What are 3 key things brands should focus on in creating a high performing digital analytics program?
1. Identifying an analytics leader who can clearly see the business problems that analytics can address and propose solutions that will generate positive ROI.
Successful analytics programs take a consolidated group effort. Success hinges on how well the organization utilizes internal domain knowledge, supplemented at times by external expertise to monetize data opportunities.
Large enterprise companies may be lucky enough to have a Chief Analytics Officer in place with strong executive sponsorship and oversight. A Director/VP of Analytics should be knowledgeable enough to play the connective tissue between the executives and true subject matter experts.
This Director or VP role will make the business case for the programs in play (and the technology that deploys them) and can answer to the ROI of the program. This individual will be tasked with assessing people, processes, and platforms needed. He or she must also be able to decide when to buy, borrow, or build talent and technology to address the opportunities at hand.
The most common failure point for an analytics program stems from not having a clear and universal alignment on what problem the analytics team is trying to solve for. Companies invest in staff and technology to pump out models and insights – but left unguided, those solutions may not specifically address a business problem.
Those squandered hours reduce the expected ROI of the program. Once it becomes a frequent issue, the Finance Team (or even the CFO) starts questioning the value of the program and the technology driving them. Without clear alignment, analytics programs may see their future budgets reduced and their perceived value in the organization diminish. Getting the right person involved up front, and identifying the problem the team is looking to solve will help drive successful outcomes.
2. Focus on the foundational elements of measurement. Evaluate and define the business requirements, create and update a Solution Design Reference (SDR) that maps to the requirements and then implement it.
An SDR is a Solution Design Reference spreadsheet that documents all business questions and proposed variables that capture data relating to those questions. It is the foundation of any analytics implementation and its quality can be the difference between success and failure.
The SDR is a blueprint of a digital analytics implementation. SDRs provides many benefits to an organization but three acute benefits are they help:
- Define business requirements identified by stakeholders
- Map those requirements to variables in the analytics solutions
- Facilitate staff understanding the implementation and variable definitions
Creating and consistently updating an SDR is a critical first step in creating a high performing digital analytics program. The process will enable organizations to capture the right data, instill trust in that data, and then allow downstream actions to be taken with confidence.
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