As you attempt to derive growth strategies for your field service business, it is important to focus on the right things - the right technologies and the right best practices.
So what are the key things to focus upon in the coming years? Let's not talk about the impact of the 2020 Covid-19 pandemics and how it has disrupted the field service industry because technology evolution didn't happen in that one year. It is true that the new normal had sped up the adoption of certain technologies or have even molded some 'good-to-have privileges into 'must-have' necessities, but the bottom line is field service industry is anyways going through a phase of technology transformation; in fact, it can be said that because this industry has been reviving with technology advances, so it could swiftly sail through the turmoils created by pandemic situations.
Certainly, a lot of things are happening in this industry, it is moving forward to a high-tech realm, and to catch the pulse you need to have a clear idea of the technologies and best practices that need to be adopted without any procrastination. So, let's discuss the top 10 field service management trends, to help you strategize business growth through effective field service management.
Predictive maintenance is the progressive future of the field service industry. It is here to stay, prosper and transform the ways maintenance services are being offered. Predictive maintenance will encourage the trend wherein service contracts will be less about the frequency of maintenance visits and more about equipment uptime.
Predictive maintenance is a pragmatic shift from preventive maintenance, also referred as 'scheduled maintenance' or 'break-fix maintenance'. At present, most of the maintenance service providers either run to fix a problem, when the outage has already happened, or in a better attempt to keep their customers happy, they try to offer preventive maintenance on a scheduled frequency. These regular services are expected to avoid major outages in equipment or appliances. But this costs a lot for the service providers as well as the customers.
In preventive maintenance, it may happen that on a scheduled date a machine is serviced while technically nothing was faulty in it, and it was not on the verge of an outage. Similarly, it may also happen that a machine narrowly misses the scheduled maintenance date, and unexpectedly break down before the due date. The undermining factor with preventive maintenance is that it is not data-driven rather it is based on calculative assumption.
Thereby, at a speedy pace maintenance service providers are progressing towards data-driven predictive maintenance facilitated by IoT and artificial intelligence (AI). IoT sensors in machines and appliances generate data like equipment age, usage data, voltage fluctuations, temperature, humidity, and much more. Software programs with AI and machine learning algorithms use this massive data or information to monitor and predict equipment failures with a very high level of accuracy. This results in benefits like need-based but on-time maintenance, fewer maintenance visits, maximum equipment uptime, reduced costs, and improved customer satisfaction.
IoT and AI-enabled predictive maintenance are here to provide customers what they want - maximum equipment uptime with fewer maintenance visits. A customer is not much concerned about the frequency of services. If fewer maintenance services can guarantee maximum uptime for his equipment or appliances, then he will be more than happy because that saves his time and money.
Who are the data users in your organization? Data consumption and analysis are no more just for the selected few or the IT department? Even the field technicians, financial analysts, HR executives, managers, senior executives, administrative staff have data analytical needs; they all consume data in different patterns to help themselves do their job more efficiently.
Effective decision-making is everyone's KPI - be it executives, employees or field staff, and also it is critical for improving business performance and driving growth across the board. The power of decision-making thrives when there is real-time access to contextually relevant data. But, the problem with traditional data analytics models is that these are designed focusing the needs of one category of users, i.e. data scientists or data analysts. These data models are not intuitive to the data consumption patterns of other users, the so-called non-IT group.
The 'One size fits all' approach in data consumption and analytics is not healthy, and it is getting replaced by the new trend of AI-driven flexible data models. These data consumption models are AI-powered enterprise intelligence and adaptable to different use cases. By incorporating AI data distribution mechanisms, flexible data models facilitate democratized access to data across the enterprise and support multiple consumption patterns of different business users.
Why do flexible data models need to be AI-driven?
To facilitate multiple consumption patterns, there is a need to create separate layers in the data lake. This is critical for keeping the data organized and managed when new data flows into the data lake, and also for categorizing and executing the user access, security, control, and data management policies. It also ensures data is easy to find, use and re-use, it avoids duplication and ensures data integrity.
Designing, developing, and deploying so many aspects of data management and making data sets relevant for specific use cases is not realistic if done manually. This is what makes AI-driven flexible data models so critical for field service businesses because these models automate and streamline access to data across the enterprise.
AI flexible data models also future-proof the whole of data-engineering pipelines by making them more tolerant to changes i.e technology upgrades; adding new consumption patterns on top of existing ones gets seamless.
Companies across the globe are in a drive of digital transformation. Core business processes and IT infrastructure are always at the center of focus when digital solutions are deployed, but field service operations often get overlooked. But now it's peak time when companies need to digitize their field service operations and bring them to the online platform.
This is because the online on-demand services market is witnessing massive growth, especially home services. "The global home services market is expected to grow 18.91% per year from 2019-2026" (Source: Verified Market Research). Consumers are increasingly using smartphones to search for home service providers like appliance repair, electrical, cleaning, roofing, pest control, plumbing, lawn care, etc. As per Google, in 2019, it saw 350 times more searches for the keywords like “near me” and “local” than in 2009. A higher percentage of consumers, as high as 90%, don't have a particular brand in mind when they search for a home service provider, and 80% of consumers are driven by customer experience when it comes to choosing their service providers.
The bottom line is businesses need to invest in customer experience, and customer experience is not just about the onsite experience. For the modern smartphone savvy customers, what is not accessible over their mobile phones is not worth their time. Thus, mobile app technology is the progressive, and potential way to peach customer experience.
Mobile apps facilitate adoption of new digital approaches that enable consumers to conveniently connect with the service providers or consume the services more easily.
Gartner's ‘Magic Quadrant for Field Service Management, in its analytics report had stated that by 2020 more than 75% of field service organizations with over 50 employees will deploy mobile apps to optimize capabilities that help their technicians succeed.’
Customer-connect apps, field service management apps, work order management apps, customized apps are gaining popularity among service providers. Field service management apps facilitate mobility for the field workforce by enabling them with on-the-move capacities like:
Even customers demand the convenience facilitated by these apps, such as online booking of services, ticket raising, on-site invoicing and billing, customer account management, etc. Mobile apps are soon to become, if not already, indispensable digital tools necessary for automating field workflow and standardizing the processes so that operational cost can be reduced and deliveries can be improved.
Integrated with other myriads of technologies like mobile connectivity, smartphones, WANs, PANs, IoT devices, etc., location technologies like GIS (geographic information systems), GPS (Global Positioning System), navigation systems, etc. have been instrumental in creating geo-data that has transformed field services by unlocking productivity and new opportunities. The good thing about location technologies is that consumers already trust and use them. Over 90% of smartphone users use navigation systems.
Location technologies like GPS, WiFi, Cellular, QR Codes, RFID, etc, provide real-time geo data that are functional in field operations in a lot many ways, such as:
The future of location-based services is poised to witness improved accuracy and further innovation with emerging technologies like 5G networks, WiFi 6, Ultra-Wideband (UWB), augmented and virtual reality, advanced LiDAR imaging solutions, machine intelligence systems, and voice assistants like Apple’s Siri.
Most businesses are already using chatbots in their websites, apps or customer connect centers. As a successor to chatbots, the digital assistant is the next big thing capable of delivering an improved customer experience. It functions as a single, convenient point of contact between customers and businesses.
Digital assistants are advanced types of chatbots that have grown more smart, functional, and accurate with advances in AI(artificial intelligence), NLP(natural language processing), and machine learning.
While chatbots deal with relatively simple conversions and interact in a computerized style of language, digital assistants can handle more complex interactions that too in a much closer human-like conversational way. Advanced NLP understanding gives digital assistants the ability to access multiple data sources and process what a customer is saying or typing with much accuracy. They can understand complex sentences and generate accurate answers. By using AI and machine learning, they are capable of better predicting the customers' preferences based on their past actions and thus can deliver a personalized experience to them.
Apart from being used as a customer connect-connect tool, digital assistants are increasingly gaining popularity in the space of employee self-service. They are capable of automating employee services and enhance the service management experience. Instead of spending their time on tedious manual processes related to self-services, employees can use the digital assistant to handle tasks like:
Field employees love the convenience facilitated by a digital assistant. It is an influential mobility solution through which employees can access unified information from multiple systems across the company- such as enterprise resource planning (ERP), human capital management (HCM), and customer relationship management (CRM).
When you talk about trends in field service businesses then perhaps the core trend is that of customer-centricity. Observe the top organizations, all their activities revolve around meeting customer needs and facilitating convenience to them. Every business understands the importance of customer-centricity and how it can deliver a competitive edge, but yet many businesses are in grey areas about how to serve their customers better.
In field service businesses, average response time is critical and this requires effective management of customers’ service requests, especially during the business's crucial growth phase when customer service requests are also on the rise. As solutions, CTI-based contact centers and telephony-based customer support systems have been in the industry for quite a time, but scalability of these systems is a challenge, especially if you want to keep your costs down.
As you look for a scalable solution to meet needs like service request management, customer engagement, customer account management, etc., a customer-service portal is your way out. These portals are gaining popularity as a perfect complement to existing contact center systems, and also as a web traffic booster.
“State of Service,” Salesforce Research, 2019 states that customer self-service constitutes a major part of the service strategy for 69% of decision-makers at service organizations. Nowadays customers' decisions are information-driven. Customers believe in enriching themselves with information before they associate with any service provider.
And as they start dealing with a service provider, they seek transparency and some amount of control in the relationship. These types of consumer behaviors have made customer portals so integral to the service industry. A customer portal is a unified platform through which a business can win customers trust and preference in ways such as:
For businesses, one of the major advantages of a customer service portal is that it allows the service agents to focus on bigger issues. Using the portals, customers can self-reliantly find resolutions for common and routine questions and concerns, so the service agents can devote their time to customers with complex issues.
As mentioned above, the current core trend in the service industry is customer-centricity. When the goal is to deliver better experiences to the customers, then a data-driven personalization strategy is one of the top favorites among the marketing departments, and it will continue to grow in its effectiveness. This strategy is all about knowing the customers so well that they can be delivered with the right kind of content at the right moment so that it hits the right cord of customers' interest.
Ascend2, a research-based marketing agency conducted a “Data-Driven Personalization Survey” to understand the usage of data-driven personalization strategy among marketers. 251 marketers participated in the survey, and it came out that marketing professionals rely on data-personalization strategy for improving customer experience(64%), increase visitor engagement (44%), increase conversion rates(43%, improve product offering and pricing (26%), and others.
Data personalization is not just about collecting data as much as possible, but it also requires having a proper system to make that raw data functional. Field service management software suites, customer portal, digital assistants, CRMs, ERPs, mobile apps, social media engagement, all these are effective ways to capture customer data. However, the critical challenge is to ensure the quality of data and its functionality. But new-age software suites, web tools, mobile apps, computer programs are designed as an end-to-end business solution. So they are more than just data-collection mediums, they do have automated functionalities to channelize the data usability.
People development is all about working with employees to enhance, refine and hone their existing skills, and also to help them develop new skills. The best practices for people development are:
What businesses gain from investing in in-house people development programs?
Performance improvement, better handling of unexpected situations, building a continuous stream of would-be-leaders, and improvement in employee engagement are some of the key benefits that organizations can achieve through people development initiatives.
But then, one of the main benefits is the long-term money-saving via employee retention. As per a Gartner report, one of the key drivers of employee attrition is the lack of future career development. As per AT&T company, the cost of replacing an inadequately-skilled worker is around 21% of his salary. As the base pay increases, the cost of replacing an employee increases, so retention is a much cost-effective option, especially in regards to senior-level executives.
But as mentioned above employees leave jobs when they feel that in a particular organization they have no career growth scope. Thus, people development is a win-win solution for both employees and employers. While it empowers the employees to groom and grow into leaders, their businesses get the revenue benefit from their employee's leadership demonstration. According to the report of Bersin by Deloitte, "Organizations with strong leadership demonstrate a +37% rise in revenue per employee and +9% in gross profit margin"
If HP knew what HP knows, we would be three times more productive.” – Lewis E. Platt, former CEO at Hewlett-Packard.
This crisp line very well defines why knowledge management is the most important asset for modern-day businesses, including field services. Poor knowledge-sharing practices not just hinder growth, but also causes money losses. On the other hand, effective knowledge management disciplines can increase employees' or company's productivity by 10-40 percent.
A well-implemented knowledge management system enables people in an organization to share, access, and update business knowledge and information. This ensures that everyone across the organization has access to the right kind of information at the time of need, which is a much-needed facility for the field workforce. Document management systems, Content management systems (CMSs), Field Service management software, Chatbots, social networking tools are different types of knowledge management solutions that organizations can implement.
A glance into the above-mentioned pointers reveals that field service management is becoming more and more data-driven. Be it about predictive maintenance, flexible data models, knowledge management, people development, customer portals, digital assistants, mobile apps, or data-driven personalization, every trend discussed here revolves around data. But data handling comes with the challenge of data and privacy protection.
With growing awareness regarding the potential risks resulting from compromised data security, businesses will continue, and they must also, with their stringent endeavors to adopt effective data and privacy protection practices.
When it comes to putting the above mentioned trends into action, the top-line businesses are still the major practitioners. But, considering the potential of these solutions in regards to technicians' efficiency empowerment, customer engagement, and field workforce management, in very little time, even small-scale and medium-scale businesses will soak up these trends leading to mass adoption.
However, while adopting these trends as business solutions, organizations must remain selective of what software they choose for the execution purpose.
It is always wise to have a unified field service tool or field service management software that can multifunction, rather than having different software programs for different purposes. This takes away the challenge of data integration. And most important is to choose a scalable tool that allows building new functionalities over the existing ones because trends will continue to change and grow more sophisticated in line with technology advances.