Judging by the success of early adopters, it’s no surprise more and more organizations are looking to adopt.
Many are grappling with how and when, but why is most important. No one starts down this path expressly to adopt cognitive technology; the whole point is to improve the organization.
Adopting cognitive technology above all else should align with business priorities. Successful early adopters identify a problem, then build a case for how solving that problem will support specific outcomes like saving money, gaining customers or increasing revenue.
Employ good planning for a specific and strategic use case
Usage patterns tend to fall into four major categories that play to the strengths of cognitive technology.
First, cognitive technology is often used to enable innovation and discovery by understanding new patterns, insights, and opportunities.
Second, it is often used to optimize operations to provide better awareness, continuous learning, better forecasting, and optimization.
Third, to augment and scale expertise by capturing and sharing the collective knowledge of the organization.
Finally, to create adaptive, personalized experiences, including individualized products and services, to better engage customers and meet their needs.
Pursue cognitive technology for the sake of technology
One temptation, however, is to pursue cognitive technology for the technology’s sake.
“Most of the failures we’ve seen are when you start with the technology instead of the business case,” according to an IBM cognitive technology architect. “There are so many things you can do with cognitive technology, and people get really excited. But you need to focus on what impacts your bottom line.”
Conversely, overthinking can lead to inaction. According to a CEO that leverages cognitive technology, “a lot of companies are over-analyzing what they should be doing. They want a fully detailed design and guaranteed quality of output, but it doesn’t work that way.
It’s better to start small with a good idea and from there scale-out and scale-up. There is no universal template for success, but focus on persistence is a proven formula.”
Prevent the perfect from becoming the enemy of the good
In some cases, the best advice is to select a use case quickly to overcome the inertia created by a misguided desire for perfection. Adoption can mean something as basic as tapping a pre-built cognitive application.
Starting small does not prohibit future expansion, and strategy can evolve over time. “Often what’s difficult is the trade-off of fixing current pain points and doing something that aligns with a long-term vision,” according to an IBM cognitive strategy specialist. “This is where people can struggle.
The challenge is to marry fixing the current problem with making sure it is the right move for the long term. So prioritizing the right use case that balances these things is the big challenge, and it’s where we can help the client the most.”
As you develop your strategy, share ideas with other forward thinkers within your organization—their support is essential—or brainstorm with a member of the IBM team.
Choose the best implementation approach for you
In another example, we can see how cognitive is applied to equipment maintenance to enable different interactive services to assist machine technicians and operators.
By directly integrating edge devices – such as machines and robots – in the cloud using Watson IoT Platform, manufacturers can develop personalized products and services. Not to mention, improve operations, reduce costs and avoid the risk of downtime.
By accessing different Watson services, in addition to other APIs on IBM Bluemix, a technician or operator is able to take a huge advantage. Particularly, of analytic functions, predictive maintenance, and visualization of information in a dashboard.