The situation
The final stage of a delivery, from local depot to the customer's door, is the most expensive and the hardest to get right. A global e-commerce company had teams of business owners, product managers and engineers working to make that last mile smoother.
The problem
Good decisions depended on regular reports about how deliveries were performing. Many of those reports were still being put together by hand, in a way that had grown up over time. It took people's time away from analysing problems, and the slow queries behind the reports made things worse.
What we did
The work had three parts. First, the team agreed with business owners which measures mattered, and built reports and dashboards that showed them clearly, so decisions could be made from the same view.
Second, the manual reporting routine was replaced by an automated one, so the report built itself on schedule.
Third, the team worked with the data engineers to set up better data pipelines, so the questions people asked of the data came back much faster.
The outcome
Automating the old reports saved 624 hours of work every year, and queries ran more than 80% faster.
What it meant for the business
People who used to spend their week assembling reports could spend it working out what the numbers meant and how to improve deliveries. Faster queries also made it easier to explore a question as it came up.
Could this work for you?
If someone in your team spends hours each week copying numbers into a report, that routine can almost always be automated. It's among the quickest wins in analytics.
Related services: Data visualization and reporting, Data engineering and warehousing
This project was led by our founder, Achyutanand Jha, in an earlier role. The client is not named, and figures are those reported at the time.