Modernization of Analytical / Reporting Platform

What you can do with data / information? According to research if you take the decision based on the data and your business knowledge (combo) then you perform 2x times better than the gut feel decision. This proves that seeing data in different perspectives will surely add value to you and your business.

In the current world of Mobile and automation, data you need should be available in the way you want it. If your current operational or analytical platform is not providing that information on a way you want it, its time for you to think modernization of your Reporting platform.

Disruption of reporting / visualization platform is here to stay. How we keep our systems adoptable for newer technologies is the question? You may have a legacy system which provide detail transactional data in multiple pages, but that wont help you to visualize the data better. So, importance of visualization is becoming high as we don’t have too much time in hand, so summarizing and depicting that data in a visual is the important thing to do. If you don’t have one in your department, then you should reach out to your IT to enable yourself with the power of new reporting environments.

See the current functionality of reporting system, technologies we use in the landscape, the channels in which we deliver the reports. If you are using legacy reporting system or there is only one or two ways to distribute the data, its the time to HIT REFRESH in your reporting / analytical function in your organization.

Firstly look at your Roadmap of Data Analytics, have a budget in place, write few POC’s to make sure your end users are buying in with your view, then take it to the next level. As the investment is high, changing the course during or after the implementation becomes very expensive.

If you are already in OLAP world for Ad hoc Analysis, look at Visualization as the next step. If you are already in Visualization world, look at ML as the next step. In today’s environment, ML can be implemented to optimize the business operations. For example if you want to predict when your booked revenue turn to cash, we can use the ML to know the date of payment from your customer. This increases the accuracy of cash prediction to run your operations better. So, find the use cases to link the data analytics output to tactical / strategic decison making capabilities.