Readers of this blog know we often tout the value of data-driven decision making. Warehouse managers who rely on gut instinct or general assumptions about anything from fleet utilization and routing to operator productivity and accident prevention will never achieve optimal results.
Now there is additional proof that leveraging data analytics pays off.
A new study from the Wharton School at the University of Pennsylvania shows – and here’s the important part – process-oriented companies have the most to gain from taking advantage of data analytics.
In an analysis of the study, strategy+business observes:
“Companies that base their business models on incremental improvements to existing products or processes…can indeed get a significant boost from exploiting data analytics.
“In short, use of data analytics seems far better suited to companies that are looking to make small incremental changes to their existing businesses than to those seeking to make a big splash with novel products or services (innovation oriented).”
If there is anything that defines or should define warehouse and distribution center management, it’s process improvement. Rather than measuring consumer preferences or habits, which for many reasons is harder to gauge, the material handling environment lends itself to analytics. Here, you are afforded the chance to isolate individual processes, set benchmarks and goals, and measure progress.
- How many pallets does each operator move per hour? How will a change in routing affect their productivity?
- How much time does your fleet spend active with load? What will it take to right size your fleet?
- Where, exactly, do forklift impacts take place in the warehouse? Which drivers tend to be more accident prone than others?
- What are the most wasteful steps in receiving? How should they be eliminated?
Until recently, warehouse managers had to rely on manually gathering data for process improvement, a cumbersome and time-consuming undertaking. Perhaps, as a result, organizations have tended to put the focus on outcome measures (“We spent $XX on supply chain last year and delivered YY packages”) that may be easy to report but only serve to solve “the problem of the day” rather than deliver true insight.
The evolution of warehouse tracking technology, however, has facilitated automatic data collection, and consequently, data analytics and process improvement. Warehouse technology connects all the pieces of your warehouse – drivers, managers, forklifts, pallets, etc. – collecting real-time information that you can use to determine where your costs lie and what the drivers of those costs are.
Spokane Industries provides a real-world example of just how impactful the use of real-time data collection can be. The company realized a 90 percent reduction in forklift accidents after switching from an informal system of letting drivers report incidents to an equipment monitoring solution. Spokane knew the issue at hand and decided to act; the technology was the enabler of the company’s goals and objectives.
Ask yourself: What is the purpose of quantifying different levels of your organization? How will it help your organization become more profitable? How will you act on the data?
“Previous studies have suggested that firms’ ability to extract value from data analytics depends not only on having the right IT platform and latest technology in place, but also on employing a larger proportion of skilled workers who can process the information.”
If you are still relying on your best guess to drive process improvement, plenty of evidence suggests it’s time let data play the leading role.