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Marc Tatarsky, SVP Marketing of FieldAware outlines the increasing importance of business intelligence in field service management.


Without doubt the use of analytics is having an increasing impact in field service. In 2018 we saw more interest than ever from field service leaders wanting better insight into their business and they understand that analytics holds the key to this.
We are expecting a further shift in the way analytics is applied in field service so what are the main challenges that organisations face that analytics can address today?

The Evolution of Analytics
The early adopters of field service analytics were quick to realise that it was not simply data that mattered, but how the data was turned into information that was key. They focused on how data was aggregated from multiple sources to give a unique and unprecedented visibility into the end-to-end operations.

They took a basic understanding of the ‘what’ and ‘where’ and enabled the next leap of the ‘why’ with advanced analytics capabilities that truly enhanced the value of their data further still. Analytics provided business insight and allowed management to focus on taking action based on decisions made from the real-time information available. Operational issues can be more easily identified and rectified quickly and effectively. Business intelligence helps identify trends and creates context, so productivity can be improved, and efficiencies made, so field service organisations have reaped the benefits.

Learn More, Serve More, Grow More
As field service organisations mature in their use of analytics they demand more from business intelligence. There is a definite shift in the application of analytics from simply turning data into outcomes, to enabling leading companies to take a more strategic approach. Analytic driven organisations can learn more about their operational performance and the needs of their customers empowering them to address the trends that are revealed.

Going forward into 2019 we will see analytical data being used in unique ways to help field service organisations leverage the findings that are uncovered to drive innovation into their products and services. Forward-thinking companies will be able to apply these insights to help customise the service they offer to their customers more easily, deepening the customer relationship and improving levels of satisfaction.

The creation of new, unique, predictive and preventative services will help them to serve more. Ultimately this greater understanding of their customers’ needs and expectations, is what will help companies differentiate themselves from their competition and lead company growth.

This shift to a strategic use of data is becoming more and more prevalent in field service and leaders are making it a priority in their business drivers.

"As field service organisations mature in their use of analytics they demand more from business intelligence..."

An Integrated Future
As company leaders recognise that field service has the potential for becoming a more strategic driver within the wider business, the need for improved integration within the business becomes even more critical.

Service teams have, in the past, often been considered to be simply an overhead within the business model rather than adding value. However, the ability to leverage information across the organisation in real time and bring additional context to the broader business insights, empowers field service organisations to become value drivers in the business.

Analytics provides the means for field service organisations to realise their potential and companies that recognise this value, see the importance of a closely integrated and connected field service within the wider business.

Field service solutions have long had the capability to integrate into other business systems, such as CRM, ERP and accounting, to extend the power of these solutions and the combined information provided. Business leaders understand that the true integration of these technologies maximises the overall value beyond the sum of the parts. A comprehensive field service management platform integrated with a suite of solutions is where we are seeing the greatest application of analytics.

As field service becomes a greater part of a fully connected business, the empowered field workforce, armed with contextual insights, are enabled to creatively interact and work with other teams and departments. These new interactions further unlock the value for the company in terms of customer service, sales or product development to fuel competitive advantage.

The Analytics Advantage
Analytics will continue to develop and the potential in field service is vast. It is no surprise that research consistently shows that field service leaders see analytical tools as a priority for their technology investments.

Business insights elevate the field service operation, transforming it to a value-driving organisation within the wider company, that delivers real results: Increasing productivity, customer satisfaction and revenue, taking service to the next level of providing competitive advantage – a vital step in any business.

Companies should take full and rapid advantage of the critical role analytics has in field service.

Mark Tatarsky, is SVP Marketing at FieldAware and will be part of a panel at Field Service USA, discussing the latest developments in field service analytics. The event takes place from April 23 to 26 at JW Marriott Palm Desert Resort and Spa, CA and ou can register for the conference here.

For more information on how to take advantage of analytics in your field service, visit FieldAware's Insights page here. 

Aberdeen’s Aly Pinder asks are we smarter than we were in the past, or do we just have better access to data?

When was the last time you asked someone for directions, or used a phone book, or waited for the day’s forecast on the morning news?

Well, that last one is probably something you still do out of habit, but the others are things which have left our consciousness as we can just “Google it” from our smart phones. The emergence of technology and the IoT has flooded the service leader with more data than ever before. Machines talk to machines, technicians collaborate with each other via mobile devices while in the field, and customers interact with the service team in real-time owning their experience.

But with all this access to information and data comes a few challenges. How much is too much data? How can we turn this data into actionable insights? Who needs to know what and when?

These are all questions that the Best-in-Class service leader is tackling right now. As seen in Aberdeen Group’s recent State of Service Management in 2016: Empower the Data-Driven CSO (March 2016) research, one of the top goals for service leadership was improving the quality and relevance of data for the service team. This is a top 3 goal, only trailing the need to improve customer retention and drive service profitability.

Happy customers, profits, and then data quality in that order shows how the impact of data is rising on the agenda of the senior service leader today. But how do we get to a place where data is useful?

Is the answer to our data problem more technology?

Top performers recognise that ensuring the service team has actionable data is a journey and not something that can be solved with one-off investments. It takes a strategy, leadership, and resolve. Connecting the field team to insights helped these organisations resolve issues faster, deliver more value to the customer conversation, and make the field team better at their jobs!

 

All these are great, and the Best-in-Class have some lessons for the rest of us:

Empower the service team with the data they need to make decisions, more isn’t always better.

Top performers ensure the field team has customized data views which provide only the pertinent information for technician for the specific task they are working on. Having the data necessary to solve complex issues at the time of service is integral to ensuring resolution can occur on a first visit, technicians are efficient, and the customer can be back up and running with minimal downtime.

Give the field team the mobile tools to have access to insights.

The field workforce is rapidly changing. We have been fearing the aging workforce for some time now, and it is finally here. But the Best-in-Class ensure that as technicians leave the business, their knowledge does not. They are able to capture best practices and expertise, and store these insights in an accessible location which can be tapped into via mobility in the field.

Leverage machine, customer, and technician data to identify the future of service excellence.

The IoT means different things to different people and industries. But the value isn’t just in the fact that we more devices are connected. The value of the IoT is in connecting the service chain to resolution, value creation, and collaboration. Smart machines and products open up a whole new world of possibilities as savvy organisations can take this data and better understand how to optimise assets performance, build better machines, deliver more targeted services to customers, and ensure technicians know the answer to the problem before they even get on site in front of the machine.

The proliferation of data in this era of the empowered customer can be a challenge for many organisations. Too much data leads to delayed action or inaction altogether. Top performing organisations have invested in technology and their internal processes to ensure they can turn all of the valuable data being captured every minute into actionable insights which drive value.

Top performers were able to take improved data capabilities and turn that into outperformance in key metrics such as customer retention, SLA compliance, and worker productivity.

Don’t be left behind looking at a phone book or reading a map. Tap into real-time data to make the decisions which will lead you into the future of service excellence.

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 By 2018, half of business ethics violations will occur through improper use of Big Data Analytics, says Gartner.

Analytics projects that utilize big data or advanced analytics are increasingly popular but present a heightened risk of failure, according to Gartner, Inc. which says analytics leaders can improve the likelihood of success by following five best practices.

"Although big data and advanced analytics projects risk many of the same pitfalls as traditional projects, in most cases, these risks are accentuated due to the volume and variety of data, or the sophistication of advanced analytics capabilities," said Alexander Linden, research director at Gartner who is  presenting on advanced analytics at Gartner's  Business Intelligence & Analytics Summit 2015, this week in Munich, Germany. "Most pitfalls will not result in an obvious technical or analytic failure. Rather they will result in a failure to deliver business value."

Failure to properly understand and mitigate the risks can have a number of unintended and highly impactful consequences. Those can include loss of reputation, limitations in business operations, losing out to competitors, inefficient or wasted use of resources, and even legal sanctions.

Gartner also predicts that, by 2018, 50% of business ethics violations will occur through improper use of big data analytics. Following key best practices will help analytics leaders to improve the likelihood of success, and they include:

1. Linking Analytics to Business Outcomes through Benefits Mapping
   Analytics must enable a business decision maker to take action, and that action should have a measurable effect — whether the effect is directly or indirectly achieved. Linking analytic outputs to traceable outcomes using a formal benefits-management and mapping process can help the analytics team navigate the complexities of the business environment, and keep analytic efforts both relevant and justifiable
2. Investing in advanced analytics with caution
   Many organizations believe that Big Data automatically requires advanced analytics. However, the data-crunching power required to manage the big data characteristics of volume, velocity and variety does not inherently require any more sophisticated algorithmic processing. It is the complexity of the analytical question to be addressed that drives the need for advanced analytic tools, and in many cases desired outcomes can be achieved without resorting to more sophisticated analysis.
3. Balancing analytic insight with the ability of the organisation to make use of the analysis
   Because analytics can only be beneficial in organizations that are willing to embrace change, it makes sense to limit investment in analytics to a level that matches the organization's ability to use the resulting insights. Analytics may not be the most suitable approach if  pertinent data is absent, when there are high levels of ambiguity, or where there are entrenched opposing points of view.In these cases, scenario planning, options-based strategies, and critical thinking should also be incorporated into analytical approaches to better support the organization's ability to take action.
4. Prioritizing incremental improvements over business transformation
   Using big data and advanced analytics to improve existing analyses, or to incrementally update and extend an existing business process, is easier than using them to deliver business transformation, because there are fewer dependencies to overcome to ensure success. Care should be taken to validate the level of overall change required. In some cases, deep reform of the business strategy may still be necessary — for instance, when a new disruptive vendor enters a market, when technology innovation changes the business model, or when an organization has become dysfunctional.
5. Considering alternative approaches to reaching the same goal
   Few objectives can only be achieved in one way. Statistical modelling, data mining and machine learning algorithms all provide means of testing ideas and refining solution propositions. Big data and advanced analytics help validate proposed hypotheses and open an even wider range of potential approaches to addressing corporate priorities. Not all problems even require a fully engineered analytical solution. Investment may be better targeted on human factors, re-education or reframing the problem.

 

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Trimble Field Service Management's John Cameron takes a look at what intelligence means in field service today...

Today, a field service operation is characterised by the running of multiple technologies, from GPS and vehicle-tracking systems to telematics, fleet management and workforce management solutions.

Each of these technologies generates vast amounts of data and businesses are increasingly realising the importance of reviewing and monitoring their performance using the data they collect. However, being able to organise and analyse data in an effective, simple and reliable way is a major challenge and without the means of turning it in to something actionable, many businesses just don’t take advantage of it. Business analytics and reporting tools have come to the fore as a solution able to tackle this and empower field service organisation’s with the information they care about to make faster, better informed decisions.

Fostering business intelligence through business analytics and reporting tools

Understandably, no field service organisation has the same reporting requirements. Many have different metrics and performance indicators to manage, from driver behaviour to vehicle usage and maintenance to overall worker performance. Many also need to report on metrics relevant to their role eg: finance, risk, customer service and operations.

Advances in business analytics and reporting tools provide businesses with the ability to view all of their data in one place then configure and cross reference it in a simple, easy way. Businesses are then able to make better decisions and better decisions mean a more effective, efficient operation.

 

Many business analytics and reporting tools offer users the chance to view the information they want, when they want it. Using drag and drop metrics, dashboards can be constructed tailored to reporting needs, to show the most important metrics and represent those metrics in ways that users choose.

For example, productivity can be looked at alongside driver safety and vehicle performance to ensure that while SLAs around completed jobs are being met, safety isn’t being compromised.

The dashboards can be utilised to run on-demand reports from any number of metrics which can then be interrogated and filtered to the level needed for individual requirements. The purpose for this data is to then be distilled to generate concrete, actionable details, which can then be used to benchmark and identify trends which will in turn help businesses to determine which assets and employees are the most productive.

Immediate and long term benefits

Fleet and workforce management systems give managers the ability to review a day’s work and measure performance results against company standards.

With the use of business analytics and reporting tools, managers can extract the data from these solutions to identify top performers, determine which schedules and routes produce the best results, and compare results from one vehicle or worker against the entire fleet. Performance analysis can also help with job assignments, helping managers match the skills of field technicians to specific service calls. This increases the prospect of first-time case resolution.

Telematics solutions alike can capture a wealth of useful information, from mechanical and emissions to driver safety habits. With the use of reliable, analysed information, knowledge can lead to action.

A manager who knows which drivers have bad driving habits is better equipped to coach those drivers; up-to-date information on the health of vehicles leads to better maintenance, which in turn leads to safer vehicles, improved fuel consumption and less wear and tear.

 

These are some of the immediate benefits, but understanding data also brings long-term benefits, as companies engage in strategic planning based on historical patterns and predictive analysis.

For example, a company which focuses on repair could make use of its historical data to know when a specific part on a specific machine is likely to fail. This could lead to preventative maintenance by fixing or changing a part before it fails, helping to deliver excellent customer service, reduced downtime and significant cost savings. The work becomes less about being reactive and more about precise, well researched planning.

Analysis of operational trends and patterns also reveals what areas businesses need to target for improvement. Perhaps drivers are using shorter routes that actually take more time because of traffic patterns, or technicians are returning to customer sites because they lack the knowledge or part to complete the job, or vehicles are left too long on idle and wasting fuel. With intelligence and analytics tools, organisations can drill down into the data to benchmark and identify situations where problems are occurring.

For more information and insight into how you empower your field staff to make more intelligent business decisions, visit: www.trimble.com/fsm

 

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Big Data remains a big topic of conversation in field service but is it really all that different to business intelligence? Dan Barber of service management software providers Zafire gave us his thoughts as we caught up with him on his stand at this years Service Management Expo.

 

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With over 20 years’ experience in the industry Chris Beling looks at the connection between ‘best-in-class’ service organisations and the use of business intelligence.

True or false? The importance of turning data into meaningful business intelligence has never been so critical for the service management industry as success criteria and the ability to deliver ‘service excellence’ continues to move further away from the ‘wrench’ and more towards a customer centric focus.

Recent reports published earlier in 2015 suggest that ‘best-in-class’ service organisations are reaping the benefits of such an approach with figures showing higher customer satisfaction and customer retention rates as well as a year-on-year increase in service margins. So why isn’t everybody adopting this approach?

One of the main challenges faced by the wider market is progressive technology. So what do I mean by this? I’m referring to the pace at which technology and service management software advance and the ability, or lack of, for service organisations to adapt and adopt these advances successfully to help drive business growth.

The service environment varies greatly, whether you’re a service centre handling thousands of repairs every day, or a service provider with a large team of field engineers managing a hugely varied portfolio of assets all over the country (or all over the world for that matter) . Consequently ‘out of the box’ solutions don’t always match organisations’ exact requirements

 

Disparate systems, legacy data, complex assets and growing customer demand all add to the challenge of providing ‘service excellence’ in the complex world of service management. So even if you know that customer satisfaction, an increase in contract renewals, improved service margins, workforce efficiency drives, moving from reactive resolution to a PPM based approach are all essential for business growth and maintaining a competitive advantage, how do you provide service excellence without impacting current performance?

Here’s how? With a service management solution that provides a comprehensive end-to-end process engine and the flexibility to match your exact requirements, keeping you in complete control of operations, whilst at the same time providing management with a holistic view across the organisation and not just delivering data but revealing business intelligence.

Leading organisations are now looking at service as a ‘profit centre’ in its own right with management embracing the concept of a ‘customer centric focus’ in order to excel at service operations and drive revenue.

With a central system receiving data automatically and simultaneously from multiple parts of the business - at the point of job creation through the service desk; from engineers in the field via mobile technology; direct from assets with M2M capabilities to name but a few – business intelligence doesn’t just report on the number of calls completed ‘on-time’ but the provides insight into what it took to close those calls and how they could have been prevented the in the first place.

It’s reported that 41% of service jobs are now Planned Preventive Maintenance (PPM) visits within best-in-class service organisations which indicates greater control of resources, planning and cost allowing them to optimise their workforce, increase productivity and improve margins. This single shift in approach from reactive to predictive can have a huge impact on margins with fewer reactive calls, an increase in ‘first-time fix’ rates, improved asset up-time and, of course, enhanced customer satisfaction.

 

In any business, and this is nothing new, it’s more costly and resource intensive to generate new business rather than nurturing existing customers. Service management is no different. So, if we find ways to achieve ‘service excellence’ and in turn improve customer satisfaction, it would be fair to expect to see an increase in contract renewals, customer retention and customer referrals.

The expertise of service management software providers, their ability to provide comprehensive solutions and their ability to work in partnership with their customers to understand requirements, are all essential for the successful implementation of a ‘service excellence’ strategy within any business. After all, you only get out of a system what you put in – so if business intelligence is the required output you must be able to input, capture and monitor the data in the first place.

The ability to connect and optimise assets, contracts, customers and workforce using one central system that can provide real-time visibility to operational performance and turn a myriad of data into meaningful business intelligence seems like a game changer to me. Investing in, and building on, solutions that offer that business intelligence will be what separates those organisations at the top of their game from the rest of the field.

 

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In the first part of this two part feature Glyn Dodd, Managing director of Centrex Services discussed how with the current economic business pressure, reducing costs in the service management supply chain without compromising customer satisfaction is a challenge which must be faced head on...

Now in the concluding part of this feature Glyn outlines why Big Data isn’t the answer to solve all the service management industries issues, why failure is a good thing, and why true Business Intelligence is perhaps the key to unlocking a successful future for service management…

Big data is not the answer

The final element of deriving complete business intelligence is the data. The arrival of complex data analytics may seem to be the answer to such issues, but I believe that the data alone is not enough to improve the current state of the service supply chain.

There is a widely held belief that generating ever increasing amounts of data is the answer to all our service supply chain needs, but alone it is irrelevant if not turned into useful information. It’s the business intelligence transforming this into relevant information which is vital for the creation of an efficient, integrated service supply chain, abolishing the silos that plague the current model.

Companies such as Centrex Services source business intelligence from reason code data and apply a layer of diagnostics. The codes detail the circumstances that have caused the code to be raised and the associated completion code. Rather than just documenting each code and applying the same reasoning to each circumstance, the business identifies repetitive causes and designs a solution to resolve the issue, without it reoccurring.

This intelligence was applied when we identified a recurring problem on the point of sale system at a fast food outlet. A plastic part of the POS hardware was continuing to break, causing the same reason code in the majority of the support calls. When the business analysed the fault, they found the operators were leaning on the part of this hardware during use. The plastic was simply not robust enough. By tooling a metal replacement part, the problem was resolved permanently.

Delivering customer satisfaction is a critical part of any business and deriving intelligence plays a large part in the experience. Diagnostics of reason codes is therefore vital, yet many do not see the long term benefits which have an adverse affect on customer satisfaction within the service supply chain.

If businesses diagnose the reason codes, business intelligence can be created, which in turn can be used to offer improved SLA’s, rather than accepting a failure rate.

Why should we plan to fail?

In addition to the people, processes and data, the service supply chain is heavily reliant on service level agreements. We need to  question the current ethos in place throughout the service supply chain, claiming some companies are in fact preparing for failure.

There are circumstances where SLA’s are not being met as a direct result of people and processes being deployed without applying context to the data which has been sourced. I also question why SLA agreements are being signed allowing up to a 15 per cent failure rate when the deployment of business intelligence can realistically create a network in which success is inevitable.

The need for such change was identified in a business intelligence not utilising business intelligence, which resulted in an SLA being missed.

A client of ours works closely with a very well known American diner chain and have in place an agreement which states once a call has been made to report a technical fault, there must be a field-service engineer on-site to resolve the issue within four hours.

The issue here was, these calls can come in at any time of the day and the mentality was that the SLA must be met at all costs. So, when a call reporting faulty point of sales systems was placed at 1.00pm, processes were set in motion to guarantee an engineer was on-site by 5.00pm.

However, once they arrived, they were turned away, as the restaurant was unable to accommodate the work during their busiest period as this would result in a decline in productivity which in turn can lead to a loss of custom. Ultimately, the SLA was not met.

This demonstrates just how vital it is that the service supply chain changes, as had business intelligence been utilised, there is no way an engineer would have been sent to a restaurant during such a busy time.

Business intelligence is the future

Efficient communication, processes and correct analytics provides the business intelligence needed to simplify the fragmented supply chain. Simplification leads to more efficient service delivery, guaranteed SLA’s, greater customer satisfaction and ultimately transforms the service supply chain for competitive advantage.

Now is the time for senior decision makers to challenge all elements of the chain; without constant innovation and new thinking the industry will continue to be perceived as a laggard – a disparate set of fragmented, commoditised services that fail to meet the required standard.

 

 

 

With the current economic business pressure, reducing costs in the service management supply chain without compromising customer satisfaction is a challenge which must be faced head on. Glyn Dodd, Managing Director of Centrex Services explains why...

Facing the challenge...

Managing this balancing act requires business intelligence, which refers to the applications, tools, infrastructure and best practices which enable raw data to be transformed into significant information, and as such can be utilised to improve outdated processes in the service management arena.

Sadly, the current service supply chain model does not use business intelligence, but relies on a silo system, in which each area of the network, namely diagnostics and scheduling, parts, logistics, field service and repair, is run by a separate company.

Although the majority of companies working within the service supply chain use this silo model, there are major pitfalls to doing so which seem to be overlooked by the decision makers which strategically drive the agenda.

Quite simply, these are issues that cannot be overlooked in modern service management.

We know the service supply chain model has been working inefficiently, with separate entities running each sector of the network. Unsurprisingly, the communication between these areas is often found lacking, as an issue which the diagnostics team are unable to resolve is simply passed on to the next stage, when in reality it may not have been necessary to do so.

The current model invariably results in the deployment of field service engineers, regardless of the scale of the problem, due to a lack of business intelligence. The cost-effectiveness of such a system must therefore be scrutinised.

There are three key elements to the service supply chain which transcend each of the five silos. By studying the people, processes and data which unite to create the service supply chain, while simultaneously identifying the inefficiencies within these silos, each element can be challenged. Ultimately, this will culminate in a far more efficient network.

Correctly skilled representatives create cost-effectiveness in service management

The three key elements which are vital to the functionality of the service supply chain must be dissected to create the most effective model available. The first of these are the people who represent businesses in the service supply chain. This is the element which is easiest to directly challenge, as this can be controlled through efficient management of correctly skilled representatives.

Personally, I believe that the current silo model within the service supply chain is in fact impeding such change.

Communication is of paramount importance in all businesses, and this applies to those working in the service management, where we live and die by the level of customer service we are able to offer.

It is therefore unacceptable that the communication silos which the majority of businesses seem to rely upon result in a system where cross-silo communication is so poor. This is especially poignant when it is the customers who pay the price. It is hard to believe, when some businesses utilise an integrated service network which improves communication, that the silo structure continues.

A recent study by the Aberdeen Group shows service supply chain customers agree with this sentiment. 58 per cent of respondents state they want to see an improvement of diagnosis of triage at the initial call level. With further statistics showing there is a 24 per cent increase in first-time fix performance, from 62-86 per cent, when all calls are routed via triage, it is clear that such intelligent communication can increase service level agreements (SLA) and in turn, customer satisfaction levels.

Inefficient processes must be challenged

Customer satisfaction levels cannot be increased solely through challenging the service supply chain businesses representatives. Alongside this, processes must also be scrutinised to construct an efficient service in which business intelligence can be utilised.

With business needs evolving continuously, the processes which are currently commonplace within the network cannot be sustained in the long term.

Although this is a vital step in the evolution of the service supply chain, this message is not reaching the relevant decision makers.

Those decision-makers who strategically alter the function within the service supply chain do not necessarily have the knowledge required to alter the inefficient processes which currently plague the system.

With businesses worried about maintaining their profit margins in these difficult times, altering the processes they use can seem like an unnecessary burden, which is then wrongly linked to excess spending. If they used a leansource approach to integrate the service supply chain rather than tactically selecting separate companies, efficiency levels would increase, while spending decreases and complex issues are transformed into competitive advantage.

A study by research organisation McKinsey looking into the priorities in the global supply chain support this. 61 per cent of respondents cited reducing operating costs as a priority over the past three years, which is a task manageable through creating more efficient processes within the service supply chain. Once achieved, the percentage of SLA’s which are successfully achieved will increase without any additional pressure being applied on the deployed field service engineers.

Read the second part of this  feature here where Glyn outlines why Big Data isn’t the answer to solve all the service management industries issues, why failure is a good thing, and why true Business Intelligence is perhaps the key to unlocking a successful future for service management...