What is Last Mile of Analytics?
The last mile of analytics is the last step in the analytics process that connects insights to business outcomes. More specifically, it is the process of using automation and collaboration to quantify, prioritize and curate analytics with a bias towards action. McKinsey found that nearly 90% of organizations that are significantly outperforming peers are devoting more than half of their analytics budget to bridging the last mile. The last mile is specifically the gap between data analytic results, outputs, dashboards and insights and effective decision making. This gap today is filled entirely by a human cognitive process that is responsible for creating business value from a report, chart or dashboard. It is the least automated step in the data and analytics value chain.
Use Cases for The Last Mile of Analytics
The use cases for the last mile of analytics span across multiple industries, including e-commerce, logistics and transportation, healthcare, and retail.
In e-commerce, last mile analytics can help businesses optimize their supply chain operations and improve delivery times, resulting in increased customer satisfaction. In logistics and transportation, last mile data can be used to track and optimize routes, reduce costs, and improve on-time delivery. For healthcare providers, last mile reporting can aid in identifying areas for process improvement and enhancing patient care. Retail businesses can benefit from last mile data collection software to analyze customer behavior, optimize inventory management, and improve marketing strategies.
By leveraging the power of last mile analytics, organizations can bridge the gap between insights and outcomes and achieve significant business value.