Most organisations do not even use their customers data, they use their instincts and think they are right, but often they tend to be more wrong than they realise. The Analytics Maturity Ladder reflects the analytic maturity of an organisation. Many of them are stuck in the lower stages of this ladder due to failure in utilising their analytics teams effectively, mainly, because they fail to identify in what step they are positioned in the scale above and invest their efforts in the wrong places. This often leads to less delivered value and significant wasted efforts.On the other hand, companies that see the value of business analytics and transforming themselves to take advantage of these opportunities, have a clear competitive advantage, and this gap is only getting wider and bigger.Stop for a moment to think, you shouldn’t rush and build a forecasting model while your day to day operational reports are not accurate or non-existing. You should ask yourself, “where is my analytics team now?” “How can I get more value from my analytics team?” You will need to answer these questions realistically and not optimistically, do not try to take any shortcuts, you will need to climb up the ladder step by step in order to generate the most value for your organisation from your analytics team.
So, how do I move forward?
The first thing is to “cover the basics”, you will need the account and product managers, senior management and every other client to have a proper set of reports / dashboards that will help them track, measure and optimise their processes easily, without engaging and seeking guidance from you on a daily basis.You will need to free your analysts to actually analyse by giving your clients more freedom with self-service BI, interactive dashboards and visualisations. Technology is easy to solve, but culture is not, in order to do this you will need to invest time and effort in educating them and build a proper platform to support them.Then, you will have to create alerts to make sure you won’t miss important changes in your products, channels, GEOs or any important dimension you might have.Finally, when all this is done and hopefully optimised, you can think about the actual “business analytics” like LTV, churn models, predictions, recommendations, segmentations, correlations etc.In the next series of posts, I will explain how to “cover the basics” from setting up and choosing the correct attribution model to create meaningful reports for your marketing team and how to properly create and maintain a self-service BI platform using Tableau server.Stay tuned!
