Millions are being spent on collection of ‘historical’ data signals that capture a point in time. Far from being old and redundant, there is a way to predict the future using this data combined with predictive analytics.
Organisations are doing it every day and it is taking the business world by storm. So much so that Gartner predicts by 2020, predictive and prescriptive analytics will attract 40% of enterprises’ net new investment in business intelligence and analytics.
As a technique, it’s developing at an accelerated rate and marketers, analysts, and business owners need to be prepared for what’s next.
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Predicting the path of predictive capabilities may seem counterintuitive but one of the biggest challenges for organisations is understanding how to leverage a range of predictive techniques becoming available today, how to productionalise predictive outputs into business processes and the expected impact these advancements are likely to have on the automation of intelligence across the business.
Customisation and control
By its nature, predictive analytics gives users a platform to personalise and customise products and services. Businesses will have much greater control with the ability to anticipate needs and the capability to deliver tailored experiences.
Long gone are the days of marketing to broad segments of similar customers, businesses are enabled to have sophisticated campaign execution that creates a one-to-one dialogue with consumers in real-time on any channel.
Right now, much of the predictive analytics activity has been focused on how customer behaviour today will impact the way in which they spend money in the future. However, many additional applications are being developed and in the coming years we will see huge diversification in this space.
This will include application of predictive analytics to help companies beyond consumer revenue generation to all business areas, such as HR for tasks like recruitment to find the the right candidates or monitoring patterns in employee health and wellbeing for productivity. We’ll also see this extend into smaller and more niche industries.
Integration with IoT
Sensors are flooding the marketplace, from mobile phones, automated homes to traditional manufacturing processes. Devices and sensors are able to collect vast amounts of data related to consumer interactions, products on a supply chain, environmental conditions and so on.
How this information is interpreted to meet customer expectations, carry out preventative maintenance, optimise processes etc. is a key battleground for businesses looking for success in tomorrow’s marketplace.
Supply and demand
As any economist will tell you, affordability and availability of a product or service is directly proportional to the number of people embracing it.
Right now, predictive analytics is relatively accessible, but as the business benefits are better understood, the pace of adoption for predictive analytics will grow from isolated pockets to enterprise wide organisational deployment. This will mean that relying on predictive analytics will become commonplace for the business leaders of all sizes.
Raw data is hard to monitor and interpret, even for experienced data analysts. That’s why data visualisation is such a hot rising trend; predictive analytics will soon take giant steps forward into projecting data in a more visual format, helping users gain intuitive takeaways and more easily communicate their conclusions.
The big and small picture
Predictive analytics tends to focus on the macro, big picture insights, trends and high-level takeaways – important for business consumption, but as the ability to perform predictive analytics at scale evolves, businesses will be able to dig much deeper when it comes to predicting the micro movements and behaviours of clients and customers.
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The entire business analytics framework, from data ingestion through to delivery, is going to evolve to become more equipped to generate real-time insights at the point of work, provide automation for mundane daily tasks, and suggest actions for business users.
This is all good. Yet, in order to remain competitive, businesses must be looking toward building predictive analytic capabilities as this is the future for data driven business, and those that aren’t investing will lag behind the competition.
Sourced by Yasmeen Ahmad, practice partner analytic business consulting at Teradata