The recent Field Service USA event gave us a chance to live our values. In our workshop on how to use real-time data and analytics, I gathered - and used - real-time data. I gave our 90+ workshop attendees the ability to vote during my presentation on questions relating to the event, and the workshop topic.
This was great as I could use the live feedback in a number of ways. Firstly,to share the results, which meant that participants could see which answers were most popular, and compare themselves with their peers. I was also able to pick up on areas of agreement or dissent and use them to stimulate discussion, and make sure I spent the most time on the interests of the majority in the room.
So, what did we find out? With fewer than 100 people answering each question, the results aren’t intended to be representative. However, as all of the attendees were field service decision makers, they provide a snapshot of how some in the industry think.
I asked about four rapidly maturing technologies: AI and predictive analytics, machine learning, virtual or augmented reality (VR) and the Internet of Things (IoT).
More than a third of the participants thought that AI and predictive analytics would make the greatest impact in field service in the next 12 months followed by 30 percent who said it would be VR (see figure 1).
Around a quarter were already using AI and IoT in their organisations and, although a quarter are not using any of these technologies (see figure 2), around a half in total will be using at least one of AI, IoT or VR within the coming year. Amongst this group, machine learning is still furthest out, with only 10 percent currently using, rising to around a quarter in total in the next year.
I also asked about the top four challenges for Field Service Leaders in 2018, as revealed in research by Field Technologies online, which were as follows:
- Optimizing efficiency
- Customer demands
- Employee engagement
- Reducing repeat trips
Participants told us that their priority for optimizing efficiency was to increase the number of first time fixes (34 percent) and to get greater visibility of productive and non-productive time (also 34%) (See figure 3).
The most popular method for staying on top of customer demands and measuring customer satisfaction was by collecting an NPS score (35 percent), and the most important business area that better employee engagement could help with was continuous training (a third of participants) followed by increased motivation (30%) (see figure 4).
All really useful information that contributed to the success of the discussion in the workshop and demonstrated that real-time data has value because it is instantly actionable.
However, I’ve yet to reveal the participants’ answer to the most important question of the day. Would Laurent (our Chief Executive) get on the mechanical bull at the after-show party that evening? The 17 percent that said ‘absolutely’ were just beaten by the 21 percent who said ‘uh, NO!’ Whilst it gives us some satisfaction to report that our polling prediction was correct, on balance we would have been happier to be wrong and to have had a picture of the great man taking up the challenge with which to illustrate this article. I guess there is always next year.