The Fog of War: A major media company struggles to understand its own data

But this story starts earlier—back when indecipherable data left executives in a fog of confusion and mixed signals. Below, we’ll take a department-by-department look at how the company’s data woes undermined performance at every turn. Then we’ll explain what it should have done differently.

The IT department
 
What went wrong:

As the exec put it, IT was the company’s “first port of call” for data. But the port was being flooded. “We were getting a ton of information, but we weren’t getting it in a unified fashion,” he said.

Data surged in from cable channels, print publications, websites and more. “There are probably 15 different sources of data that come through at any time,” said the exec. Engineers had to judge which information was most important, then compile it into coherent documents and share it with other departments – all in time for the company to act on it.
 

 
Case in point:

IT pros did their best to anticipate the needs of other departments. But assembling the data into readable documents took far too long. “Everything moves so fast,” said the executive. “If you’re taking too long to do something and somebody needs an answer, there are creative consequences and missed opportunities.”

Ultimately, IT unleashed a jumble of PowerPoint presentations and Excel spreadsheets. “It was confusing,” said the executive. “We needed everybody focused on the same goals. People in a company aren’t going to understand what’s driving the business if they don’t have a unified way of looking at things.”

What needed improvement:

• Collecting and collating data more quickly
• Producing clearer, more unified reporting

The marketing department

What went wrong:

By the time IT shared its findings, data was often obsolete. “If something was sitting in our digital platforms, and [marketers] couldn’t react to it in our outlets and on our channels by pushing it out to other digital channels, or by pushing out emails, that’s a missed revenue opportunity,” the executive explained.

The time lag also weakened the analysis. “We could never get past the top five or ten percent of the information,” said the exec. Marketers struggled to settle on basic KPIs.
 

 
Case in point:

The company offered an experiential travel service. Customers paid thousands of dollars for it—but the program was extremely costly for the company as well. Repeat customers were a must.

Equipped only with disorganized data, the company couldn’t distinguish potential customers from existing ones. It bombarded them with promotions after they were already sold. “Now we’re irritating them because we’re already selling them again,” said the executive. “Consumers have such high standards when it comes to personalization. When you don’t understand them, they have other options, and they just move on.”

What needed improvement:

• Swifter turnaround time from data collection to campaign activation
• Personalizing campaigns to individual customers

Programming and editorial

What went wrong:

The company housed a mammoth assemblage of programmers and creators. They wanted to know what consumers were saying outside the company’s own platforms, but had no way to swiftly collect and collate that information.

“You have to use all that information to figure out what should come next,” said the exec. “When you’re only looking at Nielsen, for example, you do get a nice demographic view. But you’re not really understanding viewer dynamics.”
 

 
Case in point:

The team couldn’t base its decisions on “the way consumers were reacting to the content,” the executive admitted. It couldn’t determine which programs or articles were likely to receive a favorable reaction.

Without identifying what its users wanted, or what they’d responded well to in the past, the company couldn’t build well-thought-out content verticals on its digital platforms. And it certainly couldn’t greenlight future projects with confidence. “You’re making a show for next year, not next week,” said the executive. “The right data helps you figure out what you should do.”

What needed improvement:

• Deeper insights into audience conversations
• Matching content decisions to measurable consumer interests

 
The C-suite

What went wrong:

To make efficient and informed decisions, executives need data to be parceled out with an eyedropper, not sprayed with a firehose. “What are the top three things the team should know about the business?” said the executive. “All of this complex data has to be grossly simplified so that everybody understands it.”

Unrefined information seeped into the C-suite from all directions, usually at a snail’s pace. When execs finally received it, it certainly didn’t come in the form of clear, legible dashboards. “Welcome to Microsoft Office,” the executive joked.
 

 
Case in point:

Often enough, executives withheld content from channels or markets where, they later realized, it would have garnered a wide audience. The company needed clearer, more unified data if it wanted “to do more due diligence, and to make better, more educated [decisions],” the executive said.

Forced to make decisions based on murky datastreams, executives risked signing off on marketing campaigns with no clear goals. They risked greenlighting content with no hope of finding a wide audience. “We needed to be able to say, ‘Here are all the projections we have for each platform,’” the executive said. “But it would take us weeks to figure out what data to even look at, if we even got to all of it.”

What needed improvement:

• Simplified reporting
• Succinct summaries of overall company goals
• Interactive and flexible dashboards

 
The bottom line

The company was treading on dangerous terrain, but couldn’t see its own footsteps. It needed coherence. It needed predictive capability. So it began the complex process of integrating business intelligence technology, which radically altered how it absorbed and shared data.

That’s when the fog started lifting.