Most organizations do have in-house Customer and Market Insights (CMI) teams. However, they still face unpredictable bursts for Analytics requirements in specific projects. Datamatics Advanced Analytics and Data Sciences team helps businesses address such requirements through various modes of flexible engagement models. These models are based on the nature & flow of the business workflow, vision, and business context. These are –
• Project Execution: Here, Datamatics engages at the Project level and undertakes the entire project with committed deliverables on a 'fixed cost' basis.
• Time & Material (T&M): The T&M contract comes into play for larger projects with less up-front certainty about the full scope of work. It involves diverse skill sets, for different time periods at different phases of the project. Skill sets include Data Engineers, Business Analysts, Data Scientists, Solution Architects, etc.
• Dedicated Teams: Businesses require ongoing support for model building, iterations, evolution and implementation. For such a continual kind of workflow, Datamatics recommends dedicated teams or Full-Time Equivalents (FTEs) stationed at the businesses’ work locations.
• Resource Augmentation: Datamatics identifies profiles and shares with the business for project/ dedicated requirements, with a minimum number of hours to be billed per month. The project management and deliverables stay with the business. The key advantage of this model is that the business does not have to invest fixed-costs in hiring niche resources for their teams.
• Extended Delivery Centers (EDCs): A dedicated team working from the Datamatics office, which is flexible to scale-up or down-size as per the business cycle. EDCs have become prevalent as an effective way to drive speed, scale, and flexibility within parent organizations. The EDC functions as an extended arm of the business and brings economies of scale by efficiencies across a range of projects and capabilities.
• Joint Venture: Datamatics teams work together on a solution/project wherein the business invests its vision and market experience and Datamatics invests Research and Technology expertise, thus maximizing each other's capabilities.
• Build, Operate, and Transfer (BOT): Datamatics team develops and deploys a product/solution/application custom-developed for specific business requirements, maintains, and improvises it during the entire deployment phase and then trains and transfers the model to be operated by the business teams. In fact, not just products and applications, Datamatics also engages in setting up Analytics CoEs or Practice Areas for businesses by deploying the BOT model from Inception to Scale. With growing requirements around data compliance and regulations, privacy and security controls, IP rights or the kind of PII or PHI data involved, many Datamatics customers do wish to develop and retain the Analytics capabilities in-house for higher operational control and risk mitigation. In such cases, Datamatics customers leverage its expertise in creating robust Connected Data ecosystems, building predictive & prescriptive models and institutionalizing high-impact BI dashboards. Datamatics builds such fully operational teams and data structures, and then ensures seamless transfer of such teams and knowledge base along with structured training, hand-holding, and governance models.
Datamatics partners with its customers to support them with a large pool of resources to suit not just their Analytics needs, but even the wider net of Insights & Process Consulting, Business Intelligence, Digital Experiences, and Automation, at scale and on demand.