiple activities such as planning, vendor selection if needed, project management, development, improvement of business processes impacted by the AI project, change management amongst other activities.
- What we do:
- Skill gaps & Role IQ review process;
- Talent search and/or acquisition;
- Corporate Adoption fears management;
- Organizational culture workshops;
- Regulatory compliance & engagement (e.g.: GDPR);
- Data Source Management;
- Data Systems Administration.
For all its potential and successes, AI & Data Science still do not have a ready buy-in with business and organization leaders because of the lacking critical role of bridging the technical expertise of data engineers and data scientists with the specific operational use-cases of AI and Data Science solutions.
We therefore help AI & Data Science vendors turn prospects into actual outcomes, by creating initial contacts with prospective customers/clients, analyses of the target market, providing advice on sales opportunities and coordinating actions to build, strengthen and maintain the vendor company’s position in the target market. Our services to AI & Data Science vendors fall in the realm of business development and include:
- Initial client use-case exploration (3 – 6 months);
- AI & Data Science Market Resizing;
- Key stakeholder identification;
- Persuasion Analytics (Proposal and capture management);
- Value proposition refinement;
- AI & Data Science trend predictions and analysis;
- Marketing strategy & Pricing research.