Using Service Lifecycle Management (SLM) to Support Your Customers While You’re Servicing Their Equipment

Every day you deal with a multitude of customers who vary by type, size, installed base, usage, personality and everything else that ultimately differentiates one customer from another. However, one thing always remains constant – their business systems and equipment are critically Important to their day-to-day business operations. Despite this common thread that runs through virtually all of the customers you support, it is still important to recognize that each customer account will likely be different in terms of:

  • The various types, brands, models and numbers of units they have installed at their respective sites;
  • The ages of the individual units that are covered under their various Service Level Agreements (SLAs), or supported viaa Time & Materials (T&M) basis;
  • The usage patterns of the equipment at their individual locations (i.e., continuous intermittent use; single vs.multiple shifts; simple vs.complex multifunctional peripheral applications; and so on);
  • The volume, capacity or throughput they regularly execute; and
  • Many other unique and/or specific differentiators.

For some of your customers, their equipment is an integral component of what they do on a day-to-day basis. Customers in all industry segments, whether it be legal, financial, medical, real estate, government, or other highly-demanding markets, will tell you that their systems and equipment are essential to their business operations, and that when their equipment is down, their production is severely affected. For some, even a small piece of connected equipment may be the only means they have for providing their customers with a receipt, order confirmation, or other important transaction-generated documents. In fact, for many in the latter category, their reliance on the equipment you support may be even more critical to them (at least on a relative basis).

Regardless of the specific industry market segment or type of customer, there will always be a basic level of reliance on the business systems and equipment they have installed at their facility. In addition, you will find that your customers will also be relying heavily on your organization to ensure that their equipment is always up and running as required – and as expected. As such, it is important to recognize that in the customer’s mind, if the equipment is not working optimally – regardless of the technology that may have been built into it – it is worthless.

Since there is just so much that the customer is either inclined or permitted to do in order to get the equipment back in working order following a failure, in most cases, your field technicians will be the sole entities that they can count on to make that happen (that is, aside from remote monitoring and diagnostics, etc.). Accordingly, they will need to approach the servicing and support of the equipment with a great deal of professionalism and responsibility. Customers usually do not care whether the cause of an equipment problem is due to a hardware or software failure; a paper jam; or whether it was the unit’s fault, their fault, or nobody’s fault in particular. All they know is that when they needed to use the equipment, it simply did not work.

This is typically where the organization’s field technicians come into the picture. In many cases, they represent the only “real” physical manifestation of the service and support that keeps their equipment up and running – or at the very least, they may represent their first line of service and support defense. Your customers may rely heavily on the equipment itself to support their day-to-day business operations; but they rely even more on your organization and your field technicians to ensure that the equipment can continually do what it is supposed to do.

This is a unique area where most services organizations – and their dealers and distributors – can use some help! The good news is that there is a Service Lifecycle Management (SLM) software solution available for users in every industry, size and geographic coverage segment. The implementation of anSLM solution can provide a comprehensive set of integrated business solutions that empower strategic initiatives while driving tactical execution.

Companies that install, repair, and maintain business systems and equipment can increase their competitive advantage, grow top-line revenue, and bolster bottom-line profitability through the use of an effective SLM solution. Among the basic features and benefits of SLM functionality for a typical Field Services Organization (FSO) may best be summarized as follows:

  • Comprehensive Contract and Service Level Management
  • Service and Sales Integration
  • Increased Help Desk/Contact Center Effectiveness
  • Field Service Efficiencies

Comprehensive Contract and Service Level Management

Through SLM, customer contracts and Service Level Agreements (SLAs) can be structured in ways that best fit the business, as well as the businesses of their respective customers. Key items such as maintenance and repair service; preventative (or predictive) maintenance; remote monitoring, diagnostics and repair; and draw-down contracts can all be easily established and managed. As such, the organization’s services management can be assured that all of the obligations of its customers’ SLAs are well-planned for – and met – and that all of its mission-critical commitments to the customer are being honored.

In this way, services revenues are maximized, and there is little risk of experiencing lost revenues. Company representatives can quickly and easily verify both the customer and vendor entitlements, thereby eliminating any costs that might otherwise be associated with providing customers with parts, consumables or services they are not entitled to under the terms and conditions of any existing warranties or contracts. This also ensures that any and all dealer claims will be quickly processed.

Service and Sales Integration

The Service and Sales Integration functionality of an SLM software suite can be relied on to enable the manufacturer’s and dealer organizations’ field service technicians and contact center personnel to more thoroughly service the company’s accounts, while also driving increased revenue in the process. By placing intuitive, easy-to-use sales tools into the hands of the appropriate service employees, the number of new opportunities to up-sell and cross-sell equipment, parts and consumables to existing customers will increase multifold.

The organization’s service technicians are out in the field every day talking to, and interfacing with, its customers; why not also provide them with the tools and resources they can use to close – or at least open –additional sales opportunities within this virtually captive customer base!

Increased Help Desk/Contact Center Effectiveness

SLM can also allow the organization to increase its call handling efficiencies, especially in the areas of first-call resolution and call avoidance rates. This will ultimately result in the lowering of internal service costs, and commensurate improvements in existing levels of customer satisfaction and retention. In many ways, business systems and equipment services have been somewhat commoditized over the years, and the only way that one services organization (or its dealers) can establishment a competitive advantage over another is to differentiate (i.e., improve) the way in which they support the customer base after the initial sale.

The best way to do this is to provide superior levels of help desk and call center support empowered by a robust SLM capability. By arming your call center personnel with accurate and up-to-date customer and installed equipment base information – be it entitlement, configuration, or marketing campaign data – the organization will be able to greatly increase its ability to sell, cross-sell, and upsell its entire portfolio of products, services, parts and consumables.

Field Service Efficiencies

Leveraging the field service automation tools inherent in the SLM software allows the organization to optimize its field force capacity utilization, resulting in significant operational efficiencies as field technicians quickly become empowered to increase revenue generation and recovery. By streamlining and managing the invoice process, billing cycles will be lowered, as will other key areas, such as Day Sales Outstanding (DSO), etc.

These improvements will almost immediately go directly to the bottom line as you will be able to manage your cash flow and receivables much more effectively. Similarly, by streamlining and managing your service inventories (such as trunk stock) more effectively, you will also be able to realize significant inventory cost reductions.

What many OEMs and dealer organizations seek is an end-to-end, enterprise-wide SLM solution that addresses the complete equipment/service lifecycle, from lead generation and sales quotation, to service and billing, through asset retirement. They are looking for a solution that both integrates and optimizes the critical business processes that all services organizations have to face with respect to providing their customers with the levels of service and support they require.

Services organizations that provide their customers with any combination of products, parts, services and consumables must be able to not only fix the customers’ equipment, but to fix the customer as well; however, the ability to do so may vary greatly from one organization to another. However, the most successful organizations will ultimately be the ones that have the right mix of management, personnel, tools, resources and solutions (i.e., Service Lifecycle Management), all working together to provide their customers with the levels of service and support they require – and expect!

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Why Knowledge Discovery? Your Organization May Be Sitting on a Goldmine of Data!

These days, more than ever, businesses are operating in data rich environments. Data emanating from every-day business operations, sales and customer account activities, service call activity, financial and economic transactions, regulatory reporting and all the other business-related events of the world are routinely captured and stored in databases. Existing global databases are adding terabytes of new information daily. Every moment of every day bank transactions and electronic funds transfers, point-of-sale systems, hospital tests and procedures, factory production lines, airline reservations, service calls and even electric meters and gasoline pumps are creating digital records that are stored somewhere in a database.

The vast majority of these data, however, will never see the light of day. More often than not, these data will be stored for a specified period of time, in some cases as required by law, and then “purged” to make room for more current data of the same kind. This process is likely to repeat ad infinitum, each time replacing the “old” data with “new” data until the “new” data itself becomes “old” and must once again be replaced. Yet in many cases these data can represent a “rich ore” of valuable information and knowledge about the domain from which it has been taken.

What better source is there to learn about patterns of customers’ preferences and buying habits than from the customers themselves; not just what they tell you they need or like in a Customer Needs and Requirements/Satisfaction Survey, but what they actually buy. What better source is there to learn about equipment failures and service requirements than from the equipment itself; not just from what your field technicians tell you, but directly from the equipment. What better source is there to learn about the risk in lending or extending credit than from your business’s own financial successes and failures; not just from what your banks or creditors tell you, but from your own financial experiences, both good and bad. The list goes on and on.

Organizations are always searching for knowledge that can advance their cause and keep them abreast of the market, anticipated trends and the competition. Marketing managers would love to know what makes their customers “tick”. Manufacturing managers would do anything to find out how they could improve the quality of their products, even by just a fraction of a percentage. Not to mention the securities traders who would “sell their corporate souls” just to keep a half-step ahead of the pack in being able to detect a change in trends or receive an “early warning signal”.

Oftentimes the answers to these questions are contained in the data that businesses routinely collect, store and discard from their ever-growing databases. Many companies have already recognized the potential of this source of knowledge and have invested substantial effort and significant amounts of resources to uncover the precious knowledge “hidden” in their data. Among the various emerging technologies being utilized, some employ a combination of both the traditional and newer, more “exotic” paradigms in a field known as knowledge discovery, or database mining.

Credit card issuers are using advanced knowledge discovery methods to identify usage patterns that indicate fraud in an attempt to execute more effective fraud avoidance systems and, ultimately, minimizing their exposure to losses. Warranty management organizations are using similar methods to detect fraud in an attempt to reduce their traditional losses in this area.

Digital marketing companies use related methods to create more targeted and effective lists for the products and services they are promoting to improve their overall effectiveness. Automotive companies use the same techniques to discover patterns of failures and corresponding information to incorporate into the proprietary knowledge bases that they distribute to their authorized dealers and licensed mechanics. Many more applications of a similar nature span across businesses and industry segments of all types under the banner “Let The Data Work for You”.

The analogy of database mining to quarry mining is very appropriate too. In ore mining the process goes through tons and tons of dirt in order to extract one precious gram of gold. Similarly, in database mining, one may also need to go through very large quantities of data just to get to the “one piece of information that makes it all worthwhile”.

However, it is typically at this point where traditional analytical methods and approaches have failed, and the businesses that have historically used them have pretty much “given up”. Going through a large “mine” of raw data only to transform it into a somewhat smaller pile of statistics or summary tables is of very little use and often quite discouraging, and questions like; “What do the data mean?”, “How can we make use of it?”, and “How does it relate to our bottom line?” are all hard to tell.

Traditional statistical methods make assumptions about the data used and require a model in the form of an hypothesis that one can then either accept or reject. Quite often the data do not conform with the assumptions and there is no model. In addition statistics excludes from its realm many forms of data that are quite common in the expression and representation of some of the phenomena that are around us. To overcome these drawbacks, the process of extracting knowledge from data has turned to machine learning techniques.

Machine learning techniques, developed under the umbrella of Artificial Intelligence (AI), were originally patterned after a unique human intelligence trait – the ability to acquire and create new knowledge. From this basis, new and highly sophisticated AI techniques have been developed using a broad array of disciplines and strategies, and reflecting various levels of success.

In later stages of research some of these techniques have been incorporated into a knowledge acquisition process which represents a critical step in the process of building and maintaining knowledge-based systems. Prior to the development of such a process, this was typically the area that represented the largest “bottleneck” in terms of actually having the capability of building and using knowledge-based systems in practical business applications. Moving from this point forward (i.e., to expanding the use of learning mechanisms to database mining knowledge discovery), the distance is very short.

Today, knowledge discovery tools and methods employ a broad range of technologies and methodologies. Neural networks are probably the best known and most widely used approach to machine learning. The technology is quite versatile, relatively mature and has been used very successfully in a broad array of applications ranging from the screening of credit card applications, to placing geographically-based advertisements in national magazines, to reading handwritten addresses and routing the mail. Other discovery methods are based on technologies such as information theory, fuzzy set theory, rough set theory, nearest neighbor metrics and others.

Finally, with respect to the question “Why knowledge discovery?”, the answer should be more apparent by now. Your organization may be sitting on a “goldmine” of data which could be converted into useful knowledge – knowledge that can be used to help you focus your strategic and marketing planning efforts; monitor and improve the quality of your production and service delivery processes; and explain your customers’ sensitivity to your competitive pricing structure, customer service performance, brand name recognition, advertising and promotional campaigns or anything else you would like to learn about the markets in which you operate.

Many organizations have already recognized the potential benefits of these new technology applications and are utilizing these tools to lead them to smarter, more efficient and more productive operations. The list of such companies is growing every day – and your organization should also leverage the knowledge to join them.

An SFG℠ Analysts Take: There’s Nothing Artificial About Artificial Intelligence

[After you read our latest Blog, below, please be sure to take the time to participate in our 2018 Field Service Management Survey Update. We’ve already sent out our “Last Reminder” and will be closing the survey shortly. However, we don’t want to miss out on receiving your responses and insight! Simply click on the following link to access the survey questionnaire: https://t.co/wbTKMLWdpP.] 

The global field services community is always looking for “the next big thing” to impact Field Service Management (FSM), and many research analysts (including myself) are far too willing to debate whether something like 3-D printing, wearable technology or Augmented Reality (AR) are merely new technology “fads” or, rather, transformative technologies that will ultimately (and quickly) change the face of field service forever. [Note: I believe they’re transformative!]

Whenever a new technology (or a new application for existing technology) is introduced, the initial discussions may range from “It will be the best thing since sliced bread” to “it will never be accepted by the marketplace”. Most, fortunately, find their way into the ability to support the increasingly expansive functionalities of today’s (and tomorrow’s) FSM solutions. Technologies like Augmented Reality (AR) have already established a strong foothold in field service, both as a standalone platform or, integrated with Virtual Reality (VR) into a Mixed Reality (MR) platform.

However, the one “new” technology for which there is virtually no debate, even among the industry’s diverse research analysts, is Artificial Intelligence (AI). For that matter, you can also include Machine Learning (ML) in this category.

What makes AI and ML so different from most of the “new” technologies we have seen talked about in the past is that, first and foremost, neither one is really a “new” technology. The term “Artificial Intelligence” was first introduced in 1956 at an academic conference. However, it was not until 1961 when mathematician Alan Turing (the lead character in the movie, “A Beautiful Mind”) wrote a paper on the application of machines to “simulate” human beings and their ability to perform intelligent tasks – initially to play chess (and to win at it!). [Even I co-authored a published article on neural networks and artificial intelligence applications for field service back in 1993!]

Fast forwarding to today, we see just about every services analyst writing about AI and ML. For example, analyst firm, Gartner, included both AI and ML among its “Top 10 Strategic Technology Trends for 2017”, stating that, “AI and machine learning have reached a critical tipping point and will increasingly augment and extend virtually every technology enabled service, thing or application. Creating intelligent systems that learn, adapt and potentially act autonomously rather than simply execute predefined instructions is primary battleground for technology vendors through at least 2020.”

Further, Gartner “advises CIOs to look at areas of the company that have large data sets but lack analytics. AI can provide augmented intelligence with respect to discovery, predictions, recommendations and automation at scale” – a perfect fit for field service!

However, research firm, Forrester, believes that “there is still a lot of AI progress to be made before machines can truly understand and guide next best actions” and that “Robots, AI will replace 7% of US jobs by 2025 (i.e., “16% of US jobs will be replaced, while the equivalent of 9% jobs will be created – a net loss of 7% of US jobs by 2025.”)

UK-based firm, iTouchVision cites the following four areas where it believes AI will likely have the greatest impact on the field service segment in the coming years:

  • Customer Experience – Primarily through the use of chatbots, “it will be possible to help customers with more speed and accuracy. These bots containing the customer and their equipment information can find out the problem and suggest a quick fix”.
  • Work Productivity – AI overcomes the hurdles faced by manual dispatchers. In the near future, we may also see the replacement of human dispatchers with an AI virtual assistant that considers all the service event parameters including unexpected events. It increases the job completion rate in the first visit by ensuring the worker has right tools and skills.
  • Predictive Maintenance – Predictive, rather than Preventive, maintenance is “the way to increase asset life and quality. The machine-to-machine interaction and the connected devices drive predictive maintenance. It eliminates the unnecessary technician visits to check machine condition”.
  • Data-Driven Decisions – “AI is all about data. With AI in use, it is possible to take more strategic decisions. Reduced repetitive administrative work allows human operatives to focus on predictive analysis. It governs end-to-end work and data flows with automation. Continuous data evaluation and processing presents a clear picture with analytics.

Overall, AI (and ML) are certainly not “artificial” – nor are they simply current fads or trends that will eventually bite the dust. They are real – not artificial; and, as such, should be carefully – and quickly – considered for incorporation into the field services management solution your organization uses to run its services operations.

The Future of Field Service Management (FSM) – What Lies Ahead for an Industry that Is Constantly Evolving and Reinventing Itself

[The following is a first page excerpt from SFG℠‘s Analysts Take paper on “The Future of Field Service Management (FSM)” originally published this past July, 2017. Following the conclusion of our current, updated, survey research on the topics of Field Service, Service Parts Management and Warranty Management, we will be updating this document later in Q2, 2018. In the meantime, to download the entire original document, simply click on the Weblink provided at the bottom of this page.]

The global Field Service Management (FSM) segment has re-invented itself several times over the years, from break/fix, to network services, to software support and such. However, the introduction of the Internet of Things, or IoT, is going to have a much greater and profound impact on the global services community than anything else that has preceded it! In fact, it already is!

For years, services managers have been talking about ways in which to reduce the number of “truck rolls” in order to save money, and repair the customer’s equipment remotely – first, by phone, or assisted self-help; and, now, via remote diagnostics and predictive diagnostics.

Truck rolls are not necessarily a thing of the past; however, they have greatly diminished in frequency as a result of the integration of the predictive diagnostics, remote diagnostics and the IoT into Field Service Management (FSM) systems.

“Improvements in business analytics have also assisted field service managers in their ability to manage their entire business operations – and not just the field service aspects of the business.”

Improvements in business analytics have also assisted field service managers in their ability to manage their entire business operations – and not just the field service aspects of the business. There are more analytical tools available now than ever before, and most managers are actively engaging their dashboards, so they can intelligently manage their field service operations.

Through the use of Augmented Reality (AR) apps, now actively being combined with Virtual Reality (VR) to form a more complex and robust “Mixed Reality” (MR) capability, we are likely to see even more advances in the types of technologies that will ultimately reduce the cost of performing service – for both on-site and remote repairs – over time. Artificial Intelligence (AI) and Machine Learning (ML) immediately come to mind.

Also, with technology visionaries like Elon Musk, who started out with his Tesla automobile business, branching into solar panels and, of course, SpaceX, we are likely to see more and more technological advances coming down the pike. For example, Musk’s new venture, Neuralink, has set its goals on attaining the ability to “merge” the power of the human brain with the power of the IoT, in order to upload and download “human thoughts” onto chips, and vice versa.

Imagine the impact that new ventures like this will have on all aspects of business, not just in field services, if successful! All of a sudden, veteran field services technicians will become just as important as the influx of computer-savvy millennials with respect to their experiential value to the Field Service Organization (FSO). The process goes on and on, and field service management will continue to evolve over time, as a result.

[To download the entire Analysts Take paper on “The Future of Field Service Management (FSM)”, simply click on the following Weblink: The Future of FSM (Draft-17-06-29-01).]

Lessons Learned from WBR’s 2017 Field Service Fall Conference

FSM Is Taking a More Innovative and Progressive Approach to Meeting Evolving User Expectations

Introduction to Field Service Fall: Innovation. Progression. That’s Field Service!

There were a great many lessons to be learned about field service and customer support so far in 2017 due to a number of factors, including responses to multiple natural disasters (i.e., hurricanes, floods  and earthquakes); evolving patterns of customer needs, requirements and expectations (i.e., as a result of the introduction and proliferation of new technologies); a changing competitive landscape (e.g., the consolidation and/or acquisition of many of the “traditional” Field Service Management (FSM) solution providers, as well as the influx of many new start-ups); and so on.

That’s what’s makes the WBR 2017 Field Service Fall conference at Amelia Island, Florida, so important – especially as it immediately followed the destruction caused by Hurricane Irma only a couple of weeks earlier. Innovation and progress were certainly at the forefront of those services organizations proximate to Amelia Island (and Texas only a couple of weeks earlier) that were tasked to deal with the devastation that was brought forth.

General Conference Theme

First, as conference host, Sara Mueller, WBR’s Event Producer for the conference, stated in her opening remarks, that after speaking to a number of Field Service executives leading up to the event, most suggested that they were interested in learning more about what their peers were doing (or thinking of doing) with respect to dealing with major challenges and establishing priorities for moving forward.

To that end, Sara summarized the “Big Picture” that her executive interviews painted as consisting of the following four components:

  • Business Model Transformation – moving towards selling outcomes rather than selling a product;
  • Having the Right Field Force in Place – with the right information and tools at their fingertips;
  • Leveraging Digitalization and Connected Products – for better efficiency and service; and
  • Achieving Customer Satisfaction – and growth!

The main premise behind all of this “learning”, Sara said, could be summarized in a single quote from Benjamin Franklin: “Tell me and I forget, teach me and I may remember, involve me and I learn.” The next three days certainly bore out Franklin’s thoughts – all with clear examples and background provided.

However, there is always additional, or incremental, “learning” that can be attained by participating in events such as WBR’s Field Service Fall. The following is our “take” on the primary lessons learned over the course of the three day event.

Advancing Service Together

Before delving into specific topics relating to lessons learned from the conference, first, we believe it would be helpful to. Take a more broadly-defined look at what constitutes the basis of field service and customer support.

In his keynote presentation, Martin Knook, CEO at Gomocha, defined the components of “Advancing Service Together” as being based on the the responses to a series of questions, including:

  • What can I do for you today?
  • What can I do better this time?
  • What solution do you need tomorrow?
  • Do you have any pain points that you can share?
  • Are you happy with my product/service?
  • What else do you expect?

While admittedly, this list of questions is not complete, it at least establishes a base, or basis, for both the solution provider and the customer to begin the process of working together to a common end. “It’s not rocket science!”, Knook exclaimed. But it does begin the process of information exchange.

Knook also cited W. Edwards Deming, who said that, “Without data, you are just another person with an opinion.” However, data alone does not do the entire job – the data must, first be accurate and relevant, but it must then be converted into usable information and, ultimately actionable knowledge.

The challenges, according to Knook, are:

  • Servitization
  • Technology Capabilities
  • Existing Business Processes, Products and Services
  • Innovative Learning Organization

One of the greatest challenges is predicated on the fact that “only 18% of the companies interviewed have clear performance metrics in place.” This is also supported by Strategies For Growth’s (SFG’s) most recent survey data tree along that a similar percent do not currently even have a formal Key Performance Indicator (KPI) program in place.

However, these alarmingly low percentages may be somewhat offset by the fact that up to 62% of the organizations surveyed in SFG’s 2017 Field Service Benchmark Survey are currently establishing or enhancing their existing KPI programs to include more metrics measured, more sharing of data/information and the better application of those measurements into strengthening their ability to measure and improve existing levels of performance.

Denise Rundle, GM and Partner at Microsoft, took the discussion a bit further by discussing “Turning Customers into Raving Fans.” In her keynote presentation, she cited a quote from Microsoft CEO, Satya Nadella, who stated the company’s mission statement as, “Achieving our mission requires us to evolve our culture and it all starts with a growth mindset – a passion to learn and bring our best every day to make a bigger difference in the world.”

It’s all there: culture, passion to learn, bring our best, make a difference via the execution of our “growth mindset”. And, not the other way around!

  1. In order to execute on its mission, Microsoft has identified three breakthrough experiences that it believes will take it to the next level:
  2. Artificial Intelligence – the technology that will make the virtual agent more human and helps agents be more effective,
  3. Collaborative Delivery Model – based on the simple routing to groups of experts who solve cases collaboratively, and before and after sentiment to understand how  customers feel.
  4. Achieve More Conversations – through the application of machine learning, predictive analytics and targeting, and campaigns.

Rundle also spoke of the things that Microsoft has already begun implementing in these areas including: (1) extending conversations with customers by 30 seconds in order to “add real value to customers; (2) eliminate “painful routing” and “frustrating bounces” by channeling customer calls directly to “groups of collaborative product specialists” (i.e., rather than to a worldwide assortment of engineers, etc.): and (3) provide customers with an “end-to-end” user experience to create new opportunities to customers (as well as cross-sell and upsell opportunities to Microsoft).

Greatest Lessons Learned

Perhaps the greatest lessons learned from WBR’s 2017 Field Service Fall conference were focused in the following areas:

  • Digital Transformation
  • Connected Services / The Internet of Things (IoT)
  • Augmented Reality (AI) / Artificial Intelligence (AI) / Machine Learning (ML)
  • Outcome-Based Services
  • Dealing with a Changing Workforce / Leveraging a Contingent Workforce

[To download a complete copy of SFG℠‘s “Lessons Learned from WBR’s Field Service Fall ConferenceAnalysts Take report, please click on the following Weblink: @@@ 2017 Field Service Fall Analysts Take Report (17-10-16-01).]

Companion Piece to Bill Pollock’s August, 2017 Guest Blog Post on Behalf of Sprint Business (Part 2 of 2)

[This is the companion piece to my two-part guest Blog published in July and August on the Sprint Business Blogsite. Part two also focuses on the impact of the Internet of Things (IoT) on the Field Services industry. As is the case in most analyst interview-based guest Blogs, much of my responses will not be included in the final posts. As such, please consider this Blog as a more detailed companion piece for the final five of 10 questions posed by Sprint Business. Hopefully, this will provide you with additional “between the lines” thoughts and opinions.]

Q6:   How can field service organizations monetize IoT?

The ability to monetize the IoT in field services is another variation on a theme of what has dogged the field services industry for decades! Every time there are advances in technology, the more progressive – and aggressive – Field Services Organizations (FSOs) adopt the technology to streamline their processes, reduce their internal costs, and improve their service delivery capabilities. However, customers, for the most part, see the adoption of this technology as being (1) strictly for the benefit (i.e., cost-benefit) of the services organization itself, and not them; and (2) a means that should reduce overall costs for both the services organization and its customers (i.e., themselves).

The mistake that many services organizations make is trying to sell the same services to customers, at reduced costs to themselves, but increased costs to their customers. Customers will typically see this apparent disparity and question their services providers as to why they should have to pay more for something that costs their vendors less!

What basically needs to happen is for the services organizations to move away from traditional Service Level Agreement (SLS) pricing, to an outcome-based pricing model, such as “power by the hour”, “airplanes in the air” or “x levels of output”, rather than “y hours of service coverage”. Remember the “bullion” pricing model (i.e., Platinum, Gold, Silver, Bronze)? It bit the dust (in most cases) years ago. So, too, will traditional Service Level Agreements (SLAs) as they are replaced by outcome-based services agreements.

The best current examples of this are, as noted, are selling “uptime as a service”, rather than merely “throwing hours of support” at customers – a rifle shot, rather than a scattergun approach to selling services.

Q7:   What do you see as IoT’s impact on service lifecycle management? 

Many services organizations say they offer total Service Lifecycle Management (SLM) support, but many still only offer Field Service Management (FSM) solutions in terms of field service and support, preventive maintenance, and meager parts and inventory management.

However, the IoT, in some cases for the first time, now empowers FSOs to provide “true” Lifecycle Management for their services customers – essentially “cradle to grave” support for all of their systems and devices, throughout all of their day-to-day usage and applications.

How does the IoT do this? Basically, by automating the entire services management process, end-to-end, from data collection, through device monitoring, problem identification and resolution, routine and ad hoc maintenance services, predictive and pre-emptive maintenance, parts/inventory management – and even “end-of-life” product support! SLM is more than FSM – and the IoT can support all of the organization’s SLM services processes.

Q8:   How will IoT change how companies package and deliver their services?

The IoT is more likely to change the way in which services organizations deliver their services, first; and the way they package them, second.

By that, I mean that, first, the IoT will allow services organizations to perform more maintenance and repair service remotely, rather than on-site – and the growing use of predictive diagnostics will continue to reduce the need for on-site services (in some cases, at all) over time. As a result, many services customers may not even know that their systems or equipment have been serviced, as everything that was needed was either performed remotely – or did not need to be performed at all (i.e., through routine monitoring and minor calibrations or maintenance “tweaks”, etc.).

Through the use of a customer portal, customers can typically gain full visibility of exactly what types of maintenance have been performed, on which systems, at what times, and with what results. However, those customers not electing to utilize their customer portals (or if their services provider does not offer that capability) will have virtually no visibility as to the extent of the maintenance that has been performed. This ultimately becomes problematic for some services organizations that must then report what they have done for the customer – and try to convince them that by doing so, there was added value provided.

Packaging the “new” way of providing services through an IoT-powered FSM, or SLM, involves an entirely new way of delivering services to customers. For example, instead of providing a certain number of hours of support, within a designated time window, and providing a “guaranteed” uptime percent (i.e., or you don’t have to pay your services contract fee that month), some organizations are now selling uptime – period.

Instead of throwing service contract hours at an aviation customer, they now provide “airplanes in the air” to this segment. Similarly, instead of selling a standard SLA to a wind farm customer, they are selling “power by the hour”. Instead of selling standard SLAs for extermination services, they’re selling a “rodent-free” environment. And so on.

However, this ”new” way of packaging services will be difficult for some services organizations to deliver – and for many customers to acclimate to. It will take time, and it will not be an easy conversion for some. But, it is the way of the present already, in many cases – let alone for the future.

Q9:   What specific steps should organizations take now in order to ride this transformation?

For some organizations in certain segments (e.g., aviation, energy, factory automation, medical devices, etc.), if they haven’t already embraced and incorporated the IoT into their services operations, they are already a step or two behind the market leaders. For those that are still examining the potential value of Virtual Reality, there are others that are already looking to implement Artificial Intelligence and Machine Learning.

The time is now for reading up on all things IoT, attending IoT conferences, viewing vendor demos, establishing “long lists” and reducing them to “short lists” for vendor consideration, etc. Gaining management buy-in is also a must – in fact, it is basically a must for all things services management anyway – but, especially with respect to the IoT.

Prepare a plan for embarking on the road to an IoT-powered FSM or SLM solution scenario – do it now, because many of your competitors have already done so, and many of your customers (and prospects) are already at least somewhat familiar with what the IoT can do for them. When the services management marketplace is more fully transformed, you will need to have made the transformation as well. The market leaders are already several steps ahead of you; you can’t afford to fall even further behind.

Q10: Within the field service industry, where will the greatest disruption come from – startups, midmarket, enterprises, or a combination?

The expected disruption to the global services industry will be manifested as a combination of all types, sizes and categories of “new” entries to the competitive landscape. Most (if not all) of the enterprise services providers are already offering true Services Lifecycle Management solutions (or, at least, enhanced Field Service Management solutions). They “get it”, and they’re doing something about it.

Over the past several years, we’ve seen many of the large Enterprise Resource Planning (ERP) companies (e.g., SAP, Oracle, etc.) acquire their FSM solution capabilities. For example, Oracle acquired TOA Technologies, IFS acquired Metrix, Microsoft acquired FieldOne, and so on. Some larger companies have also elected to go more organically, such as Salesforce that created its “new” Field Service Lightning solution based on ClickSoftware technology. ClickSoftware went private again, but still operates in the marketplace itself, while also licensing some of its software apps to other organizations.

The midmarket is only a step or two behind the enterprise services providers in terms of embracing and incorporating the IoT into their FSM and SLM solution offerings. However, where the most “confusion” and uncertainty lies in is the landscape populated by start-ups – and what I call the upstarts!

In addition to the ongoing spate of mergers, acquisitions and alliances, and organic development, there has also been a significant increase in the numbers of “new” entries into the FSM solution marketplace. In fact, probably more of this type of activity has occurred in this segment recently than in the past many years – or decades!

These “new” start-ups can essentially be divided into two main categories: (1) FSM Start-ups, that are trying earnestly to find a way to enter – and penetrate – the FSM market, by leveraging new technologies, experienced leadership, deep (enough) pockets, investment capital and a bit of luck into a services growth segment where they believe they can actually make a difference.

However, it is the FSM Upstarts, that are basically trying to ride the Cloud-based, or SaaS, solution wave into a “new” market (to them), in order to make a quick buck when they ultimately plan to sell out to a larger organization in another year or two. As such, it is truly a “buyer beware” market, as there are a great number of “new” upstart FSM solution providers that will not be around for very long.

Hopefully, my responses have helped you to better understand the ways in which the services management market is changing – both rapidly and pervasively. Blame it on the IoT for this rapid evolution; however, blame yourself if you’re not keeping up with the advances in services management technology!

[To access the published Blogs, please visit the Sprint Blogsite at https://business.sprint.com/blog/field-services-iot-makeover/. Or, if you prefer, you may access the complete SFG℠ Analysts Take paper simply by clicking on the following Weblink: How the IoT Is Transforming the FS Industry (Draft-17-07-21-01).]

Companion Piece to Bill Pollock’s July, 2017 Guest Blog Post on Behalf of Sprint Business (Part 1 of 2)

[This companion piece to my two-part guest Blog published in July on the Sprint Business Blogsite focuses on the impact of the Internet of Things (IoT) on the Field Services industry. As is the case in most analyst interview-based guest Blogs, much of my responses will not be included in the final posts. As such, please consider this Blog as a more detailed companion piece for the first five of 10 questions posed by Sprint Business. Hopefully, this will provide you with additional “between the lines” thoughts and opinions.]

Q1:   In what ways is IoT transforming the field service industry, and at what pace?

The Internet of Things (IoT) is transforming the field service industry in ways that most analysts –  and practitioners – could not have foreseen just a few years ago. While most of us were focusing on machine-to-machine (i.e., m2m) communications and the prospects for utilizing Augmented Reality (AR), the IoT was already beginning to be leveraged into smart systems and Connected Field Service (CFS) solutions among the more progressive services organizations in the global marketspace.

Even as we speak, while some companies are just beginning to evaluate the benefits of integrating Augmented Reality into their services operations, AR is already morphing into Mixed, or Merged, Reality (MR) through the combined deployment along with Virtual Reality (VR) applications. And this advanced trend is not only not going to stop; it is much more likely to accelerate right before our eyes.

The growing recognition that Artificial Intelligence (AI) and Machine Learning (ML) applications are ultimately poised to make the difference between those services organizations that are destined to be the market leaders versus everyone else (i.e., the followers, and laggards) is also picking up steam, and will likely join the mainstream of market adoption shortly (albeit, the inner working of AI and ML are both much more complicated than the IoT – especially with respect to AI).

The IoT is not just for m2m anymore. It is the tool that can make any services (or other) process “smart”, if applied effectively. It can (and will) take services organizations to places they never dreamed possible just a short time ago – and it will be responsible for cutting the costs of delivering services along the way.

At what pace? Basically, if you merely blink, you may find yourself quickly falling behind your more progressive competitors! Many of them are already there!

Q2:   What are the highest-impact factors in this transformation?

The highest-impact factors in field service transformation will be the normalization of the playing field across all industry segments, by vertical market, size, type, geographic coverage and any other “demographic” segments you can think of. Field Service Management (FSM) is not only for the large enterprise organizations, but for services organizations of all types, regardless of size or market coverage.

The proliferation of Cloud-based FSM solutions has also moved many organizations from the historical perpetual license pricing model to a much more manageable subscription basis pricing model. This also is having a significant impact on facilitating the entry of smaller and medium-sized organizations into the world of the IoT and smart solutions.

The integration of AR, VR and/or MR platforms into services operations will also normalize the playing field even more, thereby empowering services organizations of all types and sizes, etc., to compete head-to-head against each other (as well as the market leaders) with essentially the same levels of system capabilities. It will also lead to quicker customer equipment “fixes”, at reduced costs (to the services organization), and with far fewer visits required to the customer site to perform the repair.

Q3:   What do you see as the top three or four benefits to field service organizations?

The top benefits to field service organizations, as cited in Strategies For Growth℠’s (SFG℠’s) 2017 Field Service Management Benchmark Survey, are (1) the ability to run a more efficient field service operation by eliminating silos, etc. (cited by 44% of respondents as one of the top three benefits); (2) improved customer satisfaction (cited by 39%); (3) the ability to provide customers with an end-to-end engagement relationship (cited by 35%); (4) the ability to establish a competitive advantage (cited by 30%); and (5) improved field technician utilization and productivity (cited by 26%).

Other top benefits include (6) reduced Total Cost of Operations (TCO) (cited by 25%); (7) reduced ongoing/recurring costs of operations (cited by 19%); (8) improved service delivery time (cited by 16%); (9) fostering enhanced inter-departmental collaboration (cited by 15%); and (10) ability to complete the automation of all field service operations (cited by 12%).

However, as more and more services organizations ramp up with respect to IoT-powered technologies and applications, there will likely be even more potential benefits identified within the global services organization community.

Q4:   How can organizations best leverage all the IoT data they gather?

Many reports have been written about services organizations (and businesses of all types) “drowning in data lakes”. However, the key to success is to establish early on what data is needed to effectively run the services operations, and hone in on specifically those types of data when collecting and processing the reams and reams of data generated from your IoT-based systems. Too much data is … well, too much data, if you don’t have a plan to harvest it effectively.

Services organizations also need to be able to identify which data is “need to know” vs. which data is only “nice-to-know”. Nice-to-know data is ultimately way too expensive to collect, process, analyze, monitor and distribute; however, need-to-know data is not only invaluable – but critical to ensuring the well-being of the services organization.

You don’t go to work wearing 12 watches; you don’t buy 48 oz. of steaks, per person, to put on the grill for a summer barbecue; so, why would you pay for more data than you will ever need when you can harvest just what you need for now (plus whatever else looks like you may need in the future)?

Think of your data repository as a storage space for all of the data you will need today, tomorrow and in the future. If large enough, put it in a data lake – but make sure you don’t use Lake Superior for what a smaller data lake can do for you more efficiently.

Q5:   What barriers do organizations face in taking full advantage of IoT, and how can they overcome those barriers?

The greatest barrier in taking full advantage of the IoT is typically senior management resistance at the top of the organization structure. Coupled with a general lack of understanding of exactly what the IoT is, and exactly what it can do for the organization, these two factors can too often become “momentum-killers” within the organization.

This is why making sure that all participants comprising services management are kept up-to-date with (1) advances in IoT-based technologies, (2) the introduction of new applications and mobile tools to support field technicians (and to transfer some of their historical on-site responsibilities to more remote-based scenarios), and (3) evolutions in FSM solution capabilities, etc., is so important.

With subscription-based pricing, cost should no longer be as critical an issue to the prospects for moving forward with the desired FSM solution – however, do your CFO and Purchasing teams understand that? Or are they still entrenched in the traditional perpetual license mindset?

Attending field services trade shows and IoT-focused conferences should “shake off the cobwebs” for most of the non-believers or nay-sayers in the organization. Collect as much information as you can, schedule some demos, and invite management to witness the benefits (i.e., the outcomes) of an IoT-powered FSM solution first-hand. This will definitely sway most of the non-believers!

Hopefully, my responses have helped you to better understand the ways in which the services management market is changing – both rapidly and pervasively. Blame it on the IoT for this rapid evolution; however, blame yourself if you’re not keeping up with the advances in services management technology!

[To access the published Blogs, please visit the Sprint Blogsite at https://business.sprint.com/blog/field-services-iot-makeover/. Or, if you prefer, you may access the complete SFG℠ Analysts Take paper simply by clicking on the following Weblink: How the IoT Is Transforming the FS Industry (Draft-17-07-21-01)]