Making numbers meaningful:

Updated: Mar 28, 2019

Understanding your team.




I recently had the privilege of presenting at the Australian Higher Education Industry Association’s annual HR Benchmarking Conference to share my thoughts on turning Analytics into Action. With a background in organisational psychology and development, HR strategy and strategic workforce planning, I took a different approach to some of the speakers – focusing not on the numbers but the broader strategic, organisational and interpersonal factors that can affect the impact your analysis can have.


The first step is:


Understanding Your Team


Teams are like diamonds - the best results come from looking under the surface and adding a bit of polish.


Before you look outwards, you need to look inwards, and understand your team. Why are you there, what are you supposed to deliver and how are you supposed to deliver it.

If you are unclear in your own purpose; if you don’t know whether you are supposed to be delivering static reports on current state or future focused analytics and forecasts; and if it is unclear as to who is responsible and how the information is to be delivered, your ability to provide useful insights to the business will be compromised before you start.

Likewise, it is imperative to understand the structure of the team, the skills and capability in your team to deliver on that purpose, and the interactions between the members of the team. A new team of junior analysts and data scientists is unlikely to operate in the same way, or deliver the same outcomes, as a team that includes experienced senior business partners with established relationships across the organisation.


Understanding and using the skills, capability and influence of the team to best advantage is vital to getting the most out of not just the team, but also your data.

It is easy to stereotype analytics teams simply as bean counters and number-crunchers (think Sheldon Cooper without the wit and charm). But to be useful to the decision-makers in an organisation, analysts need to bring a whole brain approach. The methodical, sequential and quantitative approach to evidence and analysis must be balanced with strategic, holistic and relationship-based story telling, to bring the data to life and demonstrate its value in solving the real-world problems faced by the business (particularly if the business doesn’t realize they have a problem).


A great story with poor data will always Trump great data with a poor story.

When it comes to diamonds, and analytics, size does matter. One analyst with an Excel spreadsheet and pivot table may be able to provide all the information you need, but the bigger the analytical power (either in terms of people or systems), and the more time available to analyze, interpret and present the numbers (and the story), the more meaning you will be able to convey to your audience.

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Pyramadis