The study shows that nearly three quarters of respondents provide service on equipment that is sensor-enabled. The ability to collect usage patterns and document asset performance can move the service business towards a predictive model, facilitating their ability to sell assets as a service and not just a capital equipment sale with aftermarket service delivery.

Customers may in many cases want the predictability that comes from paying for a defined outcome. But for the services organisation, profits will drive this trend. Data collected by IFS reveals that more advanced servitisation can increase service profitability by almost 20 percent. But some investments in technology are needed to enable this transformation. What kind of technology? The WBR report also delves into the specifics of how technology can lead to more effective management of the workforce.

Big results from big data: Any sensor enabled device can generate huge amounts of data points. Big Data is a term used to describe the analysis of this data and its dissemination to other systems for action. The ability to gather, analyze, distill, and communicate this data can reap huge financial and operational rewards.

When sensor-enabled equipment detects a failure, a diagnostic code can be generated. Knowledge systems can be incorporated into the process to determine the part or component failure involved, recommend a part replacement, perhaps even downloading to the field technician repair instructions, asset drawings, and part location on the equipment. I recently saw this in action at a WBR trade show. It was a standalone IoT reporting system, but a very effective real world implementation of digital transformation that empowers their technicians and service partners with useful repair information prior to a visit for repair.

Cloud based: Done properly, the incorporation of AI techniques and machine learning can determine the operational health of an asset. The ability to predict failure or degradation of asset performance over time can prescribe a proactive maintenance, service call, part replacement or recalibration of a device. This allows the equipment provider or the authorised service agent, to sell performance contracts that can be managed to margin, with a high level of confidence.

These sensors can also harvest usage of the asset, including asset throughput, procedures performed, or hours of operation. Once again, performance-based contracts can be generated that guarantee what the customer will receive from the asset. These usage contracts require continual update on asset usage and asset health as the asset performance directly correlates to anticipated revenue.

Mobile technology will then push this information to the technician, or to a team that is assigned to a job. All of this data will be distilled so that it can be disseminated directly to the people that need it most. Service managers will monitor activity and service technicians can use this data to do their jobs better. The data may take different forms, from prescriptive analytics that suggest how a problem should be dealt with to visual representations of what is going on inside the equipment. The ability to use augmented reality for repair purposes is one example of how a technician may visually interact with data—by viewing an overlay of parts or components as they look at the physical machine. Team collaboration may also give a subject matter expert in a central location visibility into what a technician in the field is seeing, and can use augmented reality to advise his associate remotely. This will enable a service organizations to do more with less and smooth the transition from a shrinking, aging workforce to a newer, younger but less experienced workforce.

Right technician, right job, right time: Finally, intelligent scheduling tools will put people in the right place at the right time. Once again, using artificial intelligence (AI) techniques, these scheduling systems will position technician in the right place to be more successful in service delivery. Why is AI necessary here? Because identifying and dispatching the right technician given fluctuating demand is too complex a problem for any human dispatcher.

Lacking AI-driven scheduling, emergent jobs coming in that should take precedent over those already scheduled will probably be pushed further out. Dispatchers will struggle to make scheduling decisions based on SLAs and other contractual re    quirements, and will not be certain which technician has the skills, tools and materials to handle which job. The location of the technician is constantly changing, so identifying the closest one to an emergent service call is difficult.

When intelligent algorithms make these decisions, the service business can make commitments to customers, utilize technicians in the best way possible and improve the customer experience.

Contributed by TOM DEVROY, Product Evangelist – Enterprise Service Management, IFS

Market volatility is expected to continue, dependent on further purchases by local institutional investors. Previously, profit-taking usually followed accumulative net purchases of about Bt20 billion in 10-15 days. The followings are major issues of the week:

The US mid-term elections will take place on November 6. The latest poll indicated the Democrat Party leading the Republicans by 50.2 per cent to 42 per cent. If the Democrats managed to take control of either the House or the Senate, it could have an impact on Trump’s policies including world trade.

Global interest rates are on the upward trend, led by eight Fed rate hikes since December 2015 in the US.

The Thai policy rate is expected to remain at 1.5 per cent after the Monetary Policy Committee meeting on November 14, in view of the 5.3-per-cent contraction year on year in September exports and slowdown in inflation. The SET Index will fluctuate with resistance set at 1,700 points. Short-term trading poses high risks but investors could gradually buy stocks with strong fundamental for long-term investment.

Investment theme: Stocks which will gain from activites of the Eastern Economic Corridor. Two mega-infrastructure projects are expected to take off this month, the high-speed train connecting three airports and the Eastern aviation city (U-tapao). Stock picks are AMATA (fair value@Bt35.70), WHA (FV@Bt4.89) and EASTW (FV@Bt13). – Therdsak Thaveeteeratham, Executive Vice President/Research, Asia Plus Securities

Moody’s report “Insurers – Asean: Growth comes through new policies and innovations” is available on http://www.moodys.com. The markets include Singapore, Thailand, Malaysia, Indonesia, Vietnam and the Philippines.

Moody’s subscribers can access this report via the link provided at the end of this press release. The rating agency’s report is an update to the markets and does not constitute a rating action.

“The strong fundamentals include urbanisation, a growing middle class, low insurance penetration, and the lack of a sufficiently-funded welfare system,” says Frank Yuen, a Moody’s Assistant Vice President and Analyst.

However, the pace and quality of such growth will vary to reflect differences in market maturity, financial depth, demographics and policies, and the insurance industry in these countries are finding different ways to overcome common growth bottlenecks, says Yuen.

The bottlenecks include difficulties in expanding and enhancing distribution capabilities, low protection content in mainstream products, shallow bond markets that limit investment options, and an increasing need to improve the capacity of industries to withstand shocks and support growth through tightening risk-based capital (RBC) regimes.

Asean governments are also aware of the widening protection gaps in the region, in particular among underserved segments, and have addressed these concerns through policies.

The report notes that economic incentives for insurance coverage are emerging throughout the region, particularly in medical and retirement coverage.

The markets examined provide some health coverage, but their ability to sustain such coverage varies, leading to opportunities for commercial insurers to fill gaps.

In that regard, Thailand and Malaysia have witnessed strong premium growth for critical illness and medical products, while Singapore’s aging working population supports the steady growth in retirement annuity policies.

Similarly, economic developments in the region will continue to support the growth of non-life premiums. Rising infrastructure investment in Indonesia supports demand for property and fire insurance, while the Philippines’ high exposure to natural disasters has fueled its demand for catastrophic loss coverage.

In Vietnam, the continued economic development and increasing risk management awareness would support premium growth.

Throughout Asean, insurance distribution is dominated by agencies and brokers, which are uneven in quality, coverage and geographical reach.

In addition, there has also been a growing number of regional bank partnerships to expand client reach. Nonetheless, Moody’s expects that it will still take time and investment for insurers to strengthen the distribution capabilities of their banking partners to offer higher value products.

 She added that the higher inflation rate in October followed price increases of energy and food prices in the first ten months with an average inflation rate of 1.15 per cent.

However, the country’s inflation has been kept below 1.25 per cent as targeted, she said.