I recently collaborated with RapidMiner on a webinar discussing the value of the role of business translator in choosing a use case. We discussed which roles make up a great data science team and our methodology to identify and score analytics use cases. We talk with a lot of companies that are struggling to translate the success of a single analytics project into a different use case or have difficulty identifying the roadmap to a sustainable analytics function.
The business translator is the bridge between the technical and business teams, and they are especially skilled at hearing business challenges or pain points and describing a solution using data. During project execution, they help maintain focus on the business value and success metrics to avoid projects that drift into insights generation without actionable next steps to drive value. At the end of projects, the business translator should communicate project findings into a roadmap and confirm the ROI and success criteria.
To choose a use case, we recommend conducting business value workshops. Design thinking is a great way to think outside the box and get input from all stakeholders before consolidating inputs into distinct use cases tied to business value. These ideas are all scored and prioritized through a methodology that considers ROI, impact to the organization, and feasibility. A readiness check is another important step in understanding the maturity of the organization to support advanced analytics, including things like data architecture, data governance and quality, and organizational readiness. However, you don’t need to bring your project to a halt if every single element of analytics readiness isn’t perfect. You can still get going and work through a proof of value project, which will help you prioritize the other support pillars as you build toward fully-scaled data products.