Microsoft Dynamics 365 for Field Service comes with some great tools for measuring key performance indicators (KPIs) like:
Right out of the box, you automatically have great reporting about “what happened.”
The problem is that the metrics in Dynamics 365 for Field Service are all just… numbers. You don’t have charts and graphs and trend reports that make the information more accessible, and therefore, more useful. That’s why Power BI and other similar business analytics tools can almost immediately up-level the value of your field service software.
Here are three scenarios of how field services companies have used business analytics to get greater value from their field service software investment.
Level 1: Visualize existing field service metrics to improve results
If the ONLY thing you do is add Power BI to visualize field service data, you’re moving in the right direction! Power BI allows you to:
Start by creating simple views, such as technician utilization rates that can be sorted by:
With this simple graph, you may be able to see patterns that indicate which technicians need more training, or which products take longer than they should. Here’s an example of what your graph could look like in Power BI:
Level 2: Add new fields to field service to turn micro measurements into big picture trends
While the out-of-the-box fields provide good information, to improve the accuracy of your insight, you’ll want greater detail about the work order and/or the equipment being maintained.
Let’s say you want to be able to measure Mean Time to Equipment Failure. You’ll want to add an attribute to the work order that shows its root cause – why the technician was sent on site, such as:
By filtering to focus exclusively on break-fix work orders, your data will be more accurate.
Taking that measurement to the next level, you can start to uncover your Ideal Inventory mix. You don’t want to have a critical piece of equipment down because you’re missing a small spare part.
By combining equipment and part attributes with work order reports, you can forecast the cost and risk of your inventory replenishment strategy.
Some of our clients want to be able to attract new clients by being able to show big picture results that can be filtered by technician, dispatcher or asset:
Trending insights can help you improve your service delivery – and be used as sales and marketing tools.
Level 3: Using predictive analytics and machine learning to optimize uptime
For manufacturing and oil and gas field service companies, maintaining equipment uptime is a top goal. An oilfield site may be 200+ miles away from the nearest technician and truck. Unnecessary maintenance is expensive, but downtime and equipment failure can cost millions of dollars, and even pose safety risks.
Using a combination of Internet of Things (IoT), Machine Learning and Predictive Analytics, companies can implement connected field service features to launch self-healing scripts, and more detailed diagnoses before the technician gets on site.
Business Analytics Makes Field Service Better
If you don’t have field services software yet, that should be your first step. A field services software solution like Dynamics 365 for Field Service can help:
Adding business analytics tools gives you the opportunity to see the bigger picture, and automate activity. We’ve given you three scenarios – from simple to sophisticated – to help you understand your options and show you how easy it can be to get started.
Need our help? Contact us to learn more about Field Service software, Power BI or the power of combining both.
Author: Travis Pullen, Director, Dynamics 365 for Field Service
Other articles you might be interested in: