In almost every industry, the use of analytics is intensifying. We now have access to more data than ever before and, thanks to low-cost storage options, it comes at an affordable price.Add to that a growing list of user-friendly technologies for accessing and analysing data – and it’s no wonder the use of analytics has spread across all departments in your organisation.
It’s not unusual to see decision makers in the finance department visualising millions of rows of data while analysts in the customer experience unit deploy analytic models to identify customers for a new product offer. At the same time, data scientists are using public data sources to predict the behaviours and buying patterns of customers over the next few years.
The big challenge for you is make sure that all these efforts are accurate, aligned and beneficial to your organisation. How do you know the analytic processes are being deployed as efficiently as possible?
Without analytics governance, you don’t. Even if you are in control of your data management and data governance policies, there are benefits of putting policies and procedures around the analytics process as well. Data governance gives you structures and policies around the use of data in your organisation. Analytics governance applies the same level of scrutiny to the way analytics projects are implemented and deployed.
The MIP Data & Analytics (D&A) Governance Framework covers the elements required for the successful delivery of analytics within an organisation.