CIO Insight: The data proficiency spectrum

Where your company lies on the broad spectrum of data proficiency depends largely on how it gathers, structures and uses the massive amounts of information generated in the logistics and global trade industries every day.    It seems like all I ever read or hear about these days is data. Data management. Data curation. Data integrity. Data latency. It’s a lot for any supply chain professional to consider.
   And over the last few months, I’ve come to realize there is a broad spectrum of what I’ll call “data proficiency” in the logistics and global trade industries. To put it in modern pop literary terms, there are more than 50 shades of aptitude when it comes to collecting relevant data and applying it to supply chain decision-making.
   Perhaps a more relevant analogy is the way in which prospective job candidates list their skills on a resume. Is the job seeker an advanced user of a given system, a proficient one, or a beginner? And if the candidate claims proficiency, does it mean he/she is in the top tier of proficiency, or more like the lowest rung above beginner?
   It is way too simplistic to herd professionals into two huge corrals, one marked “tech savvy” and the other marked “luddite.” I’ve met retail supply chain executives who absolutely get the importance of data without understanding the underlying technology that gets them there. I’ve met technology folks who could talk about system architecture all day, but can’t speak to the root of a shipper’s actual daily problems.
   There are tech nerds at 3PLs and shippers who eat, sleep and breathe this era of data availability we live in today; there are those who get that something needs to happen, but have literally no idea where to start; and then there’s everyone in between.
   Almost any company will be comprised of representatives from every part of that data proficiency spectrum, and this is where meaningful application of data gets tricky. As readers of this magazine tend to cut across a few functions—from transportation procurement and management to global trade compliance—let’s get specific. Here are some simple questions to ask in order to identify where your company as a whole falls on the spectrum in terms of ocean transportation procurement:
     • Is the data already residing in your organization’s own systems (or file cabinets) or does it need to be gathered from external sources?
     • How confident are you that your data is accurate and not obsolete?
     • Is the data structured in a way that it’s comparable across systems and supply chain partners?
     • Does the data feed into a system that executes supply chain functions, or is it merely advisory in nature?
   From an ocean procurement perspective, the answer to the first question is probably “both.” Companies should have some internal record of their buying history. Now imagine marrying that with external aggregate pricing and service data on a particular lane, weather patterns, terminal delays, drayage availability, and much more.
   The second question is a crucial one, as overconfidence can lead companies down a dangerous path. “Garbage in, garbage out” is an oft-used trope to describe how companies that rely on inaccurate data inevitably make inaccurate decisions as a result. If an ocean procurement organization, for example, is relying on information that is out of date, even by a couple of hours, that could throw off any number of carefully calibrated downstream decisions.
   Also important is whether the procurement team has the ability to compare apples to apples. Three different carriers might provide the procurement team with data in three completely different formats, and without a layer of technology to homogenize that data, comparisons are essentially useless. It’s kind of like telling a football player to dunk a baseball.
   The last question really speaks to how data management has evolved. A procurement team using data to make decisions (especially if the data triggers execution automatically) is leveraging that data exponentially more than an organization simply using it to check historical performance.
   Recent American Shipper benchmark research into freight transportation and visibility has found that the majority of companies don’t yet use data to aid in decision-making.
   This all might seem basic to some—and overwhelming to others—but in truth, there are hundreds, if not thousands of software providers and consultants salivating at the chance to show anyone and everyone how this data stuff works in practice. What’s more, advances in cloud computing, machine learning, and user interfaces, and lower implementation costs means it’s cheaper and easier than ever to engage those providers and get your company ahead of the data proficiency curve.
   And here’s another encouraging thought. I recently moderated a panel with Matt Tillman, whose startup company Haven operates an advanced logistics procurement and execution platform. When asked about the volume of data logistics professionals have to manage, he had a surprising answer.
   Tillman, who has vast experience in advertising and financial data technologies, said the amount of data that needs to be processed to make enlightened logistics decisions pales in comparison to other industries, where petabytes (that’s 1 million gigabytes) are collected daily.
   In other words, while they may not be simple, logistics data initiatives require far less collection and analysis to be effective.
   So don’t despair. Start with the basics. Carefully examine the universe of providers out there to help address your specific needs, and move quickly, but methodically. The sooner you do, the further up the data proficiency spectrum you’ll be.