Smarter IT budgeting decisions in Washington State
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Decision Lens
Tech Stack
- Microsoft Excel
- Web-based solution
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Cost Savings
- Digital Expertise
- Productivity Improvements
Technology Category
- Analytics & Modeling - Data-as-a-Service
Applicable Functions
- Business Operation
Use Cases
- Demand Planning & Forecasting
Services
- Cloud Planning, Design & Implementation Services
About The Customer
The customer in this case study is the Office of the Chief Information Officer (OCIO) in Washington State Government. The OCIO is responsible for ensuring that the state's annual IT budget of over $900 million is spent in a way that advances the governor’s policy objectives. The projects must either improve revenue or reduce costs and have a direct and positive impact on citizens or public safety. The OCIO is tasked with analyzing complex IT projects and providing a set of easy-to-read recommendations. The OCIO also wanted to ensure agencies planned IT investments using certain key drivers such as building them in the cloud, implementing strong cybersecurity measures, using agile development techniques, and thinking about how technology can fuel further efficiencies and innovations.
The Challenge
The Office of the Chief Information Officer (OCIO) in Washington State Government is tasked with ensuring that the state's annual IT budget of over $900 million is spent in a way that advances the governor’s policy objectives. The projects must either improve revenue or reduce costs and have a direct and positive impact on citizens or public safety. In 2013, State agencies proposed 86 different projects that were either level 2 (medium risk/complexity) or level 3 (high risk/complexity) IT projects. The projects ranged from settling tax boundary disputes to tracking marijuana from seed to sale to Medicaid shopping plans. The challenge was to analyze these complex IT projects and provide a set of easy-to-read recommendations that even technophobes can understand. The legislature asked the OCIO to create a prioritized list that ranked the projects as high, medium, or low.
The Solution
The OCIO initially built a Microsoft Excel model to analyze and rank the projects. However, the model was not sophisticated enough to reflect everything that was important in evaluating projects. Minor changes in the model could have major implications but it was hard to identify which changes were causing issues. The OCIO then decided to use Decision Lens, a web-based solution for collaborative prioritization and resource optimization. Decision Lens is based on Thomas L Saaty’s Analytic Hierarchy Process which applies both mathematics and psychology to prioritize. The OCIO revamped the process for weighting the criteria to include not just members of the OCIO but input from the Office of Financial Management and input from members of the Technology Services Board (TSB).
Operational Impact
Quantitative Benefit
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