Data Maturity: Infrastructure
Where are we on our analytics journey? It’s a question we get asked all the time. In this series we will look at key questions to help you determine just this! We’ve graded common responses based on three levels of maturity: walk, run and fly.
Which of the following best describes your current state of data infrastructure?
Walk: Our data is scattered across various systems (e.g. backend, Salesforce, Meta etc) and requires manual processes to collect and manipulate for reporting purposes.
Run: We use an off-the-shelf tool to centralise and report on data from various sources.
Fly: We have a modern analytics stack where data from various sources are centralised and transformed for reporting and analytics purposes.
See which answer most closely matches your current situation and scroll down for some crucial advice.
Your answer: Our data is scattered across various systems (e.g. backend, Salesforce, Meta etc) and requires manual processes to collect and manipulate for reporting purposes.
Our advice: Right now you are probably missing some key information that can help your company grow, and the bigger you get, the greater the opportunity cost will be in not leveraging data. If you are looking to get started, then off-the-shelf tools are a fast and easy way to get some key metrics but we would ultimately advise that every business needs their own bespoke pipeline in order to leverage data properly.
Your answer: We use an off-the-shelf tool to centralise and report on data from various sources.
Our advice: This is a great place to get started, but the bigger you grow, the bigger your opportunity cost will be. Off-The-Shelf data tools often adopt a standardised approach to metrics and reporting. While this may work well for common use cases, it can limit the ability to tailor metrics to unique business needs. You may find yourself constrained by predefined metrics that do not align perfectly with your specific goals and objectives. Some tools charge based on data volume or require additional modules and integrations to handle advanced analytics or larger datasets. As a result, the costs of using these tools can escalate quickly. If you are thinking about scaling your business, we’d heavily advise you to implement a data stack before you grow as you’ll miss some key points of optimisation.
Your answer: We have a modern analytics stack where data from various sources are centralised and transformed for reporting and analytics purposes.
Our advice: Great, you have everything you need to build out your analytics function. Our first piece of advice is to automate as much as possible. Automating data extraction and integration processes saves time and minimises manual errors. Identify relevant data sources and explore automation tools and techniques to streamline data collection. By automating repetitive tasks, you free up valuable time for analysis and decision-making, ultimately improving efficiency and productivity. Secondly, at this stage data governance becomes more important. A robust governance framework ensures data quality, security, and compliance. It defines roles and responsibilities, data standards, and policies for data access and usage. By implementing proper governance, you can maintain the integrity and reliability of your data assets.
If you want to understand where you are on your analytics journey. Our Data Maturity review offers a holistic and independent assessment of the strengths and weaknesses of your current technology, processes and people.