CIOReview | | 9 AUGUST 2022skilled engineers that can balance the speed of agile environments with right long term decisions. Second, an analytics team, a hybrid of technical and business analysts that can take on 3 major responsibilities. 1. Defining Relevant-Actionable-Measurable (RAM) KPIs to assess business performance, and build an intuitive self service reporting suite. Understand relationship between metrics in Mutually-Exclusive-Collectively-Exhaustive (MECE) tree format to investigate declines or upticks efficiently.2. Develop an experimentation strategy to understand how customer behavior changes with different product designs and improved journeys. This includes not only clearly defining hypotheses with focus on learning but also identifying the right metrics to measure the impact and right methodology for experiment. Analytics team should have multiple methods in their repertoire to optimize learning under real world challenges i.e. if low traffic, try Bayesian vs frequentist; move fast by rolling out variations that are good long term solutions and leverage Synthetic Controls to measure impact post-hoc, leverage Multi-Arm Bandits for running multiple variations without impacting customers significantly or Multivariate testing to understand interaction between variations. 3. Utilize data science methods for customer segmentation, feature modeling to identify levers to optimize, topic model customer feedback to identify better solutions etc to proactively drive product strategy. Third, having a talented data science team with a mix of data scientists and machine learning engineers could really provide competitive advantage to any retail tech company. Data Scientists should take on some of the most complex business problems to develop most sophisticated and real time solutions with massive impact on customer and business. This could include Machine Learning recommendation algorithms that optimize customer journey in real time, operations research projects that optimize driver routes to shorten delivery times while controlling for cost, AI chatbots and more. Fourth, the analytics products team can help procure the right tools to support the data science and analytics team and help establish best practices across the organization. As we are heading towards the specialized role based org-design, it's evident that an agile environment is extremely crucial where each business has a squad designed to focus on specific customer problems with representatives from each vertical embedded in the business unit to ensure balance in speedy execution and domain expertise.In addition to right vision and setup for analytics organization, advanced tool stack and streamlined processes can help scale retail tech companies while continuing to solve most important customer problems with data driven solutions. Data and insights backed decisions could really be a strategic advantage if envisioned and executed right
< Page 8 | Page 10 >