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November 27, 2019 | 1 Mins Read

Arrow Tackles Change Management Head On

November 27, 2019 | 1 Mins Read

Arrow Tackles Change Management Head On

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Mickey Thomas, Vice President of Customer Care and Inside Sales at Arrow Exterminators, shares with Sarah how the company has conquered a major PestPac upgrade by focusing heavily on change management.

November 25, 2019 | 3 Mins Read

What Does Optimization Even Mean Any More?

November 25, 2019 | 3 Mins Read

What Does Optimization Even Mean Any More?

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By Tom Paquin

I don’t think there’s a less controversial position than admitting that you’re “pro-optimization”. Everyone wants to be optimized, but the word “optimization” has become so muddled by tech-speak over the last two decades that it now barely carries any meaning at all. “Optimization” is now some sort of vague efficiency improvement that is as shallow a statement as saying that you’ve “streamlined operations,” or “maximized efficiency”.

The term “optimization” has become a big bucket to throw empty promises into, and organizations selling you tools for service have taken advantage of that by tagging whatever they want with the phrase. If you want to see how and flagrant this is, just do a Google search for “field service optimization” and look at the vague, meaningless improvement promises that come along with the snake oil being peddled.

It’s a shame, really, because optimization should mean something, especially in service. At the Future of Field service, we believe service optimization should, by this point, be the baseline of successful service delivery. But in order for optimization to do anything, it has to actually mean something.

So let’s make optimization real.

Broad strokes here—we can break field service lifecycle into a few big buckets: Asset management, planning, scheduling, routing, delivery, parts management, invoicing, and customer retention. If we do that, it’s pretty easy to begin to apply “optimization” in a way that’s far less vague.

A good parts optimization system would, for instance, give inventory visibility across every possible channel, and offer some predictions into what parts are needed for a job, either though IoT diagnostics, or information capture from the customer (preferably both).

As you can see, that’s a lot more than a piece of software.

And that’s the real trick, here. Software alone can’t optimize your service practice. In the above example, vendors have to work with OEMs, who may have to work with dealers, who may have to work with contractors, who again may have to work with OEMs, in order to even begin to think about a piece of software. That’s not an accomplishable goal. That’s an ongoing process.

The “optimization” example that gets bandied around with the most excitement, but sometimes with the least substance, is routing optimization. What’s so infuriating about this is that routing doesn’t happen in a vacuum. You can’t just throw an optimization engine at your technicians, have it auto-route the day’s work orders, and actually expect anything to be improved.

Just like the above example, you’re dealing with a complex network of autonomous systems that need to be catalogued, categorized, and ranked by importance. This is why the best systems don’t just do routing; They making it a component of planning and scheduling, taking into consideration workers’ expertise, inventory, territory, as well as service history. For an accurate, repeatable, and verifiably improved workflow, this approach is a necessity.A holistic view means that a real optimization system can give you an actual, tangible, numerical business improvement number to stand by. This could be a decrease in overall time from ticket to invoice, increased first visit resolutions, or an increase in tickets closed per day. A truly optimized system will tell you what it did for you, and what it means to you.

Be wary the next time you hear someone talking about optimizing service in the abstract; There is, far too often, very little substance behind those words. But if you think about each area of your business, you can see how smart management can come together with the right technology tools to make optimization mean something again.

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November 21, 2019 | 4 Mins Read

Sorting Through The Digital Noise

November 21, 2019 | 4 Mins Read

Sorting Through The Digital Noise

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By Greg Lush

As I was entering the workplace in 1981, computers were not so popular for a guy in the commercial/industrial service business. Memory, and I am talking about hard-drive space, was nothing like it is today. Remember that unconfirmed quote from Bill Gates in 1981, when the IBM personal computer was introduced? Mr. Gates supposedly said that 640Kb of memory "ought to be enough for anybody.” Heck, Apple just a few years later released a cute little all in one computer (1984) named Macintosh 128k, yes signifying the amount of hard-drive space. Now, it is not uncommon to see a handheld phone with 64Gb of memory, a jump from 128,000 bytes to 67,108,864 bytes. Interestingly, a solid-state drive today, at 64Gb is a fraction of the cost of a spinning hard-drive in 1981 with only 128Kb. The point is, memory is CHEAP; forget about your past practices and assumptions regarding what to save and what to get rid of, save it all! Your biggest challenge will be to sort through the noise; a digital exhaust of sorts.

Start by establishing what you will do with the data gathered. No different than other business decisions, you need to align your input, the collection of data, with your desired output, commonly visibility and/or action. Please do not be surprised if after this exercise you discover that over 90% of your information does not translate to an action, or any value, today. To illustrate let's take an air conditioning (AC) unit, just like the one that you have at your home or office. Not too long ago I was in a meeting with an AC unit manufacturer bragging about all of the data that they could obtain, over 120 different points of information. At first pass you may think, wow, that is impressive. Yet, as you peel back the business scenarios to keep the unit running trouble-free for as long as possible, a service person would tell you that only a handful of data points are required. Where does that leave us? Acquiring that information does have a connected cost, regardless of how commoditized the hard-drive storage market has become. We need to ask, transfer, process, store, and use the data in a meaningful and relevant manner. So, now you’re confused — gather the data or don't gather the data?

Yes, is the correct response to both questions. A flood of information will hit your environments and I encourage you to save each last byte. However, during the ingestion process tease out the data needed for the handful of relevant data points. Allow the remaining data to travel directly to a data lake, or some other inexpensive mass data storage tool. One of the many features of a data lake is we can store a TON of data for hardly any cost (seen in organizing, tagging and storage space). In order to perform this "in flight" routing of data you will need a system sophisticated enough to perform analysis while the data is in motion. The top tier software companies will all have some degree of functionality in this arena, Microsoft refers to this process as Stream Analytics. It is hard to verbalize the significance of this next step. Bear in mind that all your AI algorithms feeding machine learning and other tools will use the data set that you deliver. Sure, many AI tools can take the whole lot, yet getting the most efficient package creates tremendous processing and financial benefits. Cloud platforms charge based on several variables, including yet not limited to; processor horsepower, memory (hard), memory (computer). Design for the objective and outcome. When you follow this path, you will also put the business need ahead of the technology requirement, which leads to greater adoption and overall user satisfaction.

Now, for one of the most misunderstood topics — predictive analytics and tools. It all starts with listening and understanding your client’s business. Once you understand the customer's objective(s), you need to combine that with your own business objectives. Is the reason that you are using predictive modeling is to give you an edge in the market? If that is the case than the models that you choose should be single models, possibly only looking at one element and having the right to claim, rightly so, that you are predicting an outcome. However, if you are trying to turn around or mitigate risk within your organization, you may need to look at multiple pieces of equipment and their predictive models to see how, when combined with one another, create different perspectives which may alter your course of action. These are very different approaches, they all need predictive models and data, certainly investment, but their level of sophistication is vastly different. Both are valuable, the bottom line will be how well aligned the model is to your business conditions and environment.

Learning models, and the algorithms contained within, can drive incredible value to your business. It is key that you understand how the outputs of these data science-based objects influence action within your current operating environments. Keep in mind that IIoT, data sciences, and even workforce sciences, are as much about the tools as they are about the cultural and market-based changes required to truly evolve your operation.

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November 20, 2019 | 1 Mins Read

The Field Technician of The Future

November 20, 2019 | 1 Mins Read

The Field Technician of The Future

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Rich Smith, Vice President, Product and Services Division at Komatsu America Corp., chats with Sarah about how evolving customer expectations, technology advancements, and talent challenges are contributing to what the technician of the future will look like.

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November 18, 2019 | 4 Mins Read

Preparing to Develop the Field Technicians of the Future

November 18, 2019 | 4 Mins Read

Preparing to Develop the Field Technicians of the Future

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By Sarah Nicastro, Creator, Future of Field Service

I was asked to be interviewed recently on a podcast titled Preparing Technicians for the Future of Work, which is a podcast intended for those responsible for educating and preparing the next wave of field technicians. It was a lot of fun to participate, and when the episode goes live I will share on social as well as Future of Field Service. In the meantime, I wanted to share a snippet of a question asked of me on what I see happening from a technician standpoint over the next three to five years. Check it out below and I’d love for you to share your thoughts with me! You can email me at sarah@futureoffieldservice.com.

Q: I want you to take out your crystal ball. What are you seeing as the main drivers or challenges in the upcoming years? Think "three to five years out." I mean, are Field Service Technicians going away and being replaced by apps? Or what do you see out there? Say three to five years. What do you think?

A few things come to mind. The first is, I think we will continue to see a real emphasis on the customer experience, customer centricity, and really expanding on that. And I say that because I think that we're at a point in this industry where companies have recognized — and even embraced — the fact that they HAVE to become truly customer-centric to succeed. But I think we're still at a point where some companies kind of know the steps they want to take to do that, and others are still wondering exactly what that looks like for them. So, I think that's going to be a continued focus.

We talk a lot about servitization or the outcomes-based economy. And that ties back to looking at the customer journey and really understanding, from a field technician perspective: when you send someone in with some sort of technical skill to fix a point-specific problem, that used to be acceptable. But the reality is that needs to be tied in with the whole customer journey. And there are other aspects of that journey that that technician can address. And so, shifting from delivering a service, a break-fix type service, to delivering more of an experience and more outcomes is something that I think companies will continue to embrace.

Along with that, we see companies, service organizations, really looking at how to take that customer journey and find ways to leverage it to create additional revenue streams. So, that, maybe—I could use for example Dish Network. Dish Network historically has been a company that provides, and installs, and services satellite TV equipment. And they've branched out now to where their technicians are also installing equipment from Samsung and different companies. So, they're really taking their traditional service model and sort of "turning it on its head." And with that comes the need for a significant amount of flexibility among the workforce. Because that workforce is going to be asked to do different tasks than they have before. And wear more hats than they had before. And so that's something that I think will continue.

Another is, I think, we will certainly see increased use of AI and augmented reality. Augmented reality, I think, has some significant value propositions for service organizations in a couple areas. One, related specifically to the aging workforce. So, as you have workers that are nearing retirement age, that maybe don't want to be out in the field day to day to day servicing equipment, or what have you. Using augmented reality, you can have an incredibly knowledgeable worker sitting in the back office that may use AR to interact with three, four, five newer technicians in the field, and really provide that hands-on training and support without actually being with them. And I think that that's hugely valuable for companies. Particularly when you can capture those interactions in most augmented reality solutions and sort of build a knowledge library from them. So, at the same time as you're training newer technicians, you're also capturing the tribal knowledge of some of those older workers.

I certainly don't see technicians being replaced by AI, or robots, or an app, or anything else. But I do think, as I alluded to earlier, we will continue to see the automation of non-value-added tasks. So, some of the things that can be automated, will. And that will free up bandwidth from those technicians to focus more on some of the aspects of the job that are going to become more important.

So, as I said, the higher technology used, the higher touch things need to be with the customer—to sort of balance that out. And so, I see AI as a way to give the technicians time back to do more value-added service tasks.

And finally, also related to those tasks becoming automated, I think as that happens, we will also see some re-skilling and up-skilling of the technician workforce. And that could be in a lot of different ways. It could be in more consultative positions, as I mentioned earlier. It could be training. It could be related to making use of that data. It could be related to product development. Or really just back to how the role will evolve, and just focusing more on the human experience, and being more people centric. But I think that there is no denying the fact that the role is going to evolve as we head into the next three to five years. And I think it'll be very, very interesting to see exactly what that looks like.

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November 15, 2019 | 3 Mins Read

Pricing Your Service Contracts: Three Tips for Greater Accuracy

November 15, 2019 | 3 Mins Read

Pricing Your Service Contracts: Three Tips for Greater Accuracy

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By Tom Paquin

Here at The Future of Field Service, we spend a great deal of time discussing the ways that service organizations are reinventing their businesses to be more competitive. Making the decision to fuse service into a product is a great first step, but a lot of organizations discover that their actual execution is unrealistic, poorly-informed, or a bald imitation of their competitors. If you're looking to put your best foot forward, you can do better than that.

A particular area in which we often see stumbling blocks in execution is specifically around service pricing. How do you price your service contracts? As more organizations tie service contracts to outcomes like uptime and output and move away from a warranty model, the importance of accurate and competitive pricing increases dramatically, and the inputs that an affect that pricing do, too. Pricing analysts have been around almost as long as the concept of money itself, and service is just another product category to be tabulated, valued, and commoditized. Nevertheless, the many triggers of service, especially of an outcomes-based model, make this a task with not only a lot of inputs, but the possibility that your actual sources of data might not be consistent or accurate. With that in mind, here are some tips for how to approach informed service pricing.

Audit Your Data Sources

It's no secret that data analysis is only really as valuable as the data that you're pulling from your various sources, but it bears repeating. If your source of truth is incomplete, or inconsistent, or (gasp!) somebody is putting their foot on the scale, it's impossible to get a picture of the total cost of service. The typical data sources utilized for pricing evaluation center around service execution, asset performance, inventory management, and back office utilization. If any one of these things is outputting inaccurate information, then it needs to be remedied with expedience. Moreover, are all of these systems speaking a commonly-integrated language, or are data scientists scrambling to reconcile a common value the define all of these different areas? The importance of a single source of service truth is growing, and new tools will provide greater accuracy from a common language.

Don't Fear Predictive

When your data ducks are in a row, you can start thinking about the technologies that you're employing to price properly. Some organizations are proactively triggering service, or using planning and scheduling optimization to get technicians dispatched most effectively, but that same data can give you a window into the expected cost of a service contract. Historical data from these sources alongside perpetual monitoring of assets and costs of service, when combined with predictive algorithms can now provide a fairly accurate expected lifetime cost of service. Again, though, this is really only a useful as your data sources.

Watch Your Competitors, to a Point

This one's pretty simple. Your competitors’ shifting product and pricing stagey around service can provide a useful line in the sand by which you set your own pricing, but being a follower is not a winning strategy. Competitive differentiation is won through, you know, differentiation. Service done efficiently is now the baseline for success, so businesses looking to better their competition need to think about their service products differently. Don't be afraid to take a divergent stand from your competition. As long as you have the tools to price properly, the visibility of your whole workflow, and the means to audit effectively, you have the tools to become a price leader in a whole new product category.

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November 13, 2019 | 1 Mins Read

Baker Hughes’ Digital Transformation Journey

November 13, 2019 | 1 Mins Read

Baker Hughes’ Digital Transformation Journey

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Carlos Gomez, Regional Services Director for North America at Digital Solutions, a division of Baker Hughes, joins Sarah to discuss the company’s goals, wins, challenges, and lessons learned on its digital transformation journey.

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November 11, 2019 | 3 Mins Read

How Is Your Company’s Structure Undermining Your CX Efforts?

November 11, 2019 | 3 Mins Read

How Is Your Company’s Structure Undermining Your CX Efforts?

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By Sarah Nicastro, Creator, Future of Field Service

On this last week's podcast we be featured an interview with Suman Sarkar, an international consultant and author of new book Customer-Driven Disruption. We had a great conversation and you’ll want to check back here or on your favorite podcast platform to listen to the full episode (New episodes every Wednesday!). That said, one of the points that stood out most to me from Suman’s interview is what he had to say about how organizational silos prevent companies from achieving their CX objectives.

This struck a chord for me because I think that the vast majority of field service organizations today acknowledge and even embrace the need to become truly customer centric. But as Suman pointed out, “knowing and doing are two different things.” Sure, knowing and not doing can be an act of defiance. But more often than not, I think it is a matter of knowing and not knowing how to do. For service organizations, the change necessary to become truly customer centric is in many cases a matter of overhauling some deeply-rooted processes and practices.

One of the biggest changes that needs to occur, according to Suman, is the breakdown of organizational silos. “A siloed structure doesn’t actually enable employees to meet customer needs – it makes them loyal to their bosses rather than being loyal to the customers,” says Suman. “Think about it – as a customer, I don’t care if you’re from IT, service, sales, marketing, the back-office. The silo in which you operate is irrelevant to me and what I want my experience to be.” He brings about a good point in that when you have organizational silos all responsible for their individual objectives, it makes a cohesive – let alone exceptional – customer experience nearly impossible to deliver.

In order to change your company’s structure to enable a more customer-centric approach, Suman suggests four steps:

  1. Change how your employees are incentivized and start at the top. “Seventy to 80% of CEO’s salaries come from stock and stock options,” says Suman. “As a result, CEOs care more about what they are delivering to their shareholders than what they are delivering to their customers. For true change to take place, it has to start here.” Suman believes all employee compensation needs to be tied to customer-focused metrics to create alignment.
  2. Rethink how your teams are structured. Rather than operational silos, Suman urges you to consider creating customer-focused teams so that the focus shifts from the internal goals and objectives outward.
  3. Consider what kind of culture supports a customer focus. “A good company culture doesn’t necessarily equal a customer-centric company culture,” says Suman. He suggests staying focused on delivering speedier and richer results to customers and always looking for ways to create a better experience. For him, examples of companies getting this right include Disney, Southwest, Aldi, and Amazon.
  4. Determine how to hire good people and orient them toward your customers. Your customer experience vision cannot come to life without having the talent to execute on it. Figuring out how to reshape recruiting and hiring practices to bring talent on board that is capable of customer centricity is important, as well as providing thorough training.

Being at the “knowing” phase of your customer centricity journey is a good start, but understand that when it comes to the “doing,” there is some structural, foundational change that needs to occur in most cases for the effort to have the impact you desire.

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November 7, 2019 | 4 Mins Read

The Art of Storytelling to Gain Digital Transformation Buy-In

November 7, 2019 | 4 Mins Read

The Art of Storytelling to Gain Digital Transformation Buy-In

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By Greg Lush

There are those things in your work life that you just never forget. Consider yourself fortunate if you have a few to reflect on over the years. One for me is the first time I tried to explain what was in my head to a data scientist. Let's break down that sentence a bit, first "what was in my head;” not an easy process, regardless of the topic. My married readers have firsthand experience in translating their thoughts or ideas to another human being. "Talking to a data scientist" is in of itself not too much of a challenge, instead I think about it more like speaking with any person in a field of specific expertise. Depending upon the way the question or statement is formed, your message may or may not be communicated effectively. So, you are in a tough spot. How can you take those brilliant ideas which will revolutionize your business, nay, your entire industry, and transport them to the world of artificial intelligence? Not a single week goes by that you do not run across an advertisement, colleague, or manager asking you "why aren't we using AI?” Of course, that is a very vague question, yet one that remains top of mind. Wouldn't it be great if I could just figure out a way to translate my ideas into a workable output?

You might be picking up on the fact that I like to tell stories. I have found that telling a story helps add dimension when required and makes it interesting. A few years ago, I was searching for a tool to help with my story translation needs and ran across a wonderful book. Design A Better Business by Patrick van der Pijl, Justin Lokitz, and Lisa Kay Solomon is a fantastic approach to helping businesses with their challenges written in a creative format; you must check it out. Included with the book is access to a very handy website packed with templates. Trust me, the templates are fantastic. Find the "storytelling" template and read the tips on its use – it is very helpful. The example that I am going to provide will be in context of an Industrial Internet of Things (IIoT) design that we were translating to a handful of data scientists and internal supporters. Our project, which was narrowly scoped, had a total of eight "stories." I started with the business need template to collaborate with the organization and nail down what we were trying to accomplish. Once we came to consensus, I created an outline of which stories would be relevant and support one another. It is critical that you can thread a string through all of the stories. For me, it was tough to get started, even with the tools provided by Design A Better Business. Hopefully this example, based on the IIoT project, will get you kick started:

Story: Unmanned and Unitary (highest level story)

  • Subject: Clients with unmanned buildings, a significant density of unitary systems and a desire to transition to condition-based service and maintenance
  • Goal: Maximize client comfort and asset life by consuming and correlating all factors which holistically affect the building as a constantly changing environment.
  • Audience: Our portfolio clients (with >1 building) and their customers and our internal and external workforces
  • Before: Unmanned and unitary system-based buildings often go together. While larger properties have property managers and central plants; a significant majority of unmanned buildings (94% of all buildings per a survey conducted in 2014) are less sophisticated and in many cases may only have localized elementary control
  • Set the Scene: The simple fact is the barrier to entry to work on unitary systems is quite low. In the small to medium business space it is not unusual to see inexperienced, untrained, and one-to-two-man companies. Without substantial forms of differentiation, we will continue to face margin challenges in a sliding and commoditized labor market
  • What's the Point: To go head-to-head with our competitors, simply turning wrenches is an exercise in futility. Instead our best approach would be to leverage our size and ability to invest in science-based approaches to field service
  • Conclusion: Our ability to invent, test, and tune designs across our broad customer base is unmatched in our service areas. Admittedly our concepts could be perceived as "cutting edge" and a bit risky. However, our efforts today will position us favorably for years to come with respect to margins and available labor
  • After: A digital convergence of data spanning site logistics, PM contract configuration, site automation, financial performance, asset probability of failure, client relationships, influencers affecting the building has a solution, and worker skills. These variables leveraged through artificial intelligence algorithms designed to enhance customer value and increase productivity. Our investments in IOT and science-based approaches will change our industry

Years ago, a CFO I worked with told me, "Greg, the odds of me scrolling down to read content, is very low.” He continued, "Anyone can get their point across in 100 words, yet only the skilled communicators can explain themselves in 10 words.” The folks at Design A Better Business must have also worked with our CFO; you will see that all of their story telling templates are deliberately designed with small fields for your words. It takes me days to write these stories, I take a first pass often packed with too many words. I take a break, come back and whittle down the words. Although not evidenced by this book, I typically shave off double-digit percentages of words. This is not easy; however, you will find that less is more for you, your colleagues, and AI partners.

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November 6, 2019 | 1 Mins Read

Embracing Customer-Driven Disruption

November 6, 2019 | 1 Mins Read

Embracing Customer-Driven Disruption

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Suman Sarkar, international consultant and author of the new book Customer-Driven Disruption, joins Sarah to discuss some of the barriers holding companies back from attaining true customer-centricity.

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