Gazing into the Crystal Ball:
Top 10 Trends for 2014
There is an explosion of data from a multitude of sources. From the 50 million-plus tweets per day to the 20-plus petabytes of data searched on Google (1 petabyte = 1015 bytes), you name it, we are being inundated with information. We are in the midst of an information tsunami! Today, we generate more data than the total amount generated since the dawn of computer technology. To put things in perspective, in the last two years alone, we’ve generated 90% of the world’s data! And this jaw-dropping amount will only grow astronomically larger. We will be reaching new heights with data. Some estimate in 2020 we will produce 44 times more data than what we have been producing recently. According to Cisco, by 2018, the monthly total data traffic from mobile will exceed 15 exabytes (1 exabyte = 1018 bytes).
Notice the change in our storage language: from mega and giga to peta and exa!
Having access to a flood of data and an almost infinite supply of information does not necessarily translate to knowledge, wisdom or better decisions, however! The potential intelligence in the data needs to be mined and analyzed in order to add value and better our lives. Most importantly, the hidden “gems” in the data must be operationalized and acted upon – as quickly as possible!
There are many sources and types of data. These include transactional data generated from systems of record, process and case data generated from systems of innovation or differentiation, master data, data warehouses, unstructured documents, social media, mobile data, multi-media data (especially video), and more recently “big data” sourced from the behavior of customers, as well as the Internet of Everything.
"Technology in its entirety is becoming increasingly intelligent and intuitive."
Technology in its entirety is becoming increasingly intelligent and intuitive. New and emerging techniques in databases as well as analytics are opening doors for bigger and better things. This trend will only further accelerate in the coming years, especially in the context of digitized and intelligent business processes. While many business processes are about doing things the right way, they are not necessarily always doing the right things. When it comes to software solutions, intelligence is about making the right decisions—thus, it is imperative that BPM be “intelligent” in order to optimize customer experiences and streamline complex processes, among other improvements.
Intelligence has many sources including knowledge workers, who either have it in their heads or author the rules that need to be applied to govern processes. Of course, as noted above, the ever-expanding amount of data being collected provides a huge resource for intelligent decision making.
So all this data can be mined using analytics to discover predictive models. This is particularly valuable in the next generation of iBPM enabled customer relationship management (CRM), where a deep, nuanced understanding of customer behavior can be used to guide and transform the customer relationship. While discovering predictive models from this plethora of sources has some value, the more important and exciting trend is the ability to execute and act on the discovered intelligence in the context of robust intelligent business process management (iBPM) solutions. Using automated business rules and real-time decisioning, iBPM makes predictive models active, allowing organizations not only to unlock the insights hidden in vast amounts of digital information, but then apply those insights during the course of customer interactions. iBPM unveils various key points such as deciding what marketing offer is best suited to the individual, identifying which customers are in danger of defecting and what is required to retain them (and even if the customer is worth retaining), or determining what action should be taken during a service call.
Adaptive analytics is another significant trend that is quickly turning mainstream. Predictive models are useful, but they are always based on historical data, which means that decisions are made by looking in the rear-view mirror. Adaptive analytics elevates intelligence another (large) step further, as it provides “self-learning” that can dynamically incorporate new information and insights in real time and automatically apply this current knowledge to the next applicable situation. This ability allows intelligent processes to constantly improve and continuously deliver more targeted and optimized interactions. For example, marketing and customer service can become driven by the Next-Best-Action, always fine-tuning the offer or action to match the current circumstances and specific customer. This is a great example of the hidden “gems” in the data operationalized and acted upon – as quickly as possible (real-time decisioning) with concrete business value bettering the lives of customers and businesses!