In 2015, CDOT wanted to move into big data analytics. However, with so many ways to approach, they wanted to evaluate best tactics. Focus on advancing existing technical infrastructure? Establish Governance? Identify needs? They knew they had a lot of data, different data, disparate data sets within CDOT. Also, they wanted to move from data for MIS and into data for advising decision making. Also, supporting modeling, and making it easier to access quality data. Furthermore, they wanted to understand how CDOT could increase their data management efficiencies, data quality, accessibility, interoperability. Subsequently, understand the use and value of its transportation data assets. The State Office of IT reached out to Xentity to facilitate discovery and definition direction.
Problem and Solution
Xentity proposed a discovery workshop to help CDOT investigate scope for a CDOT Data integration effort. Xentity approached this in a rapid workshop model to help executives illustrate where they can go without any high-end whitepapers. In a half-day workshop with preparation and action plan deliverable closure on either end, we were able to help CDOT backlog epic actions, plan directions, and ensure the efforts were tied with a line of sight. This three-hour discovery session with primary executive stakeholders to establish top data integration and business intelligence priorities. Also, inventory and rank questions, understand data readiness, and layout suggested scope for follow-on project definition, alternative analysis, and sprint proof of concepts and beyond.
The Actions Taken
- Mission Alignment – First, understand what parts of CDOT are most looking to engage in this capability from a strategic objective and mission question point of view. With a resulting focus on Traveler Safety, Access Mobility, and Condition/Asset Management (of the MAPP-21 areas).
- Directors Needs Alignment – Next, we examined using interactive workshop post-its, walk-abouts, and poke points to identify questions needed to be answered in those areas. We classified each by the asked level of complexity- knowledge, information, or data.
- Portfolio Alignment – From there, we took an investment point of view, and simulated budget assignments of which to invest in first.
- Architecture Alignment – From there, we aligned near-term recommendations with pre-workshop knowledge of their architecture collaborating with OIT. We held discussions on governance needs. We captured the risks such as the chasm on moving between data and knowledge.
- Investment Guidance – Guidance were captured and discussed considering the readiness, complexity, and value of the questions as compared to what capabilities and datasets were needed. The team captured a catalog of next steps in a suggested roadmap by near term, mid and long-term. They also captured an illustration of the journey to address these tasks.
Outcome and Benefit
In capturing the mission, director needs, portfolio and architecture alignment with Governance, the next step action plan resulted 18 months later with CDOT investing in a Chief Data Office construct for 5 years. This hopes to incubate the model further and later move into an enterprise data management operation. After a large open competition, Xentity won this work. Xentity supports CDOT investment in integration patterns for microservices, geospatial, real-time data, and advanced data analytics platform. Furthermore, we accomplished this while establishing a multi-year investment plan, governance, and gaining multiple director needs portfolios along the way well across all divisions.