Published Oracle.com
In the early 2000s, two vastly different businesses—Baseball and Field Service Management—began to use advanced statistical analysis to gain an advantage over their competitors. They both revolutionized their respective fields by using statistical knowledge to improve performance. The new approach replaced old models and methods and attained shockingly good results as both set new standards for their respective industries.
Great Customer Experiences are on everyone’s lips these days, and for good reasons. In the highly competitive marketplace where customer loyalty is hard earned and competition just a click away, great Customer Experiences has demonstrated to be a true competitive differentiator and highly correlated to Customer Loyalty (2015 Temkin Report).
As a customer centric company you really need to pay attention to every single step of the customer journey. Customers rate your brand based on the complete journey and not just single transactions. For the exact same reason Field Service plays a very important role in how you are conceived as brand.
Customer Effort is Key
By supporting different channels with silo or niche solutions, many companies have however created a disparate and unconnected customer journey. A very common consequence of this unconnected journey is that customer effort increases, resulting in poor customer experiences, increased churn etc. etc.
Within Field Service, a very common example of Customer Effort gone wrong, is when you as a customer are asked to reserve half or even a full working day at home, waiting for a technician to show up to install or fix your product.
In a case like this, no matter how great service you received on your previous journey (by voice, chat, in store etc.) the total brand experience will still be damaged by the fact that the customer needs to invest so much time (and money) dealing with you as a brand. Customers of today want simple and effortless experiences.
Performance Pattern Profile: Building a Technician’s Baseball Card
Getting back to the headline of this post, the movie Moneyball showed how using metrics helps baseball managers optimize their teams in order to win baseball games, even against tremendous financial inequities among teams. In managing field technicians, the use of genetic algorithms performs a similar task, but does so with even greater results.
By constantly measuring key variables like travel time, job time, skill types and non-working time, a unique DNA or performance pattern profile is created for every single technician.
With these sort of data available and the systems to support it, it is possible with a very high degree of accuracy, to predict when a technician will arrive at your address and when he/she is expected to finish the job. For the customer this dramatically reduces customer effort and naturally has a very positive effect on the brand perception.
For the company the use of individual performance pattern profiles allows for a very high degree of automization in planning and dispatch, ensuring that the organization runs as efficiently as possible.
In the white paper below, you can learn more about the general concepts behind predictive analytics and how they can be applied to a field service organization. The paper will cover the basic metrics that should be tracked, the use of performance pattern profiles, and how these principles can predict future events for your company.
