Every day, businesses are predicting the future. Huge sums of money are being spent on collecting ‘historical’ data, but far from being redundant, there is a way to predict what’s coming using this data in combination with predictive analytics. This technique is booming in the world of business, to such an extent that by 2020, Gartner predicts that predictive and prescriptive analytics will draw in 40% of enterprises' net new investment in analytics and business intelligence (BI). It’s developing rapidly and marketers, analysts, and business owners need to be prepared for what’s on the horizon.
Predicting the path of predictive capabilities may seem counterintuitive but a key challenge facing today’s businesses is understanding how to decipher and utilise the variety of predictive techniques available, how to weave predictive outputs into business processes and the anticipated affect these advancements are likely to have on the automation of intelligence across the organisation. Here’s six ways we think predictive analytics will have an impact:
1. Greater control & customisation
Predictive analytics, by its nature, provides users with a way to customise and personalise services and products. Organisations will have far greater control with the ability to anticipate needs as well as deliver tailored experiences to audiences. The days of marketing to broad segments of similar customers are long gone and businesses are enabled to have sophisticated campaign execution that creates a one-to-one dialogue with consumers in real-time on any channel of their choice.
2. Improved diversification
Currently, a large amount of predictive analytics activity is focused on how customer behaviour today will affect the way in which they spend in the future. That being said, many additional applications are being developed and we will see huge diversification in this space in the coming years. This will include the application of predictive analytics to assist businesses above and beyond consumer revenue generation to all organisational areas. For example, in HR this could impact tasks such as recruitment to find suitable candidates, or tracking patterns in employee well-being for productivity. In addition, we will see this extend into smaller, more niche industries.
3. Internet of Things integration
From mobile phones and automated homes to traditional manufacturing processes, sensors are continuing to flood the marketplace. Sensors and devices can collect huge amounts of data related to environmental conditions, consumer interactions, products on a supply chain, and more. The way this data is interpreted to meet customer needs, carry out preventative maintenance, optimise processes and so on, is a key challenge for organisations searching for success in the marketplace of tomorrow.
4. Supply and demand
Affordability and availability of a product or service is directly proportional to the amount of people embracing it (as any economist will tell you). At the moment, predictive analytics is relatively accessible, however as the organisational benefits are more clearly understood, the speed of predictive analytics adoption will expand from isolated pockets to enterprise wide business deployment. Consequently, relying on predictive analytics will become commonplace for the leaders of all companies, no matter the size.
5. Data visualisation
Data, in its raw form, is difficult to interpret and monitor, even for the most experienced data analysts. This explains why data visualisation is such a growing trend; predictive analytics will soon take huge leaps forward in terms of presenting data in an increasingly visual way, helping users gain intuitive takeaways, as well as better communicate their conclusions with improved ease.
6. Understanding the full picture
Predictive analytics often focuses on the ‘big picture’ insights, patterns and high-level takeaways, which is important for organisational consumption, however as the ability to carry out predictive analytics at scale develops, companies will be able to delve deeper when it comes to predicting the micro behaviours of customers.
What does the future look like?
From data ingestion through to delivery, the entire business analytics framework is going to develop to become better equipped to create real-time insights at the point of work, provide automation for every day, mundane activities, and advise business users of actions. This is all positive stuff. Despite this, to be able to maintain a competitive edge, companies should be looking toward progressing predictive analytic capabilities, as this is the future for data driven organisations. Those that don’t invest will only fall towards the back of the pack.