ROI? Look Past The Obvious
Author: Stewart Hill
Recently, I took some time to browse the various online discussions that occur every day regarding the workforce management and optimization industry. This is a regular activity of mine because it keeps me abreast of the latest and most relevant industry, market, and world developments and any subsequent discussion that are then generated. Occasionally, some of the discussions are newsworthy enough for them to be presented and discussed as part of Clickipedia. Just like today…
I found an interesting LinkedIn discussion surrounding an endearing subject; the Return On Investment (ROI) of field service automation solutions. The discussion was triggered in response to a posted article written by mobility expert Kevin Benedict, “Gartner Awards Vivint with Enterprise Efficiency Award for Enterprise Mobility Solution.” The article reviewed the ROI benefits Vivint are enjoying since having implemented ClickSoftware’s scheduling solution, and highlighted the fact that “Significant efficiencies [are] gained through field service automation.”
Obviously I am not making any attempt to hide the fact that Vivint is a ClickSoftware customer and that we are proud of Gartner’s award and the associated publicity, but what struck me about the subsequent conversation is that it outlined an alternative approach to measuring an ROI.
Usually, ROI discussions, presentations, and evidence concentrate on those tangible business metrics that we can all competently measure such as increases in productivity, utilization, and efficiency; reductions in mileage, fuel, and other operating costs; and improvements in customer satisfaction and retention. These are all safe measurements that are easily monitored, reported on, and defended.
But this conversation is different – it introduces the notion of considering the field service automation ROI by incorporating the improvements in data quality. Imagine being able to place a value on improved Service Level performance in front of your customers. Alternatively, imagine being able to understand engineering performances leading to you making widespread efficiency improvements in how work is conducted simply by analyzing and understanding the data and then executing positive changes. Placing a value on these however may be far from easy, particularly the latter example which opens up the whole “big brother” and “managing employees through fear” debates again, but this proves that an ROI can be found from many different angles.
So if you’re building a business case and including an ROI section to justify your proposal, look past the obvious, and also try to understand what data quality improvements can do for your business.
What are your experiences, good and bad, from trying to leverage data quality in proving the ROI from your investments?