In Part II, Wankewycz discusses emerging technologies in real estate, the role of AI and machine learning in bridging the physical and digital worlds, and how organizations can cultivate innovation.
Dr. Burcin Kaplanoglu, vice president, Oracle Industries Innovation Lab, led the discussion.
TW: We must encourage creativity and autonomy. It's hard to give a lot of autonomy to people in organizations generally, but autonomy is a must when you have different leaders and teams overcoming obstacles and trying new things all the time.
As a company, the best things we’ve done have always been when we let creative minds go on their own journey, figure things out on their own, face challenges, fail, and come back and say, "Okay, we found a new way, and this is the breakthrough."
The process isn’t for everybody. Innovation can be either painful or enjoyable depending on who is on the journey. An innovative culture is required to transform an existing process or way of doing things.
TW: My preference is to innovate at the intersection of different emerging technologies. One specific technology may be popular one day while another technology may be popular the next.
The key is to understand the overall objective and work within a broader context of technologies.
The outcome we look for is when technology is invisible or seamless to the end user. This typically happens when the technologies are converged, forming one seamless experience for the end user. That’s when the magic happens.
Many companies are now building digital command centers with field operations data merging into one central decision space. Technology is there to support accelerated decision-making and to help us make better decisions impacting new levels of operational efficiency.
We are moving towards the autonomous enterprise.
In terms of emerging technologies, we’re looking at using various forms of mobile robots to help scale dangerous, repetitive tasks and connecting them with our processes on cloud. We are still in the beginning of fully autonomous systems co-existing with the human worker and the decision-maker.
We see the combination of field robotics and AI-enabled reporting helping decision-makers form better decisions about priorities, including what to do when, why, and where.
Prioritization is difficult for organizations. Some of our clients have hundreds, even thousands, of structures under management.
If our clients’ job is to ensure the well-being of all these structures, the current method is to do random checks or answer complaints when they arise.
What if at any given time – one could know exactly what the highest impact activities need to be to achieve maintenance goals at the most optimal operational cost?
TW: When you talk about AI and learning, a lot depends on what part of this you are looking at. There's a lot of commoditization that has already taken place and that’s rapidly accelerated around the world.
The question remains if we can use AI and machine learning to embed the outcomes of such processes in an automated report which can mimic what a paper report would look like today, without the technology applied.
The biggest impact is when AI or a machine learning process is embedded into a broader workflow that supports decision-making activities.
See innovation in action at the Oracle Industries Innovation Lab.
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