Continuous improvement requires continuous intelligence
Business leaders must take the initiative to leverage their data using new technologies and approaches to adapt and succeed in the digital world.
The digital age has presented businesses with a significant challenge: adaptation. Organizations can only hope to survive in this new era if they are able to adapt to the new reality of doing business.
For the past few years, adaptation efforts have fallen under the umbrella of digital transformation. It is now widely understood that organizations must engage the groundswell of digital data and refine it into a byproduct that can inform decisions or instantaneous actions. However, because digital data flows continuously, the data engagement model should also be continuous, leveraging advances in machine learning, AI, IoT, and analytics. This sort of continuity will catalyze organizations to adapt and thrive in the new digital reality.
Because IT has historically focused on batch processing, the concept of continuous processing is fairly new to most organizations. Continuous intelligence waits for nothing. Not data collection periods, not resource availability, not processing time. It is the non-stop generation of insight and actions based on operational data stores as well as streams of data and events generated in the moment. It is the ability to harness an ever-changing environment where the data is constantly flowing and the insights and actions are perishable.
According to Gartner, success can only be achieved in a world that is constantly changing by implementing a continuous approach. Gartner suggests that continuous intelligence is at the heart of fast-paced digital business and process optimization. However, continuous intelligence is not only about IT architectures. Successful implementation requires a change in managerial approach as well.
New leadership approach
Conway’s Law gave us the insight that system designs reflect the communication structures of the organizations that design them. Because designing continuous intelligence requires new architectures, it is critical that the organizations designing them reflect the architectural intent.
Most organization structures today assume they are performing in a batch-processing world. One team works to complete a task before handing it off to the next team, there is no continuity of visibility or activity. Initiating a continuous intelligence effort with the limitations inherent in a batch processing management model will produce feet but no wings.
To fully implement the continuous intelligence approach, business leaders need to adapt to agile management methodologies. Just as the DevOps world engages continuous integration across teams, so must the larger IT organization engage in a more active and constant way. The rate of engagement is necessarily radically higher, that is the only way for the broader team to understand what’s going on in the organization. This approach will facilitate initial success and be the foundation for staying ahead in an era of new, dynamic technologies and continuous change.
The need for speed
One of the fundamental changes to the IT stack required for continuous intelligence is a new data processing layer designed to perform at extremely low levels of latency. Regardless of whether the data already exists in operational data stores or arrives in event-based streams, the concept of continuity is at odds with latency.
Our traditional systems of record do not have this design point, nor should we expect them to. They will continue to do their job well while a new, complementary data processing layer is added.
Innovations in IoT, machine learning, and AI assume both constancy and immediacy. Business value has become inextricably linked with real-time action. New applications require speed and scalability in the underlying data processing to produce responses as well as to 'feed the beast' to inform models. The money is in the microseconds, whether the data is at rest or in motion.
Digitization has permanently changed the business landscape. Continuous intelligence is achievable. Business leaders must take the initiative to leverage their data through new technologies and approaches to adapt and succeed in the digital world.
Author: Kelly Herrell