All modern organisations depend on data, but many smaller teams and businesses struggle with where to start.
Small organisations benefit from developing data skills that enable them to gather, analyse, and interpret data to make informed decisions. These skills can range from basic data management to more advanced analytical techniques, helping businesses understand stakeholder behaviour, improve operations, and gain a competitive edge.
AI is often touted as the new ‘magic’ that promises to transform efficiency and profits, but good data management is the foundation upon which AI depends.
Data skills can be considered from two perspectives – Data Mindset and Technical:
It is important for organisations to grow a data-driven mindset and culture, as it will help leaders to think strategically and critically about their investments, tools, and activities so they can be confident they are making decisions rooted in reason and evidence, not just gut feel.
Start by considering the business problems you are trying to solve with data before diving into the technical details. This will help you determine what data you’ll need to collect and what analysis to focus on.
Data literacy is the ability to read, work with, and communicate with data effectively. People will come to the table with different skill levels. Some might be able to read statistical tables with ease while others may need some extra time to interpret a graph. Because of this, it’s important to create an atmosphere where beginners feel comfortable speaking up when they need help, and help is available for them to improve their data literacy skills.
A data-driven culture is one where people make decisions based on data. While intuition is a large part of decision making, you can be more confident in your choices when you back them up with data.
Creating a data-driven culture starts at the top. Leaders should set an example by demonstrating how they back up decisions with insights gathered from data analysis.
Make sure that analysis is transparent - it’s very easy to misrepresent reality with data. Be honest with yourself when your data isn’t telling you what you want to hear – e.g. don't weigh yourself while you’re holding onto the towel rail.
Data should be used to drive decisions, not the other way around!
This involves breaking down barriers to data access and providing the necessary tools and training for users to understand, analyse, and utilise data effectively. Acceptance of the core principle that data is a valuable asset, which should be made available across the organisation, should follow the development of a data driven culture, but it will need nurturing.
While it is great to have data specialists who can do extraordinary things, data should not be hoarded behind gatekeepers and bottlenecks. There will always be necessary exceptions around sensitivity and security, but aim to allow staff access to as wide a range of data as possible, and equip them with the skills to make sense of it. Diversity of thought, perspective, and role can be tremendous accelerators of producing new insights and innovation.
For example, someone’s work on public transport reliability could have an impact on someone else looking at schools’ data, which could lead to a change in breakfast club hours, or cause a spike in road usage, prompting new traffic calming or enforcement.