Socrates in the 5th Century BC commented that children had lost respect for their elders and were generally playing up, a great example of how the passage of time changes very little. So how has twenty years changed the landscape in Utilities with their use of Field Service Automation?
The answer is disappointing, the key challenges essentially remain as they always have been even though the tools have been changed by advancing technology. Most of IT would now be howling for my blood, everything they yell has been radically improved and certainly zillions have been spent on achieving this outcome.
So to substantiate my position perhaps we first need to agree on what are the key challenges for field mobility? My assertion is that the two core challenges are still yet to be fully conquered:
Field Technician Acceptance
We commissioned a University of Technology1 study in 2016 on the key heuristics (usability principles) required in mobile design. By observation of various applications live in the field they established eight key design principles, by example the tech needing to understand what his work and data that he collects meant within the whole process. However, other highlighted requirements show that the basics of the field solution being “fit for purpose” are still rarely achieved: IT departments love to roll out a “one size fits all” strategy resulting in technicians standing in direct sunlight with iPad screens they cannot see, HTML5 based programs that work poorly when not in coverage and a workflow imposed on them that suits back-office operations and not a holistic field work process are all common issues.
Additionally, literacy issues with field technicians are rarely conceded in design: to do this would require consistency in icon usage and navigation so that rote learning is achievable, alternatives offered to replace long written descriptives (e.g. unlimited photos, videos, voice annotation) need to be supported, and workflows thought through from reducing technician input (e.g. automated GPS and time stamping) rather than seeing technicians as in-field administration workers.
What has been achieved? Attaching asset history so that the field team understands the previous maintenance activity and the attachment of GIS and LIDAR extracts to give schematic information to field teams allows field crews to work in full knowledge and make better decisions. Field devices have also evolved markedly, from luggables to truly mobile, from shockingly expensive to cheap, from offline to mobile enabled.
Management of Field Activity
No doubt the advent of 3G/4G devices sending back work-order updates is a core achievement of the period. Supervisors and management can now see in near-real time the progress that crews have made, this is in contrast to twenty years ago when the status quo was radio or phone updates on emergency jobs and next day at best for general maintenance work. So transparency of field activity can now be achieved.
However, the IT myth of this period is optimised scheduling: the principle is that computers, not schedulers, can best organise work and reduce drive time, conflicts on equipment usage and skill set requirements. The IT capability to deliver optimised scheduling is real, but its practical and successful application to the field is rare and its cost to Utilities has been enormous. The emperor with no clothes is that optimisation is often turned off as Utilities revert to local knowledge to manage their scheduling work boards.
Why does this happen?
The fundamental for optimisation to work is twofold:
- Quality data: does the Utility have reliable data for how long a particular job type takes? Availability of technicians? Skills set updates and equipment availability? Without accurate information the optimisation result is worse than wrong – it has the authority that it is right when it is not.
- Constant fine tuning: as the business changes, are the parameters on which the optimisation is based managed to reflect those business changes? This is a business analyst role which reflects data analysis of field performance and changing company priorities.
…but these two proficiencies are rarely in place, meaning that shortly after implementation the optimisation starts steering off course and by the mid-term its results are not respected internally. Millions of dollars have been spent, the internal effort has been enormous so no one wants to declare the project failure, they just move on.
There are exceptions of course: utilities that focus on data quality and the fine tuning. However, the stand out sector for success is cable. Why? Their number of job types are limited, single men rather than crews predominate, parts requirements and asset management minor in comparison to a traditional gas, electricity or water environment. So we have a solid example of technology working but need to find a newer delivery model to allow similar success in the traditional utility space.
So what for the next twenty years?
The move to out-sourcing of field crews, adding a separation layer between work preparation and in-field delivery and quality management will add complexity to the above issues rather than simplicity. However, I believe a change of attitude to IT solutions is occurring – a shift back to a pragmatic valuation of outcomes and a need for smaller steps with demonstrable advances is gaining traction. With such a trend the need is to seek solutions that are best of breed rather than IT logos or compliance to standardisation across the corporation – if we put the field worker as central to how we implement innovation then we can achieve real returns.
It is just a change of priority.
About the Author
After 20 years in the wireless data industry, of which 16 years are with Retriever, Mary Brittain-White has established herself as a thought leader in the area of wireless field automation. Prior to founding Retriever, she worked for a Silicon Valley based Motorola subsidiary, RadioMail, which pioneered wireless email. From University, she joined IBM and over a 14 year career there held Sales and Marketing executive management roles. She has a Bachelor of Economics from Sydney University and a post graduate Executive Development program from Melbourne University.
1 Reference to UTS Heuristics Study
