When AI Meets KPIs: How Connected Services and AI Can Streamline Data Analysis

We’ve seen a lot in the news lately about Artificial Intelligence (AI) and the promise (or curse, depending on your perspective) that it presents to mankind. There are a number of valid concerns with respect to AI, including, privacy, confidentiality of information, accuracy, rights of use and regulatory uncertainty. Let’s dial it back a bit and consider for just a few minutes what AI might be able to do for the material handling industry, say, as in managing a warehouse or a forklift fleet. We’ll start by looking at a common AI use case, then break it down to see where we might find value in applying AI in a work setting.

One popular exercise that is often undertaken with some of the new AI tools is to ask the tool to develop something new based on its collective knowledge about a certain topic. The results seem to range from being mystifyingly accurate to incredibly ill-informed. If nothing else, they can be somewhat inconsistent, and the inventors of the tools themselves would be the first to say that one shouldn’t rely on them alone to perform real work or make real decisions.

So, where can AI tools provide value for the warehouse or forklift fleet manager? The key might be in avoiding the temptation to use it to create something new. One thing that these tools have proven to do very well is to sift through mounds of data and information to recognize patterns and trends. They can provide another source of information we can use to help predict outcomes, based on what has already occurred. And, while many of us could do this if we only had the time, AI tools can handle it without getting bored, tired, hungry or careless, and they won’t have to choose between getting new work done and evaluating how past work was completed.

Most of us are surrounded by data and information, and we’re bombarded with even more every day. Regardless of our role, we tend to be focused on productivity, churning out more work, generating even more data that seemingly no one has time to review. It’s hard to step away from getting work done long enough to truly understand what has already been done, and how. We know we need to develop KPIs and track our performance against them, but it can be difficult to know where to start, let alone set aside the time to really analyze our performance.

With all of the current hype surrounding AI, some might be tempted to view it as the answer to this data paralysis, but, as we’ve already mentioned, even the creators of most AI tools acknowledge their shortcomings. If it can’t do the work for you, then how can AI provide value to the busy warehouse or forklift fleet manager?  By supplementing existing measurement tools and processes, acting as an intermediary layer between data collection and human evaluation to streamline analysis that turns mounds of data into nuggets of knowledge.

Thankfully, there are already such tools, including Crown’s InfoLink Operator and Fleet Management system, that can do an excellent job of capturing and organizing data regarding operator and forklift operation and productivity. Crown’s FleetSTATS Fleet Maintenance Management system does something similar with forklift repair and maintenance information, accumulating all of the historical data in one place, where it can be analyzed to help identify improvement opportunities, if only you had time to look at all that data.

These data collection tools can then be supplemented with services that can utilize the accumulated data to help you make better operational decisions. In conjunction with its InfoLink system, Crown offers InfoLink Performance Services. These services are designed to help you identify meaningful metrics and KPIs for your business, then correlate those KPIs with data that is already available to you. The InfoLink platform is also an enabler for something Crown calls Connected Maintenance. The InfoLink system gathers data about the operation of the lift truck, then the connected service program can compare data for one lift truck or one operation to aggregate data across hundreds and even thousands of vehicles and customers, to help determine how to best maintain and repair an individual vehicle. One goal is to enable service technicians to approach repairs more proactively, but an even larger goal is to help forklift users identify problems before they become problems, so unexpected downtime can be avoided.

There is potential for AI to help revolutionize some aspects of material handling. Tools will get smarter, capabilities will increase and, one day, you might welcome the idea of having an AI assistant at your disposal. After all, look at how many people ask their smartphone or countertop smart speaker for advice every day.

Until then, you don’t have to be a victim of data paralysis. There are options available today that help analyze data, compile it into KPIs and provide the knowledge you need to make better decisions about your business. Technology moves fast, but there are opportunities now to get ahead of the game, positioning you for even greater success if and when AI meets KPIs in the years to come.