ARCHIVE FOR THE ‘big-data’ CATEGORY

If there is one industry that should be leveraging data in every way possible, it’s telecommunications. The telecommunications industry services billions of people each day, generating massive amounts of data. Though not many telecom companies are leveraging this data, the introduction of data science, machine learning, and artificial intelligence in this industry are inevitable.

A study by McKinsey, Telcos: The Untapped Promise of Big Data, based on a survey of leaders from 273 telecom organizations, found that most companies had not yet seriously leveraged the data at their disposal to increase profits. And only 30 per cent say they have already made investments in big data.

So while there is certainly debate within telecom companies about whether the return on investment is worthwhile, there is no doubt that data science, machine learning (ML), and artificial intelligence (AI) are inevitable when it comes to the industry’s future. Those that figure out how to leverage these techniques and technologies will thrive; those that don’t will be left behind.

By using data science, machine learning, and artificial intelligence strategies, telecommunication companies can improve four areas of their services.

The importance of data science, ML, and AI to the telecom industry will likely present itself in these four areas in particular, which this paper will take a look at individually:

 

1. Troubleshooting:

One of the major challenges for telecom providers is being able to guarantee quality service to subscribers. Analyzing call detail records (CDR) generated by subscribers at any given moment of the day is key to troubleshooting. However, CDRs are challenging to work with because the volume of data gets massive and unwieldy quickly. For example, the largest telecommunication companies can collect six billion CDRs per day.

With data science, machine learning (ML), and artificial intelligence (AI), companies can instantaneously parse through millions of CDRs in real-time, identify patterns, create scalable data visualizations, and predict future problems.

 

2. Fraud Detection: 

Verizon estimated in 2014 that fraud costs the telecom industry upwards of $4 billion a year. However, the faster that telecom companies analyze large amounts of data, the better off they are in identifying suspicious call patterns that correlate with fraudulent activity.

Cutting-edge ML and AI strategies like advanced anomaly detection make it much easier for telecommunication companies to identify “true party” fraud quickly.

 

3. Marketing:

The high churn rate in telecommunications, estimated at between 20-40% annually, is the greatest challenge for telecom companies. Telecommunication companies can use data to build better profiles of customers, figure out how to best win their loyalty (in the most scalable and automated way), and adequately allocate a marketing budget. With improved data architecture, they are able to harvest and store a greater diversity of data that provide insights into each customer such as demographics, location, devices used, the frequency of purchases, and usage patterns. By combining data from other sources like social media, they can have a stronger understanding of their customers.

Using machine learning gives a more accurate picture of which channels are most responsible for customer conversions for better ad buying as well.

 

4. Customer Experience: 

Telecommunication companies can enhance their services by analyzing the millions of customer complaints they get every year to figure out which types of improvements will have the greatest impact on customer satisfaction and thereby increase customer retention. They can also leverage data at a larger and more automated scale to gain insights into the performance of their technicians.

The more that telecommunication companies can analyze data on customer calls, the more they can begin to recognize which types of problems are most likely to lead to unwarranted “truck rolls” and put in place measures to prevent those calls. Given the number of calls and the depth of analysis required, this necessarily dictates a machine learning approach - more specifically, a deep learning approach. Because analyzing the calls themselves means dealing with lots of unstructured data, it’s the perfect place to expand into ML and deep learning for big gains.

 

The future of data in the telecom industry

Data science is already a big part of the telecommunications industry, and as big data tools become more available and sophisticated, data science, ML, and AI will all continue to grow in this space.

In the coming years, companies that succeed will be those that figure out how to best use the massive number of data points that are flowing both through their network and around it to reduce labor costs, develop better technology and, to better understand what the seven billion potential customers around the world want to do with their smartphones and computers.

To learn more, download the whitepaper White Paper: Top 4 Growth Areas of Machine Learning in Telecommunications.

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Manuel Grenacher, CEO, Coresystems discusses the big three technologies that are driving field service productivity to ever greater heights...

More than 85 percent of field service professionals say that the strategic use of technology is a key driver of overall productivity.

Moreover, within the next two years, 70 percent of organizations will reference customer satisfaction as a primary benefit obtained from implementing modern field service management technology, according to Gartner.

Unfortunately, many organizations are resisting from updating systems due to a need to accommodate legacy systems, and are therefore missing out on the increased workforce efficiency and productivity that updated systems deliver.

[quote float="left"]Unfortunately, many organizations are resisting from updating systems due to a need to accommodate legacy systems[/quote]Recent technological progressions have made a significant impact on many industries - and field service is no exception. Keep in mind, it’s often quite difficult for businesses to ‘bolt on’ additional technology to legacy systems, and many these should be considering new projects aimed at reducing cost and improving agility. So, what is there to gain?

Big Data and Data Analytics

Big data and analytics functionalities present a digestible, clear view of relevant data, which allow staff to make real-time decisions.

Each step is visible and transparent, and companies can start offering customers more proactive service, such as more finely tuned maintenance schedule alerts or alerts on peripherals that need replacement, consistently.

Cloud and Connectivity

Many field service applications are anchored in the cloud, and this pay-on-demand nature allows businesses to reduce spend on software and hardware costs. The cloud provides an accessible, shared environment where, for example, call centre staff can access records pulled from phone, email, IM and social media – leading to quicker and improved customer service.

Technicians can also stream video, capture photos, surf the internet and communicate with connected networks and wearable technologies.

Mobility

Mobility has an impressive impact on field service workers’ productivity and efficiency. Field service workers can access real-time data and information about customer issues, machine conditions and operating environments.

What’s more, field service organizations that implement mobility solutions improve their first-time fix rates, SLA compliance levels, cash flow and field engineer utilization levels.

[quote float="right"]Companies that still use paper-based systems often have difficulty efficiently scheduling resources and tracking employee performance. [/quote]Companies that still use paper-based systems often have difficulty efficiently scheduling resources and tracking employee performance.

It also slows down invoicing, and even affects the company culture. While upgrading can be costly, legacy systems tend to be more expensive to maintain on almost every level. Software licensing models have changed, as have the nature of service agreements, and the cloud offers a cost-effective means to have an entire IT setup without the need for huge premises.

Employees who can perform their jobs without the administrative or operational baggage are happier and more efficient.

This is a positive result for companies as it translates into a proactive state-of-mind (employees critically thinking about what more can they do), rather than a reactive one (how can it be done).

The above summaries illustrate why enterprises should switch to current FSM solutions, rather than remaining with their legacy systems. We look forward to seeing (and experiencing) the results of these and future technological innovations in the service industry.

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Manuel Grenacher, CEO, Coresystems discusses the big three technologies that are driving field service productivity to ever greater heights...

More than 85 percent of field service professionals say that the strategic use of technology is a key driver of overall productivity.

Moreover, within the next two years, 70 percent of organizations will reference customer satisfaction as a primary benefit obtained from implementing modern field service management technology, according to Gartner.

Unfortunately, many organizations are resisting from updating systems due to a need to accommodate legacy systems, and are therefore missing out on the increased workforce efficiency and productivity that updated systems deliver.

Unfortunately, many organizations are resisting from updating systems due to a need to accommodate legacy systemsRecent technological progressions have made a significant impact on many industries - and field service is no exception. Keep in mind, it’s often quite difficult for businesses to ‘bolt on’ additional technology to legacy systems, and many these should be considering new projects aimed at reducing cost and improving agility. So, what is there to gain?

Big Data and Data Analytics

Big data and analytics functionalities present a digestible, clear view of relevant data, which allow staff to make real-time decisions.

Each step is visible and transparent, and companies can start offering customers more proactive service, such as more finely tuned maintenance schedule alerts or alerts on peripherals that need replacement, consistently.

Cloud and Connectivity

Many field service applications are anchored in the cloud, and this pay-on-demand nature allows businesses to reduce spend on software and hardware costs. The cloud provides an accessible, shared environment where, for example, call centre staff can access records pulled from phone, email, IM and social media – leading to quicker and improved customer service.

Technicians can also stream video, capture photos, surf the internet and communicate with connected networks and wearable technologies.

Mobility

Mobility has an impressive impact on field service workers’ productivity and efficiency. Field service workers can access real-time data and information about customer issues, machine conditions and operating environments.

What’s more, field service organizations that implement mobility solutions improve their first-time fix rates, SLA compliance levels, cash flow and field engineer utilization levels.

Companies that still use paper-based systems often have difficulty efficiently scheduling resources and tracking employee performance. Companies that still use paper-based systems often have difficulty efficiently scheduling resources and tracking employee performance.

It also slows down invoicing, and even affects the company culture. While upgrading can be costly, legacy systems tend to be more expensive to maintain on almost every level. Software licensing models have changed, as have the nature of service agreements, and the cloud offers a cost-effective means to have an entire IT setup without the need for huge premises.

Employees who can perform their jobs without the administrative or operational baggage are happier and more efficient.

This is a positive result for companies as it translates into a proactive state-of-mind (employees critically thinking about what more can they do), rather than a reactive one (how can it be done).

The above summaries illustrate why enterprises should switch to current FSM solutions, rather than remaining with their legacy systems. We look forward to seeing (and experiencing) the results of these and future technological innovations in the service industry.

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In this latest of his Momentum Case Studies, Jan van Veen, co-founder of moreMomentum, interviews proven leaders across the globe who are successfully implementing the 4 Winning Habits to lead innovative, energised and engaged teams.

Here the case study examines a global leader serving the mining and oil & gas industries. Much of their recent success has come because they take services very seriously, being seen as a knowledge partner to help their customers improve operational efficiency, reduce risks and increase profitability.

The challenges faced

The company operates in traditionally slow-moving industries with large incumbent players and has become a leader by creating a strong service business which now generates a significant portion of total revenues, deepens customer relationships and creates resilience during economic downturns.

However, it has now spotted that a potentially significant disruptive threat could emerge from ‘big data’ and data analytics technologies, enabling new types of services. In the past, they would have considered taking five years to develop new equipment to be fast for the industry, but now understands that when it comes to future services, the speed of innovation needs to be higher.

Senior management is very aware that customers will move away if they see a better way of doing things, so the company must adapt if it is to stay a market leader.

The Strategy

The company has entered a period of change. To meet the disruptive threat ahead it must be visionary: to redesign itself and its culture so it can move much faster to keep ahead, enthusiastically embracing digital technologies with a focus on the end-to-end customer experience. In fact, it has to re-imagine its relationship with its customers so that rather than selling products, it provides ways to help its customers improve their operational processes and even their business models.

The company has demonstrated success from the 4 Winning Habits for Momentum so far, but now they need to take it to another level. Here we will show how they are using each of the 4 Winning Habits in the implementation of its strategy, creating Momentum for long-term sustainable success.

Direction – the common cause that everyone can get behind

The company management has recognised that, at a time of change, a compelling vision describing their role to help customers be more profitable is important to pull everyone together in the same direction. It is being spread throughout the company using both traditional townhall meetings, the company intranet as well as new digital social sharing methods such as Salesforce, Chatter and Yammer.

It helps operational messages fit into context if there is a beacon for people to move towards if there is a vision of what the company will look like in five yearVP of Service Marketing: “It helps operational messages fit into context if there is a beacon for people to move towards if there is a vision of what the company will look like in five years, what the industry will be like, what our company will be like. Otherwise, you have isolated initiatives”.

To push the new company direction, the company has been busy hiring a new CEO, CMO and CDO (Chief Digital Officer), all with experience in driving innovation. The Board understands the need for change, but the company can be a supertanker which takes time to turn. However, it is also aware that the competitive landscape can change quite quickly.

Dialogue – open discussion at and between all levels to encourage new ideas

Digital initiatives are at the centre of this company’s reinvention, so senior managers are heavily involved in steering new ideas, to get behind them and also to prevent them from breaking current business streams.

Across the company, at least 75% of targets and incentives are collective, leading to limited silo thinking between teams since they’re all in the same boat. Where there is friction, it’s usually because goals have been set too narrowly and issues fall between the silos. As a result, there is much less politics than might be expected in a large company and a higher level of transparency on performance.

This all helps create a culture of trust with less finger pointing and blame.

VP of Service Marketing: “Rather than looking for blame, people look at how to fix issues and learn from mistakes. It works well due to open dialogue. People don’t feel threatened and are not so eager to hide problems”.

Decision-making – local decision-making empowerment

The company has always had a decentralised structure. Different markets are quite autonomous and allowed to make their own local sales decisions, choosing which sales and marketing initiatives in which to participate based on market needs. This has been a successful approach so far, but staff at all levels and across the business will need to now be included in the decision making processes if the company is to continue adapting at a fast enough pace.

Discovery – Looking for new trends, opportunities and threats (internal and external)

The newly established Digital Office is a powerhouse of new ideas to add new technology to client relationships, including tools such as the Internet of Things devices and data analytics. It has been set up to operate somewhat separately from the mainstream company in order to be free from ‘business as usual’ thinking.

Companies, middle managers actually, are often quick to kill new products they see as a threat to the status quo and that’s why it’s good to have a Chief Digital Officer, tasked to create change and disruptionVP of Service Marketing: “Companies, middle managers actually, are often quick to kill new products they see as a threat to the status quo and that’s why it’s good to have a CDO, tasked to create change and disruption. We might all be comfortable with how things are today and not want to change it but I’m damn sure there’s someone out there who wants to kill our business model, and will be aided and abetted by our customers if they see a better way of doing things”.

The company has even started trying new approaches to R&D, such as hackathons.

VP of Service Marketing: “When I first heard of hackathons I have to admit I was sceptical, but from what I’ve seen they actually allow people to look at problems in new ways and get people involved who would never normally be involved, and maybe redesign the way of doing things. And for big companies, that’s what we have to do, because our competitors don’t worry about the fact we have an established base and products, they’re actually thinking ‘How can I change the industry to make money? They don’t care if it destroys our business’”.

The company has also started involving customers in its processes, for example with surveys. They keep the company honest about its achievements, drive change and allow them to spot systemic issues. The voice of the customer can be very powerful.

Next Steps:

Change is an ongoing process at this manufacturing company, but they recognise the need to accelerate the pace of change to a new level and then make it ‘business as usual’ – a revolution in the mining sector!

The 4 Winning Habits for Momentum will be key. They are working on a clearer picture of the future state of the company, to give stronger Direction to the business units and local staff for local Decisionmaking.

Dialogue with staff will improve, so personal objectives will be better aligned to the strategy and not be so focussed on purely financial targets, but also learning, collaboration and Discovery of new opportunities. If they can do all this, then they will truly be creating a revolution in mining.

Outcomes

The huge growth in the service business at the company has brought enormous benefits for their customers, made the company a trusted ‘knowledge partner’ and expertly positioned them to forge ahead into digital transformation.

People buy from them now because of the advice they give and their approach to improving their customers’ businesses. For instance, mining equipment runs 24/7/365 and downtime can cost many €100,000s per day so, they have redesigned parts, consumables and field services to reduce the time it takes to change them, so reducing costs for their customers.

Energy efficiency has been another focus, as has the charging model – customers pay for service contracts by the ton, so they know their costs in advance. These changes epitomise the innovations that the company has achieved, and there are many more on the way.

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Steve Wellen, CEO of FieldAware outlines the evolution of analytics and how field service organisations are reaping the benefits...

Research into field service management consistently shows that when respondents are asked what they are planning to invest in or are looking to implement, analytic tools, more and more, are being highlighted above other functionality.

No great surprise given that today’s field service operations can rely on many different systems and solutions, all of which generate huge amounts of data. 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 into something actionable, many businesses just don’t benefit. So, where are we in the evolution of field service analytics and how are field service organisations making their data work smarter, not harder?

Data, data everywhere

Over the past decade, field service organisations have become overwhelmed by the increasing information coming in from multiple sources and in various formats. As field service has become more and more integrated with other business solutions, (including accounting, ERP and CRM), organising this data becomes such a complex task that it may simply end up being unused. Managers and team members may then revert to relying on what they used to do, or make decisions based on hunches to run the business, rather than use the business intelligence they need.

Business leaders understand the data they have cannot be ignored. The major challenge they face, however, is how to sift through the data and link it together in a meaningful way. Data is often from disparate systems, but needs to be collated and reported in an easily understood way, to reveal the valuable insights that are needed for day-to-day performance and longer-term business strategy.

A brief history of field service analytics

The early adopters of field service analytics have seen a transformation of the solutions available, and we have witnessed this evolution first-hand.

We have seen our customers move from their initial requirements of basic business reporting, through to needing a comprehensive business intelligence solution.

Early on, it was often a snapshot of what had happened that was required, for example, how many jobs had been completed. It soon became apparent that organisations had different performance indicators to manage, and individuals needed metrics specific to roles. A layer of sophistication was needed, with custom reports where customers could then dive deeper to retrieve further information.

They could explore the types of jobs that were being completed, monitor individual performance or compare geographies.

Using data to make business decisions then drove the need for further information and queries could be set up to examine any problems or if any differences were apparent, for example, time taken on jobs, cost variations or first-time fix rates.

In addition, alerts could be set to enable better management of SLAs by flagging potential issues such as at-risk jobs.

A continual journey

All useful perspective, but for those using analytics for the first time, there is now no reason to stop at what could simply be seen to be mimicking what paper-based processes capture on the ‘what’ and the ‘where’.

Leap forward and it is the ‘why’ within analytics capabilities that truly enhances the value. After generating basic reports, managers did not always have time, the knowledge or experience to translate the results into meaningful action.

Advances in analytics provide businesses with the ability to view data after it has been configured and cross-referenced using statistical modelling.

Better decisions can be made more easily as they are based on accurate, analysed information, and better decision-making means a more effective, efficient operation.

The future’s bright, the future is optimised 

Today, field service leaders realise they need analytics that enables them to make more informed decisions to continue to grow their business. Just having data is not enough – they need the ability to use the data to align service teams to work together towards meeting company goals and managing customer expectations. Organisations now demand analytics solutions that migrate from reactive to predictive operations.

They need to move from insight to action faster than ever before with business insights from finance, CRM, ERP, FSM solutions that they depend upon for everyday operations.

They need better teamwork and collaboration so that they can quickly arrive at consensus, act and capitalise on opportunities.

These include discovering hidden opportunities and finding the next big opportunity in the business intelligence.

The business is optimised not only through these day-to-day enhancements, but the operational insights are consistently fed back to business and management, enabling a real-time feedback loop ensuring that key metrics improve continuously - creating a cycle of continual improvement for the field service organisation and improved operations.

For more information on using analytics for your field service optimisation and how you can reap the benefits, visit www.fieldaware.com 

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Sara Mueller, Field Service Portfolio Director, WBR looks at how the rapid evolution of service excellence is a double-edged sword of opportunity and challenges...

I’ve been a conference producer for Worldwide Business Research (WBR) for over ten years, but most of my friends still don’t understand what that means or how I spend my days.

My mom finally gets it though.

I told her that I conduct market research by talking to service executives to learn what their biggest challenges and initiatives are. I also talk to their vendors and solution providers to understand what innovative technologies and services they provide to solve these challenges. Then I write a conference program and recruit thought leaders to speak about these subjects to bring the industry together and help advance service organizations.

Throw in fun parties, innovative formats that get people talking, and beautiful venues where people enjoy building business relationships, and you’ve got the essence of a WBR Field Service event!

Whether or not you grasp the function of my job, I’m sure you can relate to the four major trends I see impacting field service over the next few years.

They are:

1. Driving service innovation using technological advancements like augmented reality (AR), artificial intelligence (AI) and big data analysis.
2. Doing more with less by determining the quickest, most efficient way to automate field service operations.
3. Transitioning to a customer success organization that sells customer business outcomes.
4. Aligning talent recruitment and training with the needs of an evolved service/support business model.

Driving Service Innovation Using Technological Advancements Like Augmented Reality (AR), Artificial Intelligence (AI) And Big Data Analysis.

Augmented reality pilot programs are well underway and starting to reveal the best ways to use this technology for remote-assisted repair and troubleshooting.

Whether hands-free wearables or tablet devices are the hardware of choice, there are numerous software options to choose from to execute an AR strategy.Whether hands-free wearables or tablet devices are the hardware of choice, there are numerous software options to choose from to execute an AR strategy.

It’s clear that AR is not just a buzz word, but a concrete field service tool that’s here to stay and will be implemented by the majority of service organizations within the next three years.

Artificial intelligence, machine learning, and robotization are continually being explored in order to understand where technology can replace unnecessary human work, increase automation, and drive productivity. Bots are being used to get information to field service teams quickly and for memory nudging.

Virtual assistants or virtual customer agents are starting to be the norm. Innovative service organizations are looking to the further future to use machine learning to building autonomous services or self-healing, self-repairing products.

And, finally, data: Since devices became connected and IoT found its way into more and more products, we’ve never had more data on hand. Companies are spending their resources to ensure the data that is being gathered is clean, relevant, and easy to interpret.

It’s being used to measure product quality and gain performance insights from the field. Data visualization and analytics tools are helping to validate and adapt maintenance schedules, customer experience, and revenue generation.

Whether you classify this information as “big data” or not, it’s clear the data you now have available from connected products is essential for making “big” important business decisions and learning how you can better serve your customers.

Doing More With Less By Determining The Quickest, Most Efficient Way To Automate Field Service Operations.

Service executives are exploring the best tools for service automation in order to get more work done without increasing headcount. The speed of change and ease of implementation are key factors going into technology investment and process decisions.

Change management has never been more important. And lean, six sigma, and kaizen are being used to look beyond manufacturing to service operations to reduce complexity and streamline processes.

Artificial intelligence, as mentioned above, comes into play as a leading tool to increase automation.

Transitioning To A Customer Success Organization That Sells Business Outcomes

Service organizations are continuing their business model evolution away from selling products towards selling results, up-time or customer business outcomes.

Part of this entire company cultural shift has led to the development of “customer success” organizations.

Rather than calling the customer-facing side of the organization customer service, or support, or technical support, companies are using the name “success” to describe how they go above and beyond for the customers, owning responsibility for the success of their customer’s business.

Customer success takes into account being a trusted advisor to customers to ensure they are leveraging all the capabilities of your product offeringCustomer success takes into account being a trusted advisor to customers to ensure they are leveraging all the capabilities of your product offering. It, of course, brings together service and call centre support, as well as sales.

Customer success is sometimes its own department, or it can be a combination of sales and service. Of key importance is to understand how all parts of the organization that contribute to customer success can have aligned goals and incentives.

Service organizations are exploring customer engagement software and the best ways to measure the customer experience throughout all points of contact.

Aligning Talent Recruitment And Training With The Needs Of An Evolved Service And Support Business Model.

With a shift to more cloud and software-based services, the required skill set of technicians is changing.

Companies need to recruit for a new skill set while still trying to fill gaps in their team caused by baby boomer retirement, a lack of apprentices after apprenticeship programs were discontinued during the economic downturn, and with the positive challenge of business and customer growth.

Some companies are choosing to bring in computer science software folks, then train them on the hardware piece.

Some are using veteran career-placement programs to find qualified, screened, and trained talent.

Given field service and support is highly influenced by technology, its clear the industry, its solutions, and your customer needs will continue changing rapidly. On top of this, the current workforce needs to be trained to service products that are supported by more automation and digitization.

Even recruiting for women is taking a higher priority at many organizations, since women make up half of the workforce, but generally a much smaller percentage of the field service industry. Diversity and inclusion efforts are being carried out with the knowing that aligning goals, incentives, and measurement against these efforts is imperative to their success.

Given field service and support is highly influenced by technology, its clear the industry, its solutions, and your customer needs will continue changing rapidly.

This is a good thing as you’ve never had more ways to be able to move the needle of the service you provide your customers.

Plus it keeps things interesting for someone like me (a conference producer for your industry)!

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UK based non-profit knowledge sharing group the Service Community which Field Service News is proud to partner with has recently announced one of the most diverse events they have organised in the last couple of years.

The next Service Community event will be hosted by the Cambridge Service Alliance at the Institute for Manufacturing (a division of the University of Cambridge’s Department of Engineering) on the 19th April 2018.

Being at one of the world’s leading service research organisations means that we hope to mix the very best in thought leadership, with practical hands-on experiences of transforming service businesses. Each discussion will be approximately 40 mins enabling you to discuss real issues with real people.  We are also very lucky to have a The Digital Manufacturing Tour, where you will have a chance to hear about the research initiatives that the IfM are undertaking on digitalisation in manufacturing.

In addition to a speaker from the CSA, we have leaders from MARS, Oracle and Fujifilm joining us to discuss and share experiences on how they have tackled some of their key service business challenges.

How to register

You can reserve your place by sending an email to info@service-community.uk. We will then contact you to confirm registration and will send out the joining instructions nearer to the event.

Please feel free to forward this information to colleagues who you think would be interested. We look forward to seeing you in April

Agenda for the 19th April 2018

12.00 - 13.00: Meet at the Institute of Manufacturing at Cambridge University
13.00: Nick Frank: Welcome

The Impact of Big Data and Machine Learning technologies on developing Customer Experience in manufacturing companies Dr Mohamed Zaki: Deputy Director of the Cambridge Service Alliance will introduce the work the Cambridge Service Alliance does and share recent research he has undertaken into Customer Experience development

Leading Service to a Trusted Advisor Culture:  Ashley Weller: UK Service Director at Mars drinks will share his own journey in driving sustainable cultural change

The Digital Manufacturing Tour

Coffee & Networking break

Real World Challenges of implementing Augmented Reality in Field Service Adil Kabel: Technical Support Manager, at Fuji Film responsible for EMEA 2nd line support for Wide Format Digital Printers will share his experiences of running two pilot projects in the Field Service organisation looking at 'glasses' and handheld augmented reality apps

Benefits and Challenges of Self Service models - Stephen Darkes Snr Process Analyst: Global Systems Remote Support at Oracle: Steve will give us some insights into the different Self-Service support models that Oracle have introduced to enhance customer satisfaction and make their business more cost-effective.  He will cover a range of models, from the use of community forums for Diagnosis and Resolution to the development of Customer Replaceable Units for hardware.  He will share his experiences of the range of benefits that self-service brings, as well as the challenges of implementation.  Many businesses can make their customer support more effective through self-service business models.

17.00 Networking Drinks

Reserve your place by sending an email to info@service-community.uk. We will then contact you to confirm registration and will send out the joining instructions nearer to the event.

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Speaking at the IRTE Conference, telematics and technology company Microlise has said fleets will harness the power of Big Data in 2018 thanks to advanced data analysis techniques and growing demand for the capabilities they enable.

This is according to Matthew Hague, Microlise Executive Director – Product Strategy, who recently addressed an audience at one of the UK’s premier conferences for fleet managers and operators.

“We have spent a phenomenal amount time and resource over the last two years, running a number of successful projects involving government funding,” said Hague. “Big Data is a bit of a buzz word, but it is one of those things that will really drive our product offering forward in the coming months and years.”

Hague said that Microlise captures well over seven billion miles worth of road data each year, but working with such large data sets and harnessing its power presents a challenge. “How to glean useful information from an ocean of data is a challenge, but new technologies and techniques are enabling us to scale up and process large data sets in a quick and agile way.”

 

In 2014, with partner the University of Nottingham, Microlise was awarded funding of £359,000 from the UK’s innovation agency, the Technology Strategy Board (now Innovate UK). The objective of the “Value Enhancement for Data from Assets & Transactions” (VEDAT) project was to achieve customer and market value from the high volumes of complex data generated in real-time through telematics technology.

“We completed our work with the University of Nottingham last year and will soon be in a position to productise new and innovative tools and solutions that will create new value propositions within the transport and logistics sector,” added Hague.

According to Microlise, the first uses of this new big data resource will be predictive analytics for vehicle health, improving hazard awareness and briefing drivers. Though Hague said there are many use cases which will be developed in due course including the ability to benchmark performance against the industry or sector a fleet operates in.

“By using the anonymous data we capture every day then overlaying the government’s annualised accident black spot data, and crime data, we can very accurately predict risk while taking time of day and weather conditions into account,” said Hague.

According to Hague, it will soon be possible to rank routes according to risk, and even to alert drivers to specific risks along their route as they approach them ensuring they are prepared.

 

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We’re all in the service business now states ClickSoftware’s CMO, Claudine Bianchi before explaining how and why meaningful interpretation of data will be the key to defining a new level of customer trust...

Do you remember the last truly exceptional meal you ate at a restaurant?

If it stands out in your memory, it probably wasn’t solely because of the perfectly seared steak or sublime glass of wine. Your server was not just polite, but engaged in creating a special dining experience just for you.

You might not remember the taste of every bite, but you remember exactly how you felt throughout the meal. You’re still telling everyone to try that restaurant when they travel to the same city. Now, can you make your own customers this happy?

We are all in the service business now. And before you shrug off that idea as a meaningless truism, remember that every business transaction with a customer begins a potentially lifelong relationship.

 

Just as a rude server can ruin a delicious meal and keep you from ever returning to a restaurant, every product you sell, or service you provide, creates a contract of perceived customer expectations.

Even if someone else is responsible for a service visit, guess who will be named by a customer in a frustrated social media post. Hint: it’s not the nameless service contractor.

Research has shown customer experience is directly tied to profitability, a primary concern for all businesses. And now, big data can help.

Can data solve your service problem?

The standard bearers for great customer experiences are increasingly disruptive companies and applications that ostensibly don’t have a service component at all. It’s unlikely customers ever have human to human (H2H) interaction with anyone at Netflix or Amazon, but these companies have turned customer data into incredible recommendation engines that keep these customers coming back and spending more.

From being able to supply more personalisation through what you learn about customers, to understanding how product usage changes throughout its lifecycle, unexpected insights can completely transform the future of your business—if you’re willing to follow the data.

To build the right foundation for data-driven customer service, identify existing sources and inputs and look for ways they can be augmented with additional sources; invest in a data scientist or outside resources to conduct a meaningful analysis; and set appropriate KPIs and reporting practices that enable a continuous review of data, trends, and what actions your business can take.

 

It’s time to move beyond what’s breaking and needs fixing or what’s about to break. Rich customer data can tell you a more interesting story about how customers feel about your business.

Defining a new level of customer trust 

Data is the key to truly knowing your customers.

That knowledge is power, and with great power, comes great responsibility. As more businesses rely on data to provide better customer experiences, they’re also taking on the burden of capturing, storing, and managing that data responsibly.

While most technology consumers understand their data is interacting with various services whenever they use a website or application, few know just how complex and sophisticated these tools and algorithms are. It’s been called the “trust web”—where each party shares data and permissions granted by the core user in a way that yields some benefit.

Beyond earning customer trust by delivering on the promise of reliable products and consistent service, you must also make them feel confident that the voluminous data collected is well protected, mostly anonymous, and safeguarded from misuse.

Customer experience and trust can be fodder or poison for a brand. Ask your marketing team to help you make sense of consumer behaviour and better communicate the benefits of your enhanced offerings and collected data.

Service quality will save the business 

We are living in an experience economy, with customers craving more utility and meaning from their purchases. Competing on price alone should be a last resort, but brand differentiation is an increasingly critical competitive advantage.

 

By focusing on service and experience as integral to a successful product and sale, businesses can still compete for a sophisticated and demanding customer base.

The customer experience advantage might begin with the point of sale, but it can earn a lifetime of loyalty. Let customer data light the way to an intimate understanding of their relationship with your products or services, and then deliver experiences your competition won’t be able to replicate.

 

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