Marketing automation solutions market to reach $6.36 billion by 2025, finds Frost & Sullivan
ARCHIVE FOR THE ‘data’ CATEGORY
Sep 16, 2019 • News • Automation • Data • frost & sullivan • Marketing Services • report
Marketing automation solutions market to reach $6.36 billion by 2025, finds Frost & Sullivan
Sep 09, 2019 • Fleet Technology • Data • fleet • Fleet Operations • TomTom Telematics
Fleet managers are set to gain valuable insights into how innovative data management can help them future-proof their businesses at TomTom Telematics’ Let’s Explore 2019 on September 12 in Surrey, UK.
Fleet managers are set to gain valuable insights into how innovative data management can help them future-proof their businesses at TomTom Telematics’ Let’s Explore 2019 on September 12 in Surrey, UK.
May 20, 2019 • Features • Data • Nick Frank • digital disruption • Digitalization • Servitization • Si2Partners • Service People Matter
In a world of digitalisation, servitization and a data driven economy, the fulcrum at the heart of your service delivery needs to be digital people writes Nick Frank...
In a world of digitalisation, servitization and a data driven economy, the fulcrum at the heart of your service delivery needs to be digital people writes Nick Frank...
Over the last three years there has been a huge emphasis on the need to invest in technology to stay ahead and be the disruptor.
As many leaders struggle to move towards the enticing digital visions being painted, we have seen a more nuanced approach emerge. We perceive that leaders are switching their emphasis back to creating a solution focused culture where people have the imagination and customer focus to create and deliver new value offered by digital technologies.
In the coming years we believe we will see companies focusing on three areas in the growth journey:
1. Digital Servitization: the notion of digitising the back-office processes and enabling data capture in the product infrastructure to enable new value through services
2. Data Analytics capabilities: Turning the data into insights through being able to turn Business Problems and opportunities into Data Solutions that leverage their company unique knowledge.
3. Trusted Advisor Mindset: Having the trust of customers and the communication skills to turn intangible data into valuable actions that drive growth.
Digital Servitization
Now more than at any other time, businesses are focused on how to use shifts in technology to reduce costs and find new value propositions. But understanding how it all fits has proven more elusive to business leaders. Those that are making most progress have broken the Digital Transformation process into more meaningful chunks. They typically have two areas of focus:
1. Installed-Base Digitalisation:
Designing the products and supporting operational infrastructures that generate data, so that it can be collected, analysed and then monetized through service-based business models. Generally, investments have been made in:
The tools we use to manage our business back office which sustain and improve margins /profits. Examples might be Service Management solutions, CRM and ERP. Generally, there are two aspects to consider in terms of system and process development:
Only when companies have reached a level of maturity in both Back-Office Digitalisation and Installed-Base Digitalisation, are they ready to, explore new business models such outcome based or subscription based services.
Data Analytics Capability - Business problem before Data Solution
The use of sophisticated Data Analytics technologies to gain insights into processes and product performance is slowly becoming part of management thinking. But again, progress is slow as many leaders are intimidated by the jargon and lack of understanding of the business case. We have found successful companies have followed these three steps:
1. Articulate the business problem to solve and why (Value)
Before investing in digital technologies, the most successful companies have a clear idea of the business problem to solve and the value it can potentially bring. Often there is some experimentation/prototyping that may occur to build knowledge of the business problem and confirm value. They look wider than their own business processes or customers processes, the hand-offs between the different stakeholders in their value chain. Often, they will use ecosystem analysis, the value iceberg principal or points-of-selling approaches to identify value opportunities.
2. Define the Data Problem
The next challenge is how to turn the business problem into a business data hypothesis. This would describe an expected or speculated relationship that we hope to determine through the analysis of data. For example, the hypothesis for a predictive maintenance solution might be: ‘We can identify the failure patterns for hydraulic system as well as general machine performance using pressure, oil contamination, temperature and humidity data from the PLC, such that we can predict failures and recommend corrective actions.
Why is this important? Data Scientists cannot tell you patterns that interest you without knowing the area of interest! Hence converting the business problem into a hypothesis is a key part of the process and applying the scientific method which is question led and iterative. But the hypothesis does not have to be correct.
It is very likely that it will change as more knowledge is gained about the data being analysed or definition of the business problem evolves. One must expect a certain amount of iteration from business problem to data problem as our knowledge expands, and this in turn helps deliver optimal business value. It is critical to be very clear about the business problem and the data required to understand it.
3. Pilot before Scale Up
Now that the data problem is defined, managers can understand where they may have organisational and infrastructure gaps for their project, and from this be able to identify the first steps of their roadmap to a data solution. It is important that these early steps include a pilot of the solution. The goal is to quickly understand if our solution is likely to be successful, and the actions to be taken to scale up across the organization.
Often in business we take it for granted that we have all the capabilities in house. However, in today’s world, where the use of technology is rapidly evolving, it is very easy to become ‘out of date’ from both a business mindset as well as technology capability.
To help leaders understand the strengths and weaknesses, Si2 have worked with The Data Analysis Bureau to develop a short 10 minute maturity self-assessment which will you help you identify your strengths and weaknesses as you move from Business Problem to Data Solution.
There are just 10 questions and you will get personalised feedback as to your situation and what you can do. Use this link to access the assessment.
Trusted Advisor Mindset
The biggest enabler of the ‘digital’ ideas we have discussed is not so much the technology but the mindset of your people. The Trusted Advisor mindset is more than just being able to talk to the customer, solve problems and sell ideas. It is a whole attitude where we focus on solutions, continuously moving customers towards their goals whether they be internal or external.
This is the type of mindset that has leapt onto the potential offered by digitisation, long before it entered the language of today’s business. Trusted Advisors have clarity on their role and an understanding of how to talk to customers so that they achieve a WIN, WIN, WIN:
• A Win for the customer so that every conversation they have moves them closer to their goal
• A Win for the company to develop customer loyalty and profitability
• A Win for themselves so they feel great about their job
What makes a Trusted Advisor different? At the very minimum they are good customer problem solvers. What starts to differentiate them from others is their ability to have meaningful conversations with customers that always seem to move towards solutions. They are able to provide options together with the benefits for various decision the customer might make.
They normally have a high level of personal maturity in that they do not try to tell customers what to THINK. Instead they influence them by what they SAY and DO, and because they consistently deliver, customers trust their advice. As the notion of a Trusted Advisor is widely used across sales & service, the job context is extremely important.
For example, in field service and technical support the Trusted Advisor role is more about providing options than closing deals. Whereas in sales it is more about how we build rapport and credibility within a consultative selling process.
Clearly understanding the context in which the Trusted Advisor mindset is being developed is vitally important to successful adoption. Service leaders who want to improve how their teams communicate with customers, might consider having the following conversations with their own people:
• Clarify what you mean by a Trusted Advisor and the role they play in your organisation. In particular the customer needs and what makes them successful, as well as your companies business goals. This is where distinguishing the difference between selling and advising will be absolutely critical to your success;
• Develop a Mindset where every conversation we have with customers moves them a step closer to their goal. It may not be the complete solution, but it is a step in the right direction no matter how bad and uncomfortable the situation is. This very basic philosophy is key to training your people to deal with conflict, as well encourage them to have dynamic and collaborative relationships through solution orientated language;
• Provide Tools and methods that allow us to actively listen, to talk more effectively, to manage conflict and resolve difficult customer situations. These tools are critical to helping us to prepare ourselves to be a Trusted Advisor in what can be challenging and stressful situations;
• Practice in real-life scenarios with your team to see how they react under stress. We are constantly amazed at how confident many service people are about talking to customers in a training environment, yet it all falls apart in a customer situation.
• Refresh: Developing how your team interacts with customers is not a one-off event and needs to be constantly mentored and coached.
Digital People Increasingly we anticipate that Service organisations will take a more balanced approach to Digital. Yes, they will invest in the technology, but they will do so with a clearer idea of the value they are trying to capture. They will understand that the key to new business models will be to have automated their back-office processes as well as how to capture and action data from the product infrastructure. They will increasingly focus on developing a solution orientated innovative culture which is the key to leveraging the opportunities offered by new technologies and paradigms of thinking.
Nick Frank is Managing Partner at Si2 Partners. If you would like to talk more about any of the topics discussed in this article you can contact him at nick.frank@si2partners.com.
Over the last three years there has been a huge emphasis on the need to invest in technology to stay ahead and be the disruptor.
As many leaders struggle to move towards the enticing digital visions being painted, we have seen a more nuanced approach emerge. We perceive that leaders are switching their emphasis back to creating a solution focused culture where people have the imagination and customer focus to create and deliver new value offered by digital technologies.
In the coming years we believe we will see companies focusing on three areas in the growth journey:
1. Digital Servitization: the notion of digitising the back-office processes and enabling data capture in the product infrastructure to enable new value through services
2. Data Analytics capabilities: Turning the data into insights through being able to turn Business Problems and opportunities into Data Solutions that leverage their company unique knowledge.
3. Trusted Advisor Mindset: Having the trust of customers and the communication skills to turn intangible data into valuable actions that drive growth.
Digital Servitization
Now more than at any other time, businesses are focused on how to use shifts in technology to reduce costs and find new value propositions. But understanding how it all fits has proven more elusive to business leaders. Those that are making most progress have broken the Digital Transformation process into more meaningful chunks. They typically have two areas of focus:
1. Installed-Base Digitalisation:
Designing the products and supporting operational infrastructures that generate data, so that it can be collected, analysed and then monetized through service-based business models. Generally, investments have been made in:
- Technology that enhances the product and company infrastructure to enable Digital Support, such as remote data collection, diagnostics or predictive maintenance.
- Capabilities and technologies in the organisation that enables Data Analytics, such machine learning, visual analytics and business intelligence technologies.
2. Back-Office Digitalisation:
The tools we use to manage our business back office which sustain and improve margins /profits. Examples might be Service Management solutions, CRM and ERP. Generally, there are two aspects to consider in terms of system and process development:
- Technology that enhances the product and company infrastructure to enable Digital Support, such as remote data collection, diagnostics or predictive maintenance.
- Capabilities and technologies in the organisation that enables Data Analytics, such machine learning, visual analytics and business intelligence technologies.
Only when companies have reached a level of maturity in both Back-Office Digitalisation and Installed-Base Digitalisation, are they ready to, explore new business models such outcome based or subscription based services.
Data Analytics Capability - Business problem before Data Solution
The use of sophisticated Data Analytics technologies to gain insights into processes and product performance is slowly becoming part of management thinking. But again, progress is slow as many leaders are intimidated by the jargon and lack of understanding of the business case. We have found successful companies have followed these three steps:
1. Articulate the business problem to solve and why (Value)
Before investing in digital technologies, the most successful companies have a clear idea of the business problem to solve and the value it can potentially bring. Often there is some experimentation/prototyping that may occur to build knowledge of the business problem and confirm value. They look wider than their own business processes or customers processes, the hand-offs between the different stakeholders in their value chain. Often, they will use ecosystem analysis, the value iceberg principal or points-of-selling approaches to identify value opportunities.
2. Define the Data Problem
The next challenge is how to turn the business problem into a business data hypothesis. This would describe an expected or speculated relationship that we hope to determine through the analysis of data. For example, the hypothesis for a predictive maintenance solution might be: ‘We can identify the failure patterns for hydraulic system as well as general machine performance using pressure, oil contamination, temperature and humidity data from the PLC, such that we can predict failures and recommend corrective actions.
Why is this important? Data Scientists cannot tell you patterns that interest you without knowing the area of interest! Hence converting the business problem into a hypothesis is a key part of the process and applying the scientific method which is question led and iterative. But the hypothesis does not have to be correct.
It is very likely that it will change as more knowledge is gained about the data being analysed or definition of the business problem evolves. One must expect a certain amount of iteration from business problem to data problem as our knowledge expands, and this in turn helps deliver optimal business value. It is critical to be very clear about the business problem and the data required to understand it.
3. Pilot before Scale Up
Now that the data problem is defined, managers can understand where they may have organisational and infrastructure gaps for their project, and from this be able to identify the first steps of their roadmap to a data solution. It is important that these early steps include a pilot of the solution. The goal is to quickly understand if our solution is likely to be successful, and the actions to be taken to scale up across the organization.
"Over the last three years there has been a huge emphasis on the need to invest in technology to stay ahead..."
Often in business we take it for granted that we have all the capabilities in house. However, in today’s world, where the use of technology is rapidly evolving, it is very easy to become ‘out of date’ from both a business mindset as well as technology capability.
To help leaders understand the strengths and weaknesses, Si2 have worked with The Data Analysis Bureau to develop a short 10 minute maturity self-assessment which will you help you identify your strengths and weaknesses as you move from Business Problem to Data Solution.
There are just 10 questions and you will get personalised feedback as to your situation and what you can do. Use this link to access the assessment.
Trusted Advisor Mindset
The biggest enabler of the ‘digital’ ideas we have discussed is not so much the technology but the mindset of your people. The Trusted Advisor mindset is more than just being able to talk to the customer, solve problems and sell ideas. It is a whole attitude where we focus on solutions, continuously moving customers towards their goals whether they be internal or external.
This is the type of mindset that has leapt onto the potential offered by digitisation, long before it entered the language of today’s business. Trusted Advisors have clarity on their role and an understanding of how to talk to customers so that they achieve a WIN, WIN, WIN:
• A Win for the customer so that every conversation they have moves them closer to their goal
• A Win for the company to develop customer loyalty and profitability
• A Win for themselves so they feel great about their job
What makes a Trusted Advisor different? At the very minimum they are good customer problem solvers. What starts to differentiate them from others is their ability to have meaningful conversations with customers that always seem to move towards solutions. They are able to provide options together with the benefits for various decision the customer might make.
They normally have a high level of personal maturity in that they do not try to tell customers what to THINK. Instead they influence them by what they SAY and DO, and because they consistently deliver, customers trust their advice. As the notion of a Trusted Advisor is widely used across sales & service, the job context is extremely important.
For example, in field service and technical support the Trusted Advisor role is more about providing options than closing deals. Whereas in sales it is more about how we build rapport and credibility within a consultative selling process.
Clearly understanding the context in which the Trusted Advisor mindset is being developed is vitally important to successful adoption. Service leaders who want to improve how their teams communicate with customers, might consider having the following conversations with their own people:
• Clarify what you mean by a Trusted Advisor and the role they play in your organisation. In particular the customer needs and what makes them successful, as well as your companies business goals. This is where distinguishing the difference between selling and advising will be absolutely critical to your success;
• Develop a Mindset where every conversation we have with customers moves them a step closer to their goal. It may not be the complete solution, but it is a step in the right direction no matter how bad and uncomfortable the situation is. This very basic philosophy is key to training your people to deal with conflict, as well encourage them to have dynamic and collaborative relationships through solution orientated language;
• Provide Tools and methods that allow us to actively listen, to talk more effectively, to manage conflict and resolve difficult customer situations. These tools are critical to helping us to prepare ourselves to be a Trusted Advisor in what can be challenging and stressful situations;
• Practice in real-life scenarios with your team to see how they react under stress. We are constantly amazed at how confident many service people are about talking to customers in a training environment, yet it all falls apart in a customer situation.
• Refresh: Developing how your team interacts with customers is not a one-off event and needs to be constantly mentored and coached.
Digital People Increasingly we anticipate that Service organisations will take a more balanced approach to Digital. Yes, they will invest in the technology, but they will do so with a clearer idea of the value they are trying to capture. They will understand that the key to new business models will be to have automated their back-office processes as well as how to capture and action data from the product infrastructure. They will increasingly focus on developing a solution orientated innovative culture which is the key to leveraging the opportunities offered by new technologies and paradigms of thinking.
Nick Frank is Managing Partner at Si2 Partners. If you would like to talk more about any of the topics discussed in this article you can contact him at nick.frank@si2partners.com.
Apr 14, 2019 • Features • Management • Data • Jan Van Veen • Monetizing Service • moreMomentum • Products as a Service • Customer Focus
Jan Van Veen, founder of MoreMomentum continues his latest exclusive Field Service News series on how companies can monetise their services and data by exploring how companies can remove the obstacles that are stopping them build momentum with...
Jan Van Veen, founder of MoreMomentum continues his latest exclusive Field Service News series on how companies can monetise their services and data by exploring how companies can remove the obstacles that are stopping them build momentum with their clients.
Central question
Many manufacturers experience pressure on growth, revenue and margins. Their products and services are being commoditised. Competition from lower cost alternatives are arising. On the other hand, there are huge opportunities with new technologies, value propositions and business models.
One of the important trends is that value propositions and offerings become more data-driven and more service-oriented, which go hand in hand.
Besides predictive maintenance, most of the value from data is related to how clients use the equipment or products and to their operations and processes. Helping clients improve on this by nature is a service.
However, many manufacturers are product-driven businesses which do not fully appreciate the value that (advanced) services have for their customers and their own business.
So, one of the central questions is: How to Monetise Services and Data to Grow in a Disruptive World? The capability to monetising service and data is mission critical for sustainable performance and existence of manufacturers.
In a series of articles, we cover four critical steps that make the difference between success and failure in monetising services and data:
• Solve bigger customer problems;
• Articulate the value;
• Build momentum with clients to adopt;
• Build internal momentum.
Developing new data-driven solutions and services is all about extending the existing business model, which leads to different challenges than many other initiatives and programs in a business. Recognising this in advance will help understand the challenges and best strategies.
In the previous articles of this series, I have described critical success factors for monetising service and data, such as Solve Bigger Problems,Better Articulate Value and Remove Obstacles for Clients to Adopt. In the end, this all has to be done by people and teams in your organization.
Common mistakes
In this article I will describe common mistakes that many companies make, which holds them back in having fluid and energising change, and to move beyond business-as-usual in their endeavours to monetise service and data.
No North-Star
Many companies, including manufacturers, do not have a clear picture of where the industry is heading and where their business is heading. It is unclear for their employees what needs to be developed and why.
More specific, for many employees it is not clear why the new service and data-driven solutions are that valuable to clients, how it would fit in the overall core business and why it should be paid for by clients. Often, the indicated direction even suggests the opposite and may give room to the logic that value added services and datadriven solutions are (free) features to support the product sales.
Just imagine how a hypothetical mission statement “… being the world’s leading manufacturer of construction equipment and engines” would help develop and monetise advanced services and data-driven solutions.
Blinkered
People in manufacturing are often biased towards products, equipment and technology. They have a narrow view on:
• Customer problems beyond the requirements for the products and equipment;
• How other actors in the industry are developing with advanced data capabilities, which could become competition to the current position of a manufacturer;
• How new technology can be applied to develop new value propositions, solutions and operating models.
This will affect how product managers, marketing and innovation will develop new services and data-driven solutions. Too often, we see that the services and solutions do not always solve a customer problem and hardly differentiate from services and solutions competitors are offering as well.
It will also affect how their colleagues in the operations (sales and delivery) understand and engage, as there is no compelling context to understand the importance of the new services and solutions, let alone be engaged.
Top-down P&L thinking
Too often, we see that developing and launching innovations, such as new advanced services and data-driven solutions, stagnate because of the decision-making habits in an organisation. Typically, we see one or more of the following:
The strategic intent from senior leadership is unclear, hardly based on a well-developed shared concern, not giving a clear path on what services and solutions to develop, nor on what the strategic priorities and objectives are, to be successful. So, employees are not really enticed to take action and therefore no change.
The strategies and plans are more short-term which emphasise short term financial objectives, leading to two different scenarios:
Financial objectives are not articulating the need for services and data-driven solutions, nor specifying which portion of these objectives should come from services and data-driven solutions. Often, employees are actually motivated to stay away from developing and launching the new services and data-driven solutions.
Or, in case the financial objectives also assign financial objectives coming from services and data-driven solutions, there is a lack of description of qualitative objectives and strategic priorities on how to arrive at those financial goals. The result is often a lack of initiatives and progress, or lack of alignment and results.
Top-down strategies from senior leadership are so specific and instructive that these actually dismiss other employees taking ownership of the plans, and/or adjusting plans and local strategies where needed.
Paralysis by control
Top-down control mechanisms from the last few decades are a huge obstacle for fluid and energising change in an organisation and therefore hinder the initiatives like monetising services and data. More specifically, we often see the following patterns;
Internal conflict of interest in the product sales teams, because they are often incentivised on sales volume.
It does not make sense for them to sell complicated service contracts. It hardly affects their commission, consumes a lot of time and may even put their product sales deals at risk. Instead, it is more beneficial to please their clients by offering discounted services.
In case there is a separate service sales team, for the same reason, there are often internal arguments on who owns the client and what is the best plan forward with each client. In the worst case, this even leads to having different faces towards the clients, leaving them confused and with a bad customer experience.
Control mechanisms that are too strict create an unsafe environment in which employees show defensive and risk-avoiding behaviour. Instead of trying, learning and being successful in monetising new services and data-driven solutions, they instead become complacent and resistant.
Typical signs are pointing fingers to other teams to take action, declaring that the new services and solutions are not the core business, that customers don’t want to pay and referring to other companies who have tried and failed.
Some solutions
Many things come into play when increasing momentum for monetizing (new) services and data, and preventing existence of too many obstacles and resistance. In general, the more adaptive and fluid change in a business, the easier a specific innovation on service and data.
We have seen that leading manufacturers have adopted 4 winning habits which sets them apart. These winning habits define how both operation and innovation is lead. In the next paragraphs I will describe the 4 winning habits in relation to monetising services and data.
Direction
Leading companies have a transformative vision and mission on where the business is heading, what needs to change and develop, and why this is important considering the changes in the industry. This is a quite a holistic picture in which all stakeholders and entities in the business can relate and get direction on how to develop themselves, their teams, their department and their business unit.
It provides an outside-in picture on how the business is and will be relevant to a certain industry and customers. It explicitly points out how the business will add value to clients and that this requires certain technology, (data-driven) solutions and services.
Now imagine how the following mission statement will drive the development and implementation of new services and data-driven solutions: “Our purpose is to enable healthcare providers to increase value by empowering them on their journey towards expanding precision medicine, transforming care delivery and improving patient experience, all enabled by digitalizing healthcare.”
Discovery
Here I want to focus on two phases on innovating your services and datadriven solutions: the development phase (including ideation, selection and design) and the implementation phase
For design purpose
In general, the envisioned services and data-driven solutions differ significantly from current business logic, mindset and operations in your business. Even though anyone in the organisation could raise great ideas, it is crucial that the development of the new services and solutions are done by dedicated teams with the right expertise and focus.
They need to ensure they are open-minded and unbounded by current (and old) business logic and pathways. In terms of discovery, this means they should:
Talk with other stakeholders in client organisations (rather than the ones your organisation normally speaks with) - for example, the CFO, CEO, VP, Innovation, commercial leaders, etc. Build a new expert-network outside the organisation - which is outside the current network of partners, suppliers and clients - including the academic experts and consultants in areas you usually have no relationships with and talk about topics other than current technology, products and service, and more about major trends, visions of the future industry,key challenges and strategies of different actors in your and adjacent industries.
This will not only help to obtain more ideas for future success, it will also help to change perspectives and business logic within the innovation teams and the rest of the organisation, by sharing these insights.
For implementation purpose
Once the new solutions and services have been designed and developed to a scalable offering, it probably needs to be embedded in the existing organisation. Now, the risks of resistance or complacency may come into play.
The more developed the mindsets and habits are on “digital” and change, the more fluid the implementation and change will be. This can be promoted massively by strong Discovery habits: Involving key players in the operating organisation, well in advance of the implementation, into the initiatives for launching new services and datadriven solutions - for example, by having a frequent dialogue on shared concern and discussing the alternatives to solve these concerns. This can be done by frequent conversations or including them in the extended innovation team.
Having everyone involved in discovery activities that do not require too much expertise and dedication, for example, by having colleagues; Have broader conversations in their day-to-day conversations with clients, suppliers and partners. You can provide them with topics and questions to help open the conversations
Joining events with customers where you discuss trends, visions, needs and how they see your added value. Join conferences within your own industry and even other industries and sharing new insights and learning points from the expert teams, painting a picture of what is going on in the outside world, how this may impact your business and how this will/could be addressed.
Decision making
In line with the mission, vision and direction leadership of leading manufacturers, have a clear strategic intent on:
Result objectives - for example, overall growth aspirations that new services and data-driven solutions are crucial and how much business is expected to come from these new services and solutions. Strategic objectives on which offerings and capabilities need to be developed.
Next, they have a clear (top-down) strategy which articulates crucial choices on how to achieve these objectives in a few phases. This should provide a common roadmap on which offerings to develop, how to sell them, to whom and by whom, how to organise marketing, sales and delivery, and which obstacles to overcome.
This strategy should address all stakeholders (including R&D, marketing, product-sales, service sales and service delivery) who have direct influence on implementation and success.
With this top-down strategy, still, a lot is left open on how to achieve the objectives. Local teams are empowered to develop their local roadmap and strategy, and to take full ownership of the local development, learning, capability development and execution. This will allow them to mitigate local strengths, weaknesses, opportunities, threats and market circumstances.
Dialogue
With a constructive and forward dialogue between individuals, teams and departments, issues are solved in a fundamental and sustainable manner, hence building capabilities to perform.
For monetising service and data, this means that: Ideally, services and data-driven solutions are being sold at point of sale (when equipment is sold) - maybe not the full package, but the entry level offering which will be the first step to the next level mature offerings. Commission structure of sales people needs to be designed in such a way that it promotes the right focus and behaviour.
I have seen quite a few examples where equipment sales people were quite successful in selling service contracts once the commission they would receive was tied to the sale of a service contract.
Sales people who sell advanced services and data-driven solutions need to have specific skills and background, which are not necessarily the same as skills required for selling the products and maintenance services. Most stateof-the art sales techniques such as Solution Selling, Challenger Selling or Value Selling, assume a fluid and educated dialogue on related business domains.
Often, these conversations should happen with other stakeholders at the client organisation, maybe at higher seniority levels. The different teams need to have the confidence and safe environment to learn and develop these skills and knowledge, and become fluent in these conversations and sales approaches.
Different teams in your organisation need to be “in the same boat” without conflicts of interest. We currently see more and more companies aligning targets and incentive schemes, in which common and shared objectives prevail above individual targets.
Full transparency in key performance indicators on progress and results is required, to have all stakeholders have the necessary insights to be able to take ownership and accountability and intervene when/where needed.
Benefits
The leading manufacturers, ahead of the game, have built momentum for continuous and easy change from the inside, moving beyond “business-asusual”. Their teams are passionate and eager to perform, learn and pursue opportunities. Instead of resisting new ways of thinking about customer challenges, customer value and their business, they focus on customers and pursue opportunities to increase value.
Monetising services and data has become a logical part of their overall vision and strategy. They are better in solving bigger customer problems, better at articulating the value for customers and in removing obstacles for their clients to adopt the new solutions. As a result, they better differentiate themselves – in the eyes of their customers - from their competitors. They perform better and have more resources to keep innovating their business and hence grow in our disruptive world.
Boost your monetisation If you want to accelerate the monetisation of your (new) services and datadriven solutions, I would like to recommend:
• Review your business alongside common mistakes and suggested solutions, and add the discrepancies to your strategy;
• Download the scorecard How to Monetise Services and Data here;
• Book a Discovery Call with Jan van Veen;
• Join our upcoming Impulse Sessions on How to Monetise Service and Data. These are full day interactive meetings with like-minded peers during which we will exchange experience, insights and challenges.
Essence It’s not about making money from new services and data-driven solutions; it’s about being highly relevant and valuable to clients in a sustainable manner and empowering your people to do the same.
It goes without saying that if you deliver value for money, you also get money for value.
Jan Van Veen is Managing Director at MoreMomentum.
Central question
Many manufacturers experience pressure on growth, revenue and margins. Their products and services are being commoditised. Competition from lower cost alternatives are arising. On the other hand, there are huge opportunities with new technologies, value propositions and business models.
One of the important trends is that value propositions and offerings become more data-driven and more service-oriented, which go hand in hand.
Besides predictive maintenance, most of the value from data is related to how clients use the equipment or products and to their operations and processes. Helping clients improve on this by nature is a service.
However, many manufacturers are product-driven businesses which do not fully appreciate the value that (advanced) services have for their customers and their own business.
So, one of the central questions is: How to Monetise Services and Data to Grow in a Disruptive World? The capability to monetising service and data is mission critical for sustainable performance and existence of manufacturers.
In a series of articles, we cover four critical steps that make the difference between success and failure in monetising services and data:
• Solve bigger customer problems;
• Articulate the value;
• Build momentum with clients to adopt;
• Build internal momentum.
Developing new data-driven solutions and services is all about extending the existing business model, which leads to different challenges than many other initiatives and programs in a business. Recognising this in advance will help understand the challenges and best strategies.
In the previous articles of this series, I have described critical success factors for monetising service and data, such as Solve Bigger Problems,Better Articulate Value and Remove Obstacles for Clients to Adopt. In the end, this all has to be done by people and teams in your organization.
Common mistakes
In this article I will describe common mistakes that many companies make, which holds them back in having fluid and energising change, and to move beyond business-as-usual in their endeavours to monetise service and data.
No North-Star
Many companies, including manufacturers, do not have a clear picture of where the industry is heading and where their business is heading. It is unclear for their employees what needs to be developed and why.
More specific, for many employees it is not clear why the new service and data-driven solutions are that valuable to clients, how it would fit in the overall core business and why it should be paid for by clients. Often, the indicated direction even suggests the opposite and may give room to the logic that value added services and datadriven solutions are (free) features to support the product sales.
Just imagine how a hypothetical mission statement “… being the world’s leading manufacturer of construction equipment and engines” would help develop and monetise advanced services and data-driven solutions.
Blinkered
People in manufacturing are often biased towards products, equipment and technology. They have a narrow view on:
• Customer problems beyond the requirements for the products and equipment;
• How other actors in the industry are developing with advanced data capabilities, which could become competition to the current position of a manufacturer;
• How new technology can be applied to develop new value propositions, solutions and operating models.
This will affect how product managers, marketing and innovation will develop new services and data-driven solutions. Too often, we see that the services and solutions do not always solve a customer problem and hardly differentiate from services and solutions competitors are offering as well.
It will also affect how their colleagues in the operations (sales and delivery) understand and engage, as there is no compelling context to understand the importance of the new services and solutions, let alone be engaged.
Top-down P&L thinking
Too often, we see that developing and launching innovations, such as new advanced services and data-driven solutions, stagnate because of the decision-making habits in an organisation. Typically, we see one or more of the following:
The strategic intent from senior leadership is unclear, hardly based on a well-developed shared concern, not giving a clear path on what services and solutions to develop, nor on what the strategic priorities and objectives are, to be successful. So, employees are not really enticed to take action and therefore no change.
The strategies and plans are more short-term which emphasise short term financial objectives, leading to two different scenarios:
Financial objectives are not articulating the need for services and data-driven solutions, nor specifying which portion of these objectives should come from services and data-driven solutions. Often, employees are actually motivated to stay away from developing and launching the new services and data-driven solutions.
Or, in case the financial objectives also assign financial objectives coming from services and data-driven solutions, there is a lack of description of qualitative objectives and strategic priorities on how to arrive at those financial goals. The result is often a lack of initiatives and progress, or lack of alignment and results.
Top-down strategies from senior leadership are so specific and instructive that these actually dismiss other employees taking ownership of the plans, and/or adjusting plans and local strategies where needed.
Paralysis by control
Top-down control mechanisms from the last few decades are a huge obstacle for fluid and energising change in an organisation and therefore hinder the initiatives like monetising services and data. More specifically, we often see the following patterns;
Internal conflict of interest in the product sales teams, because they are often incentivised on sales volume.
It does not make sense for them to sell complicated service contracts. It hardly affects their commission, consumes a lot of time and may even put their product sales deals at risk. Instead, it is more beneficial to please their clients by offering discounted services.
In case there is a separate service sales team, for the same reason, there are often internal arguments on who owns the client and what is the best plan forward with each client. In the worst case, this even leads to having different faces towards the clients, leaving them confused and with a bad customer experience.
Control mechanisms that are too strict create an unsafe environment in which employees show defensive and risk-avoiding behaviour. Instead of trying, learning and being successful in monetising new services and data-driven solutions, they instead become complacent and resistant.
Typical signs are pointing fingers to other teams to take action, declaring that the new services and solutions are not the core business, that customers don’t want to pay and referring to other companies who have tried and failed.
Some solutions
Many things come into play when increasing momentum for monetizing (new) services and data, and preventing existence of too many obstacles and resistance. In general, the more adaptive and fluid change in a business, the easier a specific innovation on service and data.
We have seen that leading manufacturers have adopted 4 winning habits which sets them apart. These winning habits define how both operation and innovation is lead. In the next paragraphs I will describe the 4 winning habits in relation to monetising services and data.
"People in manufacturing are often biased towards products, equipment and technology..."
Direction
Leading companies have a transformative vision and mission on where the business is heading, what needs to change and develop, and why this is important considering the changes in the industry. This is a quite a holistic picture in which all stakeholders and entities in the business can relate and get direction on how to develop themselves, their teams, their department and their business unit.
It provides an outside-in picture on how the business is and will be relevant to a certain industry and customers. It explicitly points out how the business will add value to clients and that this requires certain technology, (data-driven) solutions and services.
Now imagine how the following mission statement will drive the development and implementation of new services and data-driven solutions: “Our purpose is to enable healthcare providers to increase value by empowering them on their journey towards expanding precision medicine, transforming care delivery and improving patient experience, all enabled by digitalizing healthcare.”
Discovery
Here I want to focus on two phases on innovating your services and datadriven solutions: the development phase (including ideation, selection and design) and the implementation phase
For design purpose
In general, the envisioned services and data-driven solutions differ significantly from current business logic, mindset and operations in your business. Even though anyone in the organisation could raise great ideas, it is crucial that the development of the new services and solutions are done by dedicated teams with the right expertise and focus.
They need to ensure they are open-minded and unbounded by current (and old) business logic and pathways. In terms of discovery, this means they should:
Talk with other stakeholders in client organisations (rather than the ones your organisation normally speaks with) - for example, the CFO, CEO, VP, Innovation, commercial leaders, etc. Build a new expert-network outside the organisation - which is outside the current network of partners, suppliers and clients - including the academic experts and consultants in areas you usually have no relationships with and talk about topics other than current technology, products and service, and more about major trends, visions of the future industry,key challenges and strategies of different actors in your and adjacent industries.
This will not only help to obtain more ideas for future success, it will also help to change perspectives and business logic within the innovation teams and the rest of the organisation, by sharing these insights.
For implementation purpose
Once the new solutions and services have been designed and developed to a scalable offering, it probably needs to be embedded in the existing organisation. Now, the risks of resistance or complacency may come into play.
The more developed the mindsets and habits are on “digital” and change, the more fluid the implementation and change will be. This can be promoted massively by strong Discovery habits: Involving key players in the operating organisation, well in advance of the implementation, into the initiatives for launching new services and datadriven solutions - for example, by having a frequent dialogue on shared concern and discussing the alternatives to solve these concerns. This can be done by frequent conversations or including them in the extended innovation team.
Having everyone involved in discovery activities that do not require too much expertise and dedication, for example, by having colleagues; Have broader conversations in their day-to-day conversations with clients, suppliers and partners. You can provide them with topics and questions to help open the conversations
Joining events with customers where you discuss trends, visions, needs and how they see your added value. Join conferences within your own industry and even other industries and sharing new insights and learning points from the expert teams, painting a picture of what is going on in the outside world, how this may impact your business and how this will/could be addressed.
Decision making
In line with the mission, vision and direction leadership of leading manufacturers, have a clear strategic intent on:
Result objectives - for example, overall growth aspirations that new services and data-driven solutions are crucial and how much business is expected to come from these new services and solutions. Strategic objectives on which offerings and capabilities need to be developed.
Next, they have a clear (top-down) strategy which articulates crucial choices on how to achieve these objectives in a few phases. This should provide a common roadmap on which offerings to develop, how to sell them, to whom and by whom, how to organise marketing, sales and delivery, and which obstacles to overcome.
This strategy should address all stakeholders (including R&D, marketing, product-sales, service sales and service delivery) who have direct influence on implementation and success.
With this top-down strategy, still, a lot is left open on how to achieve the objectives. Local teams are empowered to develop their local roadmap and strategy, and to take full ownership of the local development, learning, capability development and execution. This will allow them to mitigate local strengths, weaknesses, opportunities, threats and market circumstances.
Dialogue
With a constructive and forward dialogue between individuals, teams and departments, issues are solved in a fundamental and sustainable manner, hence building capabilities to perform.
For monetising service and data, this means that: Ideally, services and data-driven solutions are being sold at point of sale (when equipment is sold) - maybe not the full package, but the entry level offering which will be the first step to the next level mature offerings. Commission structure of sales people needs to be designed in such a way that it promotes the right focus and behaviour.
I have seen quite a few examples where equipment sales people were quite successful in selling service contracts once the commission they would receive was tied to the sale of a service contract.
Sales people who sell advanced services and data-driven solutions need to have specific skills and background, which are not necessarily the same as skills required for selling the products and maintenance services. Most stateof-the art sales techniques such as Solution Selling, Challenger Selling or Value Selling, assume a fluid and educated dialogue on related business domains.
Often, these conversations should happen with other stakeholders at the client organisation, maybe at higher seniority levels. The different teams need to have the confidence and safe environment to learn and develop these skills and knowledge, and become fluent in these conversations and sales approaches.
Different teams in your organisation need to be “in the same boat” without conflicts of interest. We currently see more and more companies aligning targets and incentive schemes, in which common and shared objectives prevail above individual targets.
Full transparency in key performance indicators on progress and results is required, to have all stakeholders have the necessary insights to be able to take ownership and accountability and intervene when/where needed.
Benefits
The leading manufacturers, ahead of the game, have built momentum for continuous and easy change from the inside, moving beyond “business-asusual”. Their teams are passionate and eager to perform, learn and pursue opportunities. Instead of resisting new ways of thinking about customer challenges, customer value and their business, they focus on customers and pursue opportunities to increase value.
Monetising services and data has become a logical part of their overall vision and strategy. They are better in solving bigger customer problems, better at articulating the value for customers and in removing obstacles for their clients to adopt the new solutions. As a result, they better differentiate themselves – in the eyes of their customers - from their competitors. They perform better and have more resources to keep innovating their business and hence grow in our disruptive world.
Boost your monetisation If you want to accelerate the monetisation of your (new) services and datadriven solutions, I would like to recommend:
• Review your business alongside common mistakes and suggested solutions, and add the discrepancies to your strategy;
• Download the scorecard How to Monetise Services and Data here;
• Book a Discovery Call with Jan van Veen;
• Join our upcoming Impulse Sessions on How to Monetise Service and Data. These are full day interactive meetings with like-minded peers during which we will exchange experience, insights and challenges.
Essence It’s not about making money from new services and data-driven solutions; it’s about being highly relevant and valuable to clients in a sustainable manner and empowering your people to do the same.
It goes without saying that if you deliver value for money, you also get money for value.
Jan Van Veen is Managing Director at MoreMomentum.
Mar 20, 2019 • Augmented Reality • connectivity • Data • Future of FIeld Service • Workforce • Bill Pollock • Cloud services • FieldAware • IoT • skills • Strategies for GrowthSM • The Big Discussion • Marc Tatarsky • SimPRO • Waste Management
Concluding our series our experts, Bill Pollock, Strategies for Growth, Marc Tatarsky at FieldAware, and Richard Pratley from SimPRO, identify potential areas of concern for service companies to look out for in 2019.
Concluding our series our experts, Bill Pollock, Strategies for Growth, Marc Tatarsky at FieldAware, and Richard Pratley from SimPRO, identify potential areas of concern for service companies to look out for in 2019.
What is the biggest area of concern that field service companies should address in the next 12 months?
BILL POLLOCK, PRESIDENT, STRATEGIES FOR GROWTH
The biggest area of concern for field service companies in the next 12 months will be, if they’re already somewhat behind the technology curve (or with respect to the competitive landscape), what do they need to do today to ensure that they will not fall further behind? And, it’s not just a matter of technology either; many FSOs will need to alter their corporate philosophy and mentality as well.
Technology goes hand-in-hand with the personnel that use it, so attention must also be given to how the organisation goes about replacing, and/or supplementing, its existing field force with new hires or the use of outside, third-party “feet on the street” support.
The services world is evolving so quickly, that any missteps along the way can be devastating – so every step, every move counts.
There will also be no time for any intra-mural infighting – only for collaboration and inter-departmental cooperation. Equipment will keep on breaking, and end-of-lifecycles are getting increasingly shorter. As such, there will always be the need for services organisations to deliver their support! However, only those that have the technological and corporate wherewithal to continually improve the way in which they deliver their services will rise to the top of the competitive order – and stay there!
MARC TATARSKY, SVP MARKETING, FIELD AWARE
The phrase ‘doing more with less’ is common in field service and that can be in relation to numerous resources and assets.
The workforce is a key element in this equation and can preoccupy a great deal of management time. There are concerns over an aging workforce in field service, a high turnover of workers and a shrinking pool of talent as demand increases.
Technology plays a critical role in any succession and resource planning. This may be empowering the workforce with automation to streamline operations, bring in best practice and increase productivity without the need to increase numbers. Using technology differently or embracing emerging technologies to enable remote expert capabilities, so a more experienced worker assists others.
Also attracting new workers, especially millennials, for whom, the latest technology is a big part of everyday life. The technology has to be right for both worker and the organisation to get maximum benefit
RICHARD PRATLEY, MANAGING DIRECTOR UK, SIMPRO
Technology is changing at a rapid pace. The technology we use today is very different from that we used five years ago so businesses will always have the challenge of how they can ensure the systems and technology they use are still current. Taking a long term view of the business requirement is vital.
Many businesses consider an off-the-shelf solution won’t fit the unique needs of the business. But think again! Overtly customised solutions can lead to restrictions with software updates and integrations with other systems in the future - not to mention a great deal of ongoing expense and time that should be spent on running the business.
Cloud-based software providers frequently release new updates (that are included in the licence fee) to help businesses stay ahead of tech trends. By ensuring the systems you use now are fit for-purpose, you’ll be able to keep up with future technological developments.
You can read the first instalment of The Big Discussion here, the second here and the third here.
Mar 11, 2019 • Augmented Reality • connectivity • Data • Future of FIeld Service • Workforce • Bill Pollock • FieldAware • IoT • skills • Strategies for GrowthSM • The Big Discussion • Marc Tatarsky • SimPRO • Waste Management
In the third of our four-part series, our industry experts Bill Pollock, Strategies for Growth, Marc Tatarsky at FieldAware, and Richard Pratley from SimPRO, identify key areas of focus for field service managers in 2019.
In the third of our four-part series, our industry experts Bill Pollock, Strategies for Growth, Marc Tatarsky at FieldAware, and Richard Pratley from SimPRO, identify key areas of focus for field service managers in 2019.
What do you think should be the key areas of focus for field service managers across the next twelve months?
BILL POLLOCK, PRESIDENT, STRATEGIES FOR GROWTH
The next most important areas of focus for field service managers in the coming 12 months will likely be among the following three items:
(1) embracing the “new” technologies to support an expanded and enhanced capability to deliver their respective service offerings. Artificial Intelligence (AI) and Machine Learning have been around for more than 50 years, but are still relatively new to the services segment – but, it’s time to build them into your service operations!
(2) Changing the way in which you deliver – and price – your service offerings. Traditional break/fix service is essentially “dead”. Long live predictive diagnostics and predictive maintenance! Have you spoken to any chat bots lately? Well, you will!
(3) Re-engineering the way you measure performance metrics, or KPIs. MeanTime Between Failures (MTBF) and Mean-Time-to-Repair (MTTR) will not mean anything in an environment where services are being performed remotely on an ongoing basis. It will be time to replace some of the old “tried and true” KPIs with new ones that can measure systemic productivity, rather than merely individual field technician productivity. It’s time to rethink the entire service delivery process – and adjust to it!
MARC TATARSKY, SVP MARKETING, FIELD AWARE
Integration capability tops software selection criteria consistently for field service leaders. Even those who have been hesitant to integrate in the past, can now see that integration capabilities are far more advanced. Working with the right FSM software creates rapid time to value and ensures minimal risk.
Essentially the integration of FSM solutions into existing business systems of record means there is no disruption to ERP, CRM and accounting systems. Ultimately the real value is delivered through synchronized workflows, enhanced reporting and extending results beyond the current systems. Data integration yields actionable outcomes and connectivity to the wider business.
Field service has long been seen as simply a business cost, but leaders now recognise that integration can elevate their service operation, transforming it to a value-driving organisation that delivers broader business results. The evolution of field service through integration should be a focus to unlock this business value.
RICHARD PRATLEY, MANAGING DIRECTOR UK, SIMPRO
We continue to see businesses turning to software and technology to improve the efficiency of their workforce and to support customer service.
Smart connected products and IoT technology is transforming field service operations and we’ll see more adoption of this over the next twelve months. The predictive model not only reduces the cost of reactive maintenance but it addresses any issues before they become critical. For the customer, they won’t ever need to worry about needing to deal with a broken asset ever again.
We already have a number of customers running trials of our IoT technology. Not only are they winning new contracts off the back of it but it’s helping to increase the lifetime value of their existing customers.
The final part of The Big Discussion. You can read the first instalment here, and the second here.
Feb 11, 2019 • Features • Data • Future of FIeld Service • Novotek
It’s no secret that data collection is important for generating valuable insight that helps plant managers improve efficiency in industrial systems. However the importance of understanding the context of the data is less well known. George Walker...
It’s no secret that data collection is important for generating valuable insight that helps plant managers improve efficiency in industrial systems. However the importance of understanding the context of the data is less well known. George Walker from Novotek explains more.
Let’s take a hypothetical scenario. Imagine that a maintenance manager has a machine that is bending wires. These wires have to bend to a very accurate angle to properly work. However, the machine isn’t bending them properly at certain times of the day, causing the business to produce faulty goods that have to be discarded.
To fix this issue, the maintenance manager brings up the data collected by the device’s onboard software. The manager then analyses the data with a digital twinning platform. Looking at the analysis, it becomes apparent that the machine is vibrating anomalously at certain hours of the day. The manager dismantles the machine, reassembles it and even runs it in an isolated scenario, but is still unable to find the source of the problem.
"It is easy to get fixated on a single goal and to forget to take a step back for a wider view of a situation..."
In this instance, if the manager had taken a moment to take a step back and looked for context, they may have realised that the anomalous vibrations coincided with the activation period of a nearby piece of heavy machinery. There is nothing wrong with the machine in question, but its surrounding context reveals the cause of the error.
This is why context in data collection is vital.With an array of smart sensors and devices, paired with a digital twinning system like GE Digital’s Predix platform, across the whole production line, the manager could have clearly seen the correlation by viewing the data in context. Another method of achieving contextual understanding would have been by comparing the machine with other similar ones in different plants.
This shows why digital twinning is such a powerful tool. Being able to recreate an entire plant in a digital model breaks silo mentality. This allows managers to have holistic insight, which reveals issues that were previously not apparent. Whatever the issue, it is evident that context in data collection matters. Being able to analyse systems is now a reality and should be used to the full extent of its potential.
With potential to reduce waste and unnecessary expenditure, digital twins will allow stronger operations. With context being easily achievable in the modern industrial arena, it no longer needs to be a trade secret among industrial businesses. And by sharing this knowledge, more businesses can make their smart networks smarter, their operations more efficient and their production processes more productive.
George Walker is Managing Director of Novotek UK and Ireland.
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Dec 13, 2018 • Features • aviation • Data • Future of FIeld Service • future of field service • mobile workforce management • Blockchain • Cyber Security • field service • IFS • Service Management • Stephen Jeff Watts • data analysis
Blockchain and its potential has been mooted in field service circles for years. Is it time we stop thinking big and instead build smaller use-cases before we lose sight of what’s actually important, the end-user? Mark Glover, Field Service News’...
Blockchain and its potential has been mooted in field service circles for years. Is it time we stop thinking big and instead build smaller use-cases before we lose sight of what’s actually important, the end-user? Mark Glover, Field Service News’ Deputy Editor finds out more.
In 2008, a person (or a group of people) known as Satoshi Nakamoto conceptualised the first blockchain. A year later, this digitised digital ledger was a critical accessory to the group’s (or his) headline act, the now ubiquitous cryptocurrency Bitcoin.
The impact of this decentralised digital currency on financial markets and a curious, confused society has been fascinating to follow. That the persona of the inventor or the inventors remains unknown adds to the plot.
Yet, without blockchain, the currency wouldn’t function. This smart ledger, driven by a peer-to-peer network has the potential to stamp itself on industry and in particular field service. But can the sector adopt the technology in a way that will ultimately benefit the end-user?
Firstly though, and apologies to all those who have a handle on the technology, what is blockchain? Scouring the internet for a simple definition is tricky, eventually, the excellent forward-thinking mission.com offered this: “Blockchain is the technology that underpins digital currency (Bitcoin, Litecoin, Ethereum and the like). The tech allows digital information to be distributed, but not copied. That means that each individual piece of data can only have one owner.”
"The tech allows digital information to be distributed, but not copied. That means that each individual piece of data can only have one owner..."
Straightforward enough. But let’s expand it to industry. How can it fit into the aerospace sector and specifically a plane engine? Parties involved include the airline, the engine manufacturer and the service company all of whom are squirting data into that asset’s blockchain.
The jet engine is a high-end valuable piece of equipment, the blockchain systems enable a single, irrefutable history of that asset. The linking of parties (blocks) removes the requirement for inter-party consultation before extracting required information meaning critical decisions can be made quicker and more effectively. It’s also secure and visible to everyone and accurate and trust, therefore, is enhanced around the chain. The benefits are tangible. So why aren’t all companies rushing to implement it?
“Like all emerging technologies there are only going to be one or two applications that are going to come up for this kind of thing in the very early days,” says Stephen Jeffs-Watts, Senior Advisor – Service Management at IFS. Stephen is an expert in blockchain, a keen enthusiast of its benefits but warns that fields service shouldn’t get too carried away just yet, particularly as sectors are only starting to dip their toes in the murky blockchain water.
"We have to try and bear in mind that it [blockchain] is also directly proportionate to the type of kit that’s been installed...“
A lot of the use cases that are coming up at the moment,” he tells me, “are in very high-value assets and very highly regulated supply chains; in aerospace, defence, nuclear and very-high-end medical applications,” he pauses. “There aren’t too many Phillips Medicals out there.”
In field service, blockchain technology can potentially trace parts, verify assets and look-up maintenance and operations history, but according to Stephen, it needs to bed-in with modern hardware before its benefits can be felt. “We have to try and bear in mind that it [blockchain] is also directly proportionate to the type of kit that’s been installed,” he warns, “Are you really going to use blockchain to authenticate the asset history or the maintenance and servicing history for a ten-year-old piece of equipment?” Another pause, “You’re not.”
Let’s go back to the jet engine blockchain analogy; the engine itself is a high-end piece of equipment.
The airlines and engine manufacturer, themselves are high-end companies: BA, KLM, Lufthansa, Rolls Royce, GE, Northrup Grumann, for example. All are big companies keen to monetise blockchain, the only real way to do this is through data-ownership but in a high-asset blockchain, this isn’t always straightforward.
Who owns the data from a jet-engine? Is it the airlines?
The thrust from their plane goes through that engine and what about linking that to the pilot who’s flying that aircraft and jet engine through the air? That’s the airline’s data too. They also have a hand in the plane’s load: the number of passengers and baggage, fuel etc. That’s also data from the airline.
The engine itself? Rolls Royce might run it on a power-by-the-hour contract, so it’s their engine, so do they own the blockchain data? Like that other revolution IoT, blockchain becomes an issue of data ownership. What can be done to grease the chains to make the process run smoother?
“You’re going to have to get industries and supply chains to actually come together and solve the underlying data ownership issue,” Steve offers. “There is going to have to be some kind of consensus; an informal consensus through co-operation; the introduction of some kind of industry standard or ultimately an enforced consensus through legislative means,
Be it an Industry standard or a regulatory framework, large-scale blockchain implementation ultimately needs sectors to work together, to come together in agreement and as Steve explains, it also becomes an issue of trust. “Let’s say there are ten people involved in the supply chain: the operator, the Original Equipment Manufacturer (OEM), there may be a service operator; they’re all contributing data to that chain.
“But does the end operator actually have enough trust in the OEM to question if they are going to use their data and benchmark it against its competitors”, he ponders.
Issues around data-ownership, trust and unfit equipment unable to handle what is essentially a large-scale, shared google document are indicators that large-scale field-service blockchain implementation isn’t as close as we might think. Perhaps we are setting our sights too high? Maybe the use-cases should be carried out on a much smaller scale?
After all, cryptocurrency, the original thread of blockchain was designed for electronic financial transactions, not necessarily jet engines. Stephen agrees, referencing a well-known tracking device, he suggests we should keep things simple. “We could use blockchain like a glorified RFID tag that authenticates, verifies and gives you a reference point,” he says. “I can look at the blockchain and I can see who made it, when it was made, how it was transported.
“Where they may be just a couple of parameters about its last usage, you can look at that by a component-by-component type level, specifically in those cases where that kind of information is critical, or the authenticity is critical.
"There’s got to be a realistic level of ambition and some specific use-cases that prove the technology and prove the value of the technology before there comes any mainstream adoption..“
There’s got to be a realistic level of ambition and some specific use-cases that prove the technology and prove the value of the technology before there comes any mainstream adoption,” Stephen urges.
My conversation with Steve has been fascinating and his contribution to this article I’m sincerely grateful for. The insight he offered - most of which I’m unable to fit into this wordcount – was invaluable, yet despite all its potential of blockchain Stephen left me with a thought that goes beyond the blockchain hype: “So what?”
So what if an asset is pumping with blockchain data? All the customer wants is the device to start working again so they can get on with their business.
“What value does that bring to me as a customer,” argues Steve. “unless I’m in a highly regulated environment. When do you start loading up past-maintenance history? Is it good? Is it worthwhile? Probably not. So what’s the use-case that going to give killer value?
Steve continues from the end user's perspective: “Great, you’ve got blockchain. What do I get from you having blockchain? What do I get from being able to prove every last working second of this particular piece of kit? Why should I care?”
It’s an excellent point that perhaps gets lost in this fourth industrial revolution we find ourselves in. Among AI, and IoT and machine learning and blockchain should we not just focus on the customer needs and their requirements? Or will we continue to pursue the hype?
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Jun 04, 2018 • Features • Connected Field Service • Data • Data Analytics • Future of FIeld Service • mobile workforce • white papers • White Papers & eBooks • eBECS • field service • field service management • field service software • Internet of Things • IoT • Service Management
Field Service News, Editor-in-Chief Editor, Kris Oldland's latest white paper, sponsored by eBECS, explores why field service organisations should be ensuring their field service technicians are collecting data from assets whilst on service calls...
Field Service News, Editor-in-Chief Editor, Kris Oldland's latest white paper, sponsored by eBECS, explores why field service organisations should be ensuring their field service technicians are collecting data from assets whilst on service calls even if they aren't ready to implement an IoT based approach to service delivery yet as by doing so they can reap some of the benefits and more importantly build the processes for a future world in which connectivity and data will be at the heart of customer service operations...
Want to know more? The bad news is the full white paper is only available exclusively for fieldservicenews.com subscribers.
The good news is that if you are a field service practitioner then you may well qualify for a complimentary industry practitioner.
The even better news is we will send you a copy of this white paper when you apply as a welcome!
Click here to apply for your complimentary industry subscription to fieldservicenews.com and access the white paper now!
Note: Please do take the time to our T&Cs (available in plain English at fieldservicenews.com/subscribe) and note that this content is sponsored by eBECS
In today’s field service sector companies are facing an increasingly complex set of challenges and the collation and analysis of data paradoxically seem to often be found at both ends of the spectrum.
Data can be at the heart of many problems for a field service organisation as they struggle to find useful insight amongst ever-increasing banks of data locked away in differing business silos. Yet the rewards for breaking down those silos and also being able to identify where the insight is within your data can lead to better service levels than have ever been possible previously.
The vast amount of data that we have access to today can potentially give us a much more intimate understanding of our customer base than ever before, giving us the ability to understand and even predict their needs, far more accurately than we have ever been able to manage previously.
The vast amount of data that we have access to today can potentially give us a much more intimate understanding of our customer base than ever beforeHowever, the flip side of this benefit is that companies are now finding themselves drowning in data - which becomes meaningless without insight, a challenge which can be magnified further if data is locked away behind walls within an organisation.
It can be a daunting challenge to not only establish processes that allow the collection of data but also to ensure that when collected, data can move seamlessly across an organisation to fulfil its maximum potential. Yet in today’s business climate where service has become a core differentiator, there has perhaps never been a more urgent need to ensure you are harnessing every tool available to you in the most efficient manner in order to stay just one step ahead of the competition - and data certainly holds many of the keys to service excellence when it’s collected, processed and analysed correctly.
An interesting symptom of operating in a world of technological advancements, is that when we talk about data collection within a field service context the topic immediately turns to IoT - but in doing so are we overlooking one of the most important resource in a service organisation already at our disposal - the field service engineers themselves?
The importance of data collection in an increasingly connected world
The question of whether the Internet of Things will play a part in field service has been and gone. The answer was a resounding ‘yes it will.’
Research from Field Service News showed that 86% of companies were actively either developing plans to implement IoT or had already done so. Indeed, in terms of IoT and field service, the question for the overwhelming majority of companies has moved from why to how.
However, the impact of IoT in field service is set to be so revolutionary that it cannot just be viewed as a new technology to be rolled out, it is a decision which must be grounded with a firm understanding of your business strategies, your future goals and a rock solid foundation of both processes and technologies that can allow an organisation to fully reap the benefits of an IoT based service strategy.
But the revolution isn’t really an IoT revolution, it is a data revolution.
The number of connected devices globally is set to reach over 30BN by 2020 (data source: Berg Insight)Asset performance data and even component performance data can open the doors towards moving towards both a more preventative maintenance focused approach as well as empowering your service engineers to be able to find a first-time-fix on a more regular basis.
Asset performance data and even component performance data can open the doors towards moving towards both a more preventative maintenance focused approach as well as empowering your service engineersYet, for many service organisations, the sheer volume of data that a fleet of connected assets will produce will cause a series of problems and pain points in and of itself.
With companies facing unprecedented levels of data coming into their service operation not only from IoT connected assets but also various digital customer touch points whether that be via contact agents, self-service portals or even sentiment analysis of relevant social media, finding meaning and value within such a deep data lakes can be a daunting task.
In addition to this, there is the further question of retrofitting assets that a discussion on IoT necessarily brings with it.
For organisations with a large install base there are a number of considerations that must be given thought including:
- Which assets are worth retrofitting with IoT connected sensors?
- Is it worth waiting for some assets in the field to reach their natural obsolescence and then replace them with newer connected models?
- Should you prioritise retrofitting assets for those clients that are the most profitable or will having multiple levels of service contract be a hindrance to service delivery?
- What data is it important to track from retro-fitted assets? What is essential and what is merely nice to have?
- What processes will you need to develop or adjust in order to facilitate this data within the workflow of your service delivery teams?
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Nov 14, 2016 • Features • Coresystems • CSO • Data • Future of FIeld Service • manuel grenacher • chief service officers
As the role of the Chief Service Officer begins to gain more prominence the focus for driving service excellence at the executive level must be data driven writes Manuel Grenacher, CEO of coresystems...
As the role of the Chief Service Officer begins to gain more prominence the focus for driving service excellence at the executive level must be data driven writes Manuel Grenacher, CEO of coresystems...
Delivering service that meets the satisfaction of ever-demanding customers is helping usher in a new C-Level role at service and manufacturing companies.
Meet the Chief Service Officer (CSO).
It’s a role that isn’t widespread yet, but one that has begun to make inroads into leading service companies as more organizations eye revenue opportunities beyond equipment sales.
As product margins slip, CSOs are tasked with orchestrating and executing the type of service that retains and creates loyal customers. Selling a piece of equipment -- even one with a multimillion- dollar price tag -- is a one-time win. Service, however, can create revenue streams that deliver profits each year until the equipment is replaced.
It’s a model that more companies are adopting.
According to McKinsey, by 2016, nearly half of manufacturing companies expect that service will account for a third of their total revenue. But as companies move from being a commodity supplier to offering an on-going service relationship, a clear strategy is necessary.
Target Areas for CSOs
Successful service relationships require a number of teams working together within an organization.
Aberdeen Research has found that 8 out of ten Best-in-Class organizations (leading field service companies) have a VP-level or higher executive leading service.
CSOs must prioritize getting accurate insights to the right service people at the right time, so that they can solve problems for customers.
Aberdeen found that Best-in-Class organizations have four main target areas (in order of priority):
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- Improve customer retention and loyalty
- Improve service-related profitability
- Improve quality / relevance of service data
- Improve service information capabilities (i.e. mobility, knowledge sharing)
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But what can companies do to help CSOs reach these goals? Data and its analysis are key. Specifically, here are the three data-driven actions that Best-in-Class companies do to empower their CSOs:
Real-Time Insight Drives Real-Time Performance
CSOs must come to grips with managing and orchestrating the efficient operations of a number of different departments and technicians. Best-in-Class companies empower their CSOs with the right data to help drive real-time performance, the ultimate goal of any service organization.
What data, in particular, do CSOs need to move toward real-time service delivery?
“Some industries have been transformed already by incorporating data analytics into their standard processes...”
Other tools are needed that let integrated data flow seamlessly from the field to the back office.
CSOs need real-time monitoring of asset operating conditions, performance, and usage. Finally, the tools CSOs use should enable real-time service visibility for senior management.
Give Your Field Team Tools That Deliver Valuable Service Experiences
The ultimate goal of service is to deliver value to the end customer. Service technicians need to ensure that a work order is completed, preferably during their first visit to the customer. But field visits represent an important opportunity for capturing data from equipment performance to visit details.
Our customer GE Power in Switzerland is using our Field Service Mobile APP to record granular data like temperature, upload or comment on pictures. This customer data can help inform the next visit or additional service needs.
Use Data to Continuously Improve Service
Customer expectations will only continue to grow. Since they are under pressure to perform too, customers are demanding real-time solutions to their service issues.
Customers won’t only compare your organization to competing firms, but also to their own customer experiences elsewhere. CSOs must study best practices across the entire service ecosystem and ensure that they are implementing these offerings.
Data and the analytics gathered on machines, equipment, and customers will help create the baseline. From there, CSOs should be able to evaluate and continue to improve service operations.
Some industries have been transformed already by incorporating data analytics into their standard processes.
To give an example, telecom companies can forecast traffic patterns, peak period bottlenecks, commercial versus domestic split, and thus perform real-time optimization of their voice and data networks. They can route around congestion to improve performance and the whole customer experience.
They take constant readings from their network data switches and build a big database of all their devices and customers to get a holistic view of the complete environment.
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