In the age of convergence, customer churn is a concern for service providers, challenging most retention techniques...
From the time off the shelf products sounded the death bell for bespoke customised software development a whole new industry sprung up trying to build products for virtually every aspect of a business. Each product tried to differentiate itself based on technology, flexibility, ease of use, experience, service delivery, pricing, industry specialisation, country specialisation etc. to name a few, the fact still remains that not a single product till date has been able to fulfil the needs of its end-user to a 100% without being customised. Moreover, in their quest to get into a one size fits all mode most product companies packaged all features into the product without bothering to find out if the end-user needed those features or not. I am sure that a lot of wisdom and thought has gone into this approach and while it’s true that software products have changed the landscape of business automation across the world, making digitisation available and affordable, there are still issues. E.g. from an end-user point of view since the product differentiation has gone to such an extent that once an organisation gets tied to a particular brand it is very expensive to get out and move to another product or banner.
What has that got to do with analytics anyway? Well, if you are reading all the news that is getting published across the web we hear about at least one product company talking about an analytics package that they have built which apparently has the magic wand to look into the future and let the executives know how bright it is or better still what problem they are going to face in the next thirty days. While at a transactional level there might be some truth in this considering the fact that mechanical processes in similar environments have similar outcomes at a strategic level this is completely a fallacy.
A tool is only as good as the person who uses it is an age old saying and in the world of analytics this is all the more true. The fundamental philosophy of analytics and more so predictive analytics is the creation of models based on various input parameters that affect the business and for each business these parameters are unique and so should be the models that support the analysis of these parameters. Another age old saying is that you need to keep sharpening your tool to ensure that you get the best out of it all the time and so is the case with analytics where the models have to be tweaked and regularly updated based on the changes in the business environment. It is therefore very important for the executives to look very closely at the tool they are buying and analyse the total cost of ownership over the entire lifecycle of the product and the ability of the organisation to use the tool itself without having to rely on expensive outside expertise.