Tag Archives: CoP

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.”

CSL Leads a Conversation on Leveraging Big Data & Analytics for Service Innovation and Growth at ISBM Academic Conference

Institute for the Study of Business Markets (ISBM) of PennState Smeal College of Business held its biannual academic conference “Advances in Business-to-Business Marketing” in August 2016 in Atlanta, Georgia. Center for Services Leadership (CSL) was invited to to lead a session on Leveraging Big Data & Analytics for Service Innovation and Growth: Promising Research Avenues Grounded in Managerial Practice with managers and academics to discuss managerial challenges and identify promising research avenues.

The session was led by Wolfgang Ulaga, CSL’s Co-Executive Director and AT&T Professor of Services Leadership at W. P. Carey School of Business, ASU. In his presentation he discussed some of the pressing issues identified by CSL’s member companies who are collaborating with Center for Services Leadership in a Community of Practice on Big Data and Analytics.

Center for Services Leadership was joined in the conversation by Georgia State University’s Center for Business and Industrial Marketing and PennState University’s Institute for the Study of Business Markets. The session included a diverse panel of experts who offered business and academic perspectives on the topic. The panelists included:

  • Jagannath Rao, President, Customer Services Business Unit, Siemens Inc.;
    Board Member, Center for Services Leadership, Arizona State University.
  • Wesley J. Johnston, CBIM RoundTable Professor of Marketing and Executive Director,
    Center for Business and Industrial Marketing (CBIM), Georgia State University.
  • Gary L. Lilien, Distinguished Research Professor of Management Science, Smeal College of Business, Pennsylvania State University, Research Director, Institute for the Study of Business Markets (ISBM)

Over the next months we will be sharing the highlights from this session and will update you on the work that Center for Services Leadership will be doing in partnership with its member companies in the area of Leveraging Big Data & Analytics for Service Innovation and Growth. Make sure to follow our blog to receive these updates.

Also, don’t miss session Monetizing Data and Analytics for Service Innovation and Growth: Commercial Challenges and Best Practices with Dr. Wolfgang Ulaga and Ed Petrozelli, CSL Board Member, President and CEO of The INSIGHT Group. This session will take place on Thursday, October 27th, 2016, at Compete Through Service Symposium in Scottsdale, Arizona. Visit our website to learn more and to register. We hope to see you there!


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.