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Today business competition is fierce and global, and companies need to employ everything in their power to thrive or even survive. Companies in todays environment are seeking to increase revenues whilst keeping operational cost to a minimum.
Enter Predictive Analytics an enabler that can help accomplish the very essence of increasing companies “Return on Investments” (ROI). If implemented successfully, it could drive your companies profit upwards. It will certainly assist you to turn your data into valuable information (insights) that you could capitalise upon, also giving you a competitive edge to out perform your competition.
Predictive Analytics enable companies to use the massive data they have accumulated from their operations as a refined resource to advance their businesses. Lets take the Financial institutions for example, they were the early adopters of Predictive Analytics, using it as a tool to boost their odds in successfully out performing the market and market participants. Other sectors of business where a little slow to respond but are catching up by adopting Predictive Analytics programmes to make industry specific improvements in operations and strategy.
So now that we understand the importance of Predictive Analytics to our business the next question is “How do we build a Predictive Analytics Model?”
To answer this question or at least getting you thinking about the best practices for implementing a Predictive Analytics Model in your business I have built a road map (actually a mind map) to assist in the process.
You can also download a copy of this Mind Map using the following link on Biggerplate http://www.biggerplate.com/mindmaps/66pXmcrA/how-to-build-a-predictive-analytic-model you can also download a working copy of the MindGenius software used to create the map.
So this mind map discusses best practices for building predictive analytics models in your business. The first and most important thing is to define your business objectives as early as possible and getting the leaders of your business to champion your project.
The map also covers the importance of preparing the data that will be used for the project, highlighting some tips to follow and help you refine the data that will be used in the project. Also to avoid that old bugbear of “Garbage in Garbage out”. It also looks at how to build deployable models, outline, test and evaluate them and also offer some guidance on how to monitor them once they are operational.
Some vital principles are needed to employ the use of Predictive Analytics in your business:
- Put the right Analytical team in place
- Provide the team with relevant and accurate data
- Let the team build the model iteratively, establishing quick wins early in the process
Finally, the map addresses organisational support: To get the predictive analytics model up and running, its important to ensure the business leaders will take actionable decisions based upon the insights the model has given them. Absolutely final, there are hints on how to foster an organisational culture that embraces the value of predictive analytics and understand the advantage of turning data patterns into actionable decisions.
So there you go I have given you the “why” and now a little bit about the “How”. From this map I will be producing an eBook in the coming weeks which I am hoping will assist people to build and deploy successful Predictive Analytics Models. In the meantime if you need to know more just ping me on LinkedIn and I will help in anyway possible.
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