What Will AI Do for Your 3PL?
In Extensiv’s 2024 Benchmark report, they asked respondents where AI would have the most significant impact on their business. What was interesting was that their responses were all over the place. It looks like every issue 3PLs typically face is represented evenly. My takeaway is that people view AI as just another tool to throw at their most challenging problems. However, I wonder if these challenges are caused by businesses lacking a tool or by insufficient processes. What do you think?…
Make Your 3PL More Profitable
Nearly 20% of 3PLs still do manual billing. Unsurprisingly the ones that have found a way to automate their billing are more profitable. So if you could automate your billing why wouldn’t you? All the Best, Tucker
Increase Billing Quality with Data-Driven Billing
Billing is one of the hardest things to do in fulfillment. It sucks for 3PLs and brands. There are so many moving pieces within the warehouse and tech stack that exceptions happen constantly, and using Excel only compounds the number of mistakes, errors, and omissions that can occur for every invoice. This is the area where being data-driven can have the largest ROI in terms of increased billing quality and customer satisfaction. Here’s three you need to do if you want to have data-driven…
Fast Track Your Project to Failure
Data projects tend towards failure. Not necessarily because of anything anyone did but rather because of the things people don’t do. Here is a brief list of all of the things you should do if you want your data project to fail: Don’t have an executive sponsor. Do have daily check-ins Avoid implementing data quality checks Don’t bother understanding the business process Focus on the technology rather than the outcome Deliver everything at once Take everything people tell you at face value;…
Two Key Stages to Unlock Data Value
Data is only valuable when it is in motion. Typically, it goes through a couple of stages of motion: ETL/ELT and Integration – This is where data is extracted from source systems, modeled, and combined into one source of truth. Reporting and Visualization – This is where you would use a BI tool like Power BI to visualize and present data to your end users as actionable insights. If you try to skip a stage or take a shortcut, either by integrating your data but not reporting on it or jumping…
Why Mixing Excel with Power BI Is a Recipe for Disaster
Using Excel as a data source for Power BI is risky business. Excel’s volatility—from typos and inconsistent entries to frequent formatting changes—makes it a poor choice for producing reliable data insights. Even minor alterations, like a column header change or sheet rename, can cause errors that take analysts hours to trace and fix. Power BI works best with structured, stable data. When Excel disrupts that stability, the risk of poor data quality and frequent report errors skyrockets. This…
Avoiding the Trap of Quick Fixes & Overplanning
Most companies today understand that data is the backbone of sustainable growth. A common trap many fall into is overemphasizing quick wins or focusing solely on long-term projects. Either approach alone often leads to internal friction, mistrust, and frustration—especially between fast-moving sales and a stretched-thin operations team still relying on outdated Excel reports. The real answer? Build for both immediate value and future scalability: Data models over quick reports: Start by…
Where Should You Fix Data Quality Issues
Data quality impacts everything, especially when building a single source of truth. But where do you fix quality issues? Often, it’s a choice between fixing data in the System of Record (where data is first captured) or in the Decision Support System (DSS), where data supports business insights and decisions. Typically, data flows from the System of Record to the DSS. Which makes it easy to identify where the issues is. But identifying the issue is only half the job—the real challenge is…
Data Warehousing Projects: 3 Indicators of Success
Data warehousing projects are highly technical, and typically involve a lot of different moving parts. So how do non-technical business leaders know if the project is going well? While you should listen to your data team there are a couple of leading indicators for project health. Leading Indicators: Documentation – While no project ever has “perfect” documentation, there should be something in place—and it should improve as the project progresses. Data Quality Checks – A healthy project…
The Silent Killer of Data Projects
Data quality is one of the silent killers of data-driven solutions. If the data is wrong, even a fraction of the time, no one will trust it. So, it’s important to tackle quality as early as possible. Here’s a couple of ways to prevent your project from being killed off: Build a Strong Data Model – I talk about data modeling a lot and for a good reason. Without a well-structured data model, it’s nearly impossible to ensure your business logic is consistently applied. A solid model helps catch…