During the QuickStart, CULytics team will work with you to assess and define your data analytics roadmap, identify business needs, and hold in-dept discussions with your team throughout the assessment cycle. Post assessment, we will work with you to identify the appropriate resources (either internal or consulting) that will work with you through the build phase, into formal journey execution and value realization.
Using a structured agenda, facilitate a requirement gathering session to quickly learn who are the stakeholders, what roles will they play, what are the high-level business needs and challenges. We will also understand how your business functions use data today, uncover key challenges in using data and find new opportunities to help drive business outcomes. We will capture these requirements and then put in a framework to collaborative come up with vision and long/short term business priorities.
In this phase, we will understand your current structure and process that are in place to drive insights and business value. Is there a technical architecture that exists to meet business capabilities requirements? Is there a structured approach to data quality and integration?
- What's the data infrastructure needed to realize the value of the data?
- What BI and analytics functionality is needed?
- What Data governance framework is needed to successfully manage, secure and use the data?
- What executive and operational reporting framework is required?
In close partnership with your team, we develop a comprehensive 18-24 months roadmap that covers people, process and technology aspects of your strategy.
Different organization models, such as centralized Data Analytics team vs de-centralized data analytics team vs hybrid are considered with pros and cons of each to come up with a model that is most effective for you. Along with this an overall team hiring (as appropriate) and skill development plan is created.
Detailed plan with priorities and timetables to enhance the processes to reduce operational/reporting inefficiencies and drive growth is outlined.
Technology implementation plan for data management, data governance, advanced analytics model development is developed.