Ben Yoskovitz recently summarised a data workshop with the following statement: “Ask the right question” A very simple but profound truth. With all the hype around ‘Big Data’ it’s easy to loose focus on what really matters. Asking the right questions is a lot easier said than done. It takes great insight to get to the heart of the matter and avoid getting distracted with superfluous ‘shiny objects’. This sentiment was echoed by a former MoD health physicist that I was talking to over dinner last night. He had fairly strong views on policy making and freedom of information, which probably better not to mention here (!) but fundamentally his view was if businesses, governments, organisations asked the right questions (of subject matter specialists) they would be (better) equipped to navigate ‘new terrains’ and put in place ‘effective’ policy and regulation; less about control and more about managing freedom of information.
So for those of us who don’t have the genius brain of Yoskovitz or a physicist, what are the best practices for managing data and analytics?
Yoskovitz and Croll define analytics as ‘a measurement of movement towards your business goals’. If what you’re measuring is not helping you understand how your business or organisation is reaching its end goal then you probably need to go back to the drawing board. Within your business what is the one metric that matters? Determine what this is and build in key metrics that support this. Remember, if a metric won’t change how you behave – it’s a bad metric
This summarised lean analytics presentation outlines some good best practice, but worth highlighting the different types of metrics:
- Qualitative (discovery) vs Quantitative (proving)
- Exploratory (the cool stuff) vs Reporting (the necessary stuff)
- Lagging (Start here) vs Leading (try and get here)
- Correlation (find) vs Causation (test)
- Vanity (feel good, superfluous) vs Actionable (these good, change behaviour)
In summary, when working with data Martin Squires (Head of Customer Insight at Boots) approach is useful in structuring the data management:
What? (the data) So what? (the insights and analysis) Now what? (the actions that should follow)