Kevin Jackson and Gerard Blokdijk: Improving Field Service With AI & Machine Learning
Internet service providers, cable companies, and communications organizations are facing some of the biggest changes in communications history. 5G networks loom on the horizon, machine-to-machine connections driven by the Internet of Things are creating data spikes beyond anything we could have previously thought possible, and smartphone behavior continues to pose new challenges and opportunities.
And customer experience expectations have never been higher, as digital natives like Airbnb, Uber, Netflix, Amazon, and Blue Apron change how we take vacations, hail taxi rides, access entertainment, and even eat.
So, how can communications organizations keep up?
It all starts with meeting customer expectations head on: providing them with constant, consistent touchpoints with your brand from online channels to onsite appointments. But that’s not to say technology innovations should be ignored. The opposite is true. Pairing the right application of technology with customer-centric field service engagement practices will unlock customer satisfaction, innovation, and greater profits.
Combined, there is no duo more powerful than artificial intelligence and machine learning. In this post, discover the science behind AI and machine learning’s constant pairing as well as questions you need to ask yourself in order to get the most out of these sophisticated technologies.
AI & Machine Learning: The Dynamic Duo
Kevin Jackson, Director Cloud Solutions & Technical Fellow, Engility Corporation
Artificial intelligence describes systems as “intelligent” based on their ability to follow previously developed rules. Machine learning, on the other hand, employs self-learning algorithms that extrapolate models based on data. “Deep learning” covers a significant intersection of these technologies, where “multi-layered models learn representations of data with multiple levels of abstraction” (definitions courtesy of Sebastian Raschka, author of “Python Machine Learning”).
While all this may sound “geeky,” these definitions point to the value both disciplines deliver to field service. AI rules set the field service boundaries based on business requirements and customer service goals. Data from actual service calls drive the self-learning algorithms of machine learning to create operational models that maximize the attainment of business requirements and customer service goals. This blend is why modern organizations use both.
AI & Machine Learning: Key Considerations
Ensure you have a clear understanding of the business goals machine learning is aiming to achieve. Keep in mind you want to lead. So, how will you lead with machine learning in mind? Here are some key thoughts to keep in mind:
Artificial Intelligence Critical Criteria:
- Is maximizing artificial intelligence protection the same as minimizing artificial intelligence loss? Are you making a balanced choice?
- Have you identified your artificial intelligence key performance indicators?
- Specifically for field service management: What does human-level artificial intelligence look like? What will your vision be?
Field Service Management Critical Criteria:
- Do your employees have the tools they need to respond to customer needs effectively and consistently? Are they supported by AI and machine learning?
- Your employees speak different languages. Can your business solution handle it? Make sure the AI and machine learning solutions you deploy bridge this gap.
- Know your options for field service management AI and machine learning now, three months from now, six months from now, and 12 months from now.
- And lastly challenge yourself to think way outside the box: What if your customer were a machine?
If You’re Not (One of the) First…
Telecommunications organizations who leverage the combined capabilities of AI and machine learning will be able to deliver faster, more personalized experiences that consistently wow their customers. It’s not a matter of if telecom companies evolve. It’s a matter of when. So, if you’re not using it, someone else will.
The question is: would you rather be leading the way or playing catch-up?