03 Aug Field Service Expert Interview: Brett Woods
As part of ourField Service Expert Series, we ask industry experts for their views on the market and what the future of field service holds. We recently talked to Brett Woods, chief technology officer at CSA, one of Australia’s leading ICT service providers. Brett has led to the transformation of CSA in response to industry demand for agile technology service partners that can run technology for business and innovate business with technology. Brett has spent many years working internationally with high-profile, global organizations across all major regions. He has achieved the highest high level of industry certification including fellowship, and has also completed programs with the London Business School and the University of Oxford, where he was the highest-ranking student.
How are field service organizations using technologies to create a competitive advantage?
A key strategic objective for most field services teams is to use technology that can optimize the allocation of people and assets such that overall efficiency is increased. To drive a competitive cost advantage, you must optimize this allocation of people and assets better than your competitors. To do this, contextual awareness is vital. For example, to gain near real-time insight into where appropriated skilled field techs, spare parts and supported sites/assets are, you need to provide the data and framework for fault remediation and scheduled maintenance. To achieve this, you need your field techs using mobile technologies and an online asset and knowledge database that also controls the processes through an asset lifecycle. Once you have this framework in place you need to overlay effective processes and algorithms to ensure that when a fault occurs, the nearest suitably skilled tech(s) and spare part(s) are routed to the correct site with accurate estimated arrival times.
What are the future opportunities for growth in field service management?
More and more devices and sensors are deployed every day to support IoT initiatives. For example, telco providers want to use “things” (i.e., devices and machines) to increase connectivity speeds, coverage and to offer higher-value services up the stack. This directly equates to an increased volume of assets and sites to be managed by field services teams. This sheer volume of assets is going to drive growth in field services. Historically, there has also been a focus on maintaining high-cost critical assets to maintain the availability of a service (e.g., data in telecommunications, gas pipelines, oil rigs, etc.). Over time, these assets and use cases have remained critical; however, there are also a number of business applications that are using higher volume, less critical, lower cost assets (e.g., parking sensors). The average cost of these devices being managed by field techs is typically falling, and this is often reflected in the expected lifetime of such devices; it’s now often cheaper to replace than repair. Field service teams need to be well positioned to respond quickly and achieve first-time resolution.
Why are metrics becoming more strategic for field service organizations?
Measurement is fundamental to driving higher levels of service and efficiency across field service teams. Having an effective measurement framework is essential. This framework must support continual service improvement initiatives and should also provide insights that can be folded back into a more dynamic pricing model used by the sales organization. Having centralized process platforms and distributed field techs with mobile technologies allows real-time data to be fed from the field techs into these centralized process platforms. The centralization and availability of data, which was previously buried in paper or distributed spreadsheets, has made analytics far more strategic for FSOs. Emerging technologies such as machine learning and artificial intelligence will play a big future role in this space.
What advice do you have for companies trying to determine how to use all the data they’re gathering from and providing to the field?
A key objective would be to develop a data-driven decision-making framework. Every piece of data presented should align to a pre-defined set of key performance indicators that can enable agile decisions about how best to improve service delivery in terms of customer satisfaction, profitability, etc. So the first point of advice would be to look at only the critical data points that need to be assessed to make decisions about service improvement. Trying to look at all data will distract; instead, focus on the key levers that can have the biggest impact. Some organizations may also split the operational and executive lenses. From an operational perspective, having an effective in-platform reporting engine can be tremendously powerful when looking to drill down into the datasets that underpin a particular KPI – trends, breaches, etc. From an executive standpoint, they’ll be interested in how they can tie this to company financials and strategic objectives. Shifting field data from operational tools into an enterprise-wide data platform can help aggregate this information to establish cause and effect relationships. An example would be tying together the number of faults resolved operationally by a particular contractor versus the invoicing and timesheets that the contractor supplies to your finance team. Connecting data that has been traditionally isolated offers new insights, and such intelligence is vital in a world where higher expectations must be met at lower costs.