How to Make a Big Problem Small
How a messy media program revealed a universal pattern—and ultimately led to the 6Qs.
About ten years ago, I helped a company use paid media to reach its target audiences. Interest was high—the company had never advertised before, and everyone wanted in. In the spirit of inclusion, leadership spread ownership across the organization. Multiple teams were responsible for securing budget, choosing where to spend it, working with media agencies, designing creative, and tracking and reporting results.
This complexity created operational chaos. My team spent weeks chasing information from stakeholders. When it arrived, it came in different formats, at different times, and with different levels of completeness. That made it hard to create tracking and trafficking tags that captured the context that actually mattered—audience, product, objective, offer, playbook, and so on.
It all came to a head with reporting. Cleaning the data took weeks. By the time Q1 results were ready, we were halfway through Q2 and planners were already working on Q3. Every report triggered a new round of questions—each one needing its own one-off analysis.
At one point we sent out a quarterly report and immediately got five replies, each asking for a different cut of the same data. That was the moment we knew the system—not the people—was the problem.
And everyone wanted something different:
Media wanted site and channel performance.
Creative wanted to see which headlines and layouts worked.
Audience owners wanted to know which targeting drove activity.
Product marketers wanted proof their lines were getting fair support.
Leadership wanted to see how each budget performed.
My team kept asking: Who do we prioritize? How should we report this? How do we handle multiple requests at once? There were challenges everywhere—which do you tackle first?
I didn’t know it then, but this was the beginning of what would eventually become the 6Qs framework.
From chaos to a pattern: the perspective shift
The well-intended advice was “keep it simple.” Unfortunately, while simplicity helps, oversimplifying doesn’t. Picking one slice of the problem just delayed other, equally important needs.
By stepping back and looking at the bigger picture, we could target a few specific solutions that would help us unravel the knot we were in. We realized our goal wasn’t to eliminate complexity, but to make complexity simple to manage.
That led us to three priorities:
Eliminate unnecessary variation by standardizing the entire media planning, trafficking, and reporting process—and giving teams clear, repeatable roles.
Enable critical variation by capturing rich metadata in discrete, governed fields (e.g., product line, audience segment, offer type, headline variant), even if we didn’t yet know which ones we’d need later.
Make requests cheap by building one canonical dataset that could be sliced many different ways.
Those priorities translated into three concrete requirements:
Normalize the data and push meaning into metadata.
Capture context as governed fields so one canonical dataset can be sliced by whatever variables matter.Use a surrogate key.
Stop encoding meaning in concatenated tracking codes. Use a unique identifier and map it to a rich description in a governed external table.Push metadata assignment to the right upstream owners.
The teams choosing the metadata to describe an insertion should be the ones designing the media plans, developing the creative, and assigning assets to placements. These are usually three different groups—and often not the operations team. Capture metadata upstream by baking selection into existing planning and creative processes.
Hard? Yes. Achievable? Also yes.
The net effect: faster decisions, better spend allocation, and fewer “mystery” results no one can explain.
The same pattern everywhere
Once you understand the problem and the high-level solution, you see these patterns everywhere:
Email wants cuts by audience, offer, cadence, segment.
Events want audience, session, role, objective.
Sales calls want account, role, topic, outcome.
Different labels, same categories of variables.
That consistency led directly to the 6Qs—a universal way to catalog context regardless of message, channel, or audience. They became the most useful “buckets” for structuring a canonical dataset:
WHO — audience / segment
WHAT — asset / offer / message
WHERE — channel / place / location
WHEN — time / cadence / priority
WHY — objective / product / initiative
HOW — playbook / execution
Once context lives in metadata, it doesn’t just help reporting—it travels with the work into your MAP, CRM, CMS, analytics tools, and AI systems.
What changes when you do this
With a canonical dataset and 6Qs metadata:
Reporting becomes self-serve. Any team can slice by the variables they care about.
Optimization becomes continuous. Shared definitions prevent drift and speed learning.
Tools like AI become reliable instead of hallucinatory. Controlled, well-understood context produces outcomes you can trust.
By shifting perspective, elegant solutions emerge from seeming chaos.
