The Three Challenges Limiting Marketing Decision-Making
The Ipsos Marketing Anchors study, published in partnership with Professor Mark Ritson, makes a compelling case for investment in marketing training. But when you look beyond the headline capability finding, the data points to something structural: a system that isn't giving marketing teams what they need to perform.
The three patterns
At Ipsos Data Labs, working with marketing teams across sectors, we see three consistent structural patterns that explain why capable teams aren’t translating good data into better decisions.
The Framing Challenge: Data without a decision context
Effective use of data begins before the data is pulled. It begins with how the question is framed, what the organisation is actually trying to decide, what information would change that decision, and what level of confidence is required. When that framing process isn’t built into the way the organisation operates, data gets consulted without a clear decision context to anchor it. The result is that organisations invest significant resource answering questions with great precision, but not always the questions that matter most. The infrastructure for translating business problems into well-framed data questions is often less developed than the capability to answer them.
The Organisational Challenge: No single source of truth
Most marketing organisations have significant data assets: tracking studies, attribution models, CRM data, ad hoc research, finance and operations feeds. The challenge is rarely availability. It’s coherence. Data sits across systems, teams, and formats with inconsistent definitions and no agreed owner. Assembling a reliable, unified picture requires manual effort that is time-consuming and error prone.
The consequence is that decision meetings default to whatever is already to hand, which is typically financial and operational data, rather than the richer marketing evidence that would give choices a more complete basis. Not because that evidence doesn’t exist. Because it isn’t yet organised into a single source of truth that can be queried quickly and confidently.
The Application Challenge: Insight disconnected from the moment of decision
The third challenge affects organisations that have invested seriously in research and analytics. The insight exists and is often high quality. The problem is that it was built to answer a different question than the one currently on the table. Brand tracking answers questions about brand health over time. Attribution models answer questions about channel efficiency. Consumer segmentations answer questions about audience structure. All valuable. But when a CMO needs to defend a budget under scrutiny or decide whether to rebalance spend between brand and performance, those assets rarely speak directly to the choice being made. Information and decision-making end up on separate tracks.
The common thread
These three patterns share a root cause: information architecture that has grown from the data available rather than from the decisions the business needs to make. The environment accumulates capability without developing coherence. Decision Clarity addresses this by reversing the sequence. We start with the decisions that drive commercial performance, mapping where they happen, what they require, and how the information environment can be redesigned to serve them.
That’s not a data project. It’s a structural one. And it’s where the leverage is.
Ready to go further?
Read more about what a decision-led information environment actually looks like in practice - and five questions to test whether yours is working. Or speak to Jeffrey Roberts to explore what Decision Clarity could mean for your organisation.
