Your data, our expert analytic solutions.
Velocity is home to the largest and most experienced data analytics team in Hong Kong. We work with cutting-edge technology and are experts in providing data analytics solutions that are cost-effective, scalable, and personalized for your business. With our powerful, easy-to-understand visualisations and analytics, you'll never overlook important data again.
Discovery is the preparatory stage in the delivery process. An effective Discovery stage has a smooth transition from pre-sales stages capturing the key inputs including: pilot project scope and results, KPIs (success metrics), source data and scope, and preliminary solution architecture and business case. The key output of this stage is a high-level project plan, and the first review should expect this as completion criteria before moving on to the next stage.
This is the stage in which the project is outlined, solutions are defined, and preparations are made for a successful project. Inputs are the requirements document and the high level project plan. Primary outputs of this stage are a detailed project plan and a solution design document. Upon successful completion of this project stage, a governance structure will be in place, the project team structure will be defined, a project implementation methodology is agreed upon, technical plans are in place (infrastructure, data sources and acquisition, application design), the project scope will be bounded, time and resource constraints should be understood, and the project risks should be well understood and mitigated.
This is the stage in which the project is executed and the solution is prepared to be deployed to users. Inputs are the detailed project plan and any referenced artifacts. Key outputs for inspection in the third stage review include the Deployment Plan, application readiness as demonstrated by test results, and an enterprise-ready application platform.
This stage uniquely leverages Velocity’s rapid development capabilities by introducing Agile development cycles that allow implementation teams to iteratively refine requirements – build – test – review – repeat. This approach generates actionable feedback, excitement, and momentum in near-real time, and as a result, this drives much of the positive customer experience that users have with data analytics applications.
Upon successful completion of this project stage, dedicated development and test environments are functional, representative data can be seen by application testers, the data model has been validated with the customer architecture, a roadmap for deployment is apparent, and project acceptance criteria have been identified. By time the implementation team reaches this point, all project risks should be well understood and mitigated.
This is the stage in which the solution developed and tested in the execution stage is formally handed over to and accepted by the (business) customer, consisting of users. Inputs include the deployment plan and any referenced documents. The primary output is the transfer of the project results and responsibility to the recipient organization(s). A final decision on deployment is made at this stage.
This is the stage in which experiences made in the project are documented and lessons learned are transferred to the organization. All outstanding issues are taken care of and the project is formally closed. Inputs include all project documents and artifacts. The output is the project‘s final report that is submitted to the executive sponsor and stakeholders for the fifth and final stage review.
Upon successful completion of this stage, users are supported in production; the final report, key deliverables and work products have been archived for future re-use. Furthermore, the historical benefits and lessons learned have been recorded for continuous improvement on future initiatives, the project sponsor has accepted and signed off the project, project financials are closed out and accounted for. By the end of this stage and the project, there is no more risk – only issues that have been carried into production.
As a full-service data analytics solutions and services provider, Velocity Business Solutions offers a comprehensive range of data analytics implementation services, including design, development, support, and enablement. We have completed hundreds of successful data analytics implementation projects for companies of all sizes.
This implementation model is best suited when you have the project structure and QA in place and need people to fit into an existing framework. We can provide consultations on long- or short-term engagements.
We offer cost-effective fixed-price services delivery models. This provides real clarity of your financial and project outcomes.
For some projects, there is an opportunity to ring-fence sections or areas. In these cases, Velocity is able to provide a mixture of resources and pricing options where risk and reward are shared.