Monday, 6th July 2020

Smart field service begins with the IoT

In this article, Steve Smith, VP, Strategic Industries at ClickSoftware explains how IoT and predictive maintenance can help you increase field service efficiency and productivity, decrease tech travel time and reduce charges incurred from missed SLAs, while giving your customers the service they expect.

Everyday your field service technicians are in the trenches resolving customer issues. What if you could help them resolve more issues on the first visit, reduce idle time, improve customer satisfaction and gain a competitive advantage? The Internet of Things (IoT) and predictive maintenance are reshaping field service as we know it today. Field service organisations that have implemented IoT and predictive maintenance are resolving problems faster, sometimes before they even occur, and gaining operational efficiencies that positively affect the bottom line.

Limit the unexpected with IoT and predictive maintenance

The old adage expect the unexpected can never be completely mitigated, even with all the technology available today. Whether the result of a major weather catastrophe, equipment failure, or security hack that disrupts business continuity, unexpected events will still happen. Although we can’t predict every issue before it arises, we can have mechanisms in place to be as proactive as possible in sustaining equipment health, and minimising downtime, which is where the Internet of Things (IoT) and predictive maintenance come into effect.

The Internet of Things opens up hundreds of cross-device possibilities and efficiencies in service. By bringing machines, devices, vehicles, and equipment online, service providers can effectively close huge communication gaps that currently exist and resolve customer issues faster. When combined with predictive analytics, the IoT empowers organisations to get ahead of problems and the impact felt by customers should a disaster strike.

Shifting IoT from novel to practical

Although IoT in field service is still relatively new, early adopters like manufacturers of capital equipment are approaching greater maturity. They’re leapfrogging other industries in terms of first-time fix rates and overall operational efficiency. Other industries are beginning to recognise the potential benefits, and conversations around IoT are shifting from wide-eyed wonder to practical next steps.

Utility and telecommunications providers are well positioned to benefit by making the infrastructure they maintain smarter and more connected. With the IOT, these industries can better empower their customers to participate in diagnosing and repairing problems. For example, the Smart Meter initiative enables consumers to have greater visibility into their energy consumption, giving them the option to alter habits to reduce their carbon footprint and energy costs.

While it may sound simple, monitoring thousands or even millions of pieces of equipment and identifying errors before they occur is a complex science and can actually cause more confusion than help for an organisation. That is why it is imperative that field service organisations identify their own key maintenance indicators and setup alerts based on their particular industry best practices and business priorities.

Determine Your Data Strategy

IoT sensors allow for large volumes of data to be collected and stored, providing companies with insights into equipment status, creating potential business opportunities, and enabling financing decisions. Every unit can generate hundreds of thousands of data points per minute. In fact, Cisco states that It would take a lifetime to manually analyse the data produced by a single sensor on a manufacturing assembly line. Therefore, the imperative for your whole organisation, not just the field service group, is to identify the key performance indicators that impact your specific group so you can make the most of all that data.

For example, a telecommunications provider monitoring a mobile phone tower may be tracking multiple forms of data such as the volume of calls being picked up through that specific tower and the number of dropped calls. Those two metrics have a different meaning depending upon the hat you wear within your organisation. For instance, an increase in call volume might be important to your strategic planning group as it may indicate the need for a new tower which requires a business case including financing options. However, monitoring the number of dropped calls could be a priority for the field service organisation as it is an indicator of a problem.

From this example, it is clear that a KPI that matters to one group may not have an impact on another group’s priorities. Field service organisations need to develop a set of key metrics that specifically impact your results and consistently monitor for when something is askew.

Execute on Your Data Strategy

Once data is collected and key monitoring metrics are defined, predictive analytics are applied to convert the data into actionable, useful information. Inventory, service scheduling, and even customer satisfaction can all be predicted. That is of course, if you have access to the right data.

Predictive analytics requires tracking historical data and leverages statistical algorithms, or machine learning techniques to identify the likelihood of future outcomes. Analysing historical data, particularly around equipment failures and past service activities allows service companies to identify patterns that might indicate a future error, and proactively address issues before they become bigger problems.

For instance, in a utility power plant, temperature is one of the most widely measured parameters, as overheating can cause serious damage to equipment, and can be a threat to the safety of the service professionals performing repairs to the equipment. By looking at past maintenance activities and patterns in temperature changes, utilities have the necessary insight to schedule preemptive maintenance when temperatures rise to levels that have led to failures in the past.

Increasingly, we're seeing more applications of IoT and predictive analytics in the service industry with sensors embedded in devices and equipment. But with greater connectivity comes greater responsibility; organisations must leverage these enhanced capabilities to transition from reactive to predictive service programmes to address breakdowns before they occur — ultimately maintaining customer satisfaction, today's number-one business priority.

Predictive maintenance: The field service opportunity

Diagnosing and addressing issues before they happen is key to saving time and money on service calls. And as more customer equipment is embedded with sensors, the opportunities for predictive maintenance will likewise increase.

But there’s an important distinction to be made between preventative, and predictive maintenance. Preventative maintenance means performing service tasks at regular intervals to ensure no major breakdowns occur and to comply with regulations.

Whereas predictive maintenance means using data-driven insights to better understand equipment, and predict when specific parts might fail, or the equipment should be replaced. When using IoT sensors and data-driven insights, predictive maintenance can completely revolutionise a field force by delivering more accurate parts performance reports, equipment lifecycles, and more.

The era of smart field service is here

Resolving jobs efficiently and quickly is key to achieving field service profitability. But often field technicians are unable to obtain necessary details for achieving swift resolution prior to arrival. The result? They return to job sites more than once.

The Internet of Things is helping to eliminate the need for return visits because you have all the information needed about the problem, and thereby first-time fix rates improve drastically.

By embedding smart devices in the field and identifying key performance indicators across a number of scenarios, field service management organisations are embarking on a new era of smarter field service. Field-based equipment can now send service signals immediately, and log performance data in real time. This means the need for service calls will soon disappear completely. In its place, machines will call for service before the customer is even aware there is a problem.

Where to implement IoT first

1.Embed sensors on equipment: The first and most obvious application is to focus on equipment that needs regular maintenance. Consider embedding temperature, pressure, or other sensors on key pieces of equipment enabling them to communicate for help when thresholds have been reached, instead of customers discovering and reporting equipment issues to service providers

2.Bring vehicles online: Effective field service requires technicians to remain efficient both on the road, and at the job site. By equipping your service vehicles with sensors, you can monitor vehicle wear and tear, and set alerts for regular required maintenance. This ensures you optimise when you take these vehicles off the road, rather than at times that will take away from the daily productivity of the field technicians.

3.Enable wearables: Empower your technicians with wearables such as smartwatches that monitor biometrics. This improves employee health and safety and alerts the back office if a technician finds himself in a potentially dangerous situation.

The advantages of IoT adoption

Many technologies hold transformative potential for field service providers, but it’s short-sighted to either hail any emerging technology as a panacea or wholesale dismiss it as a bad fit. With IoT, as with any technology, the key to getting real value is understanding which problems need solving, then finding the solution to match.

With IoT your service organisation can:

  • Reduce the cost of travel and labour by enabling remote diagnostics and fixes of equipment
  • Mitigate risk and prevent critical failures with ongoing monitoring and proactive service
  • Provide insight into usage patterns to better serve customers and inform future business decisions

The urgency around IoT adoption varies from one vertical industry to the next, but the cost of service delivery and the need for greater visibility are universal concerns. The old business adage “you can’t manage what you can’t measure” certainly applies. The business benefits of predictive maintenance are powerful and can include an increase in the number of jobs per technician per day or a significant reduction in critical failures.

Investing in the appropriate data framework, infrastructure, and processes is essential to fully leverage the potential of IoT. Although it will require rethinking your operations and the role service technicians play, if executed properly, predictive maintenance will deliver dividends in the form of measurable ROI.

With IoT, field service organisations can not only increase efficiency and productivity, but slash the cost of missed SLA penalties, directly impacting customer satisfaction and profitability. IoT can deliver the operational gains needed that positively affect your bottom line and provide the kind of customer experience that fosters retention.

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