Online and broadcast media companies now have a wealth of business intelligence, but most technology systems don’t share data to the extent that companies need. Unlocking discreet data collected by all these systems is the largest problem facing the media industry says Ashley Swartz, CEO and founder of Furious Corp.
Maximizing top line revenue, inventory planning, customer personalization opportunities—all of these needs require making intelligent decisions, but often the data is in disparate systems and sits in silos.
Strategic Planning and Technology
Practicing good data hygiene to gain real value from business intelligence requires two things: strategic planning to fully understand needs and existing systems. However, those existing systems might need another software solution to report the right information, one that can consolidate, normalize, and output data into custom reports or create dashboards for specific analytics. Developing a strategy is a combination of blue sky thinking and realistic understanding of the company’s current state of affairs. Fixing one technology with another is always challenging.
Digital has more data and smaller ad budgets, while broadcast has larger budgets but much less data. Each has lots of technology systems and many are delivered by multiple vendors. In television, there’s trafficking, order management, sales systems, CRM, measurement (Nielsen or Rentrak), and content management systems. On the digital side, there’s multiple ad servers, first- or third-party measurements (Google Analytics or ComScore), data management platforms, and a fraud or viewability partner.
“What we have in media is we are data-rich and insight-poor,” Swartz says. These disparate systems don’t share data. Without data, it’s hard to see what choices are more profitable than others.
Many companies won’t talk about how their systems are integrated, however their common questions are echoed by speakers at any industry event: Are we charging the right amount for ads? How do we measure profitability across geographic areas? Can we create standardized cross-platform measurements? Some answers to these questions may already be within the data locked in the various technologies used to power ad delivery.
Imagine a financial team that can’t do forward projections in their CRM. Sales people can’t see into the accounting systems to look at historical performance. Ad-ops can’t see credit information in finance software to help them plan capacity. That’s often the case for marketing: Each group is missing valuable data that would help them do their jobs better and make the company more profitable.
Creating a data strategy means identifying what the most important pieces of data are. For example, media companies could leverage their data to package audience segments which are significantly more valuable to advertisers.
Who Owns What?
The question is what data is important and who is responsible for coordinating a strategic data strategy?
“Sales may own the revenue forecast, but then Planning and Research own the inventory forecasting,” Swartz says. “Look at the process of how you run the business day-to-day. How much of that is manual and lives in Excel?” Non-automated reporting has many problems: high potential for error, timeliness of information, and time consuming for staff to work on. “Reporting is a great example. It’s typically a manual process that is done on Friday with spreadsheets and by the time they are read next week, the information is out of date.”
Creating an optimized data strategy can take a lot of time and money. Companies spend millions of dollars on consultants or software systems. Before doing that here’s a few high level ideas for first steps:
Identify an Owner: The person with the business function that is ultimately responsible for that process should own the responsibility for ensuring they can get the data they need from their technology.
Business Requirements: A typical mistake Swartz sees is companies bringing in consultants before understanding what their exact business requirements are. Document things by talking with all business units about how things work now and what the best possible situation looks like. “(Identify) measureable business outcomes—sales, profit, profitability,” Swartz says.
Data Identification: Do a data audit. Identify what data is needed and where it comes from. “Ask yourself if you brought these data sets together (could I) understand my revenue or my profit margin more?” says Swartz.
Process Audit: “The starting point would be to do an audit of your business processes: reporting, planning, pricing, and forecasting,” says Swartz. Identify and document how each business process is completed. “I would prioritize primary, secondary, and tertiary workflows to improve upon based on their potential impact on revenue or profit.”
Identify Inefficiencies: “When you’re doing a workflow analysis look at processes that are highly manual because they require your team members to basically connect systems that don’t talk to one another,” says Swartz. One company described a previous workflow to track inventory involving logging into the ad servers, running a forecast report, exporting the report to Excel, manipulating the spreadsheet for easier consumption, and then distributing the report to sales. “I would go back and ask your vendors how they can help you. Or look to see if there are solutions that you can bring in that would automate a lot of that manual work.”
Data Sharing: Going forward, connect enterprise technologies. “Connect all your data systems first and foremost to bring things together and use them to automate processes which are strategic to your business and strategic to revenue,” Swartz says. “In other industries, they reconcile and close the loop between their inventory forecasting and demand forecasting and their revenue forecasting. Their processes are connected and always updated. In media, they’re not.”
Making Better Choices
This is not a small problem to solve. “[Big companies like SAP, Oracle, and Microsoft, budget 60 percent of their software costs in the first year] for consulting because they go through workflow mapping and process re-engineering and change management to shepherd that process. I think media companies are sort of in a similar place,” Swartz says. “The question is how vulnerable is your business, where is it growing the most, and are there opportunities to be more efficient and more profitable?”
Creating good data hygiene means having a better chance of success unlocking the insights held in these separate systems. While it may be as painful as going to the dentist, the rewards are the difference between thriving or becoming an also-ran.