What Last-Mile Delivery Has in Common with Better Data Science

Advancements in data analysis related programming languages and new, more affordable cloud tools and technologies, allow for large-scale data analysis and prediction capabilities, leading organizations to build data analysis and data science capabilities. To meet the demand, more data science graduates are joining organizations to analyze data and provide insights on ways business can help improve products and services.

But data science takes more than just data scientists.

Leveraging data and analytics and performing data science is the “last-mile delivery” of a much bigger and longer supply chain.

A supply chain transports goods from the factories to end consumers, which can involve many different modes of transportation and steps before the goods even reach the final warehouse. From there, they need to be organized, stored and tracked so inventory can be located quickly to ship out to end consumers when orders are received. When one step in the supply chain fails, it can be catastrophic to the entire system—creating delays and dissatisfied end consumers.

To fulfill orders in a timely fashion, supply chains rely on proper systems and automated processes to make the goods available for those last-mile delivery providers. Data science is much the same way.

Data scientists can’t analyze data and provide insights to business decision makers in a timely manner without data that’s already been collected, transformed, organized and stored in a proper manner.

Business leaders and decision makers may think the work of data science is taking too long or that data science teams are ineffective, but what they might not realize is the issue is much earlier in the supply chain. They’ve hired excellent last-mile delivery providers without building the supply chain needed for them to deliver insights in a timely manner. That leads to data science teams taking on the additional effort of building the supply chain—something they may not be trained to do—instead of focusing on delivering the results they were hired to provide.

Last-mile delivery depends on a functional and effective supply chain, which is why it’s important to build your supply chain first.

Hire the right people to make the data available to the data science teams so those teams can deliver the insights businesses need to make their products and services better, grow their sales and increase their revenue.

Your supply chain team should be composed of software engineers, DevOps engineers, and data integration and transformation specialists. Your data specialists should be able to acquire, then clean and transform data into the desired formats through ETL/ELT tools and processes, and fully automate the process to support on-going development and testing capabilities, while providing a stable and secure production environment. The processes and data in your production environment must be stable enough to provide quick and reliable results to arm the business with the data they need to make the right decisions.

When integrated into a full, established process, data science is an incredible tool to help companies make data-driven decisions. Your last-mile data science team can help make sense of user behavior data, provide insights to help you better your products and services, help drive revenue and sales, and scale accordingly to meet demands on your business.