Category Archives: Service and Technology

Vixxo – Monetizing Data & Analytics



This webinar was hosted by the Center for Services Leadership Community of Practice on Monetizing Data and Analytics.

About Vixxo: Vixxo is a leading technology-enabled asset management and business insight company providing integrated facility management solutions and services that unite asset and facility management. Through deep expertise across 100+ trades, time-tested processes, and a comprehensive technology platform, Vixxo delivers the complete asset management that allows clients to focus their energy instead on their customers.

About Warren WellerWarren Weller is the Chief Sales and Marketing Officer at Vixxo, responsible for all aspects of sales, marketing and profitable revenue growth. Prior to joining Vixxo, Mr. Weller held various leadership positions at IBM, serving as the Vice President, Financial Services and also as Vice President, Mid-Market Services. During his 25+ year tenure, he drove operational excellence and innovation across the organization.

Vixxo Case Study

Over the years, Vixxo’s core business model has evolved from providing traditional facility management services, such as lighting, plumbing etc., to offering asset management and optimization services. Moving beyond improving efficiency of traditional assets (e.g. refrigerating, heating), Vixxo has built a highly successful business model around improving efficiency of revenue generating assets, e.g. coffee brewing machines at Starbucks or the baking ovens at supermarkets. The company’s services enable Vixxo’s clients to understand how these assets perform over time, and subsequently make better asset decisions from cost and investment perspectives.

Vixxo currently supports over a billion-dollar worth of spend across 65,000 assets in over 250,000 physical locations. Its primary client segment consists of businesses with widely-distributed retail-estate portfolio (supermarkets, restaurants, convenience stores etc.), where ensuring effective asset management across all locations is a major challenge. By leveraging its expansive supplier network of over 150,000 certified local suppliers, Vixxo is able to provide high quality, consistent services in a very cost-effective manner.

Vixxo’s value proposition to the customers is driven by the company’s 15-year experience in data collection and analytics. Over the years, the company has been able to collect clean and reliable data by leveraging emerging technologies such as mobile devices (tablets, smartphones), to integrate information from clients, suppliers and service centers. Vixxo applies its deep analytics and data mining capabilities to generate insights for clients to improve their CapEx management programs – understanding which assets to repair, replace, invest in etc. for greater customer experience, product reliability and profit maximization.

In the next phase of its evolution, Vixxo is working to monetize IoT and M2M capabilities, by placing sensors inside assets to get real time asset performance information. Sensors can detect and signal issues in assets, allowing Vixxo to dispatch technicians even while the asset is still operating. Vixxo is also focusing on developing the entire IoT eco-system. This includes collaborating with manufacturers to help build assets equipped with IoT capabilities, in exchange for data & insights on asset performance.

Vixxo’s revenue model is based on charging clients for various asset management services they use. The company takes a strong position to ensure clients are paying a fair and transparent price for received services, while the suppliers are guaranteed a prompt payment by Vixxo after each servicing call. Vixxo achieves this by automating its entire work-order management process through the “Continuously Analyzed Pricing System” (CAPS) application, where each supplier locks details of each service they provide to Vixxo’s client. CAPS contains pre-determined and agreed on rates for each element of the work order management process (such as for labor, duration, materials etc), guaranteeing that clients pay a fair market price and receive an itemized breakdown for delivered services. Moreover, Vixxo uses other features such as geo-fencing and supplier rating system to ensure that suppliers provide high quality and timely service. In return, suppliers receive fair and prompt payment for their services as well as training and development.

Backed by its extensive supplier network and over 15 years of data analytical capabilities, Vixxo is a clear leader in the asset management services industry. By implementing and harnessing the IoT and M2M capabilities, the company will be favorably positioned to take full advantage of analyzing granular, real-time data for deeper insights, and to help clients achieve higher profits & operational optimization.

Driving Business Value from Digital Transformation

Webinar with Dr. Michael Wade, Professor of Innovation and Strategy and Cisco Chair in Digital Business Transformation, at IMD Business School, located in Lausanne, Switzerland and Director of the Global Center for Digital Business Transformation, an IMD and Cisco Initiative

Author of Digital Vortex: How Today’s Market Leaders Can Beat Disruptive Competitors at Their Own Game

This webinar was hosted by the Center for Services Leadership Community of Practice on Monetizing Data and Analytics

The Digital Landscape has changed over the past decade. While businesses and companies understand the power of digital innovation, many firms struggle with either taking advantage of the opportunities or reducing risks that accompany digital transformation. Automotive industry is a great example that demonstrates the impact of digital transformation. The push for development of autonomous cars affects a wide spectrum of industries: from transportation & logistics to insurance, law & order, healthcare, hotels etc. Similarly, other innovations such as block-chains, machine learning, virtual reality etc. will potentially have an impact on a number of industries.

While leading digital transformation, companies have to address two fundamental questions: “Why” and “How”. ‘Why’ pertains to understanding the opportunities and threats that exist because of a rapid digitization. “How” covers the capabilities and roadmaps traditional companies need to create to sustain competitive advantage. Yet, data suggests that most digital transformations fail – the reason lies in inability to push for organizational transformation alongside technology transformations.

Beyond technology, companies need to change their approach to business strategy. According to conventional thinking, strategies are developed with a clear understanding of where the company currently is and where it wants to be. However, in today’s world, predicting the future has become extremely complex. Instead, to compete in digitally disruptive environments, companies must build multiple strategies backed by core digital business agility. The following capabilities are key to building digital business agility:

  • Hyperawareness
  • Informed Decision-Making
  • Fast Execution

Hyperawareness is being fully alert to the internal & external environments, particularly to changes that spotlight opportunities or risks. Data & information collection are the core for this principle, which can be accessed by humans, IoT machines or sensors. Key metrics to measure hyperawareness include the company’s ability to capture insights about/from its employees, customers, partners internal operating environment, competitors and about new digital technology & business trends.

Informed decision-making pertains to collaborating & empowering people to make quick, evidence-based decisions. Decision making power needs to be pushed to the edge of the network (Intelligence at the Edge) to gain speed & accuracy. Informed decision making is measured by the business’s ability to make decisions quickly & based on analytics, to empower people, to share information across organization and to access & display important data in real-time.

Finally, fast execution is putting decision into practice rapidly, mobilizing resources dynamically and continuously monitoring options and progress against goals. Fast execution is measured by our ability to act quickly based on new information, turn decisions into actions, dynamically acquire & allocate people & resources, continuously learn & adapt.

IMD’s digitization piano is one of the tools to help companies navigate the “how” of digital transformation. This tool breaks down the organization’s value chain into 10 distinct keys, broadly categorized under Digital Strategy, Digital Engagement & Digital Enablers. Companies should play multiple keys simultaneously instead of trying to address one specific area in isolation as they navigate their digital transformation journey.

Finally, at the core of transformation, the critical questions that companies must ask are:

  • How to use digital technologies to improve performance?
  • How to use digital technologies to build a more agile strategy?
  • How do we digitize across organizations?



BACKGmichael_wadeROUND: Michael Wade is a Professor of Innovation and Strategy at IMD and holds the Cisco Chair in Digital Business Transformation. He is the Director of the Global Center for Digital Business Transformation, an IMD and Cisco Initiative. His areas of expertise relate to strategy, innovation, and digital transformation. Previously, he was the Academic Director of the Kellogg-Schulich Executive MBA Program in Canada. Michael has been nominated for teaching awards in the MBA, International MBA, and Executive MBA programs. He obtained HonoursBA, MBA and PhD degrees from the Richard Ivey School of Business, University of Western Ontario, Canada.

CLIENTS & INDUSTRY EXPERIENCE: At IMD, Michael teaches in several open programs and has directed partnership programs related to strategy and digital business transformation with Vodafone, Ooredoo, AXA, Honda, Zurich Financial Services, Credit Suisse, KONE, and Richemont, among others. He co-Directs IMD’s Orchestrating Winning Performance and Leading Digital Business Transformation programs. He provides consulting services, executive education and expert evaluations to several public and private sector organizations. He has lived and worked in Britain, Canada, Japan, Norway, and Costa Rica.

RESEARCH AND THOUGHT LEADERSHIP: Michael has published works on a variety of topics, including digital business transformation, innovation, social media marketing, information systems strategy, eCommerce, and SME performance. He has more than 50 articles and presentations to his credit in leading academic journals such as Strategic Management Journal, MIS Quarterly and the Communications of the ACM. One of his articles was among the top 20 cited articles in business, management and accounting worldwide for five years, according to Scopus (the largest abstract and citation database of peer-reviewed literature). He’s published eight books, more than twenty case studies and appears frequently in the mainstream media. His Latest book is Digital Vortex: How Today’s Market Leaders Can Beat Disruptive Competitors At Their Own Game. He was named one of the top ten digital thought leaders in Switzerland by Bilanzmagazine in October, 2016.

APPROACH “I define digital business transformation as organizational change through the use of digital technologies to materially improve performance. It is a simple definition, yet difficult to master. Certain industries have been on the vanguard of this changes. Other lag behind. Eventually, digital will become the ‘new normal’. I enjoy working with organizations to help them come to terms about what digital transformation means for them, and then to take appropriate action.”

Service Excellence: Creating Customer Experiences that Build Relationships. Interview with Dr. Ruth Bolton

Podcast Transcript

This podcast is brought to you by the Center for Services Leadership, a groundbreaking research center in the W.P Carey School of Business at Arizona State University. The Center for Services Leadership provides leading edge research and education in the science of service.

Darima Fotheringham: Welcome to the CSL podcast, I’m Darima Fotheringham. Today I’m talking to Dr. Ruth Bolton, Professor of Marketing at the W. P. Carey School of Business at Arizona State University. She is the author of the new book “Service Excellence. Creating Customer Experiences that Build Relationships.” Ruth, thank you so much for joining me today, and congratulations on the new book!

Dr. Ruth Bolton: Thank you. It’s my first book, so I’m very excited.

Darima Fotheringham: It is very exciting! And I really enjoyed reading your book. It covers a lot of ground but it’s not a textbook. It is a very engaging and informative read that you can finish quickly. And it is the type of book that you want to hold on to so that you can go back to it again and again. Can you tell our listeners about what led you to write this book?

Dr. Ruth Bolton: Markets have been changing very rapidly, and I hear from the managers that there are many new opportunities and challenges. However, amidst all this change, managers kept emphasizing the importance of the customer experience. And I was intrigued that this term came from business not from academics. So what was it that managers were seeing that was so important? After thinking about it for some time, I realized that service researchers have a really important perspective to offer on the customer experience. So I decided to write a book about it!

Darima Fotheringham: Great! And it’s very timely. So as you said, customer experience is a really hot topic these days, and in your book, you emphasize a service-centered view of the customer experience. Can you talk about that? Why is this distinction important?

Dr. Ruth Bolton: Well, managers and academics who have been studying services really have a head start and understanding the customer experience. The reason is that, for many years, services research started from the premise that customer experiences are co-created by participants in a network. The participants, of course, are the company, its customers and other partners, such as suppliers. The key idea is that from a co-creation perspective, the goal of each participant is to use the resources and capabilities to support other actors in achieving their goals. So that’s how companies create value for customers.

In a service-centered view, co-creating customer experiences builds profitable relationships. But the emphasis is on innovating, designing and producing experiences that create value for both. So customer participation and engagement become key. Now if you stop and think about it, it explains the emergence of some of the innovative new business models in many industries such as the entertainment industry which is going through tremendous disruption.

Darima Fotheringham: Most companies are fairly up to speed on topics of customer satisfaction, value, loyalty, word-of-mouth, and so forth. I can imagine these are still very important when we talk about the customer experience, but what’s new today?

Dr. Ruth Bolton: Many people are fascinated by the new collaborative services such as Airbnb and Uber. These companies are co-creating with their suppliers, the people who rent out their homes or cars, and with customers, the people who travel. I think that many of us start by thinking that the technology platform, which enables the service, is important. However, the real challenge is how these three partners share information, develop group norms, and work together to achieve their goals. Uber recently recognized the Drivers Association in New York City to facilitate discussions on workplace issues. And if you stop and think about this from a service center perspective, it makes really good business sense.

Darima Fotheringham: Speaking of technology, as you note in your book, technology and new media enable customers and companies to engage in these new ways. Other than Uber, what other interesting and innovative examples can you share about how companies have been able to enhance customer experience using technology?

Dr. Ruth Bolton: I’m especially interested in how B2B companies have leveraged data driven insights to innovate and create value with customers. DuPont Pioneer was able to leverage its expertise in biotech to identify new services that help farmers map and plan how best to replace nitrogen in their fields. It lead to a new service channel and a new market that provides insights and solutions for land management. And the latest I read in the news is that folks are using drones to look at very large properties.

In China, Alibaba Group has built rural service centers in hundreds of Chinese villages so that people can search for products online and place orders as well as sell products through its online marketplaces. With an economic slowdown in China in 2015, the rural service centers are an important opportunity for new growth. So I really find the data driven insights fascinating. And an interesting feature about both these examples is that they improve societal wellbeing as well as creating benefits for customers and profits for firms.

Darima Fotheringham: Which is really great! In the chapter “the Building Blocks of the Customer Experience”, you discuss practical and emotional motives of the customers as they engage and develop relationships with companies. I think companies are usually well aware of the practical motives of their customers, but emotional motives are often much harder to identify. Why is it important that service experience is designed around both practical and emotional motives? And does this mostly apply to B2C companies or does it also matter in the B2B world?

Dr. Ruth Bolton: Oh, emotions matter for business customers too.  Businesses are composed of human beings, and human beings experience a variety of emotions such as fun, excitement, boredom, and frustration when they interact with companies. The starting point is that the business customer and its supplier are each pursuing their own goals, which may or may not be aligned. And within the business-customers organization, employees have specific roles and identities and they have their own goals.

There’s some really solid research showing that people interact with the company to achieve their goals, and when they do achieve them, they’re happy and feel in control. When they can’t make progress towards achieving their goals, look out for annoyance or even customer rage. Take a simple example, imagine a courier service is late in delivering an important package. The employee receiving the package can’t carry out his responsibilities and then there are ripple effects throughout the organization. Will we see customer rage? Quite possibly!

The effects of emotions can magnify aspects of the customer experience that might otherwise seem like small details. For example, I’ve been participating in research for the global retailer that’s been studying shopper satisfaction with the customer experience. We’ve discovered that people’s feeling of fun and frustration play a big role, no matter whether they are shopping in the store, online, or using a catalog. It’s crucially important to meet shoppers’ goals, say whether they’re browsing, searching, or buying, so that you can satisfy them. Interestingly, despite the fact that there are so many technology-enabled services, people still feel emotions in computer mediated environments.

Darima Fotheringham: I personally found the chapter “Managing Customer Relationships to Achieve Growth and Profitability” packed with great and useful insights. In that chapter, you give an example of IBM, how it successfully used the portfolio approach to managing their customers. Can you talk about that and share what we can learn from this example and this kind of approach?

Dr. Ruth Bolton: Yes, IBM successfully navigated the dot-com crash through better management of its customer portfolio, whereas Sun Microsystems did not. I’m really proud of our work looking at customer portfolios. This was a joint effort with Crina Tarasi and other colleagues at ASU, and it’s won some important awards.

You may have heard people talk about the customer asset and how customers produce cash flow streams over time. However, our research team identified an important issue that’s often overlooked, namely that customers’ cash flows are variable over time and that exposes the company to risk. Just like a stock portfolio, a customer portfolio should be diversified to minimize risk for a desired rate of return, and we were able to identify a number of strategies to reduce risk while maintaining profits.

One way is to manage the mix of customers, which is what IBM did. The general approach is to balance the market segments that your company serves so that its decreases in cash flows over time from one market segment are offset by increases in cash flows from another market segment, so that the average cash flow of the organization remains stable. This insight gives an entirely new perspective on market segmentation strategies. It’s particularly helpful for B2B companies because often they segment their markets by small, medium and large customers who have very different cash flow patterns.

Another approach is to work to increase customer satisfaction with their experiences. It turns out that satisfaction has a double whammy effect, lower cash flow variability and higher cash flow levels. I know it sounds too good to be true, but it’s backed up by solid research by many academics. And surprisingly loyalty programs may not always be the answer. Some loyalty programs lead to more variable cash flows, but not higher average cash flows. So companies need to think about designing loyalty programs to improve the experience or the intangible benefits, for example, membership recognition for consumers rather than offering economic incentives.

Darima Fotheringham: Very interesting! In conclusion, what one advice can you give companies that strive to achieve service excellence?

Dr. Ruth Bolton: I think you’re right that most companies know all about service quality, customer satisfaction, loyalty, and so forth. So my advice is: look forwards not backwards. What does the customer want for the future? Customers have goals they’re trying to accomplish by partnering with you so it’s crucial that companies understand what customers want next. In other words:

  • Understand and align with customers goals.
  • Generate trust that you can deliver experiences that satisfy these goals.
  • Offer products that are relevant to customers’ future needs not what they wanted yesterday.
  • And match the customer’s future circumstances.

Darima Fotheringham: Very helpful! Thank you so much. We were talking to Dr. Ruth Bolton, the author of “Service Excellence. Creating Customer Experiences that Build Your Relationships.” Ruth, thank you so much for your time!

Dr. Ruth Bolton: You’re welcome.

For more information on the science of service visit the Center for Services Leadership on the web at


Ruth_BoltonRuth N. Bolton is Professor of Marketing at the W.P. Carey School of Business, Arizona State University. She previously served as 2009-11 Executive Director of the Marketing Science Institute. She studies how organizations can improve business performance over time by creating, maintaining and enhancing relationships with customers. Her recent research has focused on high technology, interactive services sold in global business-to-business markets. She has extensive experience with survey research design, as well as the econometric analysis of large-scale, integrative data bases. Her research is typically conducted in partnership with businesses, such as the Marriott Corporation, Hewlett-Packard and Schneider National Inc.

Leveraging Big Data Analytics to Create Value

Interview with Professor Peter C. Verhoef, a co-author of the new book Creating Value with Big Data Analytics: Making Smart Marketing Decisions.

Podcast Transcript

This podcast was brought to you by the Center for Services Leadership, a ground-breaking research center in the W. P. Carey School of Business at Arizona State University. The Center for Services Leadership provides leading edge research and education in the science of service.

Darima Fotheringham: Today we are talking with Professor Peter C. Verhoef from University of Groningen, The Netherlands. He is a co-author of a new book Creating Value with Big Data Analytics: Making Smart Marketing Decisions. Hello Peter!

Professor Peter C. Verhoef: Hello!

Darima Fotheringham: First of all, congratulations on your new book Creating Value with Big Data Analytics: Making Smart Marketing Decisions. Can you tell the listeners about you and your co-authors and how the idea of the book came around?

Professor Verhoef: I’m a professor of Marketing at the University of Groningen and I have been an expert in, specifically, customer relationship management and customer analytics. My co-authors have been working in practice and are now the founders of MetrixLab Big Data Analytics. They have extensive experience in customer analytics and marketing intelligence. We wrote this book because, first of all, the three of us wanted to share what we learned over the last two decades of our careers. Secondly, we saw that many firms are nowadays struggling with big data, specifically big data analytics and how to create value from these analytics. So we wanted to offer firms, service professionals and students, for instance MBA students, a book about big data and specifically big data analytics.

Darima Fotheringham: Great. Everyone would agree that value creation is the ultimate goal of big data strategy. At the same time, as you pointed out in the book, value has multiple dimensions. There is value to the firm, and value to the customer, also value to the society as a whole. Can you talk about these different perspectives on value? And what is the optimal way to balance these perspectives when developing your big data strategy and should that be your goal?

Professor Verhoef: Indeed, we make a distinction between these concepts. Specifically, value creation to the customer means that you provide customers with, for instance, brand new products, good customer service that creates good experience. You want to make your customers happy. Second, value creation to the firm means that, as a firm, you also aim to benefit from the things you do for your customers. You want to extract value from your customers. For instance, you want your customers to be more loyal or you want them to buy more products or maybe advertise for you and, in that way, bring in new customers. The last concept we talk about is the value to society. What that means is that you are not only focusing on delivering value to customers but also to the grand society. Consider, for instance, the concept of corporate social responsibility and, beyond that, more sustainable value for the long run, a more sustainable development of your firm in the society in the long run.

How do you balance these perspectives in creating your big data strategy? What you’d like to consider actually is, how your marketing actions or your service improvements can benefit your customer while, maybe not in the short run but maybe in the long run, your company can also benefit from that. So we observe, for instance, many firms in the online industry may have very satisfied customers but find it pretty difficult to earn money from these customers. That might work in that industry for some time but in the long run that might not be a sustainable way of doing business. In the end, what you want is to create value for your customers in such a way that you can also benefit from it as a firm by extracting value.

Darima Fotheringham: As you point out in the new book , data analytics have been around for many years, but the recent growth of big data has taken analytics to the next level. Can you talk about a few most important and maybe unexpected changes that took place and give some examples?

Professor Verhoef: Yes. A major change has been that we see the volume of data growing. While in the past we analyzed, for instance, four hundred customers, maybe a thousand customers, we are now analyzing data of one hundred thousand or even one million customers. That has an important implication. For instance, in terms of analyzing data, many things become significant. That means, actually, we are no longer interested in significance. We should move from significance of our results to focusing on the substantive differences. When we analyze a very large database, a small change of, let’s say, 0.001 % can already be significant but, at the same time, the substantive effect can actually very limited. That’s one major change.

Second change is that we are moving from structured data to unstructured data. We still have structured data, but we have more and more unstructured data, especially online. That means that firms have to learn how to analyze and how to interpret these data and learn new techniques. That means, for instance, that companies are using more text mining techniques. It also results in new metrics, digital sentiment indices, for instance, which can tell you more about how customers feel about your brand, about your service.

And the third point that we see changing, in terms of analytics is that are we moving from traditional methods more to computer science methods. You should think about, for instance, neural networks, Bayesian model averaging techniques. That’s a new area which marketers and traditional market analytics people are not as familiar with. So we also see new people, for instance, from computer science coming into our field.

Darima Fotheringham: Very interesting. When we are talking about this volume of data that companies have access to now, we know that questions of data privacy and security have been in limelight lately. You mentioned the case of Edward Snowden in the book and there was an Apple-FBI encryption dispute going on, which is widely discussed by experts but public reaction seems somewhat indifferent or at least so far. In the chapter discussing customer privacy and data security, you mentioned privacy paradox, which I thought was very interesting. Can you explain what that is and talk a little bit about that?

Professor Verhoef: Sure. Well, the privacy paradox suggests that consumers are worried about their privacy, they think it’s important, they think that firms should take care of it, etc. But when you look at their behavior, consumers frequently don’t behave consistently with their beliefs. So there is a strong discrepancy between how they, for instance, deal with their data, what they post on social media, and what they say about privacy. That’s kind of a strange paradox. So briefly, consumers do not behave as they say or they would like to behave when they talk about privacy. That’s an interesting phenomenon. Still, I think privacy is getting more important, as mentioned in the examples. Also, from a legal perspective or a government perspective, specifically in European Union, you see that firms are restricted in how they can use that data. For instance, we observed that some companies are throwing away data, especially nowadays they keep only one year of data in their database. They don’t want to keep the history of customers for long. One of the rationales behind that is the fear of all kinds of privacy regulations.

Darima Fotheringham: When customer data is the life line of the business, digital trust also becomes very important. Based on research in this area, what policies related to data privacy and security issues companies should consider adopting?

Professor Verhoef: Well, there are multiple recommendations I could give. One of the most important things is that you should give control to the consumers or at least they should perceive that they have control. They have to be able to see or be able to control, to some extent, how the firm uses their data. There is an interesting study by Catherine Tucker from MIT. It actually shows that after Facebook implemented such a strategy, the response rates to their commercial activities or some of their commercial approaches to consumers increased. It’s a very interesting phenomenon that when you give consumers more control, they are more likely to respond to your commercial efforts.

Darima Fotheringham: That’s a very interesting effect. In the chapter ‘Building Successful Big Data Capabilities’ you discuss four main building blocks of analytical competence: processes, people, systems and organization. Can you talk about the competences that are most critical yet most challenging for the companies?

Prof Verhoef: In terms of systems, you see that firms now can choose from a wide variety of systems, where in the past you had only a few suppliers. Now you see many suppliers of all kind of databases, cloud solutions, analytical solutions, dashboards, etc. In one way or the other, you should try to build a comprehensive big data ecosystem. The organization aspect looks at how you organize your big data analytics within the firm. Is it for instance, a very centralized staff department? Or are big data analytic teams available in several business lines, several business units? And how do you incorporate their analytics in your decision making? What for instance we see nowadays is that many companies are adopting a multi-disciplinary approach where the big data analytics play a major role.

The people aspect is very important, that’s also where firms face the most challenges. There are some studies, for instance by McKinsey, which actually show that it’s very difficult to find good data scientists. There is a shortage of data scientists on the market. And firms find it very difficult to find these people. In terms of capabilities, they need to have IT capabilities, they need to have data capabilities, know how to deal with different data sources, how to integrate them. They need to have analytical capabilities to be able to do sophisticated analytics, and finally they also need to have some business sense. An important question is, of course: Are the people that have all these capabilities available? Or should you work in big data teams where each of the team members brings some of these capabilities; and, together, they form a very powerful big data analytics group.

Darima Fotheringham: In your book, you actually have an example of a company that created this special program internally to close that capability gap. Can you share that example with us?

Professor Verhoef: Yes. That was a Dutch Telecom company. At the time they had a problem of not having sufficient number of highly trained analytics people. They set up a program called the Marketing Intelligence (MI) Academy together with a consulting agency to train new people. It was an in-house training program, where a part of the time participants were doing coursework, part of the time they were also working within the company. Most of the people who entered that program just came out of a University. They were trained in doing analytics but another important aspect was that these people also applied these new skills to have an impact within the organization. So it was not only about doing analytics but also, for instance, about things like: how do you visualize what you found? or how do you communicate? how do you tell your story to the management? That was an important aspect of the program. In doing so, this company was, at that point, able to build a successful analytics team.

However, many of these companies face problems about how to retain these employees. So building up a successful analytical capability is one thing, the next step is to figure out how you retain your people and how you keep these people happy and satisfied and ensure that they still find challenges in what they do. Especially, given that the people you trained are very, very attractive for other companies as well.

Darima Fotheringham: And in conclusion, what advice would you give to organizations’ leaders as they are navigating the complexities of big data?

Professor Verhoef: I think maybe the most important advice is that you should not consider big data as some kind of revolution, as “the big new thing”. We actually think it’s more of an evolution and, by acknowledging that, it’s very important that you start with small projects which can immediately create value for your firm. For example, we have an example in our book, where we describe a case of an online retailer that wanted to improve their recommendations systems. They started very small and that proved to be successful. Then, they invested strongly in building up these recommendations systems to a much higher level. So start small, and then scale up.

Darima Fotheringham: Thank you again for your interview today. We talked to Professor Peter C. Verhoef, one of the authors of the book Creating Value with Big Data Analytics: Making Smarter Marketing Decisions. Peter, thank you for talking to us.

Professor Verhoef: Thank you.

We want you to be part of the conversation by engaging with us, on our blog and social media channels. Visit our website for more information and links.

Hub-of-All-Things: Breaking Data Silos for a Better Service

The advent of the Internet-of-Things (IoT) in today’s world of connected things and connected people has made it possible for firms to harvest lots of real-time customer data – information from people and objects, and indeed everything.

This is compounded by individuals spending much of their time generating data for others about our lives, placing more and more data about ourselves “on the internet” with firms who are providing services to us. Not surprising then, that each of us has a huge digital footprint.

Even as we are becoming increasingly concerned about the privacy, security, and confidentiality of our own data, we also find that we get almost no value from it. Similarly, although firms are able to collect more and more personal data from us, they get relatively little value from it. This data is often of questionable quality and a lot of processing is needed to convert this “big data” into useful insights on customer trends.

So how can we connect our personal data and look at it all together, to give real insight into the way we live our lives, so that we can make better informed decisions as well as enable firms to come up with more relevant and personalised offerings for our lives? And how do we do so in a safe and privacy-preserving manner?

These are some of the key questions addressed by the Hub-of-all-Things (HAT) multi-disciplinary research project, whose researchers, funded by the UK government, have spent the past 2.5 years building a multi-sided platform for personal data. The HAT personal data platform enables individuals to collect our own data through IoT-enabled objects, and to organise, visualise, control, and exchange this data in the context of our lives – managing our digital selves and putting ourselves at ‘the hub of all things’.

By giving individuals the computational ability to organise our digital assets through a secure platform that enables us to retain control of how we share our data with whomever we choose, the HAT allows us to get the best value from our personal data. It helps us to understand our wants and actions in the context of our lives to make better decisions, and by permitting the exchange of this data with firms, to access offerings more suited to how we live our lives.

This data exchange through the HAT allows firms to better understand the context of their customers’ consumption, enabling them to gain greater insights into customer wants. They are then able to offer customers great products or services that support exactly what they want, when they want it; this provides a big market discriminator and opens up new market opportunities. Better still though, by empowering their customers in returning control of their personal data to them, firms are able to build a better relationship of trust with their customers, thus creating goodwill and loyalty.

With the completion of the research project in Nov 2015, the HAT has now been handed over to the HAT Foundation, a social enterprise that will take forward the next phase of the HAT’s technology for its eventual commercialisation and global rollout in 2017. The Foundation’s operational arm, HATDEX, is on track to launch the beta HAT in July 2016, along with the Rumpel hyperdata browser used to view personal data on the HAT, currently being developed through the HARRIET research project.  This has been made possible by HATDEX’s successful Indiegogo crowdfunding campaign, which hit its £50,000 funding target ahead of its end-April deadline. The campaign now goes into In-Demand and will continue to grow the community of HAT users, whose volume is necessary for the development of the HAT Marketplace for the trading of personal data on the HAT.  Meanwhile, ongoing research on the HAT will also continue through the UK government-funded HAT Living Labs (HALL) project, which will focus on Business Model Innovation within the HAT ecosystem.

The HAT enables the forging of an entirely new social and business contract between individuals and firms in the context of the IoT, one that potentially spurs even more innovation because individuals could be private and secure and firms can offer more innovative services around a mix of all sorts of data. The timing can’t be better as industries are beginning to wake up to the Internet ‘jumping out of the box’ into the physical realm through the Internet-of-Everything. Through the HAT, we can see new ways to create new markets and in doing so, help spur greater growth in the digital economy.


Irene Ng is a Professor of Marketing and Service Systems at WMG, University of Warwick, where she is also director of the International Institute for Product and Service Innovation.  She led the Research Councils UK-funded Hub-of-All-Things (HAT) research project as its Principal Investigator, and continues in this role with the HARRIET and HALL research projects.

Irene Ng will be speaking on “Mastering Service for the Future of Things” at Compete Through Service Symposium, October 26-28, 2016, in Scottsdale, Arizona.

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Co-creating the Arab Spring

skalen_webOn December 17, 2010, Mohamed Bouazizi, a Tunisian street vendor, set himself on fire as a protest against the autocratic regimes in his Arab country. Bouazizi’s act was captured on film and quickly spread throughout the world. The images and film clips of Bouazizi triggered protests and demonstrations against regimes in other Arab countries. Bouazizi set in motion an uprising against Arab regimes that is known as the Arab Spring.

In a study of the Arab Spring, our team spotlights how activists transformed service systems to protest against the autocratic regimes. In many Arab countries press was censored. Through the use of social media platforms, such as Facebook, activists were able to freely share information with each other and with the public. The international media used this information to report on the uprisings that were taking place in the Arab countries. By transforming the media service system, the activists were able to bypass the censorship and report in real time about the acts of oppression by the autocratic regimes and injustice experienced by the greater Arab population.

In addition to the reform of the media service system, the activists also created a service system for the social movement. They used this system to coordinate and organize demonstrations and other protests against the autocratic regimes. When the protests escalated to armed conflict, the activists used the social media channels to arrange access to healthcare therefore transforming the health care service system. The activists transformed these three service systems by co-creating value in advancing democratic ambitions. This was in sharp contrast to the service systems established by incumbents in support of the oppressive regimes.

Value co-creation has become a key focus for service research in the last decade. Previous service research primarily focused on economic value co-creation (i.e., firm profit), but service research can also examine social and cultural value co-creation (i.e., connecting people and educating people about democracy). Our team’s project illustrates how these three types of value co-creation are not only interconnected but also enhance one another. For example, during the Arab Spring the activists informed each other by sharing information about protests and demonstrations via social media. Their main intention was to increase participation and the impact of the protests (social value co-creation). At the same time, the international media was able to use this information as a part of their operations (economic value co-creation) to report about the uprisings in Arab countries capturing the historic event, informing public (cultural value co-creation) and generating social support for the activists.

Value co-creation takes place in service systems constructed by different types of actors and resources. In the Arab Spring case, the actors of service systems are activists, journalists, doctors, etc. The resources they use are smart-phones, social media platforms and knowledge about technology. But it was the conflict between the activists and the regime that triggered the transformation of the service systems. Conflict and contention have not been in the center of either business research or service research, which adopts a more harmonious view of the world. We use social movement theory to argue that the transformation of service systems is always driven by a latent or overt conflict between incumbents who want to preserve status quo and challengers who want change.

The Arab Spring teaches us how service systems, including business systems, transform and work. Although conflicts appear to be negative, the Arab Spring proves that conflict may spark positive transformation. For instance, Tunisia has embarked on a democratic path since the Arab Spring of 2011. The actors behind this positive development, the so-called National Dialogue Quartet, received the Nobel Peace Prize in 2015. However, it also needs to be acknowledged that conflicts may have severe negative effects, best exemplified by the current situation in Syria.

The transformation of the music industry and service systems for distributing music is an example of how conflicts between incumbents and challengers can play out in the business world. The conflict between record companies that wanted to keep distributing music in traditional ways and so-called web-pirates that distributed music for free, but illegally, through the Internet lead to the creation of legal music streaming service firms such as Spotify. By studying what appears as negative events we can learn more about the positive transformation these negative events can lead to.

The research paper “Cocreating the Arab Spring Understanding Transformation of Service Systems in Contention” discussed in the post was published in Journal of Service Research August issue of 2015,   vol. 18 no. 3 250-264. It was the winner of the Best Paper Award for the Special Issue on Transformative Service Research.

Aligning Business Model & Culture to Maximize the Analytics Opportunity

In a recent blog post Analytics in Services: Actions versus Talk, we reviewed how companies are applying big data and analytics for both internal and external uses. That review led to a survey and executive panel discussion at the November 2015 Arizona State University Center for Services Leadership (CSL) Annual Compete Through Service Symposium where we further explored adoption rates, challenges, and lessons learned.

Adoption rates

The survey of 42 CSL member-companies and Symposium attendees revealed that roughly 25% have actually deployed initiatives using this technology, 25% have not considered how they will utilize analytics, and approximately 50% are developing a plan or are in pilot. Interestingly, these percentages are consistent whether companies are trying to improve marketing effectiveness and operational efficiency, helping set service levels, or attempting to expand markets and build new sources of services and solutions revenue.



The survey also asked respondents to describe what they were doing in each of these areas, from which the panel discussed several case studies in some detail. What emerged was an interesting set of objectives that can be captured as:

  • Efficiency – improve operational efficiency and reduce risk.
  • Experience – enhance every aspect of the customer’s experience.
  • Expansion – generate new services-based revenue streams.

As noted in our prior blog, the drive for efficiency has been well documented and the data reinforces that it is the most broadly adopted.

The second area, experience, generated a great deal of discussion and it became clear that this is where much of the energy in the market is focused. Experience encompasses all aspects of the customers’ journey: understanding each as an individual, marketing more effectively, setting and attaining appropriate service levels, providing support proactively, and anticipating future needs. It was evident that for a number of respondents this was the path to revenue growth both in terms of wallet share and market share.

Which leads to the third objective, expansion. A number of technology companies are aggressively pursuing the opportunity to be suppliers of technology, infrastructure, and consulting for analytics. However, a relative few organizations are also leveraging analytics to turn the data they own/access along with their expertise to generate new services revenue streams.

The executive panel was comprised of companies who fell into both of these categories: Siemens, IBM, DuPont Pioneer and Intel.


A broad set of inhibitors were cited by the survey respondents and we subsequently discussed during the panel. The challenges fell into three major categories, with some unexpected challenges emerging:


  • Data

There were two distinct sets of issues identified here. The first regarded the capture, integration, and filtering of data from a rapidly growing array of sources.
The second set of issues centered on data security/privacy/rights/integrity – and the potential financial and brand risks of getting it wrong.

  • Resources & Infrastructure

Not surprisingly, skills in data science and analytics were frequently cited. Not only acquiring a skill set that is not traditionally found in many companies, but also nurturing and retaining those critical resources in a highly competitive market.
The infrastructure necessary to support new analytical workloads and the growing volume of data was something that many respondents cited as a ‘hidden’ cost—or at least one which was not always factored in up front.

  • Business Model

The most frequently cited issues were associated with establishing a clear and compelling business model—particularly in regards to establishing new services revenue streams. The age-old challenge of competing priorities was compounded by the lack of effective means for calculating the ROI for the customer and the concerns over financial risk cited above. As one panelist pointed out, we are entering an age where data is the new currency—and yet there is no accepted methodology for measuring ‘return on data’.

Summary – Ideas to Consider

The executive panel shared their insights and made some compelling suggestions for companies considering leveraging big data and analytics to drive top line growth. Ideas that were discussed in the interactive session with the symposium attendees included:

  • Integrating internal & multiple external data sources combined with your expertise for more value
  • Identifying new markets and buyers for the services offerings based on data + analytics + expertise
  • Developing a ‘skunk works’ first-of-a-kind team to launch and experiment—avoiding the culture trap
  • Bringing on new skills and augment with university and industry programs
  • Considering building a partner eco-system to fill gaps in your infrastructure and skills
  • Establishing credible means for measuring the ROI for both the customer and the business