11 October 2014

GE, The Industrial Internet and the Battle to Come

During Cambridge Service Week this year we heard from Stefan Bungart, Leader of GE Software Europe. Stefan talked about GE's development of a new services platform - Predix. Think of the iStore, but for the industrial internet. GE's position is that it wants Predix to become an openly available platform that can host apps developed by others - apps that are used to remotely monitor and manage machines and equipment, indeed any device connected to the internet - hence the industrial internet.

You could argue that Apple, Facebook and Google have largely sewn up the business to consumer internet - they are the dominant platforms. Other platforms may emerge, but they face an uphill battle to overcome the incumbent players. The industrial internet, however, is still wide open. We don't yet have any dominant players and they may never emerge. However, manufacturing firms across all sectors recognise the way the world is moving. More and more devices are being connected to the internet. These devices are feeding data back to central control hubs and the best of these are using the data to make predictions about product performance and how this can be optimized, as well as using the data to inform future generations of product design. The question - hence the battle to come - is which firms will dominate the industrial internet.

GE has already declared its intent - in 2015 the Predix platform will be made publicly available. Jeff Immelt, Chairman and CEO of GE is quoted as saying "the more we can connect, monitor, and manage the world’s machines, the more insight and visibility we can give our customers to reduce unplanned downtime and increase predictability. By opening up Predix to the world, companies of any size and in any industry can benefit from the investments GE has made by eliminating the barrier to entry". What he doesn't say is what happens to the data that all of these devices generate as it passes through the GE platform. GE is reported to use 10 million sensors to monitor daily 50 million data points across $1 trillion of managed assets. The businesses order backlog is around $180 billion - a number that continues to grow as the installed base of GE assets and those that GE helps monitor increases in size. Will GE be the equivalent of Apple, Facebook and Google for the industrial internet or will someone else seize this market? Potential competitors from the software, applications and consulting industry might include IBM, Microsoft or Tata. From an industrial perspective the smart money might be on Hitachi, Samsung or Siemens. How about Apple, Google or Facebook? Can and will they make the transition to the industrial internet?

The jury's out on how this opportunity will develop, but one thing is clear. The battle for the industrial internet will heat up in the next few years. The potential for innovation and greater efficiency in product and service design, as well as operation and maintenance is too great. The winners of this race will have access to unparalleled data that if used insightfully will drive significant service efficiency and innovation. Firms will still have to deliver great service - they'll have to get the basics right - but they'll do so from a rich and data-informed position that will put them ahead of the rest of the pack and so confer significant competitive advantage.

8 July 2014

How Wearable Technology can help Servitization

Don’t switch off your Google Glass headset yet, says Professor Andy Neely, Director of the Cambridge Service Alliance. Whether it is the latest headset or even a new Smartwatch the information being gathered by the wearables is offering some really interesting opportunities for innovation in products and services. He says the information gathered by Wearable’s will have positive outcomes for firms and society more generally.

If patients can monitor their own blood pressure automatically or heart rates automatically potentially then they could feed that data back to the hospital or the doctor and they could then be smarter at how they allocate their limited resources. The doctor could be sent the data the patients were getting from monitoring their own blood pressures, and this would allow them to call in the patients with problems for further investigation.  The technology allows organisations to allocate their resource more efficiently which in the long run is going to be better for the tax payer and Society generally.

Andy uses the example of a technician, who may go out to repair something and they may look at the appliance and not know how to repair it. But if they had Google Glass they could potentially stream a video back to their base and ask other experts around the World for their suggestions too.  Support teams won’t need to travel to the site, they could offer suggestions to your technician about how to repair it and they could then carry out their suggestions. The technician could then upload their video to the internal intranet and others could then access it too if they came across the same problem sometime. 
Wearable technology can improve the quality and efficiency of the way in which services are delivered. The value is in the data, not the metal, that’s for sure. Making that shift to services requires a significant organisational change, but the key to making this change is understanding your customer and your customer’s customer, says Andy. The wearables will enable you to start that journey. 

Listen to a PODCAST by Andy Neely on this topic. In this Podcast Interview Professor Andy Neely, Director of the Cambridge Service Alliance, examines how the new Wearable technologies can help firms make the shift to services 

29 May 2014

Is servitization for everyone?

One of the questions I have been asking my students recently is whether "servitization is a strategy for everyone". Effectively I ask them to take any product they wish and develop an idea for a service that is directly related to the product. The students have come up with some great ideas. One group developed a business model for renting umbrellas. Imagine having umbrella rental kiosks at busy main line stations in London. You arrive at Kings Cross, without an umbrella, only to find it is raining. Rather than buying an overpriced umbrella in a local store, you can rent one for a day and if you don't return it, you forfeit your deposit, but are then allowed to keep the umbrella. Another group developed a business model for exchanging baby products - a store where you could buy second hand cots, toys and prams (all of which had been fully refurbished and reconditioned). As your baby grows older and bigger the store would take back products you no longer needed and sell you a new set - a child's bed rather than a cot or toys for a three year old, rather than a new born baby. Any products you returned to the shop would be refurbished, reconditioned and sold on to a new set of parents. Yet other groups have suggested technologically enabled services. One team came up with the idea of machine tool manufacturers offering environmental monitoring services. This group proposed that firms should couple an energy monitoring service with the machine tools they sell. In essence the manufacturer of the machine tool would provide guidance and advice on how to reduce energy consumption of capital equipment.

While the ideas themselves are interesting, one of the things that I have found most fascinating is that nobody has yet come up with a product that could not be accompanied by a service. Luxury goods - where ownership might confer status - are appealing as rental items. Why own that fantastic diamond necklace (and carry the risks and costs associated with ownership of a very valuable piece of jewellery) when you can rent whatever jewellery you want for particular events. A counter argument might be that jewellery as a gift is important. If I told my wife that I had rented our wedding ring rather than bought it for her I might get short shrift. But the jeweller who sold me the ring offers a reconditioning service, a personalisation service and could offer a consultancy service, providing advice on which product to select.

Move to the other end of the scale and think about commodity products. Take something as simple as a paperclip. What service could be associated with paperclips? At first blush this appears to be a more challenging question. Paperclips are so plentiful and cheap that it is more difficult to conceive a service. But think about how many paperclips are wasted, taken off sheets of paper and dropped in the bin or put in that jar that sits on your desk and gradually fills to overflowing. What about a service centred around paperclip recycling, where unwanted paperclips (like spent batteries) are collected and returned to source. What about paperclips with RFID tags on them - paperclips that could provide location information so you would never again lose that important document in a pile of paperwork!

The more I think about it, the more I feel that the world of services and solutions is endless. Some of my academic colleagues argue that products are only ever a means to deliver services. I wouldn't go quite that far, but I think it is right to say that all products can be supported or supplemented by services. I'd be interested to hear of examples of products that you think it would be difficult to support or supplement with services.

12 May 2014

Why SMEs need to put their feet on the starting line to ensure they can capture value from data…ready, steady, go!

Andy Neely - Interviewed on SMEs and Big Data
In this interconnected World all sorts of devices are creating data all of the time from when you use your mobile or when you log into the Web, or when you use cards to shop in stores or online. The systems for capturing and storing data are becoming better and faster.

With all of this innovation there is a risk for SMEs that they won’t be able to compete in this so called Big Data World. They will need to build their capabilities to understand and analyse all forms of data to make sense of it. They will need to put in place the technology to capture the data and ensure they have the right professional advice to use it, and draw up the appropriate legal agreements.   It could be that only large firms can afford these costs, but another option for the SME is to think about who they can partner with, and how can they build or share the infrastructure to capture and analyse data rather than do it all themselves. 

SMEs need to think through their data strategy clearly to ensure that they are not beaten to the starting-line by new start-ups who may launch using publicly created data sources such as Facebook or Twitter. 

However,  the issue is not one of “Big” but that of “Data”, the value lies in how SMEs us their data more generally. SMES need to do three things. They need to explore their options with data and ask what does data allow them to do that they can’t currently do? They will need to think about how the data might allow them to monitor the use of their products, or better manage their supply chains. They will need to think through who their partners are, alliances will become central to their success.  Thirdly, they will need to ask where the value in the data sits for them and how they capture that value as an SME rather than just let it leak out to other organisations in the market.  Fast footwork is going to be useful for them when the whistle blows on that starting line.

3 April 2014

Big Data for Big Business?

 March Paper

A Taxonomy of Data-driven Business Models used by Start-up Firms

The exponential growth of available and potentially valuable data compounded by the Internet, social media, cloud computing and mobile devices – often referred to as big data, has an embedded value potential that must be commercialised. Correspondingly, the quote ‘Data is the new oil’ (WEF, 2011; Rotella, 2012) became widespread and established the analogy to natural resources needing to be exploited and refined to guarantee growth and profit.

Some studies estimate an increase of annually created, replicated and consumed data from around 1,200 exabytes in 2010 to 40,000 exabytes in 2020 (Gantz and Reinsel, 2012). In some industries, such as financial services, big data has spurred entirely new business models. The CEBR (2012) has speculated that the benefits of big data innovation opportunities are projected to contribute £24 billion to the UK economy between 2012 and 2017, while the increased prospects for small start-up creation are projected to be worth £42 billion. New jobs related to big data are estimated to reach 58,000 over the same period.

In terms of exploiting data as a resource, business models supporting data-related ventures to capture value, subsequently called data-driven business models (DDBM), are needed. Notably, scholars have published surprisingly little on this topic. Hence, understanding what business models relying on data look like remains a research question. Thus, a recent study developed by the Cambridge Service Alliance contributes to closing this literature gap and focuses on identifying the different types of data-driven business model in the start-up scene – paying attention to their commercialisation approach, irrespective of their current financial success. The study aimed to contribute to answering the overarching research question:

“What types of business model are present among companies relying on data as a resource of major importance for their business (key resource)?”

In order to answer this question:

Firstly, we have to define the term ‘data-driven business model’ (DDBM), which has not yet been defined in the scholarly literature. Therefore, this paper contributes by providing a definition of a data-driven business model as a business model that relies on data as a key resourceThis definition has three implications. First, a data-driven business model is not limited to companies conducting analytics, but also includes companies that are ‘merely’ aggregating or collecting data. Second, a company may sell not just data or information, but also any other product or service that relies on data as a key resource. An example is a company called kinsa, which sells thermometers for the iPhone and provides a service to constantly monitor the body temperature. Third, it is obvious that any company uses data in some way to conduct business – even a small restaurant relies on the contact details of its suppliers and uses a reservation book. However, the focus lies on companies that are using data as a key resource for their business model.

Secondlydevelop a framework that allows systematic analysis and comparison of data-driven business models. Therefore, this paper proposes a data-driven business model framework (DDBM). The framework aims to provide a set of possible attributes for every business model dimension to comprehensively describe any DDBM. It was developed in two steps. First, the dimensions of the data-driven business model framework (DDBM) were derived from a systematic review of six of the most important existing business model frameworks, measured by the number of citations. Second, for each of the identified dimensions, a collectively exhaustive set of features was identified using literature from related disciplines, for example, data warehousing, business intelligence, data mining, and cloud-based business models. Based on this review, the DDBM framework consists of six dimensions with in total 35 features to most of the business model frameworks, namely, key resources, key activities, value proposition, customer segment, revenue model and cost structure. For each of these six dimensions, features were derived from literature to be able to exhaustively describe the DDBM.

DDBM Framework

Thirdly, develop a taxonomy to identify clusters of companies with similar business models exist in the identified sample. To develop this taxonomy, business model descriptions of a random sample of 100 start-up firms were coded using the DDBM framework. By a subsequent application of clustering algorithms to the coded descriptions different types of business model were identified:

DDBM matrix of centroids
  • Type A: ‘Free data collector and aggregator’: Companies of this type create value by collecting and aggregating data from a vast number of different, mostly free, available data sources. Subsequently, the other distinctive key activity is data distribution, for example, through an API or Web-based dashboard. Other key activities performed by companies of this type are data crawling (35%) and visualisation (24%). While companies of this type are characterised by the use of free available data (100%) – mostly social media data (65%) – other data sources like proprietary acquired data (12%) or crowdsourced data (12%) are also aggregated by some of the companies. 
  • Type B: ‘Analytics-as-a-service’: The second cluster comprises companies providing analytics as a service. These companies are characterised by conducting analytics (100%) on data provided by their customers (100%). Further noteworthy activities include data distribution (36%), mainly through providing access to the analytics results via an API and visualisation of the analytics results (36%). In addition to the data provided by customers, some companies of this type also include other data sources, mainly to improve the analytics. Sendify, for example, a company providing real-time inbound caller scoring, also joins external demographic data with inbound call data to improve the analysis
  • Type C: ‘Data generation and analysis’: Companies in this cluster all share the common characteristic that they generate data themselves rather than relying on existing data. Subsequently, all companies in this cluster share the key activity ‘data generation’. Besides generating data, most of the companies also perform analytics on this data. Within the cluster, companies can be roughly subdivided into three groups: companies that generate data through crowdsourcing; Web analytics companies; and companies that generate data through smartphones or other physical sensors 
  • Type D: ‘Free data knowledge discovery’: The companies in this cluster are characterised by the use of free available data and analytics performed on this data. Furthermore, as not all free data sources are available in a machine-readable format, some such companies crawl data from the Web (data generation 50%). An archetypical example of a ‘free data knowledge discovery’ company of this type is Gild, which provides a service for companies by helping them to recruit developers. To identify talented programmers, Gild automatically evaluates the code they publish on open source sites like GitHub or Google Code, as well as their contribution on Q&A websites like Stack Overflow. Based on this evaluation, a score is created that expresses the strength of a developer and allows hidden talents to be identified (Gild, 2013).
  •  Type E: ‘Data-aggregation-as-a-service‘: Companies in this cluster create value neither by analysing nor creating data but through aggregating data from multiple internal sources for their customers. This cluster can therefore be labelled ‘aggregation-as-a-service’. After aggregating the data, the companies provide the data through various interfaces (distribution: 83%) and/or visualise it (33%). The areas of application are focused mostly on aggregating customer data from different sources (e.g. Bluenose) or from individuals (e.g. Who@) within an organisation. Other companies focus on specific segments or problems. AlwaysPrepped, for example, helps teachers to monitor their students’ performance by aggregating data from multiple education programmes and websites. Similar to Type B (‘analytics-as-a-service’), the revenue models of such companies are primarily subscription-based and mainly business customers are targeted
  • Type F: ‘Multi-source data mash-up and analysis’: Cluster F contains companies that aggregate data provided by their customers with other external, mostly free, available data sources, and perform analytics on this data. The offering of companies in this cluster is characterised by using other external data sources to enrich or benchmark customer data. A typical example of a business model of this type is Welovroi, a Web-based digital marketing monitoring and analysing tool that allows tracking of a large number of different metrics based on data provided by customers. However, Welovroi also integrates external data and allows benchmarking of the success of marketing campaigns.
To conclude, the study provides a series of implications that may be particularly helpful to companies already leveraging ‘big data’ for their businesses or planning to do so. The proposed Data Driven Business Model (DDBM) framework represents a basis for the analysis and clustering of business models. For practitioners the dimensions and various features may provide guidance on possibilities to form a business model for their specific venture. The framework allows identification and assessment of available potential data sources that can be used in a new DDBM. It also provides comprehensive sets of potential key activities as well as revenue models.

Cambridge Service Alliance

1 March 2014

The Big Data Revolution: What Happened to Data Quality?

There's a wonderful irony in the world of Big Data Analytics. At a time when interest in Big Data appears to be growing exponentially, it appears that some are forgetting the fundamental challenges of Data Quality. A quick Google Trends analysis highlights the point. The chart below shows two trend lines extracted from Google Trends. The line in blue reflects the popularity of searches for Big Data, while the line in red shows the popularity of searches for Data Quality. It is important to note that the lines show relative popularity, not absolute volumes of search terms. In fact, Google Keywords suggests that in absolute terms searches for Big Data are about 20 times as popular as searches for Data Quality.

This raises an interesting question - what's happened to Data Quality? At a time when organisations are becoming ever more interested in using their data to create performance insights and predictions, interest the Data Quality appears to be declining. Is this because Data Quality is no longer an issue?

I don't think so. On three separate occasions in the last week alone I have been involved in discussions with senior managers from some of the world's leading manufacturing and service businesses. Each time, the issue of Data Quality has come up loud and clear. These firms recognise the potential of Big Data and Analytics, but are realistic enough to know that unless they sort out their data fundamentals - unless the track the right things and make sure the raw data if accessible and of high quality, all of the Big Data Analytics in the world is not going to help them. That's why - in the Cambridge Service Alliance - one of our projects this year is focusing on creating a data diagnostic - a methodology that can be used to check whether the data you have access to is appropriate and can be better used to optimise the delivery of your services and solutions. We're in the process of testing this data diagnostic at the moment and would love to hear from you if you'd be interested in being one of the pilot test sites.

17 February 2014

How UK Manufacturing Firms Can Create a Business Model Fit for Exports in 2014

I am optimistic that during 2014, UK companies will be exporting more if they can think radically about what the future holds for them and about what role technology will play. They need to be able to deliver value to their customers. To achieve that they will need to create new business models. They will need to put their traditional business model under the spotlight, and do some robust thinking about how they are offering good products and services to their customers, but I think there are excellent reasons to be optimistic and at the Cambridge Service Alliance, we see lots of manufacturing firms moving forward and succeeding.  Our partners  BAE systems, Caterpillar, IBM and Pearson’s have been pioneering new ways for manufacturing companies to capture value and they have lessons they can impart to others.

Take the use of technology for example. We know that the World is becoming more “instrumented", that companies are using more and more “senses” and that those senses are connected to the net and that they are “intelligent”. Those “senses” can help customers make smarter decisions. My mobile phone company knows when I leave my home because my phone starts moving. It knows when I walk to the station because it knows the pace that my phone is moving because it is tracking the GPS signal. It therefore knows the train I am catching because it knows when I start moving from a walking pace to moving to a train pace. It can predict what time I am getting into London, and it can text me a voucher saying: “Get 15 p off a cup of coffee between 8.45 am and 9 am on this particular morning”! Unbelievably it knows that my train is going to arrive in London at 8.40 am and wants to encourage me to go and buy coffee from a particular stand at Kings Cross station.

This technology already exists, I am not talking about a mythical future, it is already here and there are now endless new ways in which you can innovate your business model, to create new value for your customers.

Capturing all of the value in your business model that new technology can add will not be a quick process, it will take time. But we need to wake up to the reality that the changes taking place in manufacturing over the next five to 20 years are really profound. Manufacturing firms need to ensure that as we enter 2014 they have to be there and ready to capitalise on the economic recovery that is most likely taking place around the Globe. They will need to put their hard manufacturing yellow hats on to think about the longer term and how they can build a sustainable new business model in the light of some of the incredibly profound changes that are taking place in our economy.   
Clearly with the fast pace of technological change taking place all over the World traditional Strategic Plans will need to undergo radical change and need more flexibility than ever before. Long  term planning is essential, and our UK manufacturing firms will have to make predictions about where the World is going and they will need to think carefully about how they build the right capabilities in their organisations to capture the value from those changes. They must not lock themselves into one single path they must think about what we at the Alliance term “the alternative futures” scenario. Their business models  will need  to reveal the real future trends across sectors with a World class strategy that supports those trends.

They will need flexibility in the longer term to be able to adapt and respond to the way that the economies they are working in move, and also the way the technology moves too. They will need to be nimble and respond quickly to those challenges and changes.

One trend that they will need to be aware of, is that the traditional classification of sectors is breaking down. There will over time be a convergence of certain sectors, particularly where those sectors rely on data. There is an interesting question about what role Google or companies like IBM will play in those sectors  in the future. Both are really good at analysing data so will they suddenly find themselves in sectors that they haven’t traditionally been big players in?

Their business models will need to take into account what their competitors are doing, where their partners are and who they are collaborating with and wish to partner with in the future. It may just be right for them to embrace their traditional competitors and work with them in some way at some time in the not too distant future. This new “strategic thought” will influence their future success.

We are used to the term “ Big M manufacturing” and are aware of how manufacturing companies are supplying services to sustain the assets they sell to others for the entire life-time of these products. Manufacturing firms now work with others running everything, from the initial concept and the initial idea,  through to the design and the production process. The relatively narrow concept that people have technically thought of as manufacturing has now expanded to include the distribution of products, and the service and support and ultimately end of life care of those products, including recycling the products and components! Now that is impressive.

We know that “Big M manufacturing”, adds value across that entire set of activities that a company offers, and that manufacturing is evolving and will continue to evolve during 2014 and beyond. This new industrial age we have entered is unbelievably exciting. Factories matter, the production process matters, but manufacturing is now part of a much broader chain of services companies can supply to their customers.

One of the figures that gets quoted often is that for every pound you spend on the initial product, you spend something like four pounds on the service and support of that product through its life time. When products are created we need to think of the “through life” value and support.

For a  business model to succeed in 2014, firms will need to be innovative, a much overused word. The challenge for manufacturing companies will be to think differently about the role that their business plays and how they are going to create value from that role.  A lot of that new value is going to be created by data and technology.

I would advise companies to think robustly about the way that they can use data, either to improve the efficiency of their products and services, or to improve their customers efficiency. If they get  that combination right, particularly the innovation that can come about around the use of new data, their 2014 business models will stand a greater chance of success.   

Here we talk about how UK firms can capture value from exporting more to the BRICS, Brazil, Russia, India and China, but we need to remember that this is a global race, and that the BRIC economies will also be adapting their business models too. They know that they ARE having the same conversation and are also working towards making manufacturing fit for the 21st Century.
Manufacturers as exporters can’t afford to ignore this global race, but they will need to make the right decisions, and to realise that “Big M manufacturing” is already a reality for many of the companies they are competing with.

My first Tip for 2014 is to get companies to focus on the outcomes that their customer wants. That outcome focus will lead to more profitable companies in the longer term. Customers don’t just want your products, they want the service or solution that the product offers and if you can give customers that final solution you will succeed. It  means that companies will really need to be clear about what their customer value is.

My second Tip for 2014 is to define what you are going to do in-house, and what you are going to ask others to do for you? How you collaborate and partner with people will be pivotal to your success.

My third Tip for 2014 is to understand some of the risk that is inherent when you start to move to these outcome based contracts. Companies will need to review what risk they are taking on, and how they mitigate those risks?

If they get these three things right, if they get the customer outcome right, the value delivery system right and understand the risk and the accountability spread, then I think UK manufacturing companies will be in a good position to capture value from their business models in 2014.

And one more tip from that Smarter planet phrase that IBM has coined. You DO undoubtedly have to think smarter. The World is getting more complicated for manufacturing firms, partly because sectors are breaking down and partly because of the speed at which technology is developing, but that also means there are many new opportunities that are opening up. Thinking smarter and thinking strategically about what you will and what you will not do is essential.

I know that the manufacturing renaissance is not just a vision for many UK manufacturing firms it is already a reality. Some are doing very well providing both products and services in this country and overseas. The market may be difficult, and it may be challenging, but there are many firms UK firms who already have a firm foot in that renaissance for manufacturing. They have got their business models right, and others will need to follow the lead they are setting in 2014.

Andy Neely, Cambridge Service Alliance

5 February 2014

First Electric Vehicle Project in the World for holidaymakers in Okinawa, Japan, struggles to make a profit

Researchers at the Cambridge Service Alliance at Cambridge University, have suggested new ways of increasing the uptake of electric car usage. They have just published a new paper on a pioneering Electric vehicle rental service for holidaymakers in Okinawa Japan, and found that low usage has led to a loss for the car rental companies. It is one of the first EV rental projects of its kind in the World and aims to help improve the environmental sustainability of tourism on the island of Okinawa, Japan. 

The search for alternative fuels to reduce car CO2 emissions is an important part of the climate change challenge. In Japan 18 per cent of total CO2 emissions are caused by road transportation, in the EU it is around 12 percent. In China car usage is expected to rise from 43 cars per 1,000 in 2010 to 320 cars per 1,000 in 2035, thereby increasing the pressure to find alternative sources of fuel.  

The paper called: 'Electric vehicle rental services: Project in Okinawa, Japan', written by PhD researcher Claire Weiller, in collaboration with the Department of Systems Innovation, University of Tokyo, concludes:
“The Okinawa EV rental service at the end of its first three-year operational phase in 2013, missed its initial targets. Low usage rates mean rental companies are making a loss. Customers worry about insufficient recharging infrastructure. Sales of used rental cars are low.”
Ms Weiller suggests an ecosystems approach, favoured by the Cambridge Service Alliance, whose partners include BAE Systems, Caterpillar, IBM, and Pearson says this could help turn around the project for others wanting to introduce similar schemes in the future. She continued:
”By adopting an ecosystems approach we can look at all the companies that are involved in providing this service and that affect the outcome of this service, for instance we found there was a lack of information sharing between them all.“The information was broken down into all the different components. They were keeping the data to themselves so Nissan kept information about the battery in the car, the travel agents keep information about the customers who book their holidays, but the charging company on the Island, for example, doesn’t have this information, it doesn’t know if the user is just one person or a family. Therefore it was difficult to tailor the service or improve it for the customer.“If the customer worries about whether they will be able to drive from the airport on the South of the Island to the beaches on the North of the Island, and there is no-one in the value chain able to answer that question they will not feel reassured about the rental service. An ecosystems approach can change that. ”    
Professor Andy Neely, Director of the Cambridge Service Alliance said: 
“An ecosystems approach could be beneficial to those involved in the EV scheme in Okinawa, in Japan. All the partners involved need to think about how to capture value from the information they have in order to serve the customer better.”
“It is very conceivable that this type of rental service with electric vehicles will be offered by more and more countries, including in the UK where there are plans to develop the charging network to 70,000 stations by 2020.“Electric vehicles really are a great option for the transportation of the future, for environmental reasons to reduce greenhouse gas emissions, and also for economic reasons. This makes them attractive because they have so much lower operating costs than gasoline vehicles. Electricity is cheaper and the fuel is more efficient.“Electric vehicles are a great option for rental car companies, or taxi fleets, as well as for private users such as commuters or for people who want to sign up for car sharing schemes.”

7 January 2014

Innovating Your Service Business Model: The Capabilities to Succeed

One of the themes we have been exploring in the Cambridge Service Alliance is the question of how organisations best innovate their service business models. In some of our early work, Ivanka Visnjic and I, developed a framework of 12 capabilities that underpin successful service business model innovation. Since then we have been developing and iterating this framework, creating a maturity model that firms can used to assess the maturity of their capabilities for innovating their service business models. It seemed to me that it would a good idea to write a series of blogs on this framework and the twelve capabilities that underpin it - so here's the first one - explaining the framework.

In essence our research suggests there are four categories of capability that really matter when it comes to innovating the service business model. These are: (i) the ecosystem; (ii) the value proposition; (iii) the value delivery system and (iv) accountability spread. Let me explain these in turn.

The first set of capabilities are concerned with the ecosystem - increasingly competition is taking place at the level of the ecosystem, not the individual firm. In today's interconnected economy, what matters is the way the ecosystem is configured and how your firm is positioned to capture value from it. Apple and HP illustrate the point. If you ask the question - "of the $1,000 someone pays for an Apple or HP machine, who gets the money" - you find that Apple keep 60-70%, while HP keep only 30%. Why the difference? Because Apple use their own proprietary operating system (they don't cede money to Microsoft), they use their own chip (they don't cede money to Intel) and they have created their own distribution infrastructure (they don't cede money to the retailers).

So what can HP do? It is too late for them to develop their own operating system or get into chip manufacturing. Both technologies are too well established, with large incumbent players and high barriers to entry. The cost of establishing a retail infrastructure, certainly a high street retail infrastructure, is prohibitive. But what they can do is invest in Linux. If HP help Linux become a more dominant operating system then Linux reduces Microsoft's power in the marketplace and hence their ability to appropriate value, leaving more of the money on the table for HP. And in fact, it is in the interests of all of HP's traditional competitors to increase the power of Linux. So if HP collaborates with other laptop manufacturers, then collectively they can try to shape the ecosystem and their ability to capture value.

It is not just the ecosystem perspective that matters. The second theme that we saw in our research was the importance of innovating the value proposition - really understanding what the customer valued and the outcomes they were looking for. There's an old Theodore Levitt quote - "customers don't want quarter inch drills, they want quarter inch holes".  We don't think this is right. Customers don't even want quarter inch holes. When innovating your value proposition you have to understand why the customer wants the quarter inch hole. If it is to hang a picture, then how else might the picture be hung - you could glue it to the wall. You could invite an artist in to paint the picture on the wall. The key to innovating you value proposition is to understand deeply what your customers really value.

Beyond the value proposition, the third category of capabilities centred on the value delivery system. Here we are shifting into the question of how do we configure the resources and activities required to deliver the value proposition. What should we do? What should we ask others to do? Many of the services firms deliver today require networks of organisations to pool their capabilities. Understanding the right network structure and identifying the right partners is essential when innovating the service business model.

Finally, we shift to capabilities concerned with accountability spread. Here the idea is that by taking on responsibility for the outcomes your customers want - you increase your risk and exposure. By innovating the value delivery system - either through technology or partnering with others - you may decrease the control you have over the ecosystem. Hence you have increased your accountability, but potentially reduced your control - hence you may have increased your risk or accountability spread. Understanding the implications of this and how the risk will therefore be managed is paramount if the service business model is to be sustainable.

These four categories of capability - ecosystem, value proposition, value delivery system and accountability spread - form the highest level of our framework for understanding business model innovation. In future blogs I'll unpack each of these categories in turn and explain the capabilities that underpin them.

Professor Andy Neely
Director Cambridge Service Alliance