The Other Side of Data in the Media Business
What the steel industry can teach advertisers about data
When we think of data in relation to media, we tend to think of the “big” variety. And with good reason. Among other things, big data has helped us target consumers who want to be targeted, increase our ROI, make better use of media channels, and reduce waste. All of this has led to a better, more valuable, more sustainable future of all types of media.
“Big” data has been a huge part of media since the early part of the 21st Century. However, there is another side to data that often goes overlooked or unnoticed but has had profound effect on every industry long before the internet. To illustrate this point, we can go all the way back to the turn of 20th century and the steel magnate Charles Schwab (no, not that Charles Schwab.)
The legend goes something like this: Schwab was looking for a way to improve the output of one of his underperforming mills. The manager of the mill swore he had tried everything he could to improve his teams’ output. He threatened them, he swore at them, he reasoned with them. Nothing would work.
Schwab calmly asked the day shift foreman how many “firings” they had done on their last shift. “Six” was the answers. Schwab then took a piece of chalk and wrote a giant number 6 on the wall for all to see and promptly walked out.
Schwab returned the next morning after the night shift was completed and saw the 6 was rubbed out and replace by a 7 from the night shift foreman who clearly did not want to be outdone by the day crew. Schwab returned once more after the day shift was finished and observed the 7 had been replaced by a 10. Just like that Schwab improved his output by 66%, in 24 hours, without saying a word. The competition went on and on until that plant went on to become among his most productive. All through the careful application of a single data point.
It’s important not to take the wrong lesson from this story. Media professionals, unlike steel workers, are not measured by the volume of output but rather by the quality and value of their buys. However, understanding how data speaks to us, and motivates all of us every day will go a long way in driving results no matter what the goal.
Schwab understood not only that data are important, but he understood that the right data, delivered at the right time, in the right manner can have a much greater impact on performance than will reams of data you can’t decipher or pull together into a story. Too much data can actually be harmful to an organization. Information overload or “infobesity” as it is now known can lead to reduced quality of decision making or worse, lack of decision making at all.
We live in a world filled with almost unlimited data but much of the most important data points people use to navigate the world every day are notable for their high importance and simple delivery: the fuel gauge on your car, the balance in your bank account app, the date and time on your smartphone. The “right” points of data like these, delivered at the right moment, will have a much greater day-to-day impact on your life then almost all the data on the internet.
Of course, what constitutes the “right” data depends both on the job at hand and your ability to process it in a useful way.
Consider the pilot of a Boeing 737: to do her job safely and effectively, she has 56 controls and data points to pay attention to in flight: air speed, altitude, heading, trim, load weight, to name a few. The result of having all of this data: air travel is the safest form of mass transportation on the plant. But does anyone think that providing 56 data points to the automobile driver’s dashboard would reduce accident rates? Of course not. In most cases overwhelmed and distracted drivers would be more accident prone with all of these data delivered at once. Much of safe driving involves filtering out unnecessary distractions (as anyone with children can attest.) To cope with all of the data necessary to fly a plane, pilots have years of training, a co-pilot, and air traffic controllers helping them decode it.
Which is not to say that more data in other forms could not reduce car accidents. Early evidence suggests that computer driven cars will be much safer than human driven ones. This is because their computers can process many more datapoints and react much faster than any human and they never get distracted. Totally driverless cars may still be a few years away but in the meantime, today’s cars are being built to manage data for the driver. The data that your car’s antilock brakes and traction control computers might just save your life one day, but it would be useless to even the best formula one driver if he was left to manage it on his own.
Which brings us back to Media:
We understand that your quest as a media professional is to constantly improve and perfect all aspects of your buys. In today’s world this requires data and analytics far beyond the data traditionally used to place a buy. To stay ahead of the competition, we need data about how we execute the buy itself. How much time does it takes to analyze and execute a buy? How many resources do we need? What are the key data points we need to ensure delivery? All of these factors can impact our ability to capitalize on market opportunities and stay profitable. They can mean the difference between bringing the campaign in on budget or having disappointed clients. Viewing performance and clearance data can help us make adjustments throughout the campaign. And yes, data can motivate your teams by giving them objectives to hit.
Now…If only you had that data and means to decode it. Think of all ideas you don’t execute in TV campaigns now because you don’t have the data you need. Think of all things you don’t execute in TV because you don’t have the technology to decipher that data the way your car processes tire traction data. ProVantageX is changing how you think about those ideas.
When we decided to create ProVantageX, our objectives were simply. Make the best use of available data to help drive media value and provide the technology to execute on that data with peak operational efficiency. Just like that overwhelm driver, we understood that dumping loads data into a process where stressed out buyers and sellers are under pressure to complete buys measured primarily on CPM and dayparts GRPs would be counterproductive. Without the means to adequately process the key information they should be considering, buyers are often left vulnerable to second guessing by skeptical clients at best. At worst they are simply unable to execute as efficiently as they need to maintain profitability.
To solve for this, we first had to understand all of the elements that were most important to a buy from a quality standpoint: Programming environment, audience composition, program type, station preferences, historical data, spot limitations, do not air mandates. The list goes on and on.
Next we devised state of the art technology to gather, analyze, optimize and execute that input. We have taken the trillions of considerations buyers are expected to consider and optimized them to deliver it in the most concise, useable and applicable way possible.
Finally, we have designed features that manage operational data to allows for the collaboration, coordination, and oversight of buy execution for peak performance and improvement.
PVX goes well beyond automation. We are laser focused on the nexus of data and technology for the next generation of buyers. Our team has decades of experience understanding what data your buyers need and how to deliver those needs to outperform the competition. Charles Schwab would be proud.